Towards High Efficiency and Rapid Production of Room-Temperature Liquid Metal Wires Compatible with Electronic Prototyping Connectors.

We present in this work new methodologies to produce, refine, and interconnect room-temperature liquid-metal-core thermoplastic elastomer wires that have extreme extendibility (>500%), low production time and cost at scale, and may be integrated into commonly used electrical prototyping connectors like a Japan Solderless Terminal (JST) or Dupont connectors. Rather than focus on the development of a specific device, the aim of this work is to demonstrate strategies and processes necessary to achieve scalable production of liquid-metal-enabled electronics and address several key challenges that have been present in liquid metal systems, including leak-free operation, minimal gallium corrosion of other electrode materials, low liquid metal consumption, and high production rates. The ultimate goal is to create liquid-metal-enabled rapid prototyping technologies, similar to what can be achieved with Arduino projects, where modification and switching of components can be performed in seconds, which enables faster iterations of designs. Our process is focused primarily on fibre-based liquid metal wires contained within thermoplastic elastomers. These fibre form factors can easily be integrated with wearable sensors and actuators as they can be sewn or woven into fabrics, or cast within soft robotic components.

The effect of morphometric and geometric indices of the human calvarium on mechanical response.

BACKGROUND: When developing a surrogate model of the human skull, there is a multitude of morphometric and geometric properties to consider when constructing the model. To simplify this approach, it is important to identify only the properties that have a significant influence on the mechanical response of the skull. The objective of this study was to identify which morphometric and geometric properties of the calvarium were significant predictors of mechanical response. METHODS: Calvarium specimens (N = 24) were micro-computed tomography scanned to determine morphometric and geometric properties. The specimens were assumed to be Euler-Bernoulli beams and were subject to 4-point quasi-static bending to determine mechanical response. Univariate linear regressions were performed whereby the morphometric and geometric properties were independent or predictor variables and the mechanical responses were dependent or outcome variables. FINDINGS: Nine significant linear regression models were established (p < 0.05). In the diploë, trabecular bone pattern factor was a significant predictor of force and bending moment at fracture. The inner cortical table had more significant predictors (thickness, tissue mineral density, and porosity) of mechanical response compared to the outer cortical table and diploë. INTERPRETATION: Morphometric and geometric properties had a key influence on the calvarium's biomechanics. Trabecular bone pattern factor and the morphometry and geometry of the cortical tables must be considered when evaluating the mechanical response of the calvarium. These properties can aid the design of surrogate models of the skull that seek to mimic its mechanical response for head impact simulation.

Investigating mechanisms of laser pulse-induced reflectivity modulations in photoacoustic remote sensing with a 10 million frames-per-second camera.

Photoacoustic remote sensing has been recently developed as an all-optical imaging modality capable of imaging a variety of endogenous contrast agents label-free. Initially predicted laser pulse-induced refractive index perturbation-based interrogation beam reflectivity modulations have been found to be orders of magnitude smaller than those typically observed experimentally. In this report we utilize a 10 million frames-per-second camera to further investigate these predicted reflectivity modulations, while also exploring other potential mechanisms of laser pulse-induced reflectivity modulations. Laser-induced motion is demonstrated both laterally for gold wires suspended and submerged in air and water, respectively, and carbon fibers submerged in water, and axial motion is observed in gold wires submerged in a depth gradient of intralipid solution. This laser-induced sample motion is anticipated to cause reflectivity modulations local to the interrogation beam profile in microscopy set-ups. Non-motion-based maximum intensity modulations of 3% are also observed in gold wires submerged in water, indicating the presence of the originally predicted reflectivity modulations. Overall, these observations are important as they provide a widefield view of laser-pulse interactions unavailable in previous point scanning-based photoacoustic remote sensing microscopy configurations, where observed mechanisms occur on time-scales orders of magnitude faster than equivalent field of view point scanning capabilities.

Impact Deposition Behavior of Al/B4C Cold-Sprayed Composite Coatings: Understanding the Role of Porosity on Particle Retention.

