Low Exponent Research Articles

Carbonaceous aerosol emissions from secondary lighting sources: Emission factors and optical properties

India is shifting towards cleaner residential fuels, but this transition does not fully address household lighting challenges. Power disruptions, especially in rural areas, lead to the use of secondary lighting sources such as kerosene lamps, edible oil lamps, and candles. Our previous work identified kerosene wick and hurricane lamps as major secondary lighting sources in Indian households. This study presents the emission factors (EF) and optical properties of carbonaceous aerosols from five major secondary lighting devices in India, measured using a laboratory extractor hood system. Dominant secondary lighting devices, such as simple wick lamps (61.4 ± 9.8 g kg⁻1) and hurricane lamps (17.2 ± 4.8 g kg⁻1), exhibit higher elemental carbon (EC) EFs than typical residential biomass burning. Sesame oil lamps, primarily used in India during the Diwali festival, also have significant EC emission potential, with an EC EF of 71.6 ± 16.9 g kg⁻1. The low absorption Angstrom exponent (AAE) of ∼1 at near-UV wavelengths indicates a dominance of black carbon (BC) and negligible brown carbon absorption, corroborated by very low organic carbon concentrations. India-wide EC emissions (12.5 Gg year⁻1) from residential kerosene lighting show a higher (∼50%) contribution from eastern India. Additionally, the use of oil lamps during the Diwali festival could emit ∼3 Gg of EC in two days, with a potential reduction of ∼90% if wax-based lamps replace oil lamps. These measured EFs, aerosol optical properties, and estimated emissions will help future studies derive more accurate climate and health impacts from these otherwise overlooked lighting devices.

Synchronization transitions in adaptive Kuramoto-Sakaguchi oscillators with higher-order interactions.

Coupled oscillators models help us in understanding the origin of synchronization phenomenon prevalent in both natural and artificial systems. Here, we study the coupled Kuramoto oscillator model having phase lag and adaptation in higher-order interactions. We find that the type of transition to synchronization changes from the first-order to second-order through tiered synchronization depending on the adaptation parameters. Phase lag enables this transition at a lower exponent of the adaptation parameters. Moreover, an interplay between the adaptation and phase lag parameters eliminates tiered synchronization, facilitating a direct transition from the first to second-order. In the thermodynamic limit, the Ott-Antonsen approach accurately describes all stationary and (un)stable states, with analytical results matching those obtained from numerical simulations for finite system sizes.

Aperiodic component of EEG power spectrum and cognitive performance are modulated by education in aging

Recent studies have shown a growing interest in the so-called “aperiodic” component of the EEG power spectrum, which describes the overall trend of the whole spectrum with a linear or exponential function. In the field of brain aging, this aperiodic component is associated both with age-related changes and performance on cognitive tasks. This study aims to elucidate the potential role of education in moderating the relationship between resting-state EEG features (including aperiodic component) and cognitive performance in aging. N = 179 healthy participants of the “Leipzig Study for Mind–Body-Emotion Interactions” (LEMON) dataset were divided into three groups based on age and education. Older adults exhibited lower exponent, offset (i.e. measures of aperiodic component), and Individual Alpha Peak Frequency (IAPF) as compared to younger adults. Moreover, visual attention and working memory were differently associated with the aperiodic component depending on education: in older adults with high education, higher exponent predicted slower processing speed and less working memory capacity, while an opposite trend was found in those with low education. While further investigation is needed, this study shows the potential modulatory role of education in the relationship between the aperiodic component of the EEG power spectrum and aging cognition.

