Exact lattice chiral symmetry in 2d gauge theory

We construct symmetry-preserving lattice regularizations of 2d QED with one and two flavors of Dirac fermions, as well as the `3450' chiral gauge theory, by leveraging bosonization and recently-proposed modifications of Villain-type lattice actions. The internal global symmetries act just as locally on the lattice as they do in the continuum, the anomalies are reproduced at finite lattice spacing, and in each case we find a sign-problem-free dual formulation.Comment: v2: added references and improved discussion of discrete rotational invarianc

Elimination of pain improves specificity of clinical diagnostic criteria for adult chronic rhinosinusitis

Objective Determine whether the elimination of pain improves accuracy of clinical diagnostic criteria for adult chronic rhinosinusitis. Study Design Retrospective cohort study. Methods History, symptoms, nasal endoscopy, and computed tomography (CT) results were analyzed for 1,186 adults referred to an academic otolaryngology clinic with presumptive diagnosis of chronic rhinosinusitis. Clinical diagnosis was rendered using the 1997 Rhinosinusitis Taskforce (RSTF) Guidelines and a modified version eliminating facial pain, ear pain, dental pain, and headache. Results Four hundred seventy-nine subjects (40%) met inclusion criteria. Among subjects positive by RSTF guidelines, 45% lacked objective evidence of sinonasal inflammation by CT, 48% by endoscopy, and 34% by either modality. Applying modified RSTF diagnostic criteria, 39% lacked sinonasal inflammation by CT, 38% by endoscopy, and 24% by either modality. Using either abnormal CT or endoscopy as the reference standard, modified diagnostic criteria yielded a statistically significant increase in specificity from 37.1% to 65.1%, with a nonsignificant decrease in sensitivity from 79.2% to 70.3%. Analysis of comorbidities revealed temporomandibular joint disorder, chronic cervical pain, depression/anxiety, and psychiatric medication use to be negatively associated with objective inflammation on CT or endoscopy. Conclusion Clinical diagnostic criteria overestimate the prevalence of chronic rhinosinusitis. Removing facial pain, ear pain, dental pain, and headache increased specificity without a concordant loss in sensitivity. Given the high prevalence of sinusitis, improved clinical diagnostic criteria may assist primary care providers in more accurately predicting the presence of inflammation, thereby reducing inappropriate antibiotic use or delayed referral for evaluation of primary headache syndromes. Level of Evidence4. Laryngoscope, 127:1011-1016, 201

Genesee River Watershed Project. Volume 5. Water Quality Analysis of the Canaseraga Creek Watershed Nutrient Concentration and Loading, Identification of Point and Nonpoint Sources of Pollution, Total Maximum Daily Load, and an Assessment of Management Practices using the Soil Water Assessment Tool (SWAT) Model. A report to the USDA.

An assessment of the Canaseraga Creek watershed was undertaken to determine the nutrient and sediment contribution to the Lower Middle Main Stem of the Genesee River and to determine sources of nutrient and sediment loss geospatially within the Canaseraga Creek watershed. To accomplish this task, a multifaceted, integrated approach was taken by a combination of monitoring, segment analysis, and modeling (Soil and Water Assessment Tool). Thus, the river was monitored for discharge, water chemistry, and loss of nutrients and soil for an entire year (3 August 2010 to 14 February 2012) at the USGS stations at Shaker’s Crossing and Dansville, NY. The Canaseraga Creek Soil and Water Assessment Tool (CCSWAT) model was created, calibrated, and verified for discharge, sediment, and P loss using these data. Based on the measured loading data to a subbasin outlet and the SWAT model, segment analysis was performed on selected subwatersheds to determine sources of material loss. Together these two bodies of information, the total amount of nutrients, sediments, and bacteria lost from the watershed and the sources of these losses, served to direct watershed management. Lastly, the CCSWAT model was employed to test the effectiveness of Best Management Practices (BMPs) on land use and to determine the minimum potential P concentration expected in a forested Canaseraga Creek watershed. With approximately 76.7% of its phosphorus load from anthropogenic sources, the largest subbasin (88,578 ha) of the Genesee River, Canaseraga Creek, should be a high priority for water quality remediation. Reducing phosphorus loads from Canaseraga Creek into the Genesee River is an important step to reduce the impact that the Genesee River has on water quality in the nearshore zone of Lake Ontario. In general, nonpoint sources of agriculture were identified as the leading cause of phosphorus loss in Canaseraga Creek through segment analysis, determination of weekly and event water chemistry, and integration into the Soil and Water Assessment Tool (SWAT) model. Of the various BMPs simulated throughout the whole watershed, grassed waterways were the most effective in reducing TP loading (44.8% reduction) and reducing TP concentration (69.9 μg P/L) at Shaker’s Crossing. But grassed waterways by themselves did not reach either of the target (45 and 65 μg P/L) TP concentrations. Simulations combining grassed waterways with upgraded (tertiary) WWTPs foe the entire watershed resulted in a decreased P concentration of 49.7 μg P/L at Shaker’s Crossing. This simulation suggested a 65 μg P/L is a realistic target concentration and that the 45-μg P/L target may be met with more stringent BMPs. A less costly approach is to focus remediation to a smaller area known to deliver P to the streams. For example, by implementing grassed waterways in the impacted tributaries of Twomile and Buck Run Creeks and the Groveland Flats area, by implementing streambank stabilization in highly erodible main stem areas, and by upgrading WWTPs to tertiary treatment (Tributary Remediation 3), the CCSWAT model predicted a reduction in TP concentration from 104.3 to 71.6 μg P/L