This study explores the role of porosity in the impact deposition of a ceramic-reinforced metal-matrix (i.e., Al/B4C) composite coating fabricated via cold spraying. The Johnson-Holmquist-Beissel constitutive law and the modified Gurson-Tvergaard-Needleman model were used to describe the high strain-rate behavior of the boron carbide and the aluminum metal matrix during impact deposition, respectively. Within a finite element model framework, the Arbitrary Lagrangian-Eulerian technique is implemented to explore the roles of reinforcement particle size and velocity, and pore size and depth in particle retention by examining the post-impact crater morphology, penetration depth, and localized plastic deformation of the aluminum substrate. Results reveal that some degree of matrix porosity may improve particle retention. In particular, porosity near the surface facilitates particle retention at lower impact velocities, while kinetic energy dominates particle retention at higher deposition velocities. Altogether, these results provide insights into the effect of deposition variables (i.e., particle size, impact velocity, pore size, and pore depth) on particle retention that improves coating quality.

TASK inhibition by mild acidosis increases Ca2+ oscillations to mediate pH sensing in rat carotid body chemoreceptor cells.

Severe levels of acidosis (pH < 6.8) have been shown to cause a sustained rise in cytosolic Ca2+ concentration in carotid body Type 1 (glomus) cells. To understand how physiologically relevant levels of acidosis regulate Ca2+ signaling in glomus cells, we studied the effects of small changes in extracellular pH (pHo) on the kinetics of Ca2+ oscillations. A decrease in pHo from 7.4 to 7.3 (designated mild) and 7.2 (designated moderate) acidosis produced significant increases in the frequency and amplitude of Ca2+ oscillations. These effects of acidosis on Ca2+ oscillations were not blocked by NS383 and amiloride [acid-sensing ion channel (ASIC) inhibitors]. Mild and moderate levels of acidosis, however, caused a small but significant inhibition of two-pore domain acid-sensing K+ channels (TASK) (TASK-1- and TASK-3-like channels) and depolarized the cell by 6-13 mV. Acidosis-induced increase in Ca2+ oscillations was inhibited by nifedipine (1 µM; L-type Cav inhibitor) and by TTA-P2 (20 µM; T-type Cav inhibitor). Mild inhibition of TASK activity by N-[(2,4-difluorophenyl)methyl]-2'-[[[2-(4methoxyphenyl)acetyl]amino]methyl][1,1'-biphenyl]-2-carboxamide (A1899) (0.3 µM) and 1-[1-[6-[[1,1'-biphenyl]-4-ylcarbonyl)-5,6,7,8-tetrahydropyrido[4,3-d]pyrimidine-4-yl]-4-piperidinyl]-1-butanon (PK-THPP) (0.1 µM) increased Ca2+ oscillation frequency to levels similar to those observed with mild-moderate acidosis. Mild acidosis (pHo 7.3) and mild hypoxia (∼5%O2) produced similar levels of changes in the kinetics of Ca2+ oscillations. Block of tetraethylammonium (TEA)-sensitive Kv channels did not affect acid-induced increase in Ca2+ oscillations. Our study shows that mild and moderate levels of acidosis increase the frequency and amplitude of Ca2+ oscillations primarily by inhibition of TASK without involving ASICs, and suggests a major role of TASK for signal transduction in response to a physiological change in pHo.

The Mechanical Characterization and Comparions of Male and Female Calvaria Under Four-Point Bending Impacts.

The circumstances in which we mechanically test and critically assess human calvarium tissue would find relevance under conditions encompassing real-world head impacts. These conditions include, among other variables, impact velocities, and strain rates. Compared to quasi-static loading on calvaria, there is less reporting on the impact loading of the calvaria and consequently, there are relatively fewer mechanical properties on calvaria at relevant impact loading rates available in the literature. The purpose of this work was to report on the mechanical response of 23 human calvarium specimens subjected to dynamic four-point bending impacts. Impacts were performed using a custom-built four-point impact apparatus at impact velocities of 0.86-0.89 m/s resulting in surface strain rates of 2-3/s-representative of strain rates observed in vehicle collisions and blunt impacts. The study revealed comparable effective bending moduli (11-15 GPa) to the limited work reported on the impact mechanics of calvaria in the literature, however, fracture bending stress (10-47 MPa) was relatively less. As expected, surface strains at fracture (0.21-0.25%) were less compared to studies that performed quasi-static bending. Moreover, the study revealed no significant differences in mechanical response between male and female calvaria. The findings presented in this work are relevant to many areas including validating surrogate skull fracture models in silico or laboratory during impact and optimizing protective devices used by civilians to reduce the risk of a serious head injury.

