Size Range Research Articles

In Ukrainian

The CMs were obtained in argon in three stages: 1) heating (4 grad/min) to the specified temperature t in the range of 350–825 °С; 2) isothermal exposure 1 h; 3) cooling, washing from alkali and drying. Samples are denoted as CM(t). The CM yield (Y, %) and CMs elemental composition are determined. Based on low-temperature (77 K) nitrogen adsorption-desorption isotherms, integral and differential dependences of the specific surface area SDFT (m2/g) and pore volume V (cm3/g) on the average pore diameter (D, nm) were calculated by 2D-NLDFT-НS method (SAIEUS program). They were used to define volumes of ultramicropores (Vumi), supermicropores (Vsmi) and micropores (Vmi). The total pore volume V was calculated from the nitrogen amount adsorbed at a relative pressure p/p0 ~ 1.0. The S values of ultramicropores (Sumi), supermicropores (Ssmi) and micropores (Smi) were similarly determined. The CM yield was established to decrease linearly (R2 = 0.979) from 70.2 to 45.3 % with an increase in temperature from 350 to 825 °С. The carbon content decreases to a minimum value at 500 °С (72.6 %), and then increases to a maximum value (87.5 %) at 825 °С; the oxygen content changes antibatically. Two temperature regions were identified: region I (≤ 500 °С) of increasing the oxygen content due to reactions in which KOH acts as a donor of O atoms; region II (≥ 500 °C) of dominating the thermal destruction of functional groups (carboxyl, lactone, ester) with the release of CO and CO2, and condensation increasing the size of polyarenes of the CM secondary framework and formsng single Сar-Саr bonds between them. The CM(350) sample was found to contain only mesopores (D ≥ 10 nm) and macropores. An activation temperature increase to 400 °C initiates the additional formation of small-diameter micropores and mesopores. In samples CM(400) - CM(825), the main portion of newly formed pores falls on pores with D ≤ 5 nm. With increasing temperature, the micropores volume increases almost linearly (R2 = 0.992). The Vumi and Vsmi volumes increase up to 600 °C. At higher temperatures the ultramicropores volume decreases due to transforming ultramicropores (D ≤ 0.7 nm) into supermicropores (D = 0.7–2.0 nm). Portion of the ultramicropores volume changes with a maximum (23.9 %) in the CM(600) sample. The SBET specific surface area linearly (R2 = 0.992) increases with temperature up to 1729 m2/g. The SDFT values are close to SBET, but noticeably lower (1514–1530 m2/g) for CM(785)-CM(825). The micropores specific surface area increases to 1415 m2/g, and ultramicropore surface Sumi changes extremely with a maximum (526 m2/g) for the CM(600) sample, which should be expected based on the temperature dependence of the Vumi parameter. The decrease in Sumi values after the maximum is compensated by an increase in the supermicropore surface. Such an effect - the redistribution of pores by size in the microporous range (D ≤ 2 nm) with an increase in the alkaline activation temperature is not described in the literature. The portion of the micropores surface is dominant (92.6–97.0 %) in samples prepared at t ≥ 450 °C. The portion of the ultramicropore surface is maximum (56.3 %) in CM(500). Pores are revealed that do not form at all at 450–750 °C. These are supermicropores (D = 0.96–2.00 nm) and mesopores of small diameters (D = 2.0–2.82 nm). This effect was assumed to be due to the properties of the CM supramolecular framework, which is formed from polyarene fragments of the initial and activated coals having polyarenes with diameters of the same order (1.68–2.54 nm).

Unravelling the potential of magnetic nanoparticles: a comprehensive review of design and applications in analytical chemistry.

The study of nanoparticles has emerged as a prominent research field, offering a wide range of applications across various disciplines. With their unique physical and chemical properties within the size range of 1-100 nm, nanoparticles have garnered significant attention. Among them, magnetic nanoparticles (MNPs) exemplify promising super-magnetic characteristics, especially in the 10-20 nm size range, making them ideal for swift responses to applied magnetic fields. In this comprehensive review, we focus on MNPs suitable for analytical purposes. We investigate and classify them based on their analytical applications, synthesis routes, and overall utility, providing a detailed literature summary. By exploring a diverse range of MNPs, this review offers valuable insights into their potential application in various analytical scenarios.