Static recrystallization behavior and strengthening mechanism of a single-phase Cu–18Ni–17Zn alloy

The microstructural evolution and recrystallization behavior of a single-phase Cu–18Ni–17Zn alloy during annealing has been investigated. The strengthening effects of the solute atom concentration, grain size, and recrystallized volume fraction have also been studied. The results have shown that the difference in yield strengths for the fully recrystallized samples mainly depended on the grain boundary strengthening effect. This is attributed to a constant (∼41 MPa) solid-solution strengthening contribution in the completely recrystallized Cu–18Ni–17Zn alloy. When compared with pure copper, this alloy exhibited a high Hall-Petch constant (∼0.36 MPa m1/2), which is due to the higher grain boundary interface energy. A discontinuous recrystallization occurred in the alloy in the temperature range 400 °C–500 °C. Furthermore, the yield strength was linearly correlated to the recrystallized volume fraction in the partial recrystallized samples. Moreover, the addition of Ni and Zn increased the recrystallization temperature and slowed the recrystallization kinetics. The activation energy for the recrystallization was estimated as 92.6 ± 5.1 kJ/mol in the cold-rolled Cu–Ni–Zn alloy, which indicates that the grain boundary migration during recrystallization was mainly controlled by diffusion along the grain boundaries. In addition, the recrystallized grains preferentially nucleated at shear bands with high strain energies in the Cu–Ni–Zn alloy during annealing. As the regions of shear banding were completely consumed, new recrystallized nuclei formed at the grain corners. The limited number of nucleation sites resulted in a low Avrami exponent value that ranged from 0.41 to 0.61.

The impact of precipitation on recrystallization in a severely plastically deformed CoCrFeMnNi multi–principal element alloy

The present study investigated the rate-controlling mechanism for recrystallization kinetics in a severely plastically deformed (SPD) multi–principal element alloy. For this purpose, an equiatomic Cantor alloy (CoCrFeMnNi) was subjected to equal channel angular processing (ECAP) at room temperature and annealed at 773–973 K. The major recovery process was found to be concurrent recrystallization with precipitation. The recrystallization kinetics, investigated in the frame of the Johnson–Mehl–Avrami (JMAK) theory, gives a retarded recrystallization with a high recrystallization temperature of above 0.54Tm and an anomalous low JMAK exponent value of 1.1–1.8. The measured apparent activation energy for recrystallization exhibited a steady increase over the duration, with initial values of 220.8 ± 7.5 kJ/mol rising to 313.9 ± 23.8 kJ/mol towards the end. The systematic analysis leads to the conclusion that the rate-controlling mechanism for recrystallization in ECAP processed CoCrFeMnNi MPEA is the grain boundary migration-determined grain growth instead of nucleation. During this process, the Zener pinning effect exerted by precipitates from the concurrent precipitation with recrystallization plays the dominant role.

Aperiodic components and aperiodic-adjusted alpha-band oscillations in children with ADHD

This study aimed to investigate the aperiodic properties and aperiodic-adjusted alpha-band oscillations in children with ADHD, focusing on the influence of different scalp regions and lateralization on these neural correlates. Sixty-two ADHD children and 52 typical developing children aged 6–12 years were enrolled. EEG recordings were made with eyes closed for a minimum of 6 min. The ‘FOOOF’ was used to compute aperiodic parameters (exponent and offset), and aperiodic-adjusted alpha-band features including center frequency (CF), adjusted power (AP), and bandwidth (BW). Mixed-design ANOVAs were conducted with two between-subjects levels (ADHD and control groups) and two within-subjects’ factors (lateralization and scalp region). ANCOVAs were conducted after accounting for sex and age. The ADHD group showed a significantly lower exponent compared to the control group, and this difference was not influenced significantly by factors like lateralization, scalp region, or sex. There were no notable distinctions between the groups for other measures. We noticed alpha-band CF tends to increase with age, while only frontal AP shows a significant positive correlation with age. Significant main effects of sex and lateralization were observed for offset, along with an interaction effect between sex and lateralization for CF. Our findings indicate that children aged 6–12 with ADHD have a markedly lower exponent, suggesting that this measure could potentially serve as a biomarker for ADHD. Future studies should consider factors such as age, sex, lateralization, and scalp region when investigating aperiodic and aperiodic-adjusted features.