Adapting On Orbit: Conclusions of the STP-H6 Spacecraft Supercomputing for Image and Video Processing Experiment

Spacecraft Supercomputing for Image and Video Processing (SSIVP) was a payload aboard the Department of Defense Space Test Program – Houston 6 pallet deployed on the International Space Station. SSIVP was designed and constructed by graduate students at the NSF Center for Space, High-Performance, and Resilient Computing (SHREC) at the University of Pittsburgh. The primary objective of this experiment was to evaluate resilient- and parallel-computing capabilities in a small-satellite form factor. Five flight computers, each combining radiation-tolerant and commercial-off-the-shelf technologies, were networked by high-speed interconnects, enabling a reliable space-supercomputing paradigm. Image-processing and computer-vision experiments were conducted on Earth-observation imagery acquired from two five-megapixel cameras. The system operated for 30 months, serving as an adaptable and reconfigurable platform to host academic and industry research. Despite on-orbit challenges with thermal constraints and operations, all mission objectives were completed successfully. SSIVP resulted in a dataset of nearly 20,000 images, radiation-effects data, and an increase in the technology-readiness level for two SHREC flight computers. Its designers and operators hope that SSIVP serves as a model for future reconfigurable and adaptable space computing platforms

STP-H7-CASPR: A Transition from Mission Concept to Launch

The Configurable and Autonomous Sensor Processing Research (CASPR) project is a university-led experiment developed by student and faculty researchers at the NSF Center for Space, High-performance, and Resilient Computing (SHREC) at the University of Pittsburgh for the Space Test Program – Houston 7 (STP-H7) mission to the International Space Station (ISS). Autonomous sensor processing, the mission theme of the CASPR experiment, is enabled by combining novel sensor technologies with innovative computing techniques on resilient and high-performance flight hardware in a small satellite (SmallSat) form-factor. CASPR includes the iSIM-90, an innovative, high-resolution optical payload for Earth-observation missions developed by SATLANTIS MICROSATS SL. For the CASPR mission, the opto-mechanics of iSIM-90 will be mounted atop a gimbal-actuated platform for agile, low-GRD (ground-resolved distance), and multispectral Earth-observation imaging. This mission will also feature the Prophesee Sisley neuromorphic, event-driven sensor for space situational awareness applications. The CASPR avionics system consists of the following: three radiation-tolerant, reconfigurable space computers, including one flight-proven CSP and two next-gen SSPs; one μCSP Smart Module; one power card; and one backplane. CASPR also features a sub-experiment with an AMD GPU to evaluate new accelerator technologies for space. CASPR is a highly versatile experiment combining a variety of compute and sensor technologies to demonstrate on-orbit capabilities in onboard data analysis, mission operations, and spacecraft autonomy. As a research sandbox, CASPR enables new software and hardware to be remotely uploaded to further enhance mission capabilities. Finally, as a university-led mission, cost is a limiting constraint, leading to budget-driven design decisions and the use of affordable methods and procedures. Other factors, such as a power budget and limited equipment, facilities, and engineering resources, pose additional challenges to the CASPR mission. To address these challenges, we describe cost-effective procedures and methods used in the assembly, integration, and testing of the CASPR experiment

Heteroatom and side chain effects on the optical and photophysical properties: ultrafast and nonlinear spectroscopy of new Naphtho[1,2-b:5,6-b ']difuran donor polymers

