A visual analytics system for optimizing the performance of large-scale networks in supercomputing systems
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Fujiwara, Takanori↗
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Injectable platelet rich fibrin facilitates hair follicle regeneration by promoting human dermal papilla cell proliferation, migration, and trichogenic inductivity
Hair follicle regeneration has been successful in mice but failed in human being for years. Dermal papilla cells, a specialized mesenchymal stem cell derived from dermal papilla within hair follicles, is considered the key cells for hair follicle regeneration function as both regeneration initiator and regulator. Injectable platelet rich fibrin (i-PRF), a novel biomaterial rich in a variety of growth factors and three-dimensional scaffolds, has shown promising effects on tissue regeneration. In this study, we aimed to evaluate the application of i-PRF in human hair follicle regeneration by examining the biological effects of i-PRF on human dermal papilla cells (hDPCs). Biomaterial compatibility, cell viability, proliferation, migration, alkaline phosphatase activity and trichogenic inductivity were assessed after exposing hDPCs to different concentrations of i-PRF extracts. In addition, we investigated the ultrastructure of i-PRF with all cell components filtered. The results revealed that i-PRF possessing excellent biocompatibility and could significantly promote hDPCs proliferation, migration, and trichogenic inductivity. Furthermore, the concentration of i-PRF is able to remarkably influence hDPCs behavior in a dose-dependent pattern. Different concentrations exhibited differential effects on hDPCs behavior. In general, lower concentration promotes cell proliferation better than higher concentration, while higher concentration promotes cell function better reversely. Best concentration for hDPCs in vitro expending is 1% concentration. 20% concentration is optimal for hair follicle regeneration. In summary, our findings concluded that i-PRF facilitates hair follicle regeneration by promoting human dermal papilla cell proliferation, migration, and trichogenic inductivity.
60 APPLIED LIFE SCIENCES↗
Forest structural complexity and ignition pattern influence simulated prescribed fire effects
Background: Forest structural characteristics, the burning environment, and the choice of ignition pattern each influence prescribed fire behaviors and resulting fire effects; however, few studies examine the influences and interactions of these factors. Understanding how interactions among these drivers can influence prescribed fire behavior and effects is crucial for executing prescribed fires that can safely and effectively meet management objectives. To analyze the interactions between the fuels complex and ignition patterns, we used FIRETEC, a three-dimensional computational fluid dynamics fire behavior model, to simulate fire behavior and effects across a range of horizontal and vertical forest structural complexities. For each forest structure, we then simulated three different prescribed fires each with a unique ignition pattern: strip-head, dot, and alternating dot. Results: Forest structural complexity and ignition pattern affected the proportions of simulated crown scorch, consumption, and damage for prescribed fires in a dry, fire-prone ecosystem. Prescribed fires in forests with complex canopy structures resulted in increased crown consumption, scorch, and damage compared to less spatially complex forests. The choice of using a strip-head ignition pattern over either a dot or alternating-dot pattern increased the degree of crown foliage scorched and damaged, though did not affect the proportion of crown consumed. We found no evidence of an interaction between forest structural complexity and ignition pattern on canopy fuel consumption, scorch, or damage. Conclusions: We found that forest structure and ignition pattern, two powerful drivers of fire behavior that forest managers can readily account for or even manipulate, can be leveraged to influence fire behavior and the resultant fire effects of prescribed fire. These simulation findings have critical implications for how managers can plan and perform forest thinning and prescribed burn treatments to meet risk management or ecological objectives.
54 ENVIRONMENTAL SCIENCES↗
Stretchable and wearable polymeric heaters and strain sensors fabricated using liquid metals
Wearable electronic devices (WEDs) are receiving significant attention because of the increasing interest in soft robotics, electronic skin, and wearable sensors. Liquid metals (LMs) are compelling for WEDs owing to their metallic conductivity, fluidic nature, and low toxicity. For this study, we fabricated stretchable and soft WEDs using LM (eutectic gallium-indium alloy) wires (LMWs) patterned via force wetting through custom-made stencils on an elastic substrate. LMWs can generate thermal energy via Joule heating upon current application and deliver it to the substrate, resulting in wearable polymeric heaters. The LM mixed with carbonyl iron particles (CIPs) can also be patterned while preserving fluidic behavior. The degree of thermal energy generated through the LMWs can be manipulated as a function of the CIP concentration in the LM and geometrical factors of the electrode patterns, i.e., width and length. An elastic film patterned with LMWs attached to the human body exhibits changes in the effective electrical resistance depending on applied strain, demonstrating potential as a wearable strain sensor. This LM utilized WED that can generate thermal energy upon current application through the LMWs and detect the bodily motion has significant potential for application in wearable thermotherapy, electronic skin, and soft sensors.
