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Land surface temperature (LST) derived from satellite observations and weather modeling has been widely used for investigating Earth surface-atmosphere energy exchange and radiation budget. However, satellite-derived LST has a trade-off between spatial and temporal resolutions and missing observations caused by clouds, while there are limitations such as potential bias and expensive computation in model calibration and simulation for weather modeling. To mitigate those limitations, we proposed a WRFM framework to estimate LST at a spatial resolution of 1 km and temporal resolution of an hour by integrating the Weather Research and Forecasting (WRF) model and MODIS satellite data using the morphing technique. We tested the framework in eight counties, Iowa, USA, including urban and rural areas, to generate hourly LSTs from June 1st to August 31st, 2019, at a 1 km resolution. Upon evaluation with in-situ LST measurements, our WRFM framework has demonstrated its ability to capture hourly LSTs under both clear and cloudy conditions, with a root mean square error (RMSE) of 2.63 K and 3.75 K, respectively. Additionally, the assessment with satellite LST observations has shown that the WRFM framework can effectively reduce the bias magnitude in LST from the WRF simulation, resulting in a reduction of the average RMSE over the study area from 4.34 K (daytime) and 4.12 K (nighttime) to 2.89 K (daytime) and 2.75 K (nighttime), respectively, while still capturing the hourly patterns of LST. Overall, the WRFM is effective in integrating the complementary advantages of satellite observations and weather modeling and can generate LSTs with high spatiotemporal resolutions in areas with complex landscapes (e.g., urban). 

Abstract Tundra fires can dramatically influence plant species cover and abundance, organic layer depth, and the magnitude of seasonal permafrost thaw. However, knowledge of the impact of wildfire on short and long-term interactions between vegetation and permafrost thaw remains limited. Here, we evaluate the spatial and temporal interactions between wildfire disturbance and surface subsidence on a remotely derived proxy for species diversity (i.e. spectral diversity (SD)) of 16 fire scars within the Izaviknek and Kingaglia uplands of southwestern Alaska’s Yukon–Kuskokwim Delta with burn dates between 1971 and 2015. SD was calculated as the sum of squared spectral variance of pixel spectra from the mean spectra, within a plant community (analogous to alpha diversity), between plant communities (beta diversity), and across terrain composed of a mosaic of communities (gamma diversity). Surface subsidence was calculated from spaceborne interferometric synthetic aperture radar data from Sentinel-1. Results indicate the burn scars had consistently lower total gamma diversity and greater rates of subsidence than paired unburned reference areas, where both gamma diversity (R²= 0.74,p< 0.001) and relative subsidence (R²= 0.86,p< 0.001) decreased with the time since burn. Compared to older burn scars, young scars had higher gamma spectral diversities (0.013 and 0.005) and greater subsidence rates (−0.097 cm day⁻¹and −0.053 cm day⁻¹). Communities subsiding at higher rates had higher gamma diversities (R²= 0.81,p< 0.001). Results indicate that rates of post-fire vegetation succession are amplified by the thickening of active layers and surface subsidence that increases both spectral and species diversity over 15 years following fire. These results support the idea that SD may be used as a remotely sensed analog of species diversity, used to advance knowledge of the trajectories of plant community change in response to interacting arctic disturbance regimes. 

Cascading bandits have gained popularity in recent years due to their applicability to recommendation systems and online advertising. In the cascading bandit model, at each timestep, an agent recommends an ordered subset of items (called an item list) from a pool of items, each associated with an unknown attraction probability. Then, the user examines the list, and clicks the first attractive item (if any), and after that, the agent receives a reward. The goal of the agent is to maximize the expected cumulative reward. However, the prior literature on cascading bandits ignores the influences of user states (e.g., historical behaviors) on recommendations and the change of states as the session proceeds. Motivated by this fact, we propose a generalized cascading RL framework, which considers the impact of user states and state transition into decisions. In cascading RL, we need to select items not only with large attraction probabilities but also leading to good successor states. This imposes a huge computational challenge due to the combinatorial action space. To tackle this challenge, we delve into the properties of value functions, and design an oracle BestPerm to efficiently find the optimal item list. Equipped with BestPerm, we develop two algorithms CascadingVI and CascadingBPI, which are both computation-efficient and sample-efficient, and provide near-optimal regret and sample complexity guarantees. Furthermore, we present experiments to show the improved computational and sample efficiencies of our algorithms compared to straightforward adaptations of existing RL algorithms in practice. 

Open Modification Search (OMS) is a promising algorithm for mass spectrometry analysis that enables the discovery of modified peptides. However, OMS encounters challenges as it exponentially extends the search scope. Existing OMS accelerators either have limited parallelism or struggle to scale effectively with growing data volumes. In this work, we introduce an OMS accelerator utilizing multi-level-cell (MLC) RRAM memory to enhance storage capacity by 3x. Through in-memory computing, we achieve up to 77x faster data processing with two to three orders of magnitude better energy efficiency. Testing was done on a fabricated MLC RRAM chip. We leverage hyperdimensional computing to tolerate up to 10% memory errors while delivering massive parallelism in hardware. 