The photophysical and electronic properties of four novel conjugated donor polymers were investigated to understand the influence of heteroatoms (based on the first two member chalcogens) in the polymer backbone. The side chains were varied as well to evaluate the effect of polymer solubility on the photophysical properties. The donor–acceptor polymer structure is based on naptho[1,2-b:5,6-b′]difuran as the donor moiety, and either 3,6-di(furan-2-yl)-1,4-diketopyrrolo[3,4-c]pyrrole or 3,6-di(thiophen-2-yl)-1,4-diketopyrrolo[3,4-c]pyrrole as the acceptor moiety. Steady-state absorption studies showed that the polymers with the furan moiety in the backbone displayed a favorable tendency of capturing more solar photons when used in a photovoltaic device. This is observed experimentally by the higher extinction coefficient in the visible and near-infrared regions of these polymers relative to that of their thiophene counterparts. The excitonic lifetimes were monitored using ultrafast dynamics, and the results obtained show that the type of heteroatom π-linker used in the backbone affects the decay dynamics. Furthermore, the side chain also plays a role in determining the fluorescence decay time. Quantum chemical simulations were performed to describe the absorption energies and transition characters. Two-photon absorption cross sections (TPA-δ) were analyzed with the simulations, illustrating the planarity of the backbone in relation to its torsional angles. Because of the planarity in the molecular backbone, the polymer with the furan π-linker showed a higher TPA-δ relative to that of its thiophene counterpart. This suggests that the furan compound will display higher charge transfer (CT) tendencies in comparison to those of their thiophene analogues. The pump–probe transient absorption technique was employed to probe the nonemissive states (including the CT state) of the polymers, and unique activities were captured at 500 and 750 nm for all of the studied compounds. Target and global analyses were performed to understand the dynamics of each peak and deduce the number of components responsible for the transient behavior observed respectively. The results obtained suggest that the furan π-linker component of a donor and acceptor moiety in a conjugated polymer might be a more suitable candidate compared with its more popular chalcogenic counterpart, thiophene, for use as donor materials in bulk heterojunction photovoltaic devices.Support for this investigation is provided by the National Science Foundation (DMR-1709005) Polymers (TGIII) and (DMR 1410088/1640297) Polymers (MJE). (DMR-1709005 - National Science Foundation; DMR 1410088/1640297 - National Science Foundation)Accepted manuscrip

CASPR: Autonomous Sensor Processing Experiment for STP-H7

As computing technologies improve, spacecraft sensors continue to increase in fidelity and resolution, their dataset sizes and data rates increasing concurrently. This increase in data saturates the capabilities of spacecraft-to-ground communications and necessitates the use of powerful onboard computers to process data as it is collected. The pursuit of onboard, autonomous sensor processing while remaining within the power and memory restrictions of embedded computing becomes vital to prevent the saturation of data downlink capabilities. This paper presents a new ISS research experiment to study and evaluate novel technologies in sensors, computers, and intelligent applications for SmallSat-based sensing with autonomous data processing. Configurable and Autonomous Sensor Processing Research (CASPR) is being developed to evaluate autonomous, onboard processing strategies on novel sensors and is set to be installed on the ISS as part of the DoD/NASA Space Test Program –Houston 7(STP-H7) mission. CASPR features a flight-qualified CSP space computer as central node and two flight-ready SSP space computers for apps execution, both from SHREC, a telescopic, multispectral imager from Satlantis Inc., an event-driven neuromorphic vision sensor, an AMD GPU subsystem, and Intel Optane phase-change memory. CASPR is a highly versatile ISS experiment meant to explore many facets of autonomous sensor processing in space

Adaptive Neural Network-Based Approximation to Accelerate Eulerian Fluid Simulation

The Eulerian fluid simulation is an important HPC application. The neural network has been applied to accelerate it. The current methods that accelerate the fluid simulation with neural networks lack flexibility and generalization. In this paper, we tackle the above limitation and aim to enhance the applicability of neural networks in the Eulerian fluid simulation. We introduce Smartfluidnet, a framework that automates model generation and application. Given an existing neural network as input, Smartfluidnet generates multiple neural networks before the simulation to meet the execution time and simulation quality requirement. During the simulation, Smartfluidnet dynamically switches the neural networks to make the best efforts to reach the user requirement on simulation quality. Evaluating with 20,480 input problems, we show that Smartfluidnet achieves 1.46x and 590x speedup comparing with a state-of-the-art neural network model and the original fluid simulation respectively on an NVIDIA Titan X Pascal GPU, while providing better simulation quality than the state-of-the-art model