Size Range Research Articles

Synergy of engineered gelatin methacrylate-based porous microspheres and multicellular assembly to promote osteogenesis and angiogenesis in bone tissue reconstruction

One of the key challenges in bone defects treatment is providing adequate and stable blood supply during new tissue regeneration. Mesenchymal stem cells (MSCs) and endothelial cells (ECs) have great potential to promote osteogenesis and angiogenesis during bone defect repair through paracrine effects, but their therapeutic efficacy depends on effective cellular assembly and delivery. In this work, we developed various microspheres with different pore sizes for multi-cellular delivery to enhance the angiogenic and osteogenic capability via combining microfluidic and gradient freeze-drying techniques. The particle and pore size of fabricated porous gelatin methacrylate (GelMA)-based hydrogel microspheres (PGMS) could be controllable through adjusting the freezing time of hydrogel microspheres, the range of particles and pores size are 150–250 μm and 10–100 μm with different freezing time from 0 min to 30 min. The optimized particle size (200.8 ± 14.2 μm) and pore size (11.2 ± 1.9 μm) were explored to promote cell assemble, adhesion, growth, and proliferation in the PGMS. Furthermore, the co-assembly and delivery of bone marrow mesenchymal stem cells (BMSCs) and human umbilical vein endothelial cells (HUVECs) on the PGMS was achieved and an optimal cellular ratio of BMSCs to HUVECs (20:2) was established for co-culturing of them to achieve optimal paracrine effects, further promoting osteogenic differentiation and angiogenesis. Finally, results from both in vitro and in vivo experiments showed that the developed PGMS with co-assembly of BMSCs to HUVECs contributed to accelerate bone regeneration and vascularization process daringly, exhibited great potential in vascularized bone tissue reconstruction.

Ecological and social drivers of Mexican Wolf home range size across spatiotemporal scales

Ecological and social drivers of Mexican Wolf home range size across spatiotemporal scales

Crater Equilibrium State Characterization given Crater Production from a Single Power Law

We generalize the crater equilibrium concept, a terminal state on a cratered surface where the balance of crater production and erasure apparently limits the crater population from further growth. Assuming the crater production consists of a single power law, our model identifies four classes of crater equilibrium. The first class is the most common state, where the power-law slope for the equilibrium size–frequency distribution is independent of the crater production slope power. The second class arises when there is efficient degradation of larger craters by smaller crater production, which results in dependence of the crater equilibrium slope power on the crater production slope power. The third class is another common state when a shallow production function causes a crater equilibrium state with a similarly shallow slope. This class results from the enhanced degradation of smaller craters by larger crater production. The fourth class is a combination of the second and third classes. We further compare the concept of geometric saturation, which has been widely used to quantify the level of crater equilibrium, and that of cookie-cutter saturation. We present a crucial update to the cookie-cutter saturation concept that brings models closer to the reality of crater accumulation over a range of sizes than the geometric saturation concept. Our model offers simpler analytical formulae for cookie-cutter saturation and proposes this concept as a more meaningful reference to argue the crater equilibrium level. Our work and earlier studies confirm the consistency of the crater equilibrium concepts, enabling deeper interpretations of crater equilibrium.

Global Data Compilation Across Climate Gradients Supports the Use of Common Allometric Equations for Three Transatlantic Mangrove Species.

Predicting the distribution, structure, and biomass of mangrove forests is an area of high research interest. Across the Atlantic East Pacific biogeographic region, three species are common and abundant members of local mangrove communities; Rhizophora mangle, Avicennia germinans, and Laguncularia racemosa. Biomass prediction for these species has relied on two approaches: site-specific allometries based on the idea that environmental/climatic differences between sites drive growth differences, or the use of common allometric equations based on the idea that site driven differences are minimal. Meta-analyses of global compilations of interspecific plot level data (e.g., mean canopy height, stand basal area) show trends in size and structure with climatic variables, however this has not been critically evaluated across these species using empirical allometric growth functions. We compared allometric equations derived from 590 individuals within and across nine broadly distributed sites at interspecific and intraspecific levels and explored the influence of climatic variables on allometric slopes and intercepts. Assessing variables that can be used to predict biomass in the field (height, diameter at breast height (DBH), canopy spread), we find interspecific root mean squared errors similar to or smaller than most intraspecific or site-specific equations, particularly when examining sites with sample sizes above recommended values. We also find significant effects of several climatic variables on growth allometries with the strongest effects from minimum temperature followed by precipitation seasonality. Our results suggest that while climate has a clear influence on mangrove allometric growth, common equations may have utility in biomass prediction. Future methodological improvements, particularly larger sample sizes across the entire available size range, combined with data from a broader range of growth conditions will further inform which allometric relationships exhibit the most variability within and across sites and which variables best predict mangrove biomass.

