Range Of Target Sizes Research Articles

A Scalable and Surfactant-Free Emulsion Method for Producing Microbeads from Varied Biomass Feedstocks.

Despite national and international regulations, plastic microbeads are still widely used in personal care and consumer products (PCCPs). These exfoliants and rheological modifiers cause significant microplastic pollution in natural aquatic environments. Microbeads from nonderivatized biomass like cellulose and lignin can offer a sustainable alternative to these nondegradable microplastics, but processing this biomass into microbeads is challenging due to limited viable solvents and high biomass solution viscosities. To produce biomass microbeads of the appropriate size range for PCCPs (ca. 200-800 μm diameter) with shapes and mechanical properties comparable to those of commercial plastic microbeads, we used a surfactant-free emulsion/precipitation method, mixing biomass solutions in 1-ethyl-3-methylimidazolium acetate (EMImAc) with various oils and precipitating with ethanol. While yield of microbeads within the target size range highly depends on purification conditions, optimized protocols led to >90% yield of cellulose microbeads. Kraft lignin was then successfully incorporated into beads at up to 20 wt %; however, higher lignin contents result in emulsion destabilization unless surfactant is added. Finally, the microbead shape and surface morphology can be tuned using oils of varying viscosities and interfacial tensions. Dripping measurements and pendant drop tensiometry confirmed that the higher affinity of cellulose for certain oil/IL interfaces largely controlled the observed surface morphology. This work thus outlines how biomass composition, oil viscosity, and interfacial properties can be altered to produce more sustainable microbeads for use in PCCPs, which have desirable mechanical properties and can be produced over a wide range of shapes and surface morphologies.

Raman imaging spectroscopic solutions for microplastics advanced analysis: Insights from Choqueyapu river basin (La Paz, Bolivia)

Microplastics (MPs) are causing global concern due to their role as vectors of environmental contaminants. Evaluating their impact on environmental compartments, particularly in sediment and freshwaters, remains challenging due to difficulties in gathering chemical and morphological data. In fact, the analytical process can vary depending on the matrix considered, the non-homogeneous characteristics of MPs, and the targeted size range. Sample treatment is crucial for sediments and waters, requiring a balance between matrix removal and preservation of the MPs. Consequently, MPs often remain embedded in significant amounts of the original matrices, compromising their characterisation. In this regard, Raman spectroscopy shows promise for their comprehensive molecular analysis. However, overcoming the drawbacks associated with fluorescence from organic matter, feldspar, or clays requires considerable effort. Effective signal acquisition necessitates fine-tuning parameters, including background reduction and signal-to-noise ratio amplification. Moreover, data handling involved in chemical scanning large surfaces at high resolution is a challenging task. To overcome these drawbacks, chemometrics have demonstrated high efficacy in processing and extracting targeted information. The application of chemometrics could be relevant in environmental studies due to the large number of samples, the complexity of signal acquisition, and the dataset volumes managed. As such, this study proposes spectroscopic analytical solutions, augmented by chemical imaging and algorithmic processing, for advanced MPs analysis. A spectroscopic working approach was devised and tested through a real case study conducted in the Choqueyapu River basin (La Paz, Bolivia). This methodology allowed the morphological, molecular and quantitative identification of over 44 particles/L and 91 MPs particles/kg, in water and sediment, respectively, consisting of PE, PET, PP, PS and PMMA. MP abundance varied significantly across studied areas, spanning 2 to 4 orders of magnitude. PET fibres predominated in freshwaters, while Lipari Sector sediments were hotspots for PE and PS fragments.

Comparative analysis of plan quality and delivery efficiency: ZAP-X vs. CyberKnife for brain metastases treatment