Sequence Representations and Their Utility for Predicting Protein-Protein Interactions.

Protein-Protein Interactions (PPIs) are a crucial mechanism underpinning the function of the cell. So far, a wide range of machine-learning based methods have been proposed for predicting these relationships. Their success is heavily dependent on the construction of the underlying feature vectors, with most using a set of physico-chemical properties derived from the sequence. Few work directly with the sequence itself. In this paper, we explore the utility of sequence embeddings for predicting protein-protein interactions. We construct a protein pair feature vector by concatenating the embeddings of their constituent sequence. These feature vectors are then used as input to a binary classifier to make predictions. To learn sequence embeddings, we use two established Word2Vec based methods - Seq2Vec and BioVec - and we also introduce a novel feature construction method called SuperVecNW. The embeddings generated through SuperVecNW capture some network information in addition to the contextual information present in the sequences. We test the efficacy of our proposed approach on human and yeast PPI datasets and on three well-known networks: CD9, the Ras-Raf-Mek-Erk-Elk-Srf pathway, and a Wnt-related network. We demonstrate that low dimensional sequence embeddings provide better results than most alternative representations based on physico-chemical properties while offering a far simple approach to feature vector construction.

Signatures of increasing environmental stress in bumblebee wings over the past century: Insights from museum specimens.

Determining when animal populations have experienced stress in the past is fundamental to understanding how risk factors drive contemporary and future species' responses to environmental change. For insects, quantifying stress and associating it with environmental factors has been challenging due to a paucity of time-series data and because detectable population-level responses can show varying lag effects. One solution is to leverage historic entomological specimens to detect morphological proxies of stress experienced at the time stressors emerged, allowing us to more accurately determine population responses. Here we studied specimens of four bumblebee species, an invaluable group of insect pollinators, from five museums collected across Britain over the 20th century. We calculated the degree of fluctuating asymmetry (FA; random deviations from bilateral symmetry) between the right and left forewings as a potential proxy of developmental stress. We: (a) investigated whether baseline FA levels vary between species, and how this compares between the first and second half of the century; (b) determined the extent of FA change over the century in the four bumblebee species, and whether this followed a linear or nonlinear trend; (c) tested which annual climatic conditions correlated with increased FA in bumblebees. Species differed in their baseline FA, with FA being higher in the two species that have recently expanded their ranges in Britain. Overall, FA significantly increased over the century but followed a nonlinear trend, with the increase starting c. 1925. We found relatively warm and wet years were associated with higher FA. Collectively our findings show that FA in bumblebees increased over the 20th century and under weather conditions that will likely increase in frequency with climate change. By plotting FA trends and quantifying the contribution of annual climate conditions on past populations, we provide an important step towards improving our understanding of how environmental factors could impact future populations of wild beneficial insects.

Phase-field approach to evolution and interaction of twins in single crystal magnesium.

Crack initiation and propagation as well as abrupt occurrence of twinning are challenging fracture problems where the transient phase-field approach is proven to be useful. Early-stage twinning growth and interactions are in focus herein for a magnesium single crystal at the nanometer length-scale. We demonstrate a basic methodology in order to determine the mobility parameter that steers the kinetics of phase-field propagation. The concept is to use already existing molecular dynamics simulations and analytical solutions in order to set the mobility parameter correctly. In this way, we exercise the model for gaining new insights into growth of twin morphologies, temporally-evolving spatial distribution of the shear stress field in the vicinity of the nanotwin, multi-twin, and twin-defect interactions. Overall, this research addresses gaps in our fundamental understanding of twin growth, while providing motivation for future discoveries in twin evolution and their effect on next-generation material performance and design.

Metagenomic Geolocation Using Read Signatures.

