Measurement Of Distribution Research Articles

Characterization of Plant based spray dried powders using oil seed proteins and chokeberry extract from wine byproduct

Spray drying is a standard method for preserving bioactive ingredients and enhancing their storage stability. This study aimed to produce entirely plant-based spray-dried powders by using hemp, canola, and flax seed proteins, combined with maltodextrin, as wall material, while chokeberry extract from wine waste served as core material. We conducted a thorough analysis of the oil-seed proteins, examining their nitrogen solubility index, emulsification, and foaming capacities. The encapsulation process was evaluated based on its yield and efficiency. The spray-dried powders were further assessed through colour analysis, particle morphology and size distribution, hygroscopicity, and storage stability measurements. The encapsulation yield with oil-seed proteins ranged from 75.0 ± 6.2 to 78.5 ± 1.3%, and the efficiency from 58.4 ± 0.8 to 77.5 ± 1.9%. These plant-based spray-dried powders exhibited similar colour parameters, morphology, and stability to those of whey protein powders. The study highlights the significant potential of oil-seed proteins in producing plant-based spray-dried powders.

Cross-calibration and first vertical ECE measurement of electron energy distribution in the TCV tokamak

Abstract This paper describes the first vertical electron cyclotron emission measurement of non-thermal electron distributions in the Tokamak à Configuration Variable. These measurements were conducted in runaway electron scenarios and in the presence of electron cyclotron current drive. Measured intensities of linearly polarized X- and O-mode radiation from fast electrons allow the analysis of the energy distribution. The measurements were made possible through the creation of an operational regime for the diagnostic that is free of thermal background radiation, in relaxed electron density operations. This operational regime notably enables the cross-calibration of the diagnostic system, relying on thermal plasma measurements and modeling with the ray-tracing code SPECE.

The water vapor distribution profile in dry soil layer during evaporating with high spatial resolution monitored by distributed fibre-optic sensing technology

The dry soil layer (DSL) typically forms on the surface of sandy soils during the evaporation process, with water in the DSL moving solely as vapor. Understanding the DSL thickness and its water vapor distribution is crucial for accurately estimating soil water flux, improving evaporation mechanisms, and enhancing ecological conservation efforts. This study employed distributed fibre-optic sensing (DFOS) technology to achieve high spatial resolution measurements (up to 1 mm) of the water vapor distribution within the DSL. We measured soil water vapor profiles in a sand column subjected to evaporation over 24 days using a 60 cm long relative humidity sensing probe and an optical frequency domain reflection (OFDR) interrogator. We effectively captured the downward migration of the evaporating surface from the sand surface and quantified the inhibitory effect of DSL thickness on evaporation using a logarithmic function. Additionally, we identified a linear distribution of water vapor with depth in the DSL. Our findings offer novel insights into the role of DSL in the hydrological behaviour of unsaturated soils and demonstrate the potential of our approach for investigating dynamic changes in in-situ DSLs, particularly in arid and semi-arid regions.

PERSEPSI MASYARAKAT TERHADAP KEBERADAAN RUMAH WALET DI DESA WATUTAU KECAMATAN LORE PEORE KABUPATEN POSOSULAWESI TENGAH

This research aims to determine the public's perception of the existence of swallow houses in Watutau Village, Lore Peore District, Poso Regency, and the factors that influence people's perceptions of swallow houses. In this research, the population was taken from a community located at a radius of 250 meters, namely 31 heads of families, the number of samples taken was 31 respondents. This research is a qualitative descriptive research. The research method used by the survey method is one of the information collection techniques carried out by compiling a list of questions asked to respondents at the research location. The data analysis used is descriptive statistics using grouping, simplification and presentation of data such as frequency distribution tables and measurements using the likert and chi- square scales. Based on the results of the study, the perception of the community in Watutau Village, Lore Peore District, Poso Regency, is in the category of Disturbed / Disagreed with the exis tence of swallow houses and the most influential factors in the perception of the community in Watutau Village, Lore Peore District, Poso Regency are the distance of houses on sound and socio-cultural indicators on community perceptions.