Elevational range size of the breeding bird assemblages and its relationships with richness in the Eastern Himalayas

Species range size reflects the underlying niche of species and directly affects the spatial pattern of species richness. However, the exploration of community mean range size has received relatively limited attention compared to the emphasis on species richness patterns. Additionally, few studies have tested how the rescue effect (the proximity of the distribution limits of potentially interacting species) relates to species richness. In this study, we used a two-year dataset of breeding birds along an elevational gradient in the Lebu Valley, Eastern Himalayas of China, aiming to explore (a) the association between the mean elevational range size of bird community and elevation, using three different ways to calculate the mean elevational range size (Stevens' method, midpoint method and specimen method), (b) examine the influence of drivers (including temperature seasonality, precipitation seasonality, net primary productivity, habitat diversity, geometric constraint, and interspecific competition) on the mean elevational range size pattern, and (c) investigate the effect of rescue effect on species richness pattern. Our results showed that the pattern of mean elevational range size and its underlying drivers vary significantly depending on the assessment method used. Using Stevens' method, which were calculated based on species occurrences, we observed a low-plateau pattern in mean elevational range size. In contrast, the midpoint and specimen methods, which calculate based on the species' distributing midpoint and abundance center, respectively, revealed a mid-peak pattern. Besides, our study supports several ecological hypotheses, including the ambient energy hypothesis, mid-domain hypothesis, and interspecific competition hypothesis. Furthermore, we found that geometric constraints and interspecific competition were the most influential predictors of mean elevational range size patterns, irrespective of the calculation method. Additionally, a significantly positive correlation was observed between the overlap of range margins and species richness, suggesting a contribution of the rescue effect to species richness patterns. The significance of the correlation is associated with the definition of species range size boundaries. Remarkably, this correlation becomes significant only when species range margins reach their 43 % threshold; beyond the 78 % range margin, the increase in correlation strength becomes minimal. Moreover, the rescue effect from low-elevation species was significantly more pronounced than that from high-elevation species, resulting in a species richness hump skewed towards lower elevations. Our findings contribute to validating the applicability and limitations of hypotheses related to species distribution, enhancing both theoretical and empirical aspects of research. This provides deeper insights for a more comprehensive and profound understanding of the local dynamics and interactions within the ecosystem.

High-Performance Krawtchouk Polynomials of High Order Based on Multithreading

Orthogonal polynomials and their moments serve as pivotal elements across various fields. Discrete Krawtchouk polynomials (DKraPs) are considered a versatile family of orthogonal polynomials and are widely used in different fields such as probability theory, signal processing, digital communications, and image processing. Various recurrence algorithms have been proposed so far to address the challenge of numerical instability for large values of orders and signal sizes. The computation of DKraP coefficients was typically computed using sequential algorithms, which are computationally extensive for large order values and polynomial sizes. To this end, this paper introduces a computationally efficient solution that utilizes the parallel processing capabilities of modern central processing units (CPUs), namely the availability of multiple cores and multithreading. The proposed multi-threaded implementations for computing DKraP coefficients divide the computations into multiple independent tasks, which are executed concurrently by different threads distributed among the independent cores. This multi-threaded approach has been evaluated across a range of DKraP sizes and various values of polynomial parameters. The results show that the proposed method achieves a significant reduction in computation time. In addition, the proposed method has the added benefit of applying to larger polynomial sizes and a wider range of Krawtchouk polynomial parameters. Furthermore, an accurate and appropriate selection scheme of the recurrence algorithm is introduced. The proposed approach introduced in this paper makes the DKraP coefficient computation an attractive solution for a variety of applications.

Exploring Combat Tourniquet Application Errors and Duration Among Skilled and Novice Medical Trainees.