Purpose/ObjectivesZAP-X, a novel and dedicated radiosurgery (SRS) system, has recently emerged, while CyberKnife has solidified its position as a versatile solution for SRS and stereotactic body radiation therapy over the past two decades. This study aims to compare the dosimetric performance and delivery efficiency of ZAP-X and CyberKnife in treating brain metastases of varying target sizes, employing circular collimation.Methods and materialsTwenty-three patients, encompassing a total of 47 brain metastases, were included in the creation of comparative plans of ZAP-X and CyberKnife for analysis. The comparative plans were generated to achieve identical prescription doses for the targets, while adhering to the same dose constraints for organs at risk (OAR). The prescription isodose percentage was optimized within the range of 97–100% for each plan to ensure effective target-volume coverage. To assess plan quality, indices such as conformity, homogeneity, and gradient (CI, HI, and GI) were computed, along with the reporting of total brain volumes receiving 12Gy and 10Gy. Estimated treatment time and monitor units (MUs) were compared between the two modalities in evaluating delivery efficiency.ResultsOverall, CyberKnife achieved better CI and HI, while ZAP-X exhibited better GI and a smaller irradiated volume for the normal brain. The superiority of CyberKnife’s plan conformity was more pronounced for target size less than 1 cc and greater than 10 cc. Conversely, the advantage of ZAP-X’s plan dose gradient was more notable for target sizes under 10 cc. The homogeneity of ZAP-X plans, employing multiple isocenters, displayed a strong correlation with the target’s shape and the planner’s experience in placing isocenters. Generally, the estimated treatment time was similar between the two modalities, and the delivery efficiency was significantly impacted by the chosen collimation sizes for both modalities.ConclusionThis study demonstrates that, within the range of target sizes within the patient cohort, plans generated by ZAP-X and CyberKnife exhibit comparable plan quality and delivery efficiency. At present, with the current platform of the two modalities, CyberKnife outperforms ZAP-X in terms of conformity and homogeneity, while ZAP-X tends to produce plans with a more rapid dose falloff.

From Micro to Nano: Grinding Natural Magnetite Ore for Microalgae Harvesting

Microalgae represent a promising feedstock for sustainable biomass and energy. The low cell concentration after cultivation, however, limits the current application fields. Magnetic microalgae harvesting is a recent approach to overcome the economic limitations of exploiting this natural resource. Accordingly, different particle types have been applied, mainly synthetically produced magnetic nanoparticles, though none on an industrial scale. Particle sizes between a few micrometers and a few nanometers have not been tested. We expected 200–500 nm to be advantageous for harvesting and as a compromise between the highly available surface and good separation properties. However, this intermediate magnetite particle size between the micro- and nano-scale cannot be reached via chemical synthesis. Therefore, we ground natural magnetite ore in a planetary ball mill and an agitator bead mill producing particles in the targeted size range. Applying ore particles ground from ~6 µm to 250 nm yields harvesting efficiencies comparable to synthetically produced nanoparticles (Ø ~ 10 nm), with only half the BET surface. Complete harvesting of saline microalgae Microchloropsis salina is possible with ground particles at alkaline pH. We demonstrate the feasibility of a harvesting process with natural, low-cost, easily separable, and readily available magnetite ore particles as a promising step towards exploiting valuable microalgal products in life sciences.

One-step production of highly monodisperse size-controlled poly(lactic-co-glycolic acid) nanoparticles for the release of a hydrophobic model drug

Biodegradable polymeric nanoparticles are considered as promising drug delivery systems due to their high potential in tuning the release and alleviate side effects. However, particle greater than 200 nm can be detected by the immune system. Thus, this paper focuses on the elaboration of size-controlled nanoparticles of poly (lactic-co-glycolic acid) smaller than 200 nm encapsulating a model drug. For this purpose, the biodegradable polymer was first solubilized in ethyl acetate and then dispersed into water by different nanoemulsification devices: shear mixer, sonicator and elongational-flow reactor and micromixer. Last two devices showed the capacity to produce monomodal nanoparticles of targeted size range at different continuous to disperse phase volume ratios. On a second part, nanoparticles produced with the micromixer were employed as nanocarriers for rifampicin, a hydrophobic antibiotic. These drug-loaded nanoparticles were produced at different drug concentrations to study the effect of drug load on the particle properties. Different techniques such as dynamic light scattering, transition electron microscopy and ultraviolet spectroscopy were employed to thoroughly characterize the nanoparticle diameter, size dispersity and morphology, drug encapsulation efficiency and in vitro drug release profile. Nanoparticles produced with the micromixer, following a new phase pre-saturation approach, had a highly monomodal diameter as low as 63 nm and an encapsulation efficiency of 40% at 5% w/v drug load was measured. Drug release tests under sink conditions showed 44% ± 2% cumulative drug release within 8 days.

Binocular fusion enhances the efficiency of spot-the-difference gameplay.