47 OTHER INSTRUMENTATION↗
Later Life Changes in Hippocampal Neurogenesis and Behavioral Functions After Low-Dose Prenatal Irradiation at Early Organogenesis Stage
Purpose: To investigate long-term changes in behavioral functions of mice after exposure to low-dose prenatal radiation at an early organogenesis stage. Methods and Materials: Pregnant C57BL/6J mice were irradiated (20 cGy) at postcoitus day 5.5. The male and female offspring were subjected to different behavioral assays for affective, motor, and cognitive functions at 3, 6, and 12 months of age. Behavioral functions were further correlated with the population of CA1 and CA3 pyramidal neurons and immature neurons in hippocampal dentate gyrus. Results: Prenatally exposed mice of different age groups showed a sex-specific pattern of sustained changes in behavioral functions. Male mice showed significant changes in anxiety-like phenotypes, learning, and long-term memory at age 3 months. At 6 months of age such behavioral functions were recovered to a normal level but could not be sustained at age 12 months. Female mice showed an appreciable recovery in almost all behavioral functions at 12 months. Patterns of change in learning and long-term memory were comparable to the population of CA1 and CA3 pyramidal neurons and doublecortin-positive neurons in hippocampus. Conclusion: Our finding suggests that prenatal (early organogenesis stage) irradiation even at a lower dose level (20 cGy) is sufficient to cause potential changes in neurobehavioral function at later stages of life. Male mice showed relatively higher vulnerability to radiation-induced neurobehavioral changes as compared with female.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
An Analytical Model for the Tension-Shear Coupling of Woven Fabrics with Different Weave Patterns under Large Shear Deformation
It is essential to accurately describe the large shear behavior of woven fabrics in the composite preforming process. An analytical model is proposed to describe the shear behavior of fabrics with different weave patterns, in which tension-shear coupling is considered. The coupling is involved in two parts, the friction between overlapped yarns and the in-plane transverse compression between two parallel yarns. By introducing the concept of inflection points of a yarn, the model is applicable for fabrics with different weave patterns. The analytical model is validated by biaxial tension-shear experiments. A parametric study is conducted to investigate the effects of external load, yarn geometry, and weave structure on the large shear behavior of fabrics. The developed model can reveal the physical mechanism of tension-shear coupling of woven fabrics. Moreover, the model has a high computational efficiency due to its explicit expressions, thus benefiting the material design process.
36 MATERIALS SCIENCE↗
Critical current oscillations of elliptical Josephson junctions with single-domain ferromagnetic layers
We report that josephson junctions containing ferromagnetic layers are of considerable interest for the development of practical cryogenic memory and superconducting qubits. Such junctions exhibit a ground-state phase shift of π for certain ranges of ferromagnetic layer thicknesses. We present studies of Nb based micron-scale elliptically shaped Josephson junctions containing ferromagnetic barriers of Ni 81 Fe 19 or Ni 65 Fe 15 Co 20 . By applying an external magnetic field, the critical current of the junctions is found to follow characteristic Fraunhofer patterns and display sharp switching behavior suggestive of single-domain magnets. The high quality of the Fraunhofer patterns enables us to extract the maximum value of the critical current even when the peak is shifted significantly outside the range of the data due to the magnetic moment of the ferromagnetic layer. The maximum value of the critical current oscillates as a function of the ferromagnetic barrier thickness, indicating transitions in the phase difference across the junction between values of zero and π. Lastly, we compare the data to previous work and to models of the 0-π transitions based on existing theories.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Improved Accuracy for Automated Communication Pattern Characterization Using Communication Graphs and Aggressive Search Space Pruning
An understanding of a parallel application’s communication behavior is useful for a range of activities including debugging and optimization, job scheduling, target system selection, and system design. Because it can be challenging to understand communication behavior, especially for those who lack expertise or who are not familiar with the application, I and two colleagues recently developed an automated, search-based approach for recognizing and parameterizing application communication behavior using a library of common communication patterns. This initial approach was effective for characterizing the behavior of many workloads, but I identified some combinations of communication patterns for which the method was inefficient or would fail. In this paper, I discuss one such troublesome pattern combination and propose modifications to the recognition method to handle it. Specifically, I propose an alternative approach that uses communication graphs instead of traditional communication matrices to improve recognition accuracy for collective communication operations, and that uses a non-greedy recognition technique to avoid search space dead-ends that trap the original greedy recognition approach. My modified approach uses aggressive search space pruning and heuristics to control the potential for state explosion caused by its non-greedy pattern recognition method. I demonstrate the improved recognition accuracy and pruning efficacy of the modified approach using several synthetic and real-world communication pattern combinations.