The use of tourniquets in combat medicine continues to be a key focus as they have consistently been shown to combat one of the leading causes of preventable death on the battlefield, massive hemorrhage to extremities. The present study analyzed tourniquet application among combat medics (68W) and combat lifesavers (CLSs) in a training environment to determine whether trainees' performance is consistent among one another and whether performance can be associated with participant demographics such as experience or role. Study participants treated male and female patient simulators within a tactical field care phase, both of which experienced an amputated leg and required the application of a Combat Application Tourniquet (CAT). To assess tourniquet application variability and performance, a series of application subtasks and potential errors were measured via video coding of the scenarios by a team of 5 coders. Time to tourniquet application and tourniquet application duration were also coded to assess correlations between application duration and variability or performance. Results from analyzing tourniquet application subtasks and errors through a series of one-way ANOVA tests showed that application of the CAT first, hasty CAT application, and high tourniquet application were not predictive of participant role, time within the role, and self-reported tourniquet skill, confidence, or experience. Such demographic variables were also not predictive of successful tourniquet application as defined by the number of windlass rod rotations. Results from binomial logistic regressions showed that participant role and self-reported tourniquet skill and experience were predictors of tourniquet application duration. The findings suggest that high variability in CAT application methodology and performance exists among CLS and combat medics, which is largely not predictable by various demographics such as role, experience within the designated role, and self-reported confidence, skill, or experience. The observed disconnect between training or experience and CAT application performance suggests substantial variability in the consistency of training for both CLS and 68W soldiers. These inconsistencies may stem from variability in instructor knowledge, teaching styles, or training materials or may be developed through informal methods such as experiences in the field or recommendations from colleagues and experts. These findings highlight a potential need to reassess CAT application training, particularly in regard to consistency and validation. Finally, it should be noted that the study's findings may be limited or fail to capture some study effects because of the sample size and wide range of reported experience among participants.

Comparative Study of Callistemon citrinus (Bottlebrush) and Punica granatum (Pomegranate) Extracts for Sustainable Synthesis of Silver Nanoparticles and Their Oral Antimicrobial Efficacy.

A comparative study was applied to investigate the potential of Callistemon citrinus (bottlebrush) flower extract (BBE) and Punica granatum (pomegranate) peel extracts (PPE) for the sustainable synthesis of the silver nanoparticles, Ag-BBE and Ag-PPE, respectively. The synthesis process of Ag NPs using the selected extracts was applied under optimized conditions. Hence, the effect of the selected plant's type on the different characteristics of the synthesized green Ag NPs was investigated. The UV-Vis spectroscopy revealed the presence of the characteristic silver peaks at 419 and 433 nm of the Ag-BBE and Ag-PPE, respectively. The XRD spectra reported the fcc phase formation of Ag NPs. The TEM results highlighted the morphological features of the synthesized Ag NPs. with a size range of 20-70 nm, and with 10-30 nm for Ag-BBE and Ag-PPE, correspondingly. The Raman spectra revealed characteristic silver bands in the Ag-PPE and reflected some bands related to the natural extract in the Ag-BBE sample. The antimicrobial activity and statistical analysis investigation were conducted against four selected oral pathogens (Staphylococcus aureus (SA), Candida albicans (CA), Staphylococcus epidermidis (S. epi), and Enterococcus faecalis (EF)). Both tested extracts, BBE, and PPE, revealed potential effectivity as reducing and capping agents for Ag NP green synthesis. However, the synthesized NPs demonstrated different features, depending on the used extract, reflecting the influence of the plant's biomolecules on the nanoparticles' properties.

Influence of meteoric smoke particles on the incoherent scatter measured with EISCAT VHF

Abstract. Meteoric ablation in the Earth's atmosphere produces particles of nanometer size and larger. These particles can become charged and influence the charge balance in the D region (60–90 km) and the incoherent scatter observed with radar from there. Radar studies have shown that, if enough dust particles are charged, they can influence the received radar spectrum below 100 km, provided the electron density is sufficiently high (>109 m3). Here, we study an observation made with the EISCAT VHF radar on 9 January 2014 during strong particle precipitation so that incoherent scatter was observed down to almost 60 km altitude. We found that the measured spectra were too narrow in comparison to the calculated spectra. Adjusting the collision frequency provided a better fit in the frequency range of ± 10–30 Hz. However, this did not lead to the best fit in all cases, especially not for the central part of the spectra in the narrow frequency range of ±10 Hz. By including a negatively charged dust component, we obtained a better fit for spectra observed at altitudes of 75–85 km, indicating that dust influences the incoherent-scatter spectrum at D-region altitudes. The observations at lower altitudes were limited by the small number of free electrons, and observations at higher altitudes were limited by the height resolution of the observations. Inferred dust number densities range from a few particles up to 104 cm−3, and average sizes range from approximately 0.6 to 1 nm. We find an acceptable agreement with the dust profiles calculated with the WACCM-CARMA (Whole Atmosphere Community Climate Model-Community Aerosol Radiation Model for Atmospheres) model. However, these do not include charging, which is also based on models.