Spot-the-difference, the popular childhood game and a prototypical change blindness task, involves identification of differences in local features of two otherwise identical scenes using an eye scanning and matching strategy. Through binocular fusion of the companion scenes, the game becomes a visual search task, wherein players can simply scan the cyclopean percept for local features that may distinctly stand-out due to binocular rivalry/lustre. Here, we had a total of 100 visually normal adult (18-28 years of age) volunteers play this game in the traditional non-fusion mode and after cross-fusion of the companion images using a hand-held mirror stereoscope. The results demonstrate that the fusion mode significantly speeds up gameplay and reduces errors, relative to the non-fusion mode, for a range of target sizes, contrasts, and chromaticity tested (all, p<0.001). Amongst the three types of local feature differences available in these images (polarity difference, presence/absence of a local feature difference and shape difference in a local feature difference), features containing polarity difference was identified as first in ~60-70% of instances in both modes of gameplay (p<0.01), with this proportion being larger in the fusion than in the non-fusion mode. The binocular fusion advantage is lost when the lustre cue is purposefully weakened through alterations in target luminance polarity. The spot-the-difference game may thus be cheated using binocular fusion and the differences readily identified through a vivid experience of binocular rivalry/lustre.

Sensitivity of Surface Acoustic Wave Sensors Based LiNbO3 128° Y-X and at-Quartz to PM10 and PM2.5

IntroductionParticulate matter (PM) was estimated to cause around 7 million premature deaths worldwide per year according to World Health organization [1]. These particles can cause diseases leading to premature death [2]. Over the last decade, the monitoring of PM became an important issue on a worldwide scale. The miniaturization of the existing bulky systems has also become necessary to reduce their cost. To address this need, a new miniaturized system for PM monitoring was previously developed in our team [3]. It takes advantage of both a 3 Lpm cascade impactor and surface acoustic waves (SAW) sensors to respectively separate and measure particles. The present study aims to compare the sensitivity of two SAW devices. The first exploits Love waves on an AT cut Quartz substrate and the second is based on Rayleigh waves from a LiNbO3 Y-X 128° substrates. The latter presents a high electromechanical coupling factor that could be exploited for the self-cleaning of the device after the measurement. This could allow overcoming the fouling issue faced with impactors that wouldn’t be solved with quartz based sensors which suffer from an insufficient electromechanical coupling. Method In this study we used a dedicated 3 Lpm cascade impactor equipped with SAW delay lines as collecting plate. The Rayleigh wave sensor and the Love wave sensor were designed and fabricated respectively on LiNbO3 Y-X 128° cut and AT-Quartz cut substrates using a conventional photolithography process. The interdigital transducers (IDT) consist of double finger pairs made of 200 nm thick aluminum with a periodicity p=10 µm and a wavelength λ=40 µm. Hence, the working frequency is 125 MHz for the Love mode and 98 MHz for the Rayleigh mode. The propagation of Love wave needs a guiding layer. For that purpose, a silica layer was deposited using sputtering technique with shear velocity lower than the piezoelectric substrates. The region between the two IDTs constitutes the sensing area.Preliminary tests have been performed using candle smoke. As the obtained PM concentrations were unstable and difficult to reproduce, we have developed an experimental set-up bench consisting of a 1m3 chamber, a particle’s generator AGK 2000 and an optical system FIDAS® 100. Thus, sodium chloride (NaCl) was used to produce PM2.5 while PM10 were generated from silicon carbide (SiC) in the 0 to 200 μg/m3 concentration range. When the particles impact on the sensor surface, the velocity of the acoustic waves decreases due to the sensors’ high gravimetric sensitivity. Accordingly, the wave phase velocity shift is measured by monitoring the phase at constant frequency with an open loop interrogation [4]. It’s then correlated to the particles concentration. Results and Conclusions Figure 1 and 2 shows plots of phase derivative dϕ/dt of sensors based AT-Quartz (black) and LiNbO3 (red) with the concentration of PM10 and PM2.5 respectively measured with the optical system FIDAS®. As expected, the sensitivity of the Rayleigh wave sensor based on LiNbO3 is lower than the Love wave sensor based on quartz for both PM10 and PM2.5. The sensor’s sensitivity is estimated by applying a linear fit of the plotted data. The sensitivity of sensors based on quartz is 3.10-4 °/s.μg/m3 for PM 2.5 and 5.10-5 °/s.μg/m3 for PM10. For sensors based on LiNbO3, the sensitivity is 1.10-4 °/s.μg/m3 for PM2.5 and 1.10-5 °/s.μg/m3 for PM10. The feature that the sensors’ response is greater with PM2.5 than with PM10 can be explained by the fact that most adhesion forces are linearly dependent on particle diameter [5] which is often described as the rebound effect. As a result, the smaller particles settle more on the surface of the sensor resulting in a more significant slowdown of the wave. To ensure that each stage is measuring the targeted size range, we took images of the sensors surface at the end of the experiment using a microscope. Figures 3, 4 show the surface of the PM2.5 stage and figures 5, 6 the one of the PM10 stage. One can observe that, as expected, the PM2.5 contain more particles than the PM10 and that the particle sizes correspond well to the ranges [0.3 μm, 2.5 μm] and [2.5 μm, 10 μm]. It has therefore been shown that LiNbO3 sensors, although less sensitive, can also be used for fine particles detection. They still need work to improve their performance and limit the rebound effect, but they remain very promising for the development of self-cleaning systems.