We present a novel approach to the Metagenomic Geolocation Challenge based on random projection of the sample reads from each location. This approach explores the direct use of k-mer composition to characterise samples so that we can avoid the computationally demanding step of aligning reads to available microbial reference sequences. Each variable-length read is converted into a fixed-length, k-mer-based read signature. Read signatures are then clustered into location signatures which provide a more compact characterisation of the reads at each location. Classification is then treated as a problem in ranked retrieval of locations, where signature similarity is used as a measure of similarity in microbial composition. We evaluate our approach using the CAMDA 2020 Challenge dataset and obtain promising results based on nearest neighbour classification. The main findings of this study are that k-mer representations carry sufficient information to reveal the origin of many of the CAMDA 2020 Challenge metagenomic samples, and that this reference-free approach can be achieved with much less computation than methods that need reads to be assigned to operational taxonomic units-advantages which become clear through comparison to previously published work on the CAMDA 2019 Challenge data.

Mycorrhizal symbiosis pathway and edaphic fertility frame root economics space among tree species.

The root economics space (RES) is multidimensional and largely shaped by belowground biotic and abiotic influences. However, how root-fungal symbioses and edaphic fertility drive this complexity remains unclear. Here, we measured absorptive root traits of 112 tree species in temperate and subtropical forests of China, including traits linked to functional differences between arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) hosts. Our data, from known mycorrhizal tree species, revealed a 'fungal-symbiosis' dimension distinguishing AM from ECM species. This divergence likely resulted from the contrasting mycorrhizal evolutionary development of AM vs ECM associations. Increased root tissue cortical space facilitates AM symbiosis, whereas increased root branching favours ECM symbiosis. Irrespective of mycorrhizal type, a 'root-lifespan' dimension reflecting aspects of root construction cost and defence was controlled by variation in specific root length and root tissue density, which was fully independent of root nitrogen content. Within this function-based RES, we observed a substantial covariation of axes with soil phosphorus and nitrate levels, highlighting the role played by these two axes in nutrient acquisition and conservation. Overall, our findings demonstrate the importance of evolved mycorrhizal symbiosis pathway and edaphic fertility in framing the RES, and provide theoretical and mechanistic insights into the complexity of root economics.

Collaborative Sense-Making in Genomic Research: The Role of Visualisation.

Genomic research emerges from collaborative work within and across different scientific disciplines. A diverse range of visualisation techniques has been employed to aid this research, yet relatively little is known as to how these techniques facilitate collaboration. We conducted a case study of collaborative research within a biomedical institute to learn more about the role visualisation plays in genomic mapping. Interviews were conducted with molecular biologists (N = 5) and bioinformaticians (N = 6). We found that genomic research comprises a variety of distinct disciplines engaged in complex analytic tasks that each resist simplification, and their complexity influences how visualisations were used. Visualisation use was impacted by group-specific interactions and temporal work patterns. Visualisations were also crucial to the scientific workflow, used for both question formation and confirmation of hypotheses, and acted as an anchor for the communication of ideas and discussion. In the latter case, two approaches were taken: providing collaborators with either interactive or static imagery representing a viewpoint. The use of generic software for simplified visualisations, and quick production and curation was also noted. We discuss these findings with reference to group-specific interactions and present recommendations for improving collaborative practices through visual analytics.

3D Microstructure-Based Finite Element Simulation of Cold-Sprayed Al-Al2O3 Composite Coatings Under Quasi-Static Compression and Indentation Loading.

This study developed microstructure-based finite element (FE) models to investigate the behavior of cold-sprayed aluminum-alumina (Al-Al2O3) metal matrix composite (MMC) coatings subject to indentation and quasi-static compression loading. Based on microstructural features (i.e., particle weight fraction, particle size, and porosity) of the MMC coatings, 3D representative volume elements (RVEs) were generated by using Digimat software and then imported into ABAQUS/Explicit. State-of-the-art physics-based modeling approaches were incorporated into the model to account for particle cracking, interface debonding, and ductile failure of the matrix. This allowed for analysis and informing on the deformation and failure responses. The model was validated with experimental results for cold-sprayed Al-34 wt.% Al2O3 and Al-46 wt.% Al2O3 metal matrix composite coatings under quasi-static compression by comparing the stress versus strain histories and observed failure mechanisms (e.g., matrix ductile failure). The results showed that the computational framework is able to capture the response of this cold-sprayed material system under compression and indentation, both qualitatively and quantitatively. The outcomes of this work have implications for extending the model to materials design and for applications involving different types of loading in real-world application (e.g., erosion and fatigue).

Nonlinearity of the coefficient of thermal expansion in brain tissue.