Influence of operating parameters on the silt erosion performance of bare and coated SS304 steel

Purpose The purpose of this paper is to investigate the silt erosion performance of Bare, 75%Cr2O3 + 25%Al2O3 and 85%Cr2O3 + 15Al2O3-coated SS304 under various control parameters such as rotation speed, concentration of silt and particle size of silt used for making slurry. This can provide insight for using chromia and alumina-based coatings for hydro-turbines. Design/methodology/approach Taguchi approach was used to identify the effect of three input parameters on the bare and coated alloys. L16 orthogonal array is used for determining the signal-to-noise (S/N) ratio for each process parameter. For each level of parameters taken into consideration about the erosion wear, the arithmetic mean of the S/N ratio is calculated. On the essence of the results of S/N ratios, it is possible to determine the effect of the most dominating parameters of the erosion wear. Findings Results show that the erosion increases with an increase in silt concentration (Wt.%). It has been analyzed that the rotational speed has the most significant effect followed by the particle size and concentration on erosion wear for all uncoated and coated SS-304 samples. Maximum resistance to erosion is provided by 85%Cr2O3 + 15%Al2O3. The least erosion wear for process parameters has occurred at the optimal parametric combination of rotational speed (N) = 415 rev/min, concentration (C) = 15 Wt.% and particle size range as <53 µm for uncoated and coated stainless steel. Originality/value The study clearly shows the silt erosion performance of chromia and alumina coatings of different compositions at different input parameters. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0028/

Temporal changes in geographic range and population size of the Santa Cruz Black Salamander

Abstract The Santa Cruz Black Salamander Aneides niger is a priority 3 California species of special concern with a restricted geographic range confined to the Santa Cruz Mountains. Anecdotal observations suggest that the species was relatively abundant in the early 1900’s, but it has become more difficult to find in the past few decades. To better understand if the species has undergone population size fluctuations, we analyzed mitochondrial and nuclear sequence data to examine levels of genetic variation, phylogeographic structure, and test for signatures of population size change. We then reconstructed the climatic suitability for the species to A) determine if past climate fluctuations could have influenced range size and genetic diversity, and B) to estimate the effects of future climate change on geographic range suitability as a proxy for possible future population size change. Genetic analyses detected low levels of genetic variation and a general lack of genetic structuring, suggesting a recent genetic bottleneck. While neutrality tests of individual loci were non-significant, skyline plot and isolation-with-migration analyses detected a relatively recent reduction in population size. These genetic results should be interpreted with consideration of the limited number of localities and individuals that have been sampled for this species. Climatic suitability for Santa Cruz Black Salamanders was much lower during the last glacial maximum, which could be the cause of the detected historical change in population size. Future projections of climatic suitability under a high emission scenario suggest a dramatic geographic range restriction to coastal areas. These projections highlight the need for the protection of coastal habitat patches to preserve existing coastal populations, and to maintain connectivity between coastal and inland habitats to allow the westward movement of populations and genes in response to climate change.

Endogenous Antimicrobial-Immunomodulatory Molecules: Networking Biomolecules of Innate Immunity.

Endogenous antimicrobial-immunomodulatory molecules (EAIMs) are essential to immune-mediated human health and evolution. Conventionally, antimicrobial peptides (AMPs) have been regarded as the dominant endogenous antimicrobial molecule; however, AMPs are not sufficient to account for the full spectrum of antimicrobial-immunomodulatory duality occurring within the human body. The threat posed by pathogenic microbes is pervasive with the capacity for widespread impact across many organ systems and multiple biochemical pathways; accordingly, the host needs the capacity to react with an equally diverse response. This can be attained by having EAIMs that traverse the full range of molecular size (small to large molecules) and structural diversity (including molecules other than peptides). This review identifies multiple molecules (peptide/protein, lipid, carbohydrate, nucleic acid, small organic molecule, and metallic cation) as EAIMs and discusses the possibility of cooperative, additive effects amongst the various EAIM classes during the host response to a microbial assault. This comprehensive consideration of the full molecular diversity of EAIMs enables the conclusion that EAIMs constitute a previously uncatalogued structurally diverse and collectively underappreciated immuno-active group of integrated molecular responders within the innate immune system's first line of defence.

