On the isomorphism question for complete Pick multiplier algebras

Every multiplier algebra of an irreducible complete Pick kernel arises as the restriction algebra \mv = \{f\big|_V : f \in \cM_d\}, where $d$ is some integer or $\infty$, \cM_d is the multiplier algebra of the Drury-Arveson space $H^2_d$, and $V$ is a subvariety of the unit ball. For finite $d$ it is known that, under mild assumptions, every isomorphism between two such algebras \mv and \mw is induced by a biholomorphism between $W$ and $V$. In this paper we consider the converse, and obtain positive results in two directions. The first deals with the case where $V$ is the proper image of a finite Riemann surface. The second deals with the case where $V$ is a disjoint union of varieties.Comment: 17 pages. Final version, to appear in Integral Equations and Operator Theor

Cal Poly agBOT 2017 Challenge Autonomous Corn Seeding Tractor

The Cal Poly agBOT team researched, designed, and built a Remote Controlled tractor to compete in Gerrish Farms’ agBOT Seeding Challenge 2017. The tractor was procured from the BioResource and Agricultural Engineering department. The tractor served as the base unit, with supporting components mounted onto it. Steering the tractor was accomplished with a auxiliary hydraulic motor mounted to the steering wheel. Throttle and choke were controlled by servo and linear actuator respectively. Both the three point hitch and PowerTakeoff was controlled by linear actuators. All controls were executed by an arduino microcontroller, which was equipped with a remote control. The steering was equipped with a potentiometer for steering feedback and travel direction of the tractor. The corn seeder attached to the three point was equipped with two hoppers, seed sensors, a seed rate motor, and two vacuums to switch between different seed varieties. The tractor effectively plants corn via remote control and competed on June 24th, 2017 at Gerrish Farms, Rockville, Indiana. The days leading up to the event, the tractor was loaded onto a trailer. Three students rented a truck, loaded it up with camping equipment, and hauled the Cal Poly agBOT to Indiana in ~47hrs, with a single 5hr stop to rest. The students and tractor arrived safely, unpacked, and tested the tractor at Gerrish Farms. The day before the competition, Gerrish Farms held an expo for the surrounding community and guests. Many people from all ages and expertise walked around and were thoroughly interested in the Cal Poly teams efforts. The students competed and turned back to California. We placed 2nd in our competition, bringing home $15,000 to support next years agBOT team

Improving Access to Clean Water Through Autonomous Monitoring of Hand Pump Operation

Millions of people in developing countries rely on hand pumps for access to clean water. Proper maintenance of these pumps is impossible without timely reporting on the pump’s operation and state of repair. The Intelligent Water System, which improves access to clean water by autonomously monitoring and reporting on the health of hand pumps, has been under development for several years. The next stage for the IWP team is to prepare for field testing in Zimbabwe. Because of this, the team has been working on improving the accuracy of the calculations made by the Intelligent Water System as well as simplifying the installation procedures to allow installation by in-country pump technicians. This poster shows the progress made by the IWP team during this stage of development including the improvements in the volume calculation algorithm as well as the installation jig and procedures. Funding for this work provided by The Collaboratory for Strategic Partnerships and Applied Research.https://mosaic.messiah.edu/engr2022/1008/thumbnail.jp

A deep learning approach to downscale geostationary satellite imagery for decision support in high impact wildfires

Scarcity in wildland fire progression data as well as considerable uncertainties in forecasts demand improved methods to monitor fire spread in real time. However, there exists at present no scalable solution to acquire consistent information about active forest fires that is both spatially and temporally explicit. To overcome this limitation, we propose a statistical downscaling scheme based on deep learning that leverages multi-source Remote Sensing (RS) data. Our system relies on a U-Net Convolutional Neural Network (CNN) to downscale Geostationary (GEO) satellite multispectral imagery and continuously monitor active fire progression with a spatial resolution similar to Low Earth Orbit (LEO) sensors. In order to achieve this, the model trains on LEO RS products, land use information, vegetation properties, and terrain data. The practical implementation has been optimized to use cloud compute clusters, software containers and multi-step parallel pipelines in order to facilitate real time operational deployment. The performance of the model was validated in five wildfires selected from among the most destructive that occurred in California in 2017 and 2018. These results demonstrate the effectiveness of the proposed methodology in monitoring fire progression with high spatiotemporal resolution, which can be instrumental for decision support during the first hours of wildfires that may quickly become large and dangerous. Additionally, the proposed methodology can be leveraged to collect detailed quantitative data about real-scale wildfire behaviour, thus supporting the development and validation of fire spread models