Combustion performance modulation and agglomeration inhibition of HTPB propellants by fine Al/oxidizers integration

Modulation of burning rates and inhibition of aluminum agglomeration in solid propellants have generated considerable research interest in the field of energetic materials. In this paper, integrated Al/oxidizer composites have been prepared by a spray-drying technique, which offer intimate contact between the fuel and oxidizers. The morphologies, thermal stability, density, heats of explosion and combustion performance of the resulted solid propellants containing these Al-based composites were systematically investigated, where the condensed combustion products (CCPs) analysis and the agglomeration behavior of Al particles have been focused. After well control of the Al/oxidizers structure, 9 % higher explosion heat, 58 % higher pressurization rate and 65 % stronger flame radiation intensity were achieved in comparison to the conventional solid propellants with the same formulation. The burn rate of the propellants can also be well controlled by using different type of Al/oxidizers composites, in the range of 3.6–5.9 mm s−1 under 0.5 MPa and 9.2–10.9 mm s−1 under 15 MPa. More importantly, very low burn rate pressure exponent of 0.1 within 0.5–15 MPa was obtained. Inspired by decreasing size of CCPs, the evolution of Al on the burning surface was studied and the agglomeration inhibition was observed, whose potential mechanism was then proposed and elucidated.

Introduction of new attributes: Scaling Exponent and its double derivatives for better land seismic volume interpretation

For the first time, we propose to study the behavior of the correlation (scaling) exponent and its second order with prestack seismic data. For our research, we have chosen Dibrugarh prestack 3D seismic data from the Assam-Arakan Basin, India. We have improved the calculation process so that it is possible to read amplitude values directly from SEG-Y file and collect data from the entire chosen in- or cross-line. As a result, we can now study significant amount of data within less amount of time. After completing the analysis, we could identify the main stratigraphic layers, basement, and the zones of weak and prominent amplitudes from the survey. Strong amplitude zones correlate with low scaling exponent values. Weak amplitudes reflect as high scaling exponent zones. New attributes introduced give a scope to automatize the interpretation of 3D seismic data without learning.

Rigidity of Euclidean product structure: breakdown for low Sobolev exponents

Rigidity of Euclidean product structure: breakdown for low Sobolev exponents

Multi-faceted analysis of dust storm from satellite imagery, ground station, and model simulations, a study in China

An intense dust storm from 8 April to 11 April 2023 originated from the Gobi deserts bordering Mongolia and Inner Mongolia of China and affected most parts of northern, central, and eastern China, the Korean Peninsula, and Japan. It has a significant impact on air quality in these regions and alters the optical and microphysical properties of the aerosols. In this work, a comprehensive analysis of the storm was carried out by using reanalysis data, model simulation, satellite, and ground-based observations. The geopotential height along with the wind flow reveals that the development, transportation, and dissipation of the dust storms were closely related to the movement of the Mongolia cyclones caused by Mongolia low and its surrounding highs. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data showed a two-layer dust vertical distribution, with the bottom one below 5 km and the upper one stretching from 5 to 10 km over the Japan Sea. The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) backward trajectory uncovered Central Mongolia being the origin of the dust storm that arrived over the Japan Sea on April 9, 2022, and the forward trajectory revealed that the dust aerosols would be further transported to the Pacific Ocean. Air quality analysis demonstrated that the regions of inner Mongolia (IMG) and Jing-Jin-Ji (JJJ) suffered the most from the dust storm events, followed by the Yangtze River Delta (YRD), while the Pearl River Delta (PRD) was hardly affected, as indicated by the regional-averaged PM10 and PM2.5. It was also found that the dust storm event has almost no significant influence on the other air quality indicators including CO, NO2, O3, and SO2. Historical record tracking revealed that the springtime averaged PM10 and PM2.5 of the year 2023 are comparable to those in 2021 which has the record-breaking dust storm case. AERONET data indicated dramatic increments of aerosol optical depth at 550 nm (AOD550) and effective radius of total size (ReffT) in regions of Gobi and JJJ, accompanied by low Angstrom Exponent (AE), and high SSA870 values, while in the regions of Korea and Japan, minor increments of AOD550 and ReffT were found. This study provides a holistic scientific view of the dust storm which could aid in the implementation of protective measures against dust storms.

Topological mechanism in the nonlinear power-law relaxation of cell cortex.