Perancangan Produk Aksesoris Fashion dengan Pemanfaatan Limbah HDPE dan PPE

Plastic is the most frequently used material as a storage container by the public. Its various purposes, wide range of colors, types, and sizes, its versatility makes plastic a popular choice of material. One of the characteristics of plastic is its single-use, which implies it often being thrown away after one use and increases the amount of plastic waste in circulation. One of the most frequently found plastic wastes in circulation is HDPE plastic, which has become a pollutant that contaminates both land and bodies of water. Management of plastic waste is currently still ineffective, that eventually end up in landfills or burned. HDPE plastic waste can be processed and repurposed into a new product to produce jewelry designs. HDPE plastic that will be processed will undergo a meticulous and attentive process to ensure its quality and cleanliness, so it can remain safe when it has direct contact to human skin. Plastic that is one of the biggest pollutants in the world, can be repurposed and produced as a new product that can be used every day, to reduce the number of plastic pollutants.

Microplastic concentration, characterization, and size distribution in the Delaware Bay estuary

Microplastic (MP) pollution has been widely reported across water matrices including in estuaries, which are important for the understanding of oceanic MPs. Estuaries can greatly alter the fate, transport, size distribution, and abundance of plastic pollution. The aim of this study was to quantify and characterize MP pollution in the Delaware Bay estuary USA, including the size distribution. Samples (N = 31) were collected from the mouth of the Delaware River to the coastal ocean including multiple frontal zones across two sampling campaigns (2019 and 2022). MP were extracted from the collected particles using wet peroxide oxidation and density separation with saturated sodium chloride. Particles collected on 500 μm mesh sieves were analyzed via Fourier transform infrared (FTIR) spectroscopy. Across all samples, 324 of the 1015 particles analyzed were MP, and 11 macroplastics were observed. MP concentrations ranged from below detection to 4.12 MP/m3 (mean 0.34 ± 0.80 MP/m3). No significant differences were observed between sampling sites; nonetheless, the two highest MP concentrations were observed when sampling along frontal zones with visible debris including macroplastics. Polyethylene (53%) and polypropylene (43%) were the most abundant polymers observed. The majority of the non-plastic particles were classified as particulate natural organic matter (82% of non-plastics). Particles from samples collected during 2022 (N = 864) also had color, morphology, and two size dimensions recorded. MP particle size was significantly associated with sampling site, with the coastal ocean sampling site generally having the smallest MPs. A correlation between total post-extraction particles and total plastic particles was observed. Aspect ratios for the plastics ranged from one to 40.7, with larger ratios for fibers, with a mean (±standard deviation) of 3.39 ± 4.72 (unitless). These aspect ratios can be used to select shape factors used to estimate the total volume of MP in the studied size range. Overall, these results can help inform fate, transport, and risk assessments related to estuarine plastic pollution.

Scrutinizing the chemical and morphological alterations of microfibers released from household washing machines under varying temperature conditions

AbstractTo fulfill a huge demand that is arising globally due to the skyrocketing population, the textile industry is shifting toward cheaper, sturdier, enduring fabrics. Apparently, innovations are turning out to be banes instead of boons, as they are generating a lot of waste, leading to the destruction of the environment. Microfibers are one such example of an emerging environmental contaminant with several irreversible, health, and ecosystem repercussions. This study deals with the effects of temperature on the generation of microfibrils from washing machines. Three different temperatures ranging from lower to higher were considered. The net weight of microfibers released from higher temperatures was found to be 1132.5 ± 41.3 mg/20 L using gravimetric analysis. The fibers released from the higher temperature, that is, 60°C, were 2.7 and 1.6 times higher than those released from colder temperatures, 30 and 40°C, respectively. The length and diameter of these microfibers were in the microplastic size range. The polyester fiber was found to be released in higher amounts after identification with Fourier transform infrared and Raman spectroscopy. The results of this study can help consumers implement sustainable behavior and regulations to lessen the release of microfibers from washing household textiles.

Porous ZnO Nanoparticles for Low‐Temperature, Specific and Selective Acetone Sensing

AbstractThis study used a hydrothermal approach to create porous ZnO nanoparticles with the help of glucose (Glu), cetyltrimethylammonium bromide (CTAB), and polyvinylpyrrolidone (PVP). The morphological characterization revealed some small pores on the surface of the samples, all of which were in the 10–20 nm pore size range. The gas test revealed that the Glu‐ZnO material performed best for acetone at 120 °C, with a response value of 82 for 100 ppm, which was approximately ten times for that of pure ZnO (8.6), and the response/recovery time was also twice as short.

