Virginia Tech Ionospheric Scintillation Measurement Mission

The Virginia Tech Ionospheric Scintillation Measurement Mission (VTISMM) is a small spacecraft design, build, and fly project being funded by the Air Force Research Laboratory, the Defense Advanced Research Projects Agency, and NASA\u27s Goddard Space Flight Center. The mission concept includes one 10 kg spacecraft that will fly in formation with two similar satellites being built by students at Utah State University and the University of Washington. The three satellites will fly in close proximity, using GPS receivers for position determination, microsensors for attitude determination, interlink communications for data transmission and relative position determination, microthrusters and differential drag for formation-keeping, and GlobalStar for telemetry, tracking, and commanding. The three satellites will share two ground stations to be located at Utah State and Virginia Tech. The VTISMM science mission focuses on collecting and analyzing GPS data to characterize ionospheric scintillation effects on the communications signals, and all three satellites will operate probes for collecting additional data about the ionosphere. The three-satellite formation is called the Ionosphere Observation Nanosatellite Formation (ION-F), and will be launched on a space shuttle via the Shuttle Hitchhiker Experiment Launch System (SHELS)

Imaging in Suspected Renal Colic: Systematic Review of the Literature and Multispecialty Consensus

Background Renal colic is common, and CT is frequently utilized when the diagnosis of kidney stones is suspected. CT is accurate but exposes patients to ionizing radiation and has not been shown to alter either interventional approaches or hospital admission rates. This multi-organizational transdisciplinary collaboration sought evidence-based, multispecialty consensus on optimal imaging across different clinical scenarios in patients with suspected renal colic in the acute setting. Methods In conjunction with the American College of Emergency Physicians (ACEP) eQual network, we formed a nine-member panel with three physician representatives each from ACEP, the ACR, and the American Urology Association. A systematic literature review was used as the basis for a three-step modified Delphi process to seek consensus on optimal imaging in 29 specific clinical scenarios. Results From an initial search yielding 6,337 records, there were 232 relevant articles of acceptable evidence quality to guide the literature summary. At the completion of the Delphi process consensus, agreement was rated as perfect in 15 (52%), excellent in 8 (28%), good in 3 (10%), and moderate in 3 (10%) of the 29 scenarios. There were no scenarios where at least moderate consensus was not reached. CT was recommended in 7 scenarios (24%), with ultrasound in 9 (31%) and no further imaging needed in 12 (45%). Summary Evidence and multispecialty consensus support ultrasound or no further imaging in specific clinical scenarios, with reduced-radiation dose CT to be employed when CT is needed in patients with suspected renal colic

Fit to Predict? Ecoinformatics for Predicting the Catchability of a Pelagic Fish in Near Real-Time

The ocean is a dynamic environment inhabited by a diverse array of highly migratory species, many of which are under direct exploitation in targeted fisheries. The timescales of variability in the marine realm coupled with the extreme mobility of ocean-wandering species such as tuna and billfish complicates fisheries management. Developing ecoinformatics solutions that allow for near real-time prediction of the distributions of highly mobile marine species is an important step towards the maturation of dynamic ocean management and ecological forecasting. Using 25 years (1990-2014) of NOAA fisheries\u27 observer data from the California drift gillnet fishery, we model relative probability of occurrence (presence-absence) and catchability (total catch) of broadbill swordfish Xiphias gladius in the California Current System (CCS). Using freely-available environmental datasets and open source software, we explore the physical drivers of regional swordfish distribution. Comparing models built upon remotely-sensed datasets with those built upon a data-assimilative configuration of the Regional Ocean Modelling System (ROMS), we explore trade-offs in model construction and address how physical data can affect predictive performance and operational capacity. Swordfish catchability was found to be highest in deeper waters (\u3e1500m) with surface temperatures in the 14-20 degrees C range, isothermal layer depth (ILD) of 20-40m, positive sea surface height anomalies and during the new moon