Microdosimetric modeling of the relative efficiency of the optical absorption of LiF:Mg,Ti (TLD-100) detectors exposed to 1H and 4He ions

The Microdosimetric d(z) Model was used in combination with simulated microdosimetric specific energy probability distributions for monoenergetic 1H and 4He ions (energy range = 0.1–1000 MeV/n, target size range = 1–2000 nm) to investigate the possibility of modeling the relative efficiency of two optical absorption (OA) bands (4.77 and 5.08 eV) in the OA energy spectra of LiF:Mg,Ti (TLD-100) thermoluminescent detectors. This work represents the first application of the model to a physical system other than thermally- and optically-stimulated luminescence.The 4.77 eV OA trap is populated by electrons liberated during irradiation and its experimental OA relative efficiency was successfully predicted using a target size of 9 nm in the simulations. On the other hand, the model was not able to reproduce the values of the experimentally-observed proton induced OA efficiency above unity for the 5.08 eV OA band associated with the F centers in LiF:Mg,Ti (electron occupied Fluoride vacancy). The F centers are initially present in the LiF lattice but are also created by the irradiation. Since the absence of defect creation by the irradiation is a necessary condition of the microdosimetric model, the discrepancy between the model results for the F band and the experimental data was not unexpected.The calculations for both OA bands are presented as a function of the particle energy and the simulated microdosimetric target size and will be useful in further applications of the model OA relative efficiencies for charged particles.

Facilitating target search in polymer networks: Effects of target size and mixed one-dimensional and three-dimensional diffusion.

We theoretically investigate the problem of diffusive target search and mean first passage times (MFPTs) of a tracer in a three-dimensional (3D) polymer network with a particular focus on the effects of combined one-dimensional (1D) diffusion along the polymer chains and 3D diffusion within the network. For this, we employ computer simulations as well as limiting theories of a single diffusive tracer searching for a spherical target fixed at a cross-link of a homogeneous 3D cubic lattice network. The free parameters are the target size, the ratio of the 1D and 3D friction constants, and the transition probabilities between bound and unbound states. For a very strongly bound tracer on the chains, the expected predominant set of 1D lattice diffusion (LD) is found. The MFPT in the LD process significantly depends on the target size, yielding two distinct scaling behaviors for target sizes smaller and larger than the network mesh size, respectively. In the limit of a pointlike target, the LD search becomes a random walk process on the lattice, which recovers the analytical solution for the MFPT previously reported by S. Condamin, O. Bénichou, and M. Moreau [Phys. Rev. Lett. 95, 260601 (2005)PRLTAO0031-900710.1103/PhysRevLett.95.260601]. For the very weakly bound tracer, the expected 3D free diffusion (FD) dominates, extrapolating to the well-known Smoluchowski limit. A critical target size is found above which the MFPT in the FD process is faster than in the LD process. For intermediate binding, i.e., a combination of LD and FD processes, the target search time can be minimized for an optimal range of target sizes and partitions between FD and LD, for which the MFPTs are substantially faster when compared to the limiting FD or LD processes. Our study may provide a theoretical basis to better understand and predict search and reaction processes in complex structured materials, thereby contributing to practical applications such as designing nanoreactors where catalytic targets are immobilized in polymer networks.

Predicting specific impulse distributions for spherical explosives in the extreme near-field using a Gaussian function

Accurate quantification of the blast load arising from detonation of a high explosive has applications in transport security, infrastructure assessment and defence. In order to design efficient and safe protective systems in such aggressive environments, it is of critical importance to understand the magnitude and distribution of loading on a structural component located close to an explosive charge. In particular, peak specific impulse is the primary parameter that governs structural deformation under short-duration loading. Within this so-called extreme near-field region, existing semi-empirical methods are known to be inaccurate, and high-fidelity numerical schemes are generally hampered by a lack of available experimental validation data. As such, the blast protection community is not currently equipped with a satisfactory fast-running tool for load prediction in the near-field. In this article, a validated computational model is used to develop a suite of numerical near-field blast load distributions, which are shown to follow a similar normalised shape. This forms the basis of the data-driven predictive model developed herein: a Gaussian function is fit to the normalised loading distributions, and a power law is used to calculate the magnitude of the curve according to established scaling laws. The predictive method is rigorously assessed against the existing numerical dataset, and is validated against new test models and available experimental data. High levels of agreement are demonstrated throughout, with typical variations of &lt;5% between experiment/model and prediction. The new approach presented in this article allows the analyst to rapidly compute the distribution of specific impulse across the loaded face of a wide range of target sizes and near-field scaled distances and provides a benchmark for data-driven modelling approaches to capture blast loading phenomena in more complex scenarios.