Wolverine population density and home range size in Arctic Alaska

AbstractUnderstanding the spatial requirements of exploited wildlife species, including population density and home range size, is important for wildlife management and conservation. Wolverines (Gulo gulo) are hunted and trapped across the Arctic, and are vulnerable to numerous, often interrelated, threats resulting from anthropogenic changes in their environment. Previous population density estimates for wolverines in the Arctic range tenfold, from the lowest to highest available for the species, limiting their utility outside the specific areas and times they were derived. The most recent density estimate in Arctic Alaska, USA, was produced 4 decades ago and was derived from a relatively small study area. We evaluated wolverine population density and home range size across the North Slope of Alaska during 2017–2022 using global positioning system (GPS)‐based collar data and spatial capture‐recapture models. Population density estimates were 2.0 individuals/1,000 km2 (95% credible interval = 1.3–3.5) in 2018 and 2.8 individuals/1,000 km2 (95% credible interval = 1.7–3.5) in 2021. Median home range sizes modeled with autocorrelated kernel density estimators and Ornstein‐Uhlenbeck foraging movement processes were 699 km2 (range = 158–2,895 km2) among 12 females and 2,332 km2 (range = 797–4,699 km2) among 10 males. These population density estimates are nearly 10 times lower than the previous estimate for Arctic Alaska. We recommend incorporating this information into management strategies to ensure sustainable harvest, particularly as the region's remote areas are more efficiently accessed by hunters and are being considered for transportation corridors supporting new industrial development.

Long‐term tracking reveals the influence of body size and habitat type on the home range of Antillean manatees (Trichechus manatus manatus)

AbstractAntillean manatees (Trichechus manatus manatus) are endangered coastal, marine, and riverine megaherbivores with high environmental plasticity, constrained by tidal and seasonal water level cycles that affect access to food and fresh water. Accurate quantification of the species' habitat requirements, typically achieved through home range (HR) estimation, is required to implement area‐based conservation initiatives. In this study, we used GPS tracking data from 38 wild and captive‐rehabilitated released manatees to estimate HR using autocorrelated kernel density estimators (AKDE) and average time speed. We investigated whether body size, habitat type, sex and behavioural group influence home range size due to energy requirements, resources availability, a scramble‐competitive polygyny mating system, and adaptation to the wild. Eighteen manatees exhibited range‐resident behaviour, with a mean 95% home range of 72.96 km2 (± 218.52) and a median of 10.69 km2. The mean daily speed was estimated to be 13.47 km/day (± 4.16). Home range and body size were positively correlated, consistent with HR allometry theory. Long‐term tracked individuals showed a trend of increasing HR over time. Only four released animals (17.4%) were range‐resident, suggesting that they may need additional time to establish a home range. Individuals using only the marine environment had larger home ranges compared to mixed (marine and estuarine) and estuarine environments, probably due to freshwater availability. Our study contributes to the understanding of the factors driving manatee movement and provides more accurate estimates of area requirements, which can inform the establishment and zoning of marine protected areas.

Correction method for depth and field size dependence in Octavius 1000 SRS patient-specific QA

Stereotactic body radiation therapy (SBRT) and stereotactic radiosurgery (SRS) are advanced techniques capable of delivering higher doses of radiation precisely to small and complex targets. As these higher doses are delivered, the significance of patient-specific quality assurance becomes increasingly crucial to ensure both the effectiveness and safety of treatment. This study investigates the depth and field size dependence in Octavius 1000 SRS patient-specific quality assurance (PSQA), which is vital for ensuring accuracy in modern radiotherapy treatments. It comprehensively compares the performance of the Octavius 1000 SRS array against standard treatment planning system calculations, focusing on various field sizes and depths. An extensive measurement process was performed, wherein output factors were analyzed across a range of field sizes, from very small (1 × 1 cm2) to larger fields (10 × 10 cm2), at different depths (5 cm, 10 cm, and 15 cm). Our results highlighted significant variations in the measurement accuracy, dependent on the field size and depth, which underscored the challenge involved in ensuring precise dosimetry in PSQA for small fields. The largest discrepancy observed was 2.65% for a 1 × 1 cm2 field size at a depth of 15 cm. Based on these findings, a novel correction method tailored for small field sizes and varying depths was proposed. This method enhances the accuracy and reliability of PSQA in advanced radiotherapy to ensure that the delivered dose conforms closely to the planned dose, which is a critical aspect in treatments targeting small and complex tumor volumes. Through the proposed correction, this study aims to bridge the gap between calculated and measured dose distributions, thus contributing significantly to the refinement of PSQA processes in radiotherapy.

