ASTRO: Reducing COVID-19 Exposure through Contact Prediction and Avoidance

The fight against the COVID-19 pandemic has highlighted the importance and benefits of recommending paths that reduce the exposure to and the spread of the SARS-CoV-2 coronavirus by avoiding crowded indoor or outdoor areas. Existing path discovery techniques are inadequate for coping with such dynamic and heterogeneous (indoor and outdoor) environments—they typically find an optimal path assuming a homogeneous and/or static graph, and hence they cannot be used to support contact avoidance. In this article, we pose the need for Mobile Contact Avoidance Navigation and propose ASTRO ( A ccessible S patio- T emporal R oute O ptimization), a novel graph-based path discovering algorithm that can reduce the risk of COVID-19 exposure by taking into consideration the congestion in indoor spaces. ASTRO operates in an A * manner to find the most promising path for safe movement within and across multiple buildings without constructing the full graph. For its path finding, ASTRO requires predicting congestion in corridors and hallways. Consequently, we propose a new grid-based partitioning scheme combined with a hash-based two-level structure to store congestion models, called CM-Structure , which enables on-the-fly forecasting of congestion in corridors and hallways. We demonstrate the effectiveness of ASTRO and the accuracy of CM-Structure ’s congestion models empirically with realistic datasets, showing up to one order of magnitude reduction in COVID-19 exposure.

Computation of local permeability in granular soils using spatial time domain reflectometer

This letter proposes semi-analytical methods to obtain the local permeability for granular soils based on indirect measurements of the local porosity profile in a large coaxial cell permeameter using spatial time domain reflectometry. The porosity profile is used to obtain the local permeability using the modified Kozeny-Carman and Katz-Thompson equations, which incorporated an effective particle diameter that accounted for particle migration within the permeameter. The profiles of the local permeability obtained from the proposed methods are compared with experimentally obtained permeability distributions using pressure measurements and flow rate. The permeabilities obtained with the proposed methods are comparable with the experimentally obtained permeabilities and are within one order of magnitude deviation, which is an acceptable range for practical applications.

Low-background neutron reflectometry from solid/liquid interfaces

Liquid cells are an increasingly common sample environment for neutron reflectometry experiments and are critical for measuring the properties of materials at solid/liquid interfaces. Background scattering determines the maximum useful scattering vector, and hence the spatial resolution, of the neutron reflectometry measurement. The primary sources of background are the liquid in the cell reservoir and the materials forming the liquid cell itself. Thus, characterization and mitigation of these background sources are necessary for improvements in the signal-to-background ratio and resolution of neutron reflectometry measurements employing liquid cells. Single-crystal silicon is a common material used for liquid cells due to its low incoherent scattering cross section for neutrons, and the path lengths of the neutron beam through silicon can be several centimetres in modern cell designs. Here, a liquid cell is constructed with a sub-50 µm thick liquid reservoir encased in single-crystal silicon. It is shown that, at high scattering vectors, inelastic scattering from silicon represents a significant portion of the scattering background and is, moreover, structured, confounding efforts to correct for it by established background subtraction techniques. A significant improvement in the measurement quality is achieved using energy-analyzed detection. Energy-analyzed detection reduces the scattering background from silicon by nearly an order of magnitude, and from fluids such as air and liquids by smaller but significant factors. Combining thin liquid reservoirs with energy-analyzed detection and the high flux of the CANDOR polychromatic reflectometer at the NIST Center for Neutron Research, a background-subtracted neutron reflectivity smaller than 10−8 from a liquid cell sample is reported.

Polyhedral-Based Compilation Framework for In-Memory Neural Network Accelerators

Memristor-based processing-in-memory architecture is a promising solution to the memory bottleneck in the neural network ( NN ) processing. A major challenge for the programmability of such architectures is the automatic compilation of high-level NN workloads, from various operators to the memristor-based hardware that may provide programming interfaces with different granularities. This article proposes a source-to-source compilation framework for such memristor-based NN accelerators, which can conduct automatic detection and mapping of multiple NN operators based on the flexible and rich representation capability of the polyhedral model. In contrast to previous studies, it implements support for pipeline generation to exploit the parallelism in the NN loads to leverage hardware resources for higher efficiency. The evaluation based on synthetic kernels and NN benchmarks demonstrates that the proposed framework can reliably detect and map the target operators. Case studies on typical memristor-based architectures also show its generality over various architectural designs. The evaluation further demonstrates that compared with existing polyhedral-based compilation frameworks that do not support the pipelined execution, the performance can upgrade by an order of magnitude with the pipelined execution, which emphasizes the necessity of our improvement.