Sensitivity of Surface Acoustic Wave Sensors Based LiNbO3 128° Y-X and at-Quartz to PM10 and PM2.5

Introduction Particulate matter (PM) was estimated to cause around 7 million premature deaths worldwide per year according to World Health organization [1]. These particles can cause diseases leading to premature death [2]. Over the last decade, the monitoring of PM became an important issue on a worldwide scale. The miniaturization of the existing bulky systems has also become necessary to reduce their cost. To address this need, a new miniaturized system for PM monitoring was previously developed in our team [3]. It takes advantage of both a 3 Lpm cascade impactor and surface acoustic waves (SAW) sensors to respectively separate and measure particles. The present study aims to compare the sensitivity of two SAW devices. The first exploits Love waves on an AT cut Quartz substrate and the second is based on Rayleigh waves from a LiNbO3 Y-X 128° substrates. The latter presents a high electromechanical coupling factor that could be exploited for the self-cleaning of the device after the measurement. This could allow overcoming the fouling issue faced with impactors that wouldn’t be solved with quartz based sensors which suffer from an insufficient electromechanical coupling. Method In this study we used a dedicated 3 Lpm cascade impactor equipped with SAW delay lines as collecting plate. The Rayleigh wave sensor and the Love wave sensor were designed and fabricated respectively on LiNbO3 Y-X 128° cut and AT-Quartz cut substrates using a conventional photolithography process. The interdigital transducers (IDT) consist of double finger pairs made of 200 nm thick aluminum with a periodicity p=10 µm and a wavelength λ=40 µm. Hence, the working frequency is 125 MHz for the Love mode and 98 MHz for the Rayleigh mode. The propagation of Love wave needs a guiding layer. For that purpose, a silica layer was deposited using sputtering technique with shear velocity lower than the piezoelectric substrates. The region between the two IDTs constitutes the sensing area.Preliminary tests have been performed using candle smoke. As the obtained PM concentrations were unstable and difficult to reproduce, we have developed an experimental set-up bench consisting of a 1m3 chamber, a particle’s generator AGK 2000 and an optical system FIDAS® 100. Thus, sodium chloride (NaCl) was used to produce PM2.5 while PM10 were generated from silicon carbide (SiC) in the 0 to 200 μg/m3 concentration range. When the particles impact on the sensor surface, the velocity of the acoustic waves decreases due to the sensors’ high gravimetric sensitivity. Accordingly, the wave phase velocity shift is measured by monitoring the phase at constant frequency with an open loop interrogation [4]. It’s then correlated to the particles concentration. Results and Conclusions Figure 1 and 2 shows plots of phase derivative dϕ/dt of sensors based AT-Quartz (black) and LiNbO3 (red) with the concentration of PM10 and PM2.5 respectively measured with the optical system FIDAS®. As expected, the sensitivity of the Rayleigh wave sensor based on LiNbO3 is lower than the Love wave sensor based on quartz for both PM10 and PM2.5. The sensor’s sensitivity is estimated by applying a linear fit of the plotted data. The sensitivity of sensors based on quartz is 3.10-4 °/s.μg/m3 for PM 2.5 and 5.10-5 °/s.μg/m3 for PM10. For sensors based on LiNbO3, the sensitivity is 1.10-4 °/s.μg/m3 for PM2.5 and 1.10-5 °/s.μg/m3 for PM10. The feature that the sensors’ response is greater with PM2.5 than with PM10 can be explained by the fact that most adhesion forces are linearly dependent on particle diameter [5] which is often described as the rebound effect. As a result, the smaller particles settle more on the surface of the sensor resulting in a more significant slowdown of the wave. To ensure that each stage is measuring the targeted size range, we took images of the sensors surface at the end of the experiment using a microscope. Figures 3, 4 show the surface of the PM2.5 stage and figures 5, 6 the one of the PM10 stage. One can observe that, as expected, the PM2.5 contain more particles than the PM10 and that the particle sizes correspond well to the ranges [0.3 μm, 2.5 μm] and [2.5 μm, 10 μm]. It has therefore been shown that LiNbO3 sensors, although less sensitive, can also be used for fine particles detection. They still need work to improve their performance and limit the rebound effect, but they remain very promising for the development of self-cleaning systems.