Roth, Philip↗
Hydrodynamics of countercurrent flows in a structured packed column: effects of initial wetting and dynamic contact angle
The structured packed column has gained considerable attention as a prospective technology to mitigate carbon dioxide emissions from thermal power plants. The computational flow investigation of such systems is a multiscale problem, and local hydrodynamics plays a key role in overall column efficiency. Accordingly, multiphase flow studies in the representative elementary unit (REU) of a packed column can offer insights into the local flow behavior such as flow pattern, interfacial area, etc. The interfacial area plays a key role in the overall interphase mass transfer and thereby in separation efficiency. The predicted effective area matches well with corresponding ones in experiments for Mellapak 250.Y packings. The contact angle (i.e., solid substrate behavior) is one of the critical factors that dictates wettings, and thereby the interfacial area. The dynamic contact angle (DCA) was considered in order to explore the effects of contact angle hysteresis on the interfacial area. DCA has more pronounced impact on the interfacial area for a solvent possessing a higher value of surface tension and equilibrium contact angle. The interfacial area shows temporal undulation and does not achieve a pseudo steady state due to the capillary force. In contrary, the interfacial area gets a net value for a solvent having low surface tension value. Further, specification of the static contact angle at the solid substrate shows the least value of the interfacial area. We also extensively studied the effect of the initial sheet condition (dry vs wet) on the interfacial area. The initially wetted sheets show slightly higher value of the interfacial area as compared to the initially dry sheets at a fixed flow rate for a solvent having high surface tension value. Wetting hysteresis decreases with increasing liquid loads. On the other hand, wetting hysteresis does not occur for a solvent having value of low surface tension and equilibrium contact angle.
structured packings, dynamic contact angle, interf↗
Theoretical description of atomtronic Josephson junctions in an optical lattice
Experimental realizations of “atomtronic” Josephson junctions have recently been created in annular traps in relative rotation with respect to potential barriers that generate the weak links. If these devices are additionally subjected to an optical lattice potential, then they can incorporate strong-coupling Mott physics within the design, which can modify the behavior and can allow for interesting new configurations of barriers and of superfluid flow patterns. We examine theoretically the behavior of a Bose superfluid in an optical lattice in the presence of an annular trap and a barrier across the annular region which acts as a Josephson junction. As the superfluid is rotated, circulating super-currents appear. Beyond a threshold superfluid velocity, phase slips develop, which generate vortices. We use a finite temperature strong-coupling expansion about the mean-field solution of the Bose Hubbard model to calculate various properties of such devices. Additionally, we discuss some of the rich behavior that can result when there are Mott regions within the system.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Granular chaos and mixing: Whirled in a grain of sand
In this paper, we overview examples of chaos in granular flows. We begin by reviewing several remarkable behaviors that have intrigued researchers over the past few decades, and we then focus on three areas in which chaos plays an intrinsic role in granular behavior. First, we discuss pattern formation in vibrated beds, which we show is a direct result of chaotic scattering combined with dynamical dissipation. Next, we consider stick-slip motion, which involves chaotic scattering on the micro-scale, and which results in complex and as yet unexplained peculiarities on the macro-scale. Finally, we examine granular mixing, which we show combines micro-scale chaotic scattering and macro-scale stick-slip motion into behaviors that are well described by dynamical systems tools, such as iterative mappings.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Octahedral rotation patterns in strained EuFeO 3 and other Pbnm perovskite films: Implications for hybrid improper ferroelectricity