Human milk fat globule size distributions: comparison between laser diffraction and 3D confocal laser scanning microscopy

Milk fat globules (MFGs) in human milk provide energy to breastfed infants and support infant development. Accurate measurements of MFG size distributions are important to better understand MFG function and origin, as well as the influence of MFG size on milk composition analysis methods. Nevertheless, commonly used laser diffraction systems have never been thoroughly validated for size distribution measurements in human milk. Here, we introduce a new method for determining the size distribution of milk fat globules in human milk, using 3D confocal laser scanning microscopy (CLSM) in combination with fluorescent labeling of MFGs. We validate and compare 3D CLSM to laser diffraction (Mastersizer 2000, Malvern Panalytical), using polystyrene microsphere size standards. Next, we apply both methods to evaluate MFG size distributions in human milk. We show that 3D CLSM can be used to obtain more accurate size distributions between 500 nm and 10 μm compared to laser diffraction. Importantly, MFG size distributions obtained with 3D CLSM contain no secondary population around 1 μm, in contrast to laser diffraction measurements. This suggests that the bimodal MFG distribution obtained by laser diffraction can be an artifact of the built-in fitting algorithm, instead of an actual feature of human milk. This work demonstrates that care should be taken when interpreting size distributions of MFGs measured with laser diffraction and that 3D CLSM is an accurate alternative for measuring size distributions in lactation and dairy research.

Re-investigation of the interplay of fission modes and non-equilibrium fission processes in heavy actinide nuclei 249Bk and 257Md

Measurements of mass and angular distributions of fission fragments from actinide nuclei 249Bk and 257Md, produced in fusion reactions 11B and 19F + 238U, are presented. Experimentally observed mass ratio distributions indicate “multi-chance fission” through the interplay of fission modes in the fission process, and they agree well with predictions from calculations using the GEF (“GEneral description of Fission observables”) model code. Furthermore, to test the signatures of events from non-compound nuclear processes in the fission of 249Bk and 257Md nuclei, Monte Carlo statistical decay model calculations using GEMINI++ were performed for the measured mass distribution at all energies. For comparison purposes, the fission fragment mass distributions of neighboring heavy actinide nuclei, previously measured in the fission of 250Cf and 254Fm nuclei produced by 12C and 16O projectiles on a 238U target, are also presented. The measured angular anisotropy data for the 19F + 238U reaction differ from the results of the Transition State Model (TSM) at energies below the fusion barrier. As a result of the present study, we suggest considering the interplay between K relaxation time, dynamic dissipation, and their influence on shell correction to understand the evolution of fission dynamics in heavy-ion-induced actinide nuclei.

Long-range transport of coarse mineral dust: an evaluation of the Met Office Unified Model against aircraft observations

Abstract. Coarse mineral dust particles have been observed much further from the Sahara than expected based on theory. They have impacts different to finer particles on Earth's radiative budget, as well as carbon and hydrological cycles, though they tend to be under-represented in climate models. We use measurements of the full dust size distribution from aircraft campaigns over the Sahara, Canaries, Cabo Verde and Caribbean. We assess the observed and modelled dust size distribution over long-range transport at high vertical resolution using the Met Office Unified Model, which represents dust up to 63.2 µm diameter, greater than most climate models. We show that the model generally replicates the vertical distribution of the total dust mass but transports larger dust particles too low in the atmosphere. Importantly, coarse particles in the model are deposited too quickly, resulting in an underestimation of dust mass that is exacerbated with westwards transport; the 20–63 µm dust mass contribution between 2 and 3.7 km altitude is underestimated by factors of up to 11 in the Sahara, 140 in the Canaries and 240 in Cabo Verde. In the Caribbean, there is negligible modelled contribution of d > 20 µm particles to total mass, compared to 10 % in the observations. This work adds to the growing body of research that demonstrates the need for a process-based evaluation of climate model dust simulations to identify where improvements could be implemented.