ABSTRACT We conducted a GPU-accelerated reprocessing of $$\sim 87~{{\ \rm per\ cent}}$$ of the archival data from the High Time Resolution Universe South Low Latitude (HTRU-S LowLat) pulsar survey by implementing a pulsar search pipeline that was previously used to reprocess the Parkes Multibeam Pulsar Survey (PMPS). We coherently searched the full 72-min observations of the survey with an acceleration search range up to $$|50|\, \rm m\, s^{-2}$$, which is most sensitive to binary pulsars experiencing nearly constant acceleration during 72 min of their orbital period. Here we report the discovery of 71 pulsars, including six millisecond pulsars, of which five are in binary systems, and seven pulsars with very high dispersion measures (DM $$\gt 800 \, \rm pc \, cm^{-3}$$). These pulsar discoveries largely arose by folding candidates to a much lower spectral signal-to-noise ratio than in previous surveys and by exploiting the coherence of folding over the incoherent summing of the Fourier components to discover new pulsars as well as candidate classification techniques. We show that these pulsars could be fainter and on average more distant as compared with both the previously reported 100 HTRU-S LowLat pulsars and the background pulsar population in the survey region. We have assessed the effectiveness of our search method and the overall pulsar yield of the survey. We show that through this reprocessing we have achieved the expected survey goals, including the predicted number of pulsars in the survey region, and discuss the major causes why these pulsars were missed in previous processing of the survey. 

An increasing number of location-based service providers are taking the advantage of cloud computing by outsourcing their Point of Interest (POI) datasets and query services to third-party cloud service providers (CSPs), which answer various location-based queries from users on their behalf. A critical security challenge is to ensure the integrity and completeness of any query result returned by CSPs. As an important type of queries, a location-based skyline query (LBSQ) asks for the POIs not dominated by any other POI with respect to a given query position, i.e., no POI is both closer to the query position and more preferable with respect to a given numeric attribute. While there have been several recent attempts on authenticating outsourced LBSQ, none of them support the shortest path distance that is preferable to the Euclidian distance in metropolitan areas. In this paper, we tackle this open challenge by introducing AuthSkySP, a novel scheme for authenticating outsourced LBSQ under the shortest path distance, which allows the user to verify the integrity and completeness of any LBSQ result returned by an untrusted CSP. We confirm the effectiveness and efficiency of our proposed solution via detailed experimental studies using both real and synthetic datasets. 

Catalytic torrefaction using potassium carbonate (K2CO3) impregnation is a pretreatment method demonstrated to catalyze wood powder’s thermal degradation for energy use. In this study, beech wood boards were impregnated with K2CO3, with the aim to scale up from the studies on wood powder found in the literature. The beech boards were impregnated with five different concentrations and torrefied at 300◦C for four durations (5–60 min). The impregnation procedure was successful with a linear increase of K content in wood from 0.103 wt% for raw to 0.207 wt% for the 0.012 M sample. The weight loss during torrefaction increased with the increasing potassium (K) content in wood, reaching a maximum increase of 27.17% between 0.012 M and washed (no K2CO3) after 30 min. For the longest duration, the extent of the catalytic action of K decreased, similar to what is observed in wood powder. After 60 min torrefaction, potassium increased the torrefaction severity index by up to 10% and the higher heating value (HHV) by up to 55%. Potassium efficiently increasedthe fixed carbon and decreased the volatile matter to values comparable to coal by catalyzing the devolatilization during torrefaction. The atomic H/C and O/C ratios shifted to similar ratios as coal. The energy yield (EY) was above 80% for the shorter durations but dropped drastically at 30 and 60 min torrefaction. The prediction of the solid yield (SY), energy yield (EY), and enhancement factor of the HHV (EF) through an artificial neural network was robust with a fit quality R2≥0.999. The proposed method for catalytic torrefaction on wood boards was efficient and could be used prior to grinding and transportation for bioenergy production. This process could decrease the production costs of biomass fuel to compete with fossil fuels. 

We report the discovery of ten new pulsars in the globular cluster Terzan 5 as part of the Transients and Pulsars with MeerKAT (TRAPUM) Large Survey Project. We observed Terzan 5 atL-band (856–1712 MHz) with the MeerKAT radio telescope for four hours on two epochs, and performed acceleration searches of 45 out of 288 tied-array beams covering the core of the cluster. We obtained phase-connected timing solutions for all ten discoveries, covering nearly two decades of archival observations from the Green Bank Telescope for all but one. Highlights include PSR J1748−2446ao which is an eccentric (e = 0.32) wide-orbit (orbital periodP_b = 57.55 d) system. We were able to measure the rate of advance of periastron (ω̇) for this system allowing us to determine a total mass of 3.17 ± 0.02 M_⊙. With a minimum companion mass (M_c) of ∼0.8 M_⊙, PSR J1748−2446ao is a candidate double neutron star (DNS) system. If confirmed to be a DNS, it would be the fastest spinning pulsar (P = 2.27 ms) and the longest orbital period measured for any known DNS system. PSR J1748−2446ap has the second highest eccentricity for any recycled pulsar (e ∼ 0.905) and for this system we can measure the total mass (1.997 ± 0.006 M_⊙) and estimate the pulsar and companion masses, (1.700_−0.045^+0.015 M_⊙and 0.294_−0.014^+0.046 M_⊙, respectively). PSR J1748−2446ar is an eclipsing redback (minimumM_c ∼ 0.34 M_⊙) system whose properties confirm it to be the counterpart to a previously published source identified in radio and X-ray imaging. We were also able to detectω̇for PSR J1748−2446au leading to a total mass estimate of 1.82 ± 0.07 M_⊙and indicating that the system is likely the result of Case A Roche lobe overflow. With these discoveries, the total number of confirmed pulsars in Terzan 5 is 49, the highest for any globular cluster so far. These discoveries further enhance the rich set of pulsars known in Terzan 5 and provide scope for a deeper understanding of binary stellar evolution, cluster dynamics and ensemble population studies.