The coefficient of thermal expansion (CTE) in biological tissues is an integral parameter behind the application of electromagnetic energy to biomedical technologies; however, its behavior is far from being fully characterized. In this study, we apply digital image correlation (DIC) to non-invasively measure the microscale thermal expansions of recently excised embryonic E18 rodent brain tissue slices. Although the CTE has been measured previously in soft tissues, the literature surrounding the expansion of brain tissue remains sparse. Previous work in measuring the thermal expansion behavior of soft tissue often simplifies the results into a single measurement of a linear CTE parameter and fails to convey the temperature-dependent nonlinearity that exists. In this work, we demonstrate that: (1) the coefficient of brain tissue is more similar to fat than blood, and (2) there exists a significant nonlinear increase in CTE at physiologically-relevant temperatures. This suggests some limitations with the interpretation of previously reported values of the CTE, which are often measured at room temperature.

Smart Textiles for Visible and IR Camouflage Application: State-of-the-Art and Microfabrication Path Forward.

Protective textiles used for military applications must fulfill a variety of functional requirements, including durability, resistance to environmental conditions and ballistic threats, all while being comfortable and lightweight. In addition, these textiles must provide camouflage and concealment under various environmental conditions and, thus, a range of wavelengths on the electromagnetic spectrum. Similar requirements may exist for other applications, for instance hunting. With improvements in infrared sensing technology, the focus of protective textile research and development has shifted solely from providing visible camouflage to providing camouflage in the infrared (IR) region. Smart textiles, which can monitor and react to the textile wearer or environmental stimuli, have been applied to protective textiles to improve camouflage in the IR spectral range. This study presents a review of current smart textile technologies for visible and IR signature control of protective textiles, including coloration techniques, chromic materials, conductive polymers, and phase change materials. We propose novel fabrication technology combinations using various microfabrication techniques (e.g., three-dimensional (3D) printing; microfluidics; machine learning) to improve the visible and IR signature management of protective textiles and discuss possible challenges in terms of compatibility with the different textile performance requirements.

Invasion and rapid adaptation of guppies (Poecilia reticulata) across the Hawaiian Archipelago.

How much does natural selection, as opposed to genetic drift, admixture, and gene flow, contribute to the evolution of invasive species following introduction to a new environment? Here we assess how evolution can shape biological invasions by examining population genomic variation in non-native guppies (Poecilia reticulata) introduced to the Hawaiian Islands approximately a century ago. By examining 18 invasive populations from four Hawaiian islands and four populations from the native range in northern South America, we reconstructed the history of introductions and evaluated population structure as well as the extent of ongoing gene flow across watersheds and among islands. Patterns of differentiation indicate that guppies have developed significant population structure, with little natural or human-mediated gene flow having occurred among populations following introduction. Demographic modeling and admixture graph analyses together suggest that guppies were initially introduced to O'ahu and Maui and then translocated to Hawai'i and Kaua'i. We detected evidence for only one introduction event from the native range, implying that any adaptive evolution in introduced populations likely utilized the genetic variation present in the founding population. Environmental association tests accounting for population structure identified loci exhibiting signatures of adaptive variation related to predators and landscape characteristics but not nutrient regimes. When paired with high estimates of effective population sizes and detectable population structure, the presence of environment-associated loci supports the role of natural selection in shaping contemporary evolution of Hawaiian guppy populations. Our findings indicate that local adaptation may engender invasion success, particularly in species with life histories that facilitate rapid evolution. Finally, evidence of low gene flow between populations suggests that removal could be an effective approach to control invasive guppies across the Hawaiian archipelago.

Cortical and trabecular morphometric properties of the human calvarium.