Global analysis of acoustic frequency characteristics in birds.

Animal communication plays a crucial role in biology, yet the wide variability in vocalizations is not fully understood. Previous studies in birds have been limited in taxonomic and analytical breadth. Here, we analyse an extensive dataset of >140 000 recordings of vocalizations from 8450 bird species, representing nearly every avian order and family, under a structural causal model framework, to explore the influence of eco-evolutionary traits on acoustic frequency characteristics. We find that body mass, beak size, habitat associations and geography influence acoustic frequency characteristics, with varying degrees of interaction with song acquisition type. We find no evidence for the influence of vegetation density, sexual dimorphism, range size and competition on our measures of acoustic frequency characteristics. Our results, built on decades of researchers' empirical observations collected across the globe, provide a new breadth of evidence about how eco-evolutionary processes shape bird communication.

Characterizing heterogeneities in the subsurface with an ultra-wideband GPR: Application to WISDOM, the GPR of the Rosalind Franklin ExoMars mission

Ultra-wideband Ground Penetrating Radars (GPR) are sensitive to a large range of scatterer sizes. Considering fractal heterogeneities in the subsurface, we propose a method to retrieve their typical size L. The determination of L with this method does not require a priori knowledge of the statistical distribution of permittivity values in the investigated subsurface. The method relies on the analysis of the backscattered signal by frequency/wavelength sub-bands. It is adapted to WISDOM, the GPR onboard the rover of the Rosalind Franklin ExoMars mission (ESA), but can be applied to any ultra-wideband GPR. Based on numerical simulations, a maximum in volume backscattering is reached at the wavelength (in the subsurface) . We demonstrate that this maximum, and therefore L, can be identified even in presence of moderate electrical losses, compatible with conditions expected on the Moon or Mars. Assuming an average permittivity of 5, WISDOM (0.5-3 GHz) data products could be used to estimate L as long as it is in the range 0.9-4.2 cm The retrieval method for L is validated on experimental WISDOM data acquired in a controlled environment.

A study on the effect of cylindrical shell scaled model size on ESCM prediction accuracy

Abstract Current research on similitude theory has introduced numerous methods to address the distortion similitude model. However, these methods still encounter some challenges in guiding the design of scale models, such as insufficient accuracy and a limited range of design sizes. In this paper, the Energy Similitude Correction Method (ESCM) is used to analyze the effect of size design on the accuracy of cylindrical shell-scaled models, taking into account distortion factors such as wall thickness and thermal environment. The research shows that the closer the model size is to the prototype size, the higher the prediction accuracy is. Additionally, larger size combinations are more reliable for predicting the prototype frequency in scaled model tests. The research results provide a basis for the reasonable design of the size of the scaled model group and make a positive contribution to improving the prediction accuracy of the scaled model.

Liquid and gas permeabilities of nanostructured layers: Three-dimensional lattice Boltzmann simulation