Micropolar effects on the effective shear viscosity of nanofluids

The modified size-dependent Einstein's and Brinkman's solutions are established for the effective shear viscosity of rigid particle suspensions taking into account the micropolar effects in the base fluid. Solutions are obtained based on the homogenization approach and allow us to take into account the influence of the particle size. Two non-classical parameters arise in the considered micropolar solutions: the length scale parameter and the coupling (micropolarity) number of the base fluid. The solutions developed are validated using tests performed with polydimethylsiloxane based TiO2 nanofluids as well as other published data on the size-dependent shear viscosity of different nanofluids. Good agreement between the predictions and the experimental data is established across a wide range of volume fractions and size of nanoparticles. The possibility for unique identification (at given temperature) of the micropolar parameters of the base fluids is shown. Temperature-dependent values of non-classical rotational and spin viscosities of polydimethylsiloxane, ethylene glycol, and water are evaluated.

Toward Building a Virtual Laboratory to Investigate Rainfall Microphysics at Process Scales

Abstract A 3D numerical model was built to serve as a virtual microphysics laboratory (VML) to investigate rainfall microphysical processes. One key goal for the VML is to elucidate the physical basis of warm precipitation processes toward improving existing parameterizations beyond the constraints of past physical experiments. This manuscript presents results from VML simulations of classical tower experiments of raindrop collisional collection and breakup. The simulations capture large raindrop oscillations in shape and velocity in both horizontal and vertical planes and reveal that drop instability increases with diameter due to the weakening of the surface tension compared with the body force. A detailed evaluation against reference experimental datasets of binary collisions over a wide range of drop sizes shows that the VML reproduces collision outcomes well including coalescence, and disk, sheet, and filament breakups. Furthermore, the VML simulations captured spontaneous breakup, and secondary coalescence and breakup. The breakup type, fragment number, and size distribution are analyzed in the context of collision kinetic energy, diameter ratio, and relative position, with a view to capture the dynamic evolution of the vertical microstructure of rainfall in models and to interpret remote sensing measurements. Significance Statement Presently, uncertainty in precipitation estimation and prediction remains one of the grand challenges in water cycle studies. This work presents a detailed 3D simulator to characterize the evolution of drop size distributions (DSDs), without the space and functional constraints of laboratory experiments. The virtual microphysics laboratory (VML) is applied to replicate classical tower experiments from which parameterizations of precipitation processes used presently in weather and climate models and remote sensing algorithms were derived. The results presented demonstrate that the VML is a robust tool to capture DSD dynamics at the scale of individual raindrops (precipitation microphysics). VML will be used to characterize DSD dynamics across scales for environmental conditions and weather regimes for which no measurements are available.

Enhancing data retrieval efficiency in large-scale JavaScript object notation datasets by using indexing techniques

<div class="translate-tooltip-mtz green sm-root translate hidden_translate"><div class="header-wrapper"><div class="header-controls"><span>The use of JavaScript Object Notation (JSON) format as a Not only Structured Query Language (NoSQL) storage solution has grown in popularity, but has presented technical challenges, particularly in indexing large-scale JSON files. This has resulted in slow data retrieval, especially for larger datasets. In this study, we propose the use of JSON datasets to preserve data in resource survey processes. We conducted experiments on a 32-gigabyte dataset containing 1,000,000 transactions in JSON format and implemented two indexing methods, dense and sparse, to improve retrieval efficiency. Additionally, we determined the optimal range of segment sizes for the indexing methods. Our findings revealed that adopting dense indexing reduced data retrieval time from 15,635 milliseconds to 55 milliseconds in one-to-one data retrieval, and from 38,300 milliseconds to 1 millisecond in the absence of keywords. In contrast, using sparse indexing reduced data retrieval time from 33,726 milliseconds to 36 milliseconds in one-to-many data retrieval and from 47,203 milliseconds to 0.17 milliseconds when keywords were not found. Furthermore, we discovered that the optimal segment size range was between 20,000 and 200,000 transactions for both dense and sparse indexing.</span></div></div></div>