Integrating Dynamic Subsurface Habitat Metrics Into Species Distribution Models

Species distribution models (SDMs) have become key tools for describing and predicting species habitats. In the marine domain, environmental data used in modeling species distributions are often remotely sensed, and as such have limited capacity for interpreting the vertical structure of the water column, or are sampled in situ, offering minimal spatial and temporal coverage. Advances in ocean models have improved our capacity to explore subsurface ocean features, yet there has been limited integration of such features in SDMs. Using output from a data-assimilative configuration of the Regional Ocean Modeling System, we examine the effect of including dynamic subsurface variables in SDMs to describe the habitats of four pelagic predators in the California Current System (swordfish Xiphias gladius, blue sharks Prionace glauca, common thresher sharks Alopias vulpinus, and shortfin mako sharks lsurus oxyrinchus). Species data were obtained from the California Drift Gillnet observer program (1997-2017). We used boosted regression trees to explore the incremental improvement enabled by dynamic subsurface variables that quantify the structure and stability of the water column: isothermal layer depth and bulk buoyancy frequency. The inclusion of these dynamic subsurface variables significantly improved model explanatory power for most species. Model predictive performance also significantly improved, but only for species that had strong affiliations with dynamic variables (swordfish and shortfin mako sharks) rather than static variables (blue sharks and common thresher sharks). Geospatial predictions for all species showed the integration of isothermal layer depth and bulk buoyancy frequency contributed value at the mesoscale level (\u3c 100 km) and varied spatially throughout the study domain. These results highlight the utility of including dynamic subsurface variables in SDM development and support the continuing ecological use of biophysical output from ocean circulation models

Large Language Models Encode Clinical Knowledge

Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and generation, but the quality bar for medical and clinical applications is high. Today, attempts to assess models' clinical knowledge typically rely on automated evaluations on limited benchmarks. There is no standard to evaluate model predictions and reasoning across a breadth of tasks. To address this, we present MultiMedQA, a benchmark combining six existing open question answering datasets spanning professional medical exams, research, and consumer queries; and HealthSearchQA, a new free-response dataset of medical questions searched online. We propose a framework for human evaluation of model answers along multiple axes including factuality, precision, possible harm, and bias. In addition, we evaluate PaLM (a 540-billion parameter LLM) and its instruction-tuned variant, Flan-PaLM, on MultiMedQA. Using a combination of prompting strategies, Flan-PaLM achieves state-of-the-art accuracy on every MultiMedQA multiple-choice dataset (MedQA, MedMCQA, PubMedQA, MMLU clinical topics), including 67.6% accuracy on MedQA (US Medical License Exam questions), surpassing prior state-of-the-art by over 17%. However, human evaluation reveals key gaps in Flan-PaLM responses. To resolve this we introduce instruction prompt tuning, a parameter-efficient approach for aligning LLMs to new domains using a few exemplars. The resulting model, Med-PaLM, performs encouragingly, but remains inferior to clinicians. We show that comprehension, recall of knowledge, and medical reasoning improve with model scale and instruction prompt tuning, suggesting the potential utility of LLMs in medicine. Our human evaluations reveal important limitations of today's models, reinforcing the importance of both evaluation frameworks and method development in creating safe, helpful LLM models for clinical applications

Identification of Nine Novel Loci Associated with White Blood Cell Subtypes in a Japanese Population

White blood cells (WBCs) mediate immune systems and consist of various subtypes with distinct roles. Elucidation of the mechanism that regulates the counts of the WBC subtypes would provide useful insights into both the etiology of the immune system and disease pathogenesis. In this study, we report results of genome-wide association studies (GWAS) and a replication study for the counts of the 5 main WBC subtypes (neutrophils, lymphocytes, monocytes, basophils, and eosinophils) using 14,792 Japanese subjects enrolled in the BioBank Japan Project. We identified 12 significantly associated loci that satisfied the genome-wide significance threshold of P<5.0×10−8, of which 9 loci were novel (the CDK6 locus for the neutrophil count; the ITGA4, MLZE, STXBP6 loci, and the MHC region for the monocyte count; the SLC45A3-NUCKS1, GATA2, NAALAD2, ERG loci for the basophil count). We further evaluated associations in the identified loci using 15,600 subjects from Caucasian populations. These WBC subtype-related loci demonstrated a variety of patterns of pleiotropic associations within the WBC subtypes, or with total WBC count, platelet count, or red blood cell-related traits (n = 30,454), which suggests unique and common functional roles of these loci in the processes of hematopoiesis. This study should contribute to the understanding of the genetic backgrounds of the WBC subtypes and hematological