Liquid water and gas permeabilities in nanostructured catalyst layers (CLs) (pore size ∼10–150 nm) and microporous layers (MPLs) (pore size ∼50 nm-5 μm) are crucial to reduce the mass transport loss in proton exchange membrane fuel cells (PEMFCs). Experimental measurement of their permeabilities poses great challenges due to their brittle and thin characteristics. Presently, considerable discrepancy exists in the reported permeability values for CLs and MPLs in the literature with variation spanning several orders of magnitude. This study digitally reconstructed various nanostructures of similar pore size as CLs and MPLs to calculate their permeabilities using the Lattice Boltzmann Method (LBM) based on no-slip (e.g. for liquid water flow in MPL and CL's secondary pores) or slip condition (e.g. for gas flow in MPL). Analysis was performed to evaluate the range of pore size in nanostructures for the two boundary conditions. A comprehensive investigation was conducted under various parameters such as the Reynolds number (Re), sphere diameter, porosity, and pore structure. The results revealed that permeability exhibits an increasing trend with the diameter and porosity. The predicted permeability of randomly arranged spheres agrees well with established correlations. The random sphere structure demonstrates higher permeability than their body-centered cubic (BCC) and face-centered cubic (FCC) counterparts. Under slip boundary condition, the permeability was enhanced, compared to the no-slip condition. This study's novelty lies in using distinct boundary conditions to assess the permeabilities of liquid and air, based on flow pattern analysis in the CL and MPL pore structures. A new empirical correlation describing the influence of the Knudsen number (Kn) on the slip permeability was developed, exhibiting consistency with simulation across the entire porosity spectrum.

Statistics of drops generated from ensembles of randomly corrugated ligaments

The size of drops generated by the capillary-driven disintegration of liquid ligaments plays a fundamental role in several important natural phenomena, ranging from heat and mass transfer at the ocean-atmosphere interface to pathogen transmission. The inherent nonlinearity of the equations governing the ligament destabilization leads to significant differences in the resulting drop sizes, owing to small fluctuations in the myriad initial conditions. Previous experiments and simulations reveal a variety of drop size distributions, corresponding to competing underlying physical interpretations. Here, we perform numerical simulations of individual ligaments, the deterministic breakup of which is triggered by random initial surface corrugations. The simulations are grouped in a large ensemble, each corresponding to a random initial configuration. The resulting probability distributions reveal three stable drop sizes, generated via a sequence of two distinct stages of breakup. Four different distributions are tested, volume-based Poisson, Gaussian, Gamma, and Log-Normal. Depending on the time, range of droplet sizes and criteria for success, each distribution has successes and failures. However, the Log-Normal distribution roughly describes the data when fitting both the primary peak and the tail of the distribution while the number of droplets generated is the highest, while the Gamma and Log-Normal distributions perform equally well when fitting the tail. The study demonstrates a precisely controllable and reproducible framework, which can be employed to investigate the mechanisms responsible for the polydispersity of drop sizes found in complex fluid fragmentation scenarios.

Thermodynamics of Giant Molecular Clouds: The Effects of Dust Grain Size

The dust grain size distribution (GSD) likely varies significantly across star-forming environments in the Universe, but its impact on star formation remains unclear. This ambiguity arises because the GSD interacts nonlinearly with processes like heating, cooling, radiation, and chemistry, which have competing effects and varying environmental dependencies. Processes such as grain coagulation, expected to be efficient in dense star-forming regions, reduce the abundance of small grains and increase that of larger grains. Motivated by this, we investigate the effects of similar GSD variations on the thermochemistry and evolution of giant molecular clouds (GMCs) using magnetohydrodynamic simulations spanning a range of cloud masses and grain sizes, which explicitly incorporate the dynamics of dust grains within the full-physics framework of the STARFORGE project. We find that grain size variations significantly alter GMC thermochemistry: the leading-order effect is that larger grains, under fixed dust mass, GSD dynamic range, and dust-to-gas ratio, result in lower dust opacities. This reduced opacity permits interstellar radiation field and internal radiation photons to penetrate more deeply. This leads to rapid gas heating and inhibited star formation. Star formation efficiency is highly sensitive to grain size, with an order-of-magnitude reduction when grain size dynamic range increases from 10−3–0.1 μm to 0.1–10 μm. Additionally, warmer gas suppresses low-mass star formation, and decreased opacities result in a greater proportion of gas in diffuse ionized structures.

PCGmix: A Data-Augmentation Method for Heart-Sound Classification.