Here, we report the relationship between epitaxial strain and the crystallographic orientation of the in-phase rotation axis and A -site displacements in Pbnm-type perovskite films. Synchrotron diffraction measurements of EuFeO 3 films under strain states ranging from 2% compressive to 0.9% tensile on cubic or rhombohedral substrates exhibit a combination of a - a + c - and a + a - c - rotational patterns. We compare the EuFeO 3 behavior with previously reported experimental and theoretical work on strained Pbnm-type films on nonorthorhombic substrates, as well as additional measurements from LaGaO 3 , LaFeO 3 , and Eu 0.7 Sr 0.3 MnO 3 films on SrTiO 3 . Compiling the results from various material systems reveals a general strain dependence in which compressive strain strongly favors a - a + c - and a + a - c - rotation patterns and tensile strain weakly favors a - a - c + structures. In contrast, EuFeO 3 films grown on Pbnm-type GdScO 3 under 2.3% tensile strain take on a uniform a - a + c - rotation pattern imprinted from the substrate, despite strain considerations that favor the a - a - c + pattern. Our results point to the use of substrate imprinting as a more robust route than strain for tuning the crystallographic orientations of the octahedral rotations and A -site displacements needed to realize rotation-induced hybrid improper ferroelectricity in oxide heterostructures.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NMF-Based Anomaly Detection in CMS 2D Tracking Occupancy Histograms
The CMS experiment relies on Data Quality Monitoring (DQM) to ensure that recorded collision data are suitable for physics analysis. During LHC Run 3, each run contains many lumisections and tracking monitoring elements, making offline inspection challenging, especially for localized detector effects that may appear only for short periods of time. This poster presents an unsupervised machine-learning approach to identify anomalous lumisections in CMS tracking occupancy histograms using Non-Negative Matrix Factorization (NMF). The workflow uses offline CMS DQMIO tracking histograms retrieved with the CMS DIALS API and organized as two-dimensional occupancy maps for each lumisection. After selecting stable lumisections, the occupancy maps are normalized and arranged into a non-negative data matrix. The NMF model learns a compact set of basis patterns describing normal tracking occupancy. Each lumisection is then reconstructed from these learned components, and the reconstruction error is used as an anomaly score. Large residuals indicate occupancy patterns that deviate from normal detector behavior and are flagged for further inspection. This NMF-based approach provides a fast and interpretable way to flag lumisections whose tracking occupancy patterns differ from normal detector behavior. Preliminary studies show sensitivity to known tracking anomalies, and ongoing work is focused on validating the method across additional Run 3 Pixel and Strip detector issues.
Rodríguez Ramos, Iliomar [Puerto Rico U., Mayaguez↗
Manipulation of self-organized multi-vortical states in active magnetic roller suspensions
Ensembles of active magnetic colloids demonstrate complex collective behavior and self-organization when driven out of equilibrium by external magnetic fields. The interplay between magnetic and hydrodynamic interactions often result in spontaneous self-assembly and the emergence of localized vortices in ensembles of ferromagnetic rollers. We report experimental and computational study of the self-organized multi-vortical state in ensembles of magnetic rollers under the imposed external confining potential realized by patterned substrates. We explore the behavior of the system on a substrate patterned with shallow wells ordered in a lattice with square symmetry and lattice spacing smaller than the wells’ diameter. Here we demonstrate, that ensembles of active magnetic rollers evolve in response to changes in the geometry of the confining lattice from a globally correlated state characterized by anti-ferromagnetic vortex ordering to a state with rapidly changing particle flows and self-organized vortical states with a lattice constant larger than one of the confining pattern. Our experimental observations are accompanied by numerical simulations based on phenomenological coarse grained particle dynamics coupled to Navier–Stokes hydrodynamics in shallow water approximation. The reported results provide insights into the collective behavior of active magnetic rollers under confinement and suggest strategies for the manipulation of collective dynamic states in active magnetic liquids.