Brain tumor classification utilizing pixel distribution and spatial dependencies higher-order statistical measurements through explainable ML models

Brain tumors are among the most fatal and devastating diseases, and they often result in a significant reduction in life expectancy. The devising of treatment plans that can extend the lives of affected individuals hinges on an accurate diagnosis of these tumors. Identifying and analyzing large volumes of magnetic resonance imaging (MRI) data manually proves to be both challenging and time-consuming. As a result, there exists a pressing need for a reliable machine-learning approach to accurately diagnose brain tumors, and numerous methods have already been proposed over the last decade. In this paper, a novel, comprehensive approach is proposed for identifying and classifying a given MR brain image as abnormal. Three common brain diseases, namely glioma, meningioma, and pituitary tumor, are chosen as abnormal brains, and the Figshare MRI brain image dataset was collected from the Kaggle and IEEE websites. The proposed method is initiated by employing 1st-order statistics, 2nd-order statistics, and higher-order transformed (DWT) feature extraction to extract features from images. Then missing data is addressed and handled using KNNImputer, followed by the application of the ExtratreesClassifier and PCA feature selection methods to identify the most relevant features and reduce the dimensions of these features. Subsequently, the reduced features are submitted to seven machine learning models, namely RF, GB, CB, SVM, LGBM, DT, and LR. The strategy of k-fold cross-validation is utilized to enhance the performance of those models. Finally, the models are evaluated using XAI approaches, which ensure transparent decision-making processes and provide insights into the model’s predictions. Remarkably, our approach achieves the highest accuracy, precision, recall, F1 score, MCC, Kappa, AUC-ROC, and R2, as well as the lowest loss, among the seven models evaluated, proving its effectiveness and applicability in multiple analytic applications relying on publicly available datasets.

Visualization of Aerial Droplet Distribution for Unmanned Aerial Spray Systems Based on Laser Imaging

Unmanned aerial spray systems (UASSs) are a commonly used spraying method for plant protection operations. However, their spraying parameters have complex effects on droplet distribution. The large-scale 3D droplet density distribution measurement method is insufficient, especially since the downwash wind is easily affected by the environment. Therefore, there is a need to develop a technique that can quickly visualize 3D droplet distribution. In this study, a laser imaging method was proposed to quickly scan moving droplets in the air, and a test method that can visualize 3D droplet distribution was constructed by using the traveling mode of the machine perpendicular to the scanning plane. The 3D droplet distribution of targeted and conventional UAVs was tested, and the methods for signal processing, noise reduction, and point cloud rebuilding for laser imaging were developed. Compared with the simulation results, laser imaging showed the pattern of droplet distribution from the two UAV structures well. The results showed that the laser imaging based method for detecting 3D droplet distribution is feasible, fast, and environmentally friendly.

Flame temperature and emissivity distribution measurement of solid propellant based on clustering analysis of multispectral radiation images.

To measure the combustion parameters of a solid propellant, this Letter researches the fitting method for flame temperature and emissivity based on multispectral images and proposes the particle swarm optimization-K-means (PSO-K-means) clustering optimization algorithm of a flame multispectral image. Considering the difference in flame radiation characteristics in different regions, the flame multispectral image is clustered, and spectra in different regions are analyzed and selected in different fitting bands to inverse temperature and emissivity. On this basis, the method is applied to measure solid propellant combustion parameters with different formulations. The measurement shows that the flame temperature is between 1700 and 2100 K, and the emissivity is concentrated in 0.1-0.5. Compared with temperature measurements obtained from tungsten-rhenium thermocouples, the relative deviation of multispectral imaging thermometry is less than 5%. The distribution characteristics of solid propellant combustion parameters with different formulations were analyzed, which provided important data support for evaluating combustion conditions and optimizing solid propellant formulations.