A new approach to modeling the microdosimetry of proton therapy beams.

To revisit the formulation of the mean chord length in microdosimetry and replace it by the particle mean free path appropriate for modelings in radiobiology. We perform a collision-by-collision followed by event-by-event Geant4 Monte Carlo simulation and calculate double-averaged stepping length, 〈〈l〉〉, for a range of target sizes from mm down to μm and depth in water. We consider 〈〈l〉〉 to represent the particle mean free path. We show that 〈〈l〉〉 continuously drops as a function of depth and asymptotically saturates to a minimum value in low energies, where it exhibits a universal scaling behavior, independent of particle nominal beam energy. We correlate 〈〈l〉〉 to linear density of DNA damage, complexities of initial lethal lesions and illustrate a relative difference between predictive RBEs in model calculations using mean chord length vs the proposed mean free path. We demonstrate consistency between rapid increase in RBE within and beyond the Bragg peak and 〈〈l〉〉, a decreasing function of depth. An interplay between localities in imparted energy at nanometer scale and subsequent physio-chemical processes, causalities and pathways in DNA damage requires substitution of geometrical chord length of cell nuclei by mean-free path of proton and charged particles to account for a mean distance among sequential collisions in DNA materials. To this end, the event averaging over cell volume in the current microdosimetry formalism must be superseded by the collision averaging scored within the volume. The former, is fundamentally a global attribute of the cell nuclei surfaces and boundaries and is characterized by their membrane diameters, hence such global indices are not appropriate to quantitatively represent the radiobiological strength of the particles and their RBE variabilities that is associated with the sensitivities to local structure of the collisions and their spatio-temporal collective patterns in DNA materials.

From zygote to a multicellular soma: Body size affects optimal growth strategies under cancer risk

AbstractMulticellularity evolved independently in multiple lineages, yielding organisms with a wide range of adult sizes. Building an intact soma is not a trivial task, when dividing cells accumulate damage. Here, we study “ontogenetic management strategies,” that is rules of dividing, differentiating and killing somatic cells, to examine two questions: first, do these rules evolve differently for organisms differing in the target mature body size, and second, how well a strategy evolved in small‐bodied organisms performs if implemented in a large body—and vice versa (“large”‐evolved strategies in small bodies). We model the growth and mature lifespan of an organism starting from a single cell and optimize, using a genetic algorithm, trait combinations across a range of target sizes, with seven evolving traits: (a) probability of asymmetric division, (b) probability of differentiation (per symmetric cell division), (c) Hayflick limit, (d) damage response threshold, (e) damage response strength, (f) number of differentiation steps and (g) division propensity of cells relative to “stemness.” Some but not all traits evolve differently depending on body size: large‐bodied organisms perform best with a smaller probability of differentiation, a larger number of differentiation steps on the way to form a tissue and a higher threshold of cellular damage to trigger cell death, than small organisms. Strategies evolved in large organisms are more robust: they maintain high performance across a wide range of body sizes, while those that evolved in smaller organisms fail when attempting to create a large body. This highlights an asymmetry: under various risks of developmental failure and cancer, it is easier for a lineage to become miniaturized (should selection otherwise favour this) than to increase in size.

Double-Emulsion Copolyester Microcapsules for Sustained Intraperitoneal Release of Carboplatin.

Despite on-going medical advances, ovarian cancer survival rates have stagnated. In order to improve IP delivery of platinum-based antineoplastics, we aimed to develop a sustained drug delivery system for carboplatin (CPt). Toward this aim, we pursued a double emulsion process for obtaining CPt-loaded microcapsules composed of poly(ethylene terephthalate-ethylene dilinoleate) (PET-DLA) copolymer. We were able to obtain PET-DLA microspheres in the targeted size range of 10–25 µm (median: 18.5 µm), to reduce intraperitoneal clearance by phagocytosis and lymphoid transit. Empty microspheres showed the lack of toxicity in vitro. The double emulsion process yielded 2.5% w/w CPt loading and obtained microcapsules exhibited sustained (>20 day) zero-order release. The encapsulated CPt was confirmed to be bioavailable, as the microcapsules demonstrated efficacy against human ovarian adenocarcinoma (SK-OV-3) cells in vitro. Following intraperitoneal injection in mice, we did not observe adhesions, only mild, clinically-insignificant, local inflammatory response. Tissue platinum levels, monitored over 14 days using atomic absorption spectroscopy, revealed low burst and reduced systemic uptake (plasma, kidney), as compared to neat carboplatin injection. Overall, the results demonstrate the potential of the developed microencapsulation system for long-term intraperitoneal sustained release of carboplatin for the treatment of ovarian cancer.