36 MATERIALS SCIENCE↗
A novel technique for investigation of complete and partial anisotropic wetting on structured surface by X-ray microtomography
An experimental study about the anisotropic wetting behavior of a surface patterned with parallel grooves is presented as an application example of a novel technique for investigation of complete and partial anisotropic wetting on structured surface by X-ray microtomography. Shape of glycerin droplets on such surface is investigated by X-ray micro computed tomography (microCT) acting as a non-intrusive, full volume 3D microscope with micrometric spatial resolution. The reconstructed drop volumes enable to estimate the exact volumes of the drops, their base contours, and 3D static contact angles, based on true cross-sections of the drop-surface couple. Droplet base contours are compared to approximate geometrical contour shapes proposed in the literature. Contact angles along slices parallel and perpendicular to the grooves direction are compared with each other. The effect of the sessile drop volume on the wetting behavior is discussed. The proposed technique, which is applicable for any structured surface, enables the direct measure of Wenzel ratio based on the microCT scan in the wetted region usually inapproachable by any others. Comparisons with simplified models are presented and congruence of results with respect to the minimum resolution needed is evaluated and commented.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Patterning non-equilibrium morphologies in stimuli-responsive gels through topographical confinement
Stimuli-responsive “smart” polymers have generated significant interest for introducing dynamic control into the properties of antifouling coatings, smart membranes, switchable adhesives and cell manipulation substrates. Switchable surface morphologies formed by confining stimuli-responsive gels to topographically structured substrates have shown potential for a variety of interfacial applications. Beyond patterning the equilibrium swelling behavior of gels, subjecting stimuli-responsive gels to topographical confinement could also introduce spatial gradients in the various timescales associated with gel deformation, giving rise to novel non-equilibrium morphologies. In this work, we show how by curing poly(N-isopropylacrylamide) (pNIPAAm)-based gel under confinement to a rigid, bumpy substrate, we can not only induce the surface curvature to invert with temperature, but also program the transient, non-equilibrium morphologies that emerge during the inversion process through changing the heating path. Finite element simulations show that the emergence of these transient morphologies is correlated with confinement-induced gradients in polymer concentration and position-dependent hydrostatic pressure within the gel. To illustrate the relevance of such morphologies in interfacial applications, we show how they enable us to control the gravity-induced assembly of colloidal particles and microalgae. Finally, we show how more complex arrangements in particle assembly can be created through controlling the thickness of the temperature-responsive gel over the bumps. Patterning stimuli-responsive gels on topographically-structured surfaces not only enables switching between two invertible topographies, but could also create opportunities for stimuli ramp-dependent control over the local curvature of the surface and emergence of unique transient morphologies. Harnessing these features could have potential in the design of multifunctional, actuatable materials for switchable adhesion, antifouling, cell manipulation, and liquid and particle transport surfaces.
42 ENGINEERING↗
Nano-enhanced solid-state hydrogen storage: Balancing discovery and pragmatism for future energy solutions
Nanomaterials have revolutionized the battery industry by enhancing energy storage capacities and charging speeds, and their application in hydrogen (H 2 ) storage likewise holds strong potential, though with distinct challenges and mechanisms. H 2 is a crucial future zero-carbon energy vector given its high gravimetric energy density, which far exceeds that of liquid hydrocarbons. However, its low volumetric energy density in gaseous form currently requires storage under high pressure or at low temperature. This review critically examines the current and prospective landscapes of solid-state H 2 storage technologies, with a focus on pragmatic integration of advanced materials such as metal-organic frameworks (MOFs), magnesium-based hybrids, and novel sorbents into future energy networks. These materials, enhanced by nanotechnology, could significantly improve the efficiency and capacity of H 2 storage systems by optimizing H 2 adsorption at the nanoscale and improving the kinetics of H 2 uptake and release. We discuss various H 2 storage mechanisms—physisorption, chemisorption, and the Kubas interaction—analyzing their impact on the energy efficiency and scalability of storage solutions. The review also addresses the potential of “smart MOFs”, single-atom catalyst-doped metal hydrides, MXenes and entropy-driven alloys to enhance the performance and broaden the application range of H 2 storage systems, stressing the need for innovative materials and system integration to satisfy future energy demands. High-throughput screening, combined with machine learning algorithms, is noted as a promising approach to identify patterns and predict the behavior of novel materials under various conditions, significantly reducing the time and cost associated with experimental trials. In closing, we discuss the increasing involvement of various companies in solid-state H 2 storage, particularly in prototype vehicles, from a techno-economic perspective. In conclusion, this forward-looking perspective underscores the necessity for ongoing material innovation and system optimization to meet the stringent energy demands and ambitious sustainability targets increasingly in demand.
25 ENERGY STORAGE↗
State-of-the-art on research and applications of machine learning in the building life cycle
Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Finally, findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