Single-stage NBI sampler for PM1 mass and five-stage NBI-NMCI sampler for PM1 mass distribution measurements

In recent years, concerns about the health and environmental risks associated with PM1 particles have increased. However, existing PM1 sampling instruments remain to be improved mainly because their PM1 inlets have particle loading and bounce issues. To address these challenges, PM1 inlets based on the Non-Bouncing Impactor (NBI) technique were developed. These inlets employ vacuum oil-wetted glass fiber filter (GFF) substrates to eliminate particle bounce and incorporate a daily vacuum oil injection to prevent particle loading. The 16.7 L/min PM1 NBI, modified from the PM2.5 M-WINS design with a reduced diameter of the single nozzle, was designed to adapt readily with current standard sampling and monitoring systems. The cut-size (Dpa50) of 0.99 ± 0.02 μm was determined by considering the effects of Reynold number and the ratio of jet-to-plate distance and nozzle diameter. Field tests comparing the 16.7 L/min PM1 NBI sampler to the 9-stage NCTU Micro-orifice Cascade Impactor (NMCI9) revealed small sampling biases, with a mean difference of +0.26 ± 2.28 μg/m3 for PM1 measurements when silicone oil-coated aluminum foil (AF) and GFF-AF were used in the NMCI9. The NBI with the oil-wetted GFF substrate effectively removed particles larger than 1.0 μm, resulting in more accurate PM1 mass concentration measurements. Additionally, the development of a 5-stage NMCI with the 30 L/min PM1 NBI as the first stage enabled detailed measurement of PM1 mass distribution in two modes, which was challenging when measuring the entire mass distribution of ambient aerosols. The distribution of size-dependent water-soluble inorganic ions in PM1 showed dominance of SO42− and NH4+ in PM1 compared to PM2.5. In summary, the PM1 NBI enhances accuracy for long-term atmospheric sampling by addressing particle loading and bounce, making it a more reliable standard sampling instrument.

On the reliability of image analysis for bubble size distribution measurements in electrolyte solutions in stirred reactors

The translation of chemical processes from laboratory to industrial scale is crucial for the effective and sustainable implementation of new technologies. This transition presents significant challenges, particularly in multiphase systems where variations in physical chemistry can complicate scale-up efforts. A key aspect of this challenge is understanding bubble dynamics in gas-liquid systems, which are pivotal in processes such as hydrogen production and CO2 absorption. Bubble size significantly influences mass transfer rates and process efficiency, necessitating accurate measurement methods. A factorial design approach was employed to assess the sensitivity of results to key parameters. The findings provide quantitative guidelines for optimizing image analysis techniques and improving the accuracy of bubble size measurements in diverse operational conditions. This work advances the understanding of bubble dynamics in gas-liquid systems and offers practical insights for refining measurement techniques, ultimately supporting more effective scale-up of chemical processes.

Preparation of α-zein loaded with baicalincomposites: A study on their in vitro simulated digestive behavior and molecular dynamics simulation

In order to improve the bioavailability of baicalin, this article prepared for α-zein loaded with baicalin composites (α-zein@BA) by pH driven method and they were characterized using scanning electron microscopy, infrared spectroscopy, and measurement of particle size distribution in water solution phase techniques. The digestive behavior and antioxidant activity of composites before and after simulating gastrointestinal fluid in vitro were studied as well. At the same time, molecular dynamics simulation techniques were used to reveal the molecular mechanism behind the formation of the composite between the two. The results indicated that the composites of α-zein@BA were observed to be approximately spherical under a scanning electron microscope, and their particle size was mainly distributed in the range of 94.55-145.10 μm in aqueous solution, whose encapsulation efficiency of baicalin was (86.61 ± 0.71) %. Infrared spectroscopy analysis indicated that α-zein and baicalin mainly formed complexes through hydrogen bonding, electrostatic and hydrophobic interactions. The measurement results of baicalin residue in simulated digestion of gastric and intestinal fluids in vitro are as follows: α-zein@BA > Baicalin, while both significantly increased in the gastric digestion stage (P < 0.05) and significantly decreased in the intestinal digestion stage (P < 0.05). Molecular dynamics simulation studies have shown that baicalin has a promoting effect on protein structural stability, and protein 158SER and GLN196 were mainly formed hydrogen bonds with it, while hydrophobic interactions were mainly manifested between non-polar amino acids such as PHE201 and PRO200. This study indicates that α-zein and baicalin can form stable composites, improving the bioavailability of baicalin.