Predicting Future Space Near-IR Grism Surveys using the WFC3 Infrared Spectroscopic Parallels Survey

We present near-infrared emission line counts and luminosity functions from the HST WFC3 Infrared Spectroscopic Parallels (WISP) program for 29 fields (0.037 deg^2) observed using both the G102 and G141 grisms. Altogether we identify 1048 emission line galaxies with observed equivalent widths greater than 40 Angstroms, 467 of which have multiple detected emission lines. The WISP survey is sensitive to fainter flux levels (3-5x10^-17 ergs/s/cm^2) than the future space near-infrared grism missions aimed at baryonic acoustic oscillation cosmology (1-4x10^-16 ergs/s/cm^2), allowing us to probe the fainter emission line galaxies that the shallower future surveys may miss. Cumulative number counts of 0.7<z<1.5 galaxies reach 10,000 deg^-2 above an H-alpha flux of 2x10^-16 ergs/s/cm^2. H-alpha-emitting galaxies with comparable [OIII] flux are roughly 5 times less common than galaxies with just H-alpha emission at those flux levels. Galaxies with low H-alpha/[OIII] ratios are very rare at the brighter fluxes that future near-infrared grism surveys will probe; our survey finds no galaxies with H-alpha/[OIII] < 0.95 that have H-alpha flux greater than 3x10^-16 ergs/s/cm^2. Our H-alpha luminosity function contains a comparable number density of faint line emitters to that found by the NICMOS near-infrared grism surveys, but significantly fewer (factors of 3-4 less) high luminosity emitters. We also find that our high redshift (z=0.9-1.5) counts are in agreement with the high redshift (z=1.47) narrow band H-alpha survey of HiZELS (Sobral et al. 2013), while our lower redshift luminosity function (z=0.3-0.9) falls slightly below their z=0.84 result. The evolution in both the H-alpha luminosity function from z=0.3--1.5 and the [OIII] luminosity function from z=0.7-2.3 is almost entirely in the L* parameter, which steadily increases with redshift over those ranges.Comment: 18 pages, 14 figures, Accepted by Ap

Laboratory and tentative interstellar detection of trans-methyl formate using the publicly available Green Bank Telescope PRIMOS survey

The rotational spectrum of the higher-energy trans conformational isomer of methyl formate has been assigned for the first time using several pulsed-jet Fourier transform microwave spectrometers in the 6-60 GHz frequency range. This species has also been sought toward the Sagittarius B2(N) molecular cloud using the publicly available PRIMOS survey from the Green Bank Telescope. We detect seven absorption features in the survey that coincide with laboratory transitions of trans-methyl formate, from which we derive a column density of 3.1 (+2.6, -1.2) \times 10^13 cm-2 and a rotational temperature of 7.6 \pm 1.5 K. This excitation temperature is significantly lower than that of the more stable cis conformer in the same source but is consistent with that of other complex molecular species recently detected in Sgr B2(N). The difference in the rotational temperatures of the two conformers suggests that they have different spatial distributions in this source. As the abundance of trans-methyl formate is far higher than would be expected if the cis and trans conformers are in thermodynamic equilibrium, processes that could preferentially form trans-methyl formate in this region are discussed. We also discuss measurements that could be performed to make this detection more certain. This manuscript demonstrates how publicly available broadband radio astronomical surveys of chemically rich molecular clouds can be used in conjunction with laboratory rotational spectroscopy to search for new molecules in the interstellar medium.Comment: 40 pages, 7 figures, 4 tables; accepted for publication in Ap

Indirect eff ects of childhood pneumococcal conjugate vaccination on invasive pneumococcal disease: a systematic review and meta-analysis