Cardiovascular diseases (CVDs) are a leading cause of mortality worldwide, responsible for 32% of all deaths, with the annual death toll projected to reach 23.3 million by 2030. The early identification of individuals at high risk of CVD is crucial for the effectiveness of preventive strategies. In the field of deep learning, automated CVD-detection methods have gained traction, with phonocardiogram (PCG) data emerging as a valuable resource. However, deep-learning models rely on large datasets, which are often challenging to obtain. In recent years, data augmentation has become a viable solution to the problem of scarce data. In this paper, we propose a novel data-augmentation technique named PCGmix, specifically engineered for the augmentation of PCG data. The PCGmix algorithm employs a process of segmenting and reassembling PCG recordings, incorporating meticulous interpolation to ensure the preservation of the cardinal diagnostic features pertinent to CVD detection. The empirical assessment of the PCGmix method was utilized on a publicly available database of normal and abnormal heart-sound recordings. To evaluate the impact of data augmentation across a range of dataset sizes, we conducted experiments encompassing both limited and extensive amounts of training data. The experimental results demonstrate that the novel method is superior to the compared state-of-the-art, time-series augmentation. Notably, on limited data, our method achieves comparable accuracy to the no-augmentation approach when trained on 31% to 69% larger datasets. This study suggests that PCGmix can enhance the accuracy of deep-learning models for CVD detection, especially in data-constrained environments.

Data Science Enables Management of Stealth Asphaltene Flow-Assurance Risk

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 216216, “Managing Stealth Asphaltene Flow-Assurance Potential Risk in Gas-Injection Field Based on Data Science Using Over 20-Year Accumulated Data Set,” by Hideharu Yonebayashi, SPE, and Takeshi Hiraiwa, SPE, Japan Oil Development, and Khuloud T. Al Khlaifi, SPE, ADNOC, et al. The paper has not been peer reviewed. _ Gas injection is recognized generally not only to improve oil recovery but also to increase the risk of asphaltene destabilization. The recent discovery of asphaltene deposits in a subject field motivated the operator to launch an immediate investigation to evaluate what critical risks might exist and consider appropriate mitigation. It was found that precipitated but invisible asphaltenes still can be flowable. This stealth asphaltene behavior could explain a possible mechanism of the first asphaltene observation in the upper reservoir. Introduction The subject giant offshore field in the Arabian Gulf has not experienced asphaltene-induced production deterioration during long-term lean hydrocarbon gas injection. The gas has been injected into the crestal area of two reservoirs (upper and lower) with peripheral powered seawater injection. Both reservoir fluids contain a small amount of asphaltenes (0.1–1.5 wt%) distributed at higher concentration at deeper locations. In May 2022, the first discovery of asphaltene deposits from the historical no-issued area in the upper reservoir motivated an immediate investigation for risk assessment and mitigation. A resulting study captured stealth asphaltenes, which were detected by a laser-light-scattering technique while high-pressure microscopy detected no visible asphaltene solid particles. Historical Asphaltene Data Accumulation The permeability range and pore-throat size of the subject field are relatively low in the lower reservoir compared with the upper. Both reservoirs are under highly unstable asphaltene-stability conditions. The reservoir pressure-maintenance scheme, consisting of dump-floodwater injection followed by peripheral powered seawater injection and crestal gas injection, however, has maintained asphaltene-free production except for the gas-injection pilot (GIP) during 2005–2009. No asphaltenes have been observed in the crestal gas-injection area; however, asphaltene deposits were observed in the GIP area in 2007. The injected gas was enriched gradually by a vaporizing gas-drive process. The previous studies involving numerical modeling analysis and laboratory experiments reported that enriched hydrocarbon gas can more easily allow asphaltene precipitation compared with lean hydrocarbon gas. GIP Asphaltene Risk Analysis (Upper Reservoir). In 2009, an asphaltene flow-assurance risk evaluation was conducted using the single-phase bottomhole sample collected from Well 6, which is 90 ft shallower that the GIP area and far from the crestal gas-injection area. Therefore, the Well 6 reservoir fluid was not affected by injection gas. The bottomhole condition of the GIP production well was entered into the asphaltene precipitation envelope (APE) that was expanded by injection-gas enrichment but never covered by the APE without an enrichment process. Latest Laboratory Analysis (Lower Reservoir). In 2022, an asphaltene flow-assurance risk evaluation was conducted. After the location was narrowed to a depth range, Well 1 was selected by taking an asphaltene gradient into account.