Dependence of aerosol-borne influenza A virus infectivity on relative humidity and aerosol composition.

We describe a novel biosafety aerosol chamber equipped with state-of-the-art instrumentation for bubble-bursting aerosol generation, size distribution measurement, and condensation-growth collection to minimize sampling artifacts when measuring virus infectivity in aerosol particles. Using this facility, we investigated the effect of relative humidity (RH) in very clean air without trace gases (except ∼400 ppm CO2) on the preservation of influenza A virus (IAV) infectivity in saline aerosol particles. We characterized infectivity in terms of 99%-inactivation time, t 99, a metric we consider most relevant to airborne virus transmission. The viruses remained infectious for a long time, namely t 99 > 5 h, if RH < 30% and the particles effloresced. Under intermediate conditions of humidity (40% < RH < 70%), the loss of infectivity was the most rapid (t 99 ≈ 15-20 min, and up to t 99 ≈ 35 min at 95% RH). This is more than an order of magnitude faster than suggested by many previous studies of aerosol-borne IAV, possibly due to the use of matrices containing organic molecules, such as proteins, with protective effects for the virus. We tested this hypothesis by adding sucrose to our aerosolization medium and, indeed, observed protection of IAV at intermediate RH (55%). Interestingly, the t 99 of our measurements are also systematically lower than those in 1-μL droplet measurements of organic-free saline solutions, which cannot be explained by particle size effects alone.

Upconverting thermal history paint for investigations of short thermal events

The main goal of the work was to develop phosphorescent coating for investigations of surface temperature distribution resulted from short duration and high energy thermal events such as small rocket engine testing. For that purpose, we developed thermal history paint with upconverting Gd2O3: Er3+, Yb3+, Mg2+ nanopowder. The developed paint was heated by Joule effect with precise control over temperature and heating time. Photoluminescence signal of cooled samples was excited with 980 nm laser and collected in automatic manner with use of an optical fibre probe connected to photospectrometer. The results show that irreversible changes of paint emission are temperature and heating time specific for calcination temperatures from 700 °C to 1150 °C. Calibration curves were prepared for heating times of 10, 60 and 180 seconds. Finally, 2D surface temperature samples were determined with use of upconverting thermal history paint and compared to IR camera and pyrometric measurements. The results indicate that uncertainty of temperature measurement below 10 °C was achieved for temperatures above 1000 °C. It has been demonstrated that developed thermal history paint allows for measurements of 2D surface temperature distribution with high spatial resolution and good agreement to standard measurements techniques like thermal camera and pyrometer.

Surface Ages in the Vicinity of the Chang’e-6 Landing Site

The samples from lunar farside have great significance for the study of the Moon, and even the solar system. Chang’e-6 landed successfully on the southern mare of the Apollo basin and returned ~2 kg of samples from lunar farside. To provide a better understanding for the background of the returned samples, we conducted detailed crater size-frequency distribution (CSFD) measurements in the Chang’e-6 landing region, the southern mare of the Apollo basin. The southern mare is divided into the western mare (W region) and the eastern mare (E region), and then subdivided into five subunits (W1, W2, W3, W4, W5) and three units (E1, E2, E3), respectively, according to the elevation, TiO2, and FeO abundances. Within the W2 and W5 region, more detailed subunits were separated out. The results show that the southern mare surface was active during two epochs, the Imbrian period and the Eratosthenian period. The basalt eruption lasted for ~1.7 Ga, from 3.28 Ga of the eastern mare to 1.54 Ga of the western mare. The W region is younger than the E region, while the three units of the E region have an age of ~3.2 Ga. The ages of the western mare basalts range from 2.98 Ga to 1.54 Ga, lasting for 1.4 Ga. It is worth noting that the age of the basalt at the Chang’e-6 sampling site is ~1.68 Ga, indicating the samples returned may include components with this very young age.