Optimization of MLC parameters for TPS calculation and dosimetric verification: application to single isocenter radiosurgery of multiple brain lesions using VMAT

Linac and MLC-based stereotactic radiosurgery (SRS) using single-isocenter-multiple-target (SIMT) VMAT has become increasingly popular in the management of multi-focal cranial metastases. However, significant geometrical and dosimetric challenges exist due to the typically small target volumes and in most cases, non-isocentric locations. To the best of our knowledge, there hasn’t been a study in the optimization of MLC parameters, in the context of SIMT SRS, to ensure TPS calculation accuracy. In this work, we set out to optimize the dosimetric leaf gap (DLG) for the HD MLC installed on dedicated stereotactic Varian STx systems using a diverse group of 21 clinical SRS and SBRT plans. These plans featured a broad range of target sizes and target-to-isocenter distances that are typical of the stereotactic cases treated on these systems. Dose discrepancies between TPS calculations and verification measurements using a previously validated diode array Delta4 (ScandiDos) were minimized in a balanced manner to accommodate the variety of stereotactic plans. A DLG of 0.6 mm was found to be ‘optimal’ for the HD MLC and for the ‘typical’ plans treated on our STx systems. The finding was independently verified using commercially available 3D polymer gel dosimeter CrystalBallTM (MGS Research Inc.). 3D verification for 6 SIMT SRS plans, consisted of 5 to 15 targets, achieved an average gamma score of 97.3% (σ = 2.0%) on 3%/2 mm criteria with a cutoff isodose level of 20%. We further examined the practice of routine dosimetric verifications including the selection of appropriate detectors and optimal gamma parameters. We found that the commonly used standard 3%/3 mm criteria would have resulted in all but 4 (out of 2840) clinical plans achieving a gamma score of 95% or better, and therefore, losing sensitivity to detect potential dosimetric discrepancies. Based on the characteristics of stereotactic plans, a more stringent distance-to-agreement parameter is needed.

The relative rate of optical expansion controls speed in 1D pedestrian followin

Last year, we compared six models of speed control for a pedestrian following behind a leader (Bai & Warren, VSS 2018). The results showed that Rio, Rhea & Warren’s (JoV, 2014) optical expansion model best fit the data, and explained the decreasing response with distance. The model uses the rate of expansion (or contraction) of the target’s visual angle to control the follower’s deceleration (acceleration), thereby canceling the optical expansion. However, the model predicts that a larger target should produce a greater acceleration, because the rate of expansion is a monotonically increasing function of target size (over a moderate range of target sizes). Here we propose an alternative model in which the relative rate of expansion (expansion rate/visual angle) controls acceleration, which mitigates the sensitivity to target size. To compare the two models, we asked participants to follow a moving target, the size of which varied randomly on each trial (width = 0.2, 0.6, 1 m, height = 3 m).12 participants walked in a virtual environment wearing a head-mounted display, while head position was recorded at 90 Hz. They were instructed to follow a virtual target (a green cylinder) on a textured ground plane. In each trial, the target appeared in front of the participant (distance = 1, 3, 6 m) and started to move on a straight path at a constant speed (1.2 m/s). After 3–4 seconds, the target changed its speed (+0.3, 0, −0.3 m/s). Bayesian model comparison revealed that the relative expansion model had a lower RMS error (.085 m/s2) and BIC value (−284.88) than the expansion model (0.094 m/s2, −272.15), which exhibited larger error for the extreme target sizes (0.2 and 1 m). The results provide ‘very strong’ support that the relative rate of expansion is used to control speed in pedestrian following.

Production of solid biofuel granules from drum granulation of bio-waste with silicate-based binders

Herein compost was selected as a model bio-waste substrate to make solid biofuel granules using wet drum granulation and a sodium silicate binder. Using a laboratory-scale drum granulator (300 g/batch), spherical compost granules within the targeted size range (3.35–14 mm) could be produced with a good compressive strength in good to excellent yields. The effects of compost moisture content, process parameters (drum speed, granulation time) and binder parameters (binder concentration, binder to compost ratio) on the properties of the resulting granules (size distribution, bulk density, compressive strength, water resistance, gross calorific value, ash content) were investigated. The optimal conditions for producing granules as a solid biofuel with competitive properties when compared with woody biomass fuels were achieved by applying a drum rotational speed of 32–37 rpm, granulation time of 15 min, sodium silicate solution 1–3 wt% and binder to solid ratio 0.77–0.90.