Effects of La3+ doping on the structural, vibrational, elemental, and dielectric characteristics of Sr-Ba-Zr2 R-type hexaferrite

Hexagonal ferrites possess physicochemical and dielectric features that make them highly favorable for absorption purposes. Due to its excellent characteristics at high frequencies, R-type hexagonal ferrite is specifically designed for efficient microwave absorption. Samples of R-type hexaferrite were prepared using the sol-gel auto-combustion process. The samples had the chemical composition Sr0.7Ba0.3Zr2Fe4-xLaxO11, where x ranged from 0.00 to 0.09 in increments of 0.03. This replacement seeks to enhance the understanding of how the La3+ ions affect the physicochemical characteristics of these ferrites, such as their structure, dielectric properties, XPS, and FTIR properties. The single phase of R-type hexaferrite is confirmed by the FTIR and XRD methods. The crystallite size of the samples of R-type hexaferrite doped with La was determined using three different methods. The crystallite size, determined using Sherrer's formula, ranged from 25.865 to 41.393 nm. Meanwhile, the size calculated using Williamson's method was between 36.084 nm and 62.32 nm. The Size-strain analysis revealed a size range of 24.26 nm to 27.31 nm. The FTIR spectra exhibit two intrinsic vibrational bands, labelled as υ1 and υ2, in the wavenumber range of 400 to 600 cm-1. The XPS examination verifies the elemental composition of a representative specimen that has been swapped with La. As the La3+ content increases, additional semicircles are formed, suggesting the existence of more mechanisms for polarization relaxation and a greater capacity for polarization loss. Out of all the compositions that were created, the material with a composition of x = 0.09 exhibits the highest absorption capabilities. This is because of its minimal reflection loss. By replacing the La3+ element in R-type hexaferrites, the peak of the sample moves towards the higher frequency range, indicating excellent microwave absorption properties. R-type hexaferrites are utilized in transformers to reduce eddy current losses and in microwave absorption devices.

Phase evolution and sintering behavior of high-performance IGTO sputtering targets

In-Ga-Sn-O (IGTO) targets are vital in preparing high-mobility IGTO thin film transistors. This study uses pressure slip casting and conventional sintering methods to prepare IGTO targets with three atomic ratios(IGTO-711=70:15:15, IGTO-712=70:10:20, IGTO-721=70:20:10 In:Ga:Sn at.%). With the increase of Ga content in the system, the phase composition of the IGTO targets changes from In2O3 and Ga1.6In6.4Sn2O16 to In2O3, Ga2In6Sn2O16 and GaInO3. Their densification activation energy has been calculated using constant heating rate experiments. It shows that the activation energy is independent of the density in the relative density range of 0.70-0.85, and the activation energy is significantly affected by the ease of reaction of the physical phases. The densification activation energies of samples IGTO-711, IGTO-712 and IGTO-721 are 230.5±42 kJ/mol, 926.4±58 kJ/mol, 582.9±52 kJ/mol, respectively. The presence of the GaInO3 phase facilitates the densification process of IGTO targets. Ultimately, IGTO-712 targets with a relative density of 99.01%, a resistivity of 0.42 mΩ·cm, a microhardness of 1024.31 HV2, and a uniform grain size range of 3∼5 μm are achieved at 1450°C for 20 hours in an oxygen atmosphere.

Pore-expanded phosphate-functionalized mesoporous silica microsphere composites: One-pot synthesis and application for removing uranium from water

This study focused on the development of mesoporous silica microspheres with controllable mesopores for the efficient removal of uranium from nuclear waste. Utilizing n-dodecylamine as a structure-directing agent and di(2-ethylhexyl)phosphoric acid (HDEHP) as a co-templating agent, we achieved the synthesis of large silica microspheres (10–100 µm) with uniform mesopores. The incorporated HDEHP served as both a swelling agent and a phosphate-functionalization reagent, facilitating the adsorption of bulky organic uranium sequestration agents. Our approach circumvented the need for high-temperature calcination and extensive use of organic solvents, making it an environmentally friendly and cost-effective alternative. The synthesized silica microspheres demonstrated superior adsorption capacity for uranyl ions, which was attributed to their large pore size and high surface area. The adsorption isotherms, well-fitted to the Langmuir model, suggested a maximum adsorption capacity of 136 mg g−1 at pH 4.0 with a uranium concentration of 100 mg L−1 to maintain a stable soluble phase. However, many studies have often overlooked solid-phase formation due to hydrolysis, which can overestimate the adsorption capacity. In addition, the particle size range enabled easy recovery through low-g-force centrifugation or natural sedimentation. This study highlighted the potential of phosphate-functionalized mesoporous silica microspheres as effective and reusable uranium adsorbents, thereby addressing both energy sustainability and environmental safety. The practical applications of these materials in uranium recovery and nuclear waste management underscore their importance in the nuclear industry.