Different types of cells exhibit a universal power-law rheology, but the mechanism underneath is still unclear. Based on the exponential distribution of actin filament length, we treat the cell cortex as a collection of chains of crosslinkers with exponentially distributed binding energy, and show that the power-law exponent of its stress relaxation should scale with the chain length. Through this model, we are able to explain how the exponent can be regulated by the crosslinker number and imposed strain during cortex relaxation. Network statistics show that the average length of filament-crosslinker chains decreases with the crosslinker number, which endows a denser network with lower exponent. Due to gradual molecular alignment with the stretch direction, the number of effectively stretched crosslinkers in the network is found to increase with the imposed strain. This effective growth in network density diminishes the exponent under large strain. By incorporating the inclined angle of crosslinkers into the model without in-series structure, we show that the exponent cannot be altered by crosslinker rotation directly, refining our previous conjectures. This work may help to understand cellular mechanics from the molecular perspective.

High-temperature tensile behaviors of a bimodal-grained Mg-Mn-Ce alloy

In this work, the high-temperature tensile behaviors of an extruded Mg-0.9Mn-0.5Ce (wt%) alloy with bimodal-grained microstructure were investigated, and the tensile tests were conducted at 423 K ∼ 523 K with the strain rate ranging from 6.0 × 10−3 s−1 to 1.5 × 10−1 s−1. It was found that the alloy exhibited a maximum fracture elongation of ∼156% and a highest strain-rate sensitivity exponent of 0.36 when deformed at 473 K. The softening effects generated by continuous dynamic recrystallization, the activation of < c + a > slipping on the pyramidal planes and grain boundaries migration collaboratively contributed to the high fracture elongation. As temperature increases to 523 K, microstructure stability was rapidly decreased and the deformation ability was severely restricted owing to the growth of grains, resulting in the adequate fracture elongation and low strain-rate sensitivity exponent.

A new modified Skew Tent Map and its application in pseudo-random number generator

Everyday, a vast amount of information is created and shared on the internet. Security steps and methods are needed to ensure the data is sent and stored safely. Random numbers are essential to cryptography because they are crucial to securing data. In recent years, the use of chaos theory has become increasingly important in producing pseudo-random number sequences in the field of cryptography. But the majority of fundamental chaotic maps have a variety of limitations, such as constrained chaotic regions, a low Lyapunov Exponent (LE), chaotic annulling conditions, and high computational cost. In this research, we construct a new chaotic map based on the skew tent map (STM) in order to find a better solution to these problems. The proposed chaotic map includes significantly enhanced chaotic behaviour and has a more comprehensive chaotic range and higher LE. Furthermore, two novels Pseudo-random Number Generators (PRNGs) based on a new M-STM chaotic map, have been built to investigate its application in security-related fields. The performance evaluations of these generators demonstrate their ability to generate pseudo-random number sequences that exhibit improved statistical properties efficiently.

Fuzzing-based grammar learning from a minimal set of seed inputs

To be effective, a fuzzer needs to generate inputs that are well formed, so that they are not outright rejected by the Software Under Test (SUT) and can thus detect meaningful bugs. Grammar based fuzzers solve this problem, but they obviously require a grammar of the input language accepted by the SUT. Many times such grammar is unknown. Therefore, different black- and white-box algorithms have been proposed for learning them from SUTs. Black-box algorithms rely only on membership queries, but need access to carefully crafted well formed inputs in order to obtain good results. White-box algorithms require access to the source code and generally produce grammars with higher precision and recall, but at the expense of working only for specific programming languages and libraries. We propose a new algorithm and show through extensive experimentation that it can learn grammars from recursive descendent parsers with consistently high levels of both, recall and precision. Notably, this result was obtained starting with a couple of arbitrary seed inputs and includes evaluations with sophisticated languages such as Java Script Object Notation (JSON). Different to other state of the art white-box approaches, our method does not require sophisticated program analysis techniques such as dynamic tainting or symbolic execution. In fact, the experiments confirm that our method performs extremely well with just a (standard) generic Abstract Syntax Tree (AST) of the parsing program as input. The core of our method uses fuzzing techniques combined with fundamental theoretical results on grammar learning. Compared to other white-box approaches, ours is not tied to specific programming languages and tools, and thus can be easily ported. Regarding performance, we have shown that our algorithm works well in practice and that, under reasonable assumptions, its worst-case complexity is polynomial (with low exponents) w.r.t. time and space requirements.