Forecast of omicron wave time evolution

Adopting an early doubling time of three days for the rate of new infections with the omicron mutant the temporal evolution of the omicron wave in different countries is predicted. The predictions are based on the susceptible-infectious-recovered/removed (SIR) epidemic compartment model with a constant stationary ratio k=mu(t)/a(t) between the infection (a(t)) and recovery (mu(t)) rate. The fixed early doubling time then uniquely relates the initial infection rate a0 to the ratio k, which therefore determines the full temporal evolution of the omicron waves. For each country three scenarios (optimistic, pessimistic, intermediate) are considered and the resulting pandemic parameters are calculated. These include the total number of infected persons, the maximum rate of new infections, the peak time and the maximum 7-day incidence per 100000 persons. Among the considered European countries Denmark has the smallest omicron peak time and the recently observed saturation of the 7-day incidence value at 2478 is in excellent agreement with the prediction in the optimistic scenario. For Germany we predict peak times of the omicron wave ranging from 32 to 38 and 45 days after the start of the omicron wave in the optimistic, intermediate and pessimistic scenario, respectively, with corresponding maximum SDI values of 7090, 13263 and 28911, respectively. Adopting Jan 1st, 2022 as the starting date our predictions implies that the maximum of the omicron wave is reached between Feb 1 and Feb 15, 2022. Rather similar values are predicted for Switzerland. Due to an order of magnitude smaller omicron hospitalization rate, due to the high percentage of vaccinated and boostered population, the German health system can cope with maximum omicron SDI value of 2800 which is about a factor 2.5 smaller than the maximum omicron SDI value 7090 in the optimistic case. By either reducing the duration of intensive care during this period of maximum, and/or by making use of the nonuniform spread of the omicron wave across Germany, it seems that the German health system can barely cope with the omicron wave avoiding triage decisions. The reduced omicron hospitalization rate also causes significantly smaller mortality rates compared to the earlier mutants in Germany. In the optimistic scenario one obtains for the total number of fatalities 7445 and for the maximum death rate 418 per day which are about one order of magnitude smaller than the beta fatality rate and total number.

The microbiome of the pelagic tunicate Dolioletta gegenbauri: a potential link between the grazing and microbial food web

Doliolids often form massive blooms during upwelling conditions in sub-tropical shelves. However, their trophic role, including their nutritious fecal pellets, in pelagic marine food webs remains poorly investigated. In this study, we performed three independent feeding experiments of cultured Dolioletta gegenbauri and used qPCR analysis and 16S rRNA metabarcoding to characterize the microbial community associated with full gut (FG) and empty (EG) doliolids, fresh (FP2Hrs) and senescing (FP24Hrs) fecal pellets, and the surrounding natural seawater (SW). Bacterial abundance (i.e., 16S rRNA gene copies) in EG samples was an order of magnitude lower than in SW and three orders lower than in FP24Hrs. Diversity analyses, based on the 16S rRNA metabarcoding data, supported a richer microbial community in SW, FP2Hrs, FP24Hrs, and FG samples. Furthermore, microbial community structure was determined by sample type, with FG samples appearing more similar to either FP2Hrs or FP24Hrs. These patterns resulted from the higher number of shared ASVs and consequently the contribution of similar major bacterial taxa (e.g., Rhodobacteraceae, Pirellulaceae). These observations support the hypothesis that there are significant ecological and trophic interactions between D. gegenbauri and the ocean microbiome. Predicted gene function recovered many genes related to key processes in the marine environment and supported greater similarity between FP2Hrs, FP24Hrs, and FG samples. These observations suggest that pelagic marine bacteria are utilized by D. gegenbauri to digest captured prey particles, and the subsequent release of fecal pellets supports the rapid proliferation of distinct microbial communities which likely influence key biogeochemical processes in the ocean.