Thermo sensitive and pH responsive surface modulated transdermal green tea nanogel: Structural, physiochemical and in vitro safety investigations

An altered simplistic biomimetic whole green tea extract-loaded nanogel (GE-C-NGL) was fabricated possessing pH-responsive and temperature-dependent intracellular transdermal nanotherapy. A biocompatible chitosan nanogel subsequently surface modified with oleic acid aiding Pluronic 127 discharging green tea extract on transdermal delivery was evaluated in light of structural, physiochemical, thermal, and in vitro toxicological factors by optical class, index class and spectrophotometrically class, and in vitro cell line toxicological evaluations, which precisely elaborated the nanosize particle size range and significant drug entrapment suggesting a spherical and thermo stable nanogel system. Additionally, sustained drug release configuration is displayed in mildly acidic conditions (pH 6) signifying ultra-pH sensitivity of GE-C-NGL. Moreover, strong mucin binding ability, pH-dependent swelling efficiency, negligible hemolytic ratio, and high antioxidant activity were obtained for enhanced transdermal efficacy. The comprehensive augmented polymeric blend transdermal nanogel, in light of the above preclinical biological and toxicological evaluations, evidently targets transdermal potential with promising bacterial biodegradable nanodrug therapy in clinical platforms.

Microbial biosurfactant-mediated green synthesis of zinc oxide nanoparticles (ZnO NPs) and exploring their role in enhancing chickpea and rice seed germination

Malnutrition is one of the greatest challenges faced by humanity, which may be addressed by improving crop productivity to ensure food security. However, extensive use of synthetic fertilizers can lead to soil fertility degradation. This study highlights the potential of combining nanotechnology with biotechnology to enhance the germination rates of commercially important crop seeds. Bacterial biosurfactant extracted from a newly isolated Klebsiella sp. strain RGUDBI03 was used as a reducing and capping agent for the synthesis of zinc oxide nanoparticles (ZnO NPs) through a simple method. Extensive characterization of ZnO NPs through electron microscopic analysis showed well-dispersed, homogeneous NPs with a size range of 2–10 nm. High-resolution transmission electron microscopy (HR-TEM) images also revealed molecular fringes of 0.26 nm in single crystal ZnO NPs, with approximately 50% of the NPs exhibiting a size range of 2–4 nm. X-ray diffraction (XRD) results of ZnO NPs indicated the presence of (100), (002), (101), (102), (200), and (112) planes, confirming their crystalline nature. The presence of C = C–H, C = C, C–H, and C = C groups in both the bacterial biosurfactant and ZnO NPs, as depicted by Fourier-transform infrared spectroscopy (FTIR) spectra, confirmed the function of the biosurfactant as a reducing and capping agent. The nano-primed chickpea (Cicer arietinum) and rice (Oryza sativa) seeds showed an increase in water uptake rate, 89% and 92% respectively, compared to the control (73% and 44%), leading to an enhanced germination rate of 98% and 76%, compared to their respective controls (80% and 30%) under optimized conditions. Additionally, the nano-primed seeds exhibited higher levels of α-amylase activity in both seeds (0.37 mg/g for chickpea and 2.49 mg/g for rice) compared to the control. Notably, the ZnO NP priming solution exhibited no cytotoxicity on red blood cells and earthworms (Eudrilus eugeniae), indicating their non-cytotoxic and eco-friendly nature for future field trials.

Vertical Variability in morphology, chemistry and optical properties of the transported Saharan air layer measured from Cape Verde and the Caribbean.