On the inherent strength of Cr23C6 with the complex face-centered cubic D84 structure

The deformation behavior of single crystals of Cr23C6 with the complex D84 crystal structure based on the face-centered cubic lattice has been investigated by micropillar compression as a function of crystal orientation and specimen size at room temperature. For the first time, the {111}<1‾01> slip system is identified to be the only operative slip system. The 1/2<1‾01> dislocation dissociates into two partial dislocations with identical collinear Burgers vectors (b) as confirmed by transmission electron microscopy (TEM) and atomic-resolution scanning transmission electron microscopy (STEM). The energy of the stacking fault bounded by two coupled partial dislocations with the b = 1/4<1‾01> is evaluated from their separation distances to be 840 mJ/m2. The critical resolved shear stress (CRSS) for {111}<1‾01> slip increases with the decrease in the specimen size, following the inverse power-law relationship with a relatively low exponent of ∼ -0.19. The room-temperature bulk CRSS value evaluated by extrapolating this inverse relationship to the specimen size of 20∼30 μm is 0.79 ± 0.15 GPa. The exact position of the slip plane among many different parallel {111} atomic planes and possible dislocation dissociations on the relevant slip planes are discussed based on the calculated generalized stacking fault energy (GSFE) curves. The inter-block layer slip is deduced to occur for {111}<1‾01> slip based on the TEM/STEM observations and the result of GSFE calculations. Finally, plausible atomic structures for stacking faults on (111) and coherent twin boundaries are discussed.

Probing modulated liquid crystal media with dielectric spectroscopy

We use impedance spectroscopy to probe modulated liquid crystals. Chiral nematic samples are characterized and fabricated with a fixed amount of chiral dopant and Smectic-A in different geometries. The data are adjusted with a Poisson-Nernst-Planck (PNP)-like model. The low-frequency behavior of the conductivity is studied, and the behavior is associated with the ionic diffusivity across the cell. Diffusion across layered structures, contrary to what occurs when the structures are not layered, requires permeation of ions, which is reflected in the very low exponent characterizing diffusivity, indicating a cage-like behavior diffusion. Thus, this simple non-destructive technique can be used to probe the morphology of the material.

Enhanced Thermal Decomposition and Safety of Spherical CL-20@MOF-199 Composites via Micro-Nanostructured Self-Assembly Regulation.

The characteristics of high burning rate, high energy output, and low pressure exponent have always been the focus of development in the field of composite solid rocket propellants. In this paper, a metal-organic framework (MOF-199) compound is introduced to prepare micro-nanospherical CL-20@MOF-199 composites via the spray-drying self-assembly technique to reach the above goals. MOF-199, which acts as an attractive combustion catalyst and a safety regulator, is uniformly coated on the surface of CL-20 with close interface contact between particles, effectively accelerating the thermal decomposition of CL-20 and ensuring safety performance. The average noncovalent interaction (aNCI) analysis illustrates that there are strong C-H···O hydrogen bonds and van der Waals interaction between CL-20 and MOF-199 molecules, greatly enhancing the effect of interparticle assembly. The effects of different contents of MOF-199 on the thermal, safety, and energy properties of CL-20 were discussed. The thermal analysis demonstrates that MOF-199 has a significant thermal catalytic effect on CL-20, with an advanced peak temperature of thermal decomposition of 14.2 °C and a reduced activation energy barrier of 34.2 kJ·mol-1, mainly benefitting from more exposed catalytic active sites and close interface contact. In addition, CL-20@MOF-199 composites exhibit decreased mechanical sensitivity (IS: 21-40 cm, FS: 80-240 N) and excellent energy performance. This work clearly demonstrates that MOF-199 is both a superior combustion catalyst and a good safety buffer for CL-20, and it opens new potential for further applications of CL-20 in composite solid propellants.