Performance of a magnetorheological fluid-based robotic end effector

Robotic end effectors are needed for a variety of terrestrial and space-based tasks. End effectors are commonly inspired by the human hand, with a range of complexity, including varying number of fingers, joints and degrees of freedom. Hand and pincher-type grippers can require complicated actuation and/or a significant sensing and control system to ensure proper orientation of the gripper about the target prior to gripping as well as to avoid crushing the target. Universal grippers, most notably exemplified by the universal Jamming Gripper (Brown et al 2010 Proceedings of the National Academy of Science 107, 18809–18814), provide an alternative design that aims to simplify the actuation, sensing and control of robotic fixturing end-effectors. The universal Jamming Gripper is actuated pneumatically, by applying vacuum to granular media, thereby causing the grains to jam, when confined by an external bladder. We present the design and performance of a universal gripper that is actuated by applying a magnetic field, thereby eliminating the need to supply vacuum (and a reinflation source) to actuate the gripper. The magnetic field actuates a magnetorheological fluid composed of a bi-disperse mixture of carbonyl iron grains suspended in a silicone oil. The performance of this novel gripper design is characterized for a range of target sizes and shapes, and gripper design characteristics.

Considerations on the miniaturization of detectors for in vivo dosimetry in radiotherapy: A Monte Carlo study

The evolution of technology in radiotherapy nowadays allows us to deliver much higher doses to the target volumes, thanks to better absorbed dose distribution accuracy and conformation, while better sparing healthy tissues. In photon radiotherapy, higher precision usually entails employing small and moving beams. This emphasizes the role of in vivo dosimetry, which assesses internal absorbed dose rather than entrance dose. This, along with advances in materials science, results in a tendency towards the miniaturization of dosimeters. However, the stochastic nature of the radiation-matter interaction takes on greater importance at smaller scales, resulting in fluctuations in energy deposition whose effect may not be negligible. Miniaturization needs to take this into account. We estimated such fluctuations by Monte Carlo simulations considering energy deposition in cylindrical volumes of different sizes and for several absorbed dose values. We not only present and discuss the probability distributions of absorbed doses for a large range of target sizes (0.1–10μm) and clinically relevant doses (0.1–10Gy), but also derive an estimation of the risk of measuring an absorbed dose with a value outside a given interval of tolerance (3, 5 and 10%) around the expected dose. The distributions presented features consistent with the theory of microdosimetry. Those for dosimeter sizes smaller than 0.3μm showed a very high dispersion in specific energy, while those for 10μm dosimeters tended to become Gaussian and narrower with increasing absorbed dose. The probability of measuring an absorbed dose outside the defined interval of tolerance is close to 100% for the smallest size, regardless of the dose and the interval width considered. It decreases with increasing dose, dosimeter size and width of the interval of tolerance. The best results were obtained with 10μm dosimeters, for which the probability of doses outside the tolerance range is always zero for absorbed doses equal or greater than 1Gy and for all the absorbed doses in the case of the largest interval of tolerance. The ability of a small dosimeter to give measurements within a suitable range of values depends on its size and on the absorbed dose to be measured. An excessively small dosimeter size yields a distribution of specific energies spread over a very large range of values, which makes it harder to obtain accurate measurements of absorbed dose. On the other hand, a dosimeter of about 10μm in size may allow for good accuracy of the measurements in a wider range of doses and with different intervals of tolerance.

Accuracy of eye position for saccades and smooth pursuit.

In this study, we address the question of whether a target is foveated during smooth pursuit. Specifically, we examine whether smooth pursuit eye movements land near the center-of-mass of the target, as is the case for saccades. To that end, we instructed eight untrained, healthy participants to follow moving targets, presented monocularly in a scanning laser ophthalmoscope. Stimuli moved either in a modified step-ramp (smooth pursuit), or made a single step (saccade), stepping 6° from the center. Targets were ring-shaped and either 0.6° or 1.7° in diameter. In an additional set of experiments, two participants collected more extensive data on smooth pursuit and saccades for a larger range of target sizes (0.6°, 1.7°, or 4.3°). During pursuit, eyes were rarely placed at target center, even when participants' fixational stability was taken into account. Furthermore, there was a clear tendency for distance from target center to increase with target size. This outcome was in contrast to saccades, where there was no effect of target size across participants. The difference in foveal placement between the two types of eye movements is consistent with their different purposes: closer inspection of the target for saccades versus maintenance of the target in the visual field for smooth pursuit.