Controlling polarization direction in epitaxial Pb(Zr0.2Ti0.8)O3 films through Nb (n-type) and Fe (p-type) doping

Fe (acceptor) and Nb (donor) doped epitaxial Pb(Zr0.2Ti0.8)O3 (PZT) films were grown on single crystal SrTiO3 substrates and their electric properties were compared to those of un-doped PZT layers deposited in similar conditions. All the films were grown from targets produced from high purity precursor oxides and the doping was in the limit of 1% atomic in both cases. The remnant polarization, the coercive field and the potential barriers at electrode interfaces are different, with lowest values for Fe doping and highest values for Nb doping, with un-doped PZT in between. The dielectric constant is larger in the doped films, while the effective density of charge carriers is of the same order of magnitude. An interesting result was obtained from piezoelectric force microscopy (PFM) investigations. It was found that the as-grown Nb-doped PZT has polarization orientated upward, while the Fe-doped PZT has polarization oriented mostly downward. This difference is explained by the change in the conduction type, thus in the sign of the carriers involved in the compensation of the depolarization field during the growth. In the Nb-doped film the majority carriers are electrons, which tend to accumulate to the growing surface, leaving positively charged ions at the interface with the bottom SrRuO3 electrode, thus favouring an upward orientation of polarization. For Fe-doped film the dominant carriers are holes, thus the sign of charges is opposite at the growing surface and the bottom electrode interface, favouring downward orientation of polarization. These findings open the way to obtain p-n ferroelectric homojunctions and suggest that PFM can be used to identify the type of conduction in PZT upon the dominant direction of polarization in the as-grown films.

High drain-current-density and high breakdown-field Al0.36Ga0.64N-channel heterojunction filed-effect transistors with a dual AlN/AlGaInN barrier layer

In this study, we fabricated and characterized heterojunction field-effect transistors (HFETs) based on an Al0.36Ga0.64N-channel heterostructure with a dual AlN/AlGaInN barrier layer. The device fabrication was accomplished by adopting a regrown n++-GaN layer for ohmic contacts. The fabricated HFETs with a gate length of 2 μm and a gate-to-drain distance of 6 μm exhibited an on-state drain current density as high as approximately 270 mA/mm and an off-state breakdown voltage of approximately 1 kV, which corresponds to an off-state critical electric field of 166 V/μm. This breakdown field, as a comparison in devices without field-plate electrodes, reaches approximately four-fold higher than that for conventional GaN-channel HFETs and was considered quite reasonable as an Al0.36Ga0.64N-channel transistor. It was also confirmed that the devices adopting the dual AlN/AlGaInN barrier layer showed approximately one order of magnitude smaller gate leakage currents than those for devices without the top AlN barrier layer.

Observation of a transition to a localized ultrasonic phase in soft matter

Anderson localization arises from the interference of multiple scattering paths in a disordered medium, and applies to both quantum and classical waves. Soft matter provides a unique potential platform to observe localization of non-interacting classical waves because of the order of magnitude difference in speed between fast and slow waves in conjunction with the possibility to achieve strong scattering over broad frequency bands while minimizing dissipation. Here, we provide long sought evidence of a localized phase spanning up to 246 kHz for fast (sound) waves in a soft elastic medium doped with resonant encapsulated microbubbles. We find the transition into the localized phase is accompanied by an anomalous decrease of the mean free path, which provides an experimental signature of the phase transition. At the transition, the decrease in the mean free path with changing frequency (i.e., disorder strength) follows a power law with a critical exponent near unity. Within the localized phase the mean free path is in the range 0.4–1.0 times the wavelength, the transmitted intensity at late times is well-described by the self-consistent localization theory, and the localization length decreases with increasing microbubble volume fraction. Our work sets the foundation for broadband control of localization and the associated phase transition in soft matter, and affords a comparison of theory to experiment.

4D evolution of Cr23C6 precipitates in neutron-irradiated and annealed HT-UPS steel observed via synchrotron micro-computed tomography

High-temperature-ultrafine precipitate strengthened (HT-UPS) steel is a potential structural material for advanced nuclear reactors; however, its irradiation response is not well understood. This research provides insight into irradiation-induced effects, such as precipitate evolution mechanisms and four-dimensional morphological evolution, in HT-UPS steel using synchrotron micro-computed tomography. Identical specimens were characterized pre-irradiation and post-irradiation following neutron exposure up to 0.3 displacements per atom at 600 °C. Irradiation effects were also differentiated from the annealing response of precipitates. Following neutron irradiation, the average Cr23C6 precipitate size reduced, affected by the synergy of nucleation and growth, ballistic dissolution, and inverse coarsening, which was observed at fluences an order of magnitude lower than previously observed. Annealing at 600 °C for 32 h increased the average Cr23C6 precipitate size and decreased the phase fraction, attributed to precipitate coarsening. The precipitate morphology evolution and resultant mechanisms can be utilized to parameterize and validate microstructural models simulating radiation damage or annealing. Graphical abstract