Kinetic model of CO2 methanation in a microreactor under Power-to-Gas conditions

The kinetics of CO2 methanation using a 12%Ni/γ-Al2O3 catalyst was modeled in a catalytic microreactor, considering the three-dimensional momentum, heat and species continuity balances in stationary state. The microreactor consisted of 80 microchannels with dimensions 0.45 × 0.15 × 50 mm3 in each one with an average 0.04 mm catalytic thickness. Several experimental tests were carried out at various conditions of flow rate (110, 130 and 140 mL/min), temperature (275, 300, 325 and 350 °C) and reactants partial pressure. Kinetic parameters were modeled and fitted using COMSOL Multiphysics 6.0 and Matlab 2021 R. Using the corrected Akaike information criterion (AICc), it was determined that a power kinetic model with a low kinetic exponent, 0.12 ≤ n ≤ 0.18, is adequate to represent a wide range of experimental CO2 conversion and CH4 yield (up to 86%) data. An activation energy around 83–85 kJ/mol was estimated, as well as a correlation between the different parameters of the power rate law. The temperature raise significantly increases the CO2 conversion and methane yield under the operational conditions used, due to the distance from thermodynamic equilibrium. It was numerically verified that under the experimental conditions the microchannels operate isothermally. Using this model, it is possible to evaluate the effect of operational variables (temperature, volumetric flow and H2/CO2 ratio) and reactor design (microchannel surface/volume ratio) on methane production, proving potential application in catalytic efficiency studies for Power-to-Gas applications. It is clear that processes intensification is useful to achieve higher CO2 conversions fostering sustainable development of closed-carbon production cycles.

POSSIBILITY OF USING BLACK OLIVE SEED POWDER IN FORMULATIONS TO FUNCTIONALIZE BREAD

This study aimed to evaluate the potential use of olive seed pulp powder (BOP), a by-product of the olive oil industry, as a functional raw material. The physicochemical, rheological, and bioactive properties and consumer acceptance preferences of bread produced by adding wheat flour at 1%, 2.5%, 5%, and 7.5% ratios were investigated. Depending on the increase in BOP addition, it decreased the stickiness and specific volume of the bread and increased the brown index, hardness, and stickiness values. The increase in BOP addition in both the shell and the core increased phenolic and antioxidant activity. The BOP shot had a positive impact on consumer preference. The 5% and 7.5% BOP are more stable and of good quality in terms of preserving shape due to lower exponents. For this reason, BOP appears to be a good candidate for enriching bread on an industrial scale

The impact of different aerosol layering conditions on the high-resolution MODIS/MAIAC AOD retrieval bias: The uncertainty analysis

The Eastern Mediterranean/Middle East (EMME) region belongs to one of the most polluted and vulnerable to climate change related areas in the world. To monitor these changes, comprehensive set of measurements need to be conducted. Ground-level monitoring sites provide continuous measurements, yet their spatial coverage in EMME is very limited. Satellite data largely expand spatial coverage, however, retrieval accuracy over arid regions with bright surface background, mixed with urban and industrial sources, remains challenging. In this study, we analyzed the agreement between aerosol optical depth (AOD) data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm at 1-km spatial resolution and corresponding ground-based Aerosol Robotic Network (AERONET) measurements, using data from September 2019 to October 2022 in Tel Aviv, Israel. We identified all overestimation and underestimation MAIAC AOD measurements, relative to AERONET, and used multiwavelength polarization lidar observations of vertical aerosol profiles to characterize these conditions. Our findings suggest that under clear atmospheric conditions (AOD¡0.12), MAIAC overestimation prevails, while under dusty (AOD¿0.3), and partially cloudy conditions, MAIAC underestimation prevails. We found that dust component (high particle depolarization ratio, and low Angstrom exponent) is often presented in cases of underestimation, while a single layer overestimation cases typically related to anthropogenic pollution. The two-layers overestimation cases tend to have marine aerosols at the bottom and mixed pollution sources at the top. Our study highlights the importance of studying the different layering conditions that largely bias the MAIAC AOD retrieval accuracy. This knowledge is highly important since AOD is widely used as input variable in numerous modeling studies and air quality applications and rarely prepossessed for such a bias.