Background The full extent to which childhood pneumococcal conjugate vaccines (PCV) can indirectly reduce illness in unvaccinated populations is not known. We aimed to estimate the magnitude and timing of indirect eff ects of PCVs on invasive pneumococcal disease. Methods In this systematic review and meta-analysis, we searched bibliographic databases for non-randomised quasiexperimental or observational studies reporting invasive pneumococcal disease changes following PCV introduction in unvaccinated populations (studies published Sept 1, 2010, to Jan 6, 2016), updating the previous systematic review of the same topic (studies published Jan 1, 1994, to Sept 30, 2010). Two reviewers extracted summary data by consensus. We used a Bayesian mixed-eff ects model to account for between-study heterogeneity to estimate temporal indirect eff ects by pooling of invasive pneumococcal disease changes by serotype and serogroup. Findings Data were extracted from 70 studies included in the previous review and 172 additional studies, covering 27 high-income and seven middle-income countries. The predicted mean times to attaining a 90% reduction in invasive pneumococcal disease were 8·9 years (95% credible interval [CrI] 7·8–10·3) for grouped serotypes contained in the seven-valent PCV (PCV7), and 9·5 years (6·1–16·6) for the grouped six additional serotypes contained in the 13-valent PCV (PCV13) but not in PCV7. Disease due to grouped serotypes contained in the 23-valent pneumococcal polysaccharide vaccine (PPV23) decreased at similar rates per year in adults aged 19–64 years (relative risk [RR] 0·85, 95% CrI 0·75–0·95) and 65 years and older (0·87, 0·84–0·90). However, we noted no changes in either group in invasive pneumococcal disease caused by the additional 11 serotypes covered by PPV23 but not PCV13. Interpretation Population childhood PCV programmes will lead, on average, to substantial protection across the whole population within a decade. This large indirect protection should be considered when assessing vaccination of older age groups

Forecasting ward-level bed requirements to aid pandemic resource planning: Lessons learned and future directions

During the COVID-19 pandemic, there has been considerable research on how regional and country-level forecasting can be used to anticipate required hospital resources. We add to and build on this work by focusing on ward-level forecasting and planning tools for hospital staff during the pandemic. We present an assessment, validation, and deployment of a working prototype forecasting tool used within a modified Traffic Control Bundling (TCB) protocol for resource planning during the pandemic. We compare statistical and machine learning forecasting methods and their accuracy at one of the largest hospitals (Vancouver General Hospital) in Canada against a medium-sized hospital (St. Paul's Hospital) in Vancouver, Canada through the first three waves of the COVID-19 pandemic in the province of British Columbia. Our results confirm that traditional statistical and machine learning (ML) forecasting methods can provide valuable ward-level forecasting to aid in decision-making for pandemic resource planning. Using point forecasts with upper 95% prediction intervals, such forecasting methods would have provided better accuracy in anticipating required beds on COVID-19 hospital units than ward-level capacity decisions made by hospital staff. We have integrated our methodology into a publicly available online tool that operationalizes ward-level forecasting to aid with capacity planning decisions. Importantly, hospital staff can use this tool to translate forecasts into better patient care, less burnout, and improved planning for all hospital resources during pandemics

Decoupling of Sleep-Dependent Cortical and Hippocampal Interactions in a Neurodevelopmental Model of Schizophrenia

SummaryRhythmic neural network activity patterns are defining features of sleep, but interdependencies between limbic and cortical oscillations at different frequencies and their functional roles have not been fully resolved. This is particularly important given evidence linking abnormal sleep architecture and memory consolidation in psychiatric diseases. Using EEG, local field potential (LFP), and unit recordings in rats, we show that anteroposterior propagation of neocortical slow-waves coordinates timing of hippocampal ripples and prefrontal cortical spindles during NREM sleep. This coordination is selectively disrupted in a rat neurodevelopmental model of schizophrenia: fragmented NREM sleep and impaired slow-wave propagation in the model culminate in deficient ripple-spindle coordination and disrupted spike timing, potentially as a consequence of interneuronal abnormalities reflected by reduced parvalbumin expression. These data further define the interrelationships among slow-wave, spindle, and ripple events, indicating that sleep disturbances may be associated with state-dependent decoupling of hippocampal and cortical circuits in psychiatric diseases