In situ optical measurement of particles in sediment plumes generated by a pre-prototype polymetallic nodule collector

This study presents in situ, high-resolution optical measurements of particle size distributions (PSD) within sediment plumes generated by a pre-prototype deep seabed nodule collector vehicle operating in the abyssal Pacific Ocean. These measurements were obtained using a cutting-edge instrument, the LISST-RTSSV sensor. The data collected in situ reveal marked differences compared to previously reported laboratory-based, ex situ measurements. The grain size and other key particle shape characteristics are found to be dependent on multiple factors, including the collector vehicle maneuvers, the time elapsed following sediment discharge, and the complex hydrodynamic processes that generate the sediment in suspension. Significantly, the PSD from a highly complex succession of straight-line maneuvers converges to that of the canonical case of a simple straight-line driving maneuver within a timescale of ten minutes. Our results underscore the importance of parameterizing sediment plume transport models based on well-informed, comprehensive PSDs of detrained suspended sediment measured in situ at adequate timescales and in regions no longer strongly influenced by active and complex hydrodynamic processes.

High-Resolution Reconstruction of Temperature Fields Based on Improved ResNet18.

High-precision measurement of temperature value distributions in production scenarios is of great significance for industrial production, but traditional temperature field reconstruction algorithms rely on the design of manual feature extraction methods with high computational complexity and poor generalization ability. In this paper, we propose a high-precision temperature field reconstruction algorithm based on deep learning, using an efficient adaptive feature extraction method for temperature field reconstruction. We design an improved temperature field reconstruction algorithm based on the ResNet18 neural network; introduce the CBAM attention mechanism in the model; and design a feature pyramid, using M-FPN, a multi-scale feature aggregation network fusing PAN and FPN, to make the extracted feature information propagate multi-dimensionally among different layers to improve the feature characterization ability. Finally, the mean square error is used to guide the model to optimize the training so that the model pays more attention to the data and reduces the large error to ensure that the gap between the predicted value and the real value is small. The experimental results show that the reconstruction accuracy of the improved algorithm presented in this paper is significantly better than that of the original algorithm in the case of typical peaked temperature field distributions.

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We investigate the possibility of disentangling different new physics contributions to the rare meson decays and through kinematic distributions in the missing energy . We employ dimension-6 operators within the Low-Energy Effective Field Theory (LEFT), identifying the invisible part of the final state as either active or sterile neutrinos. Special emphasis is given to lepton-number violating (LNV) operators with scalar and tensor currents. We show analytically that contributions from vector, scalar, and tensor quark currents can be uniquely determined from experimental data of kinematic distributions. In addition, we present new correlations of branching ratios for K and B-decays involving scalar and tensor currents. As there could a priori also be new invisible particles in the final states, we include dark-sector operators giving rise to two dark scalars, fermions, or vectors in the final state. In this context, we present new calculations of the inclusive decay rate for dark operators. We show that careful measurements of kinematic distributions make it theoretically possible to disentangle the contribution from LEFT operators from most of the dark-sector operators, even when multiple operators are contributing. We revisit sum rules for vector currents in LEFT and show that the latter are also satisfied in some new dark-physics scenarios that could mimic LEFT. Finally, we point out that an excess in rare meson decays consistent with a LNV hypothesis would point towards highly flavor non-democratic physics in the UV, and could put high-scale leptogenesis under tension.

Synthesis of perylene‐PEO hyperdispersants for aqueous graphene dispersion

AbstractGraphene, with excellent thermal conductivity, electrical and corrosion shielding performance has great application potential in the fields of heat dissipation coating, conductive agent and anticorrosion composite coatings. However, due to its large specific surface area, resulting strong aggregation behavior limits its application. Herein, the hyperdispersants with perylene anchoring groups are synthesized through the amidation coupling reaction between diacid anhydride and polyetheramine. The branching degree and length of hydrophilic chains on hyperdispersant are revealed to be the very important factors to affect the dispersion stability of aqueous graphene dispersion. The hyperdispersant with a single hydrophilic chain and the molecular weight 2000 of polyetheramine has the excellent dispersal activity discovered by Rheology, particle size distribution and Raman measurements. The possible mechanism is the strongest anchoring effect of perylene on graphene surface and thus achieving in best effective spatial exclusion stabilization effect of hydrophilic chains.