The structural properties of the Saharan air layer (SAL) including chemical, morphological and optical properties were measured during the Saharan Aerosol Longrange TRansport and Aerosol Cloud interaction Experiment (SALTRACE- June/July 2013). Flight measurements were done from Cape Verde and the Caribbean. Changes happening with the chemical composition, mixing, shape and absorption of aerosol single particles (particle diameter range 0.5-3.0 µm) inside SAL during its transport are detailed. Dust-dominated SAL (relative number abundance >90%) and generally low mixing (<1% with sea-salt and sulphates) are observed at both locations. The change in shape (determined as aspect ratio (AR)) after transatlantic transport was statistically not significant. The iron oxide fraction, important for light absorption, contributed 6.0-6.8% to SAL dust. A lower amount of Fe oxides was observed in transported SAL, especially for the size range 0.5-1.5 µm. This reduction in Fe oxide content resulted in a 4% decrease (0.0046-0.0044) in dust imaginary refractive index and a 1% decrease in single scattering albedo (0.802-0.809) at 520 nm. Our work suggests including the size distribution of iron oxides and their particular behaviour in future experiment/model studies.

The Effect of Lifting Straps on the Prediction of the Maximal Neuromuscular Capabilities and 1 Repetition Maximum During the Prone Bench Pull Exercise.

Miras-Moreno, S and García-Ramos, A. The effect of lifting straps on the prediction of the maximal neuromuscular capabilities and 1 repetition maximum during the prone bench pull exercise. J Strength Cond Res 38(11): e638-e644, 2024-This study examined the effects of using lifting straps in the prone bench pull exercise on (a) the magnitude of the load-velocity (L-V) relationship variables (load-axis intercept, velocity-axis intercept, and area under the L-V relationship line) and (b) the accuracy of the L-V relationship in predicting the 1 repetition maximum (1RM). In a counterbalanced sequence, 20 resistance-trained male subjects performed 2 identical experimental sessions, 1 with and 1 without lifting straps. During each session, subjects sequentially lifted 4 loads (14 kg, 85% 1RM, and 2 intermediate loads), followed by 1RM attempts. The L-V relationship was modelled using both multiple-point (4 loads) and 2-point (14 kg-85% 1RM) methods, whereas 3 types of minimal velocity thresholds (MVT) were used for 1RM prediction: (a) general MVT (averaged across the subjects velocity of the 1RM trial), (b) individual MVT (individual velocity of the 1RM trial), and (c) average optimal MVT (averaged across the subjects velocity that eliminates the differences between the actual and predicted 1RM). Irrespective of lifting straps use, which had no impact on the L-V relationship or the accuracy of 1RM prediction, we observed: (a) greater L-V relationship variables when obtained by the 2-point method compared with the multiple-point method (p < 0.001; effect size range = 0.353-0.639) and (b) the lowest absolute errors (<4.0 kg) in 1RM prediction for the 2-point method combined with the average optimal MVT (p < 0.001). These results reinforce the 2-point method applied in field conditions and the average optimal MVT for the routine testing of the L-V relationship.

Evaluating the role of sex-related structure-function differences on airway aerosol transport and deposition.

Several experimental studies have found that females have higher particle deposition in the airways than males. This has implications for the delivery of aerosolized therapeutics and for understanding sex differences in respiratory system response to environmental exposures. This study evaluates several factors that potentially contribute to sex differences in particle deposition, using scale-specific structure-function models of one-dimensional (1-D) ventilation distribution, particle transport, and deposition. The impact of gravity, inhalation flow rate, and dead space are evaluated in 12 structure-based models (7 females; 5 males). Females were found to have significantly higher total, bronchial, and alveolar deposition than males across a particle size range from 0.01 to 10 μm. Results suggest that higher deposition fraction in females is due to higher alveolar deposition for smaller particle sizes and higher bronchial deposition for larger particles. Females had higher alveolar deposition in the lower lobes and slightly lower particle concentration in the left upper lobe. Males were found to be more sensitive to changes due to gravity, showing greater reduction in bronchial deposition fraction. Males were also more sensitive to change in inhalation flow rate and to scaling of dead space due to the larger male baseline airway size. Predictions of sex differences in particle deposition-that are consistent with the literature-suggest that sex-based characteristics of lung and airway size interacting with particle size gives rise to differences in regional deposition.NEW & NOTEWORTHY Sex differences in airway tract particle deposition are analyzed using computational models that account for scale-specific structure and function. We show that sex-related differences in lung and airway size can explain experimental observations of increased deposition fraction in females, with females tending toward enhanced fine particle deposition in the alveolar airways and enhanced bronchial deposition for larger particles.