There is currently a gap in the literature that quantitatively describes the complex bone microarchitecture within the diploë (trabecular bone) and cortical layers of the human calvarium. The purpose of this study was to determine the morphometric properties of the diploë and cortical tables of the human calvarium in which key interacting factors of sex, location on the calvarium, and layers of the sandwich structure were considered. Micro-computed tomography (micro-CT) was utilized to capture images at 18 µm resolution of male (n = 26) and female (n = 24) embalmed calvarium specimens in the frontal and parietal regions (N = 50). All images were post-processed and analyzed using vendor bundled CT-Analyzer software to determine the morphometric properties of the diploë and cortical layers. A two-way mixed (repeated measures) analysis of variance (ANOVA) was used to determine diploë morphometric properties accounting for factors of sex and location. A three-way mixed ANOVA was performed to determine cortical morphometric properties accounting for factors of cortical layer (inner and outer table), sex, and location. The study revealed no two-way interaction effects between sex and location on the diploë morphometry except for fractal dimension. Trabecular thickness and separation in the diploë were significantly greater in the male specimens; however, females showed a greater number of trabeculae and fractal dimension on average. Parietal specimens revealed a greater porosity, trabecular separation, and deviation from an ideal plate structure, but a lesser number of trabeculae and connectivity compared to the frontal location. Additionally, the study observed a lower density and greater porosity in the inner cortical layer than the outer which may be due to clear distinctions between each layer's physiological environment. The study provides valuable insight into the quantitative morphometry of the calvarium in which finite element modelers of the skull can refer to when designing detailed heterogenous or subject-specific skull models to effectively predict injury. Furthermore, this study contributes towards the recent developments on physical surrogate models of the skull which require approximate measures of calvarium bone architecture in order to effectively fabricate a model and then accurately simulate a traumatic head impact event.

Learning supervised embeddings for large scale sequence comparisons.

Similarity-based search of sequence collections is a core task in bioinformatics, one dominated for most of the genomic era by exact and heuristic alignment-based algorithms. However, even efficient heuristics such as BLAST may not scale to the data sets now emerging, motivating a range of alignment-free alternatives exploiting the underlying lexical structure of each sequence. In this paper, we introduce two supervised approaches-SuperVec and SuperVecX-to learn sequence embeddings. These methods extend earlier Representation Learning (RepL) based methods to include class-related information for each sequence during training. Including class information ensures that related sequence fragments have proximal representations in the target space, better reflecting the structure of the domain. We show the quality of the embeddings learned through these methods on (i) sequence retrieval and (ii) classification tasks. We also propose an hierarchical tree-based approach specifically designed for the sequence retrieval problem. The resulting methods, which we term H-SuperVec or H-SuperVecX, according to their respective use of SuperVec or SuperVecX, learn embeddings across a range of feature spaces based on exclusive and exhaustive subsets of the class labels. Experiments show that the proposed methods perform better for retrieval and classification tasks over existing (unsupervised) RepL-based approaches. Further, the new methods are an order of magnitude faster than BLAST for the database retrieval task, supporting hybrid approaches that rapidly filter the collection so that only potentially relevant records remain. Such filtering of the original database allows slower but more accurate methods to be executed quickly over a far smaller dataset. Thus, we may achieve faster query processing and higher precision than before.

Ca2+ oscillations in rat carotid body type 1 cells in normoxia and hypoxia.

We studied the mechanisms by which carotid body glomus (type 1) cells produce spontaneous Ca2+ oscillations in normoxia and hypoxia. In cells perfused with normoxic solution at 37°C, we observed relatively uniform, low-frequency Ca2+ oscillations in >60% of cells, with each cell showing its own intrinsic frequency and amplitude. The mean frequency and amplitude of Ca2+ oscillations were 0.6 ± 0.1 Hz and 180 ± 42 nM, respectively. The duration of each Ca2+ oscillation ranged from 14 to 26 s (mean of ∼20 s). Inhibition of inositol (1,4,5)-trisphosphate receptor and store-operated Ca2+ entry (SOCE) using 2-APB abolished Ca2+ oscillations. Inhibition of endoplasmic reticulum Ca2+-ATPase (SERCA) using thapsigargin abolished Ca2+ oscillations. ML-9, an inhibitor of STIM1 translocation, also strongly reduced Ca2+ oscillations. Inhibitors of L- and T-type Ca2+ channels (Cav; verapamil>nifedipine>TTA-P2) markedly reduced the frequency of Ca2+ oscillations. Thus, Ca2+ oscillations observed in normoxia were caused by cyclical Ca2+ fluxes at the ER, which was supported by Ca2+ influx via Ca2+ channels. Hypoxia (2-5% O2) increased the frequency and amplitude of Ca2+ oscillations, and Cav inhibitors (verapamil>nifedipine>>TTA-P2) reduced these effects of hypoxia. Our study shows that Ca2+ oscillations represent the basic Ca2+ signaling mechanism in normoxia and hypoxia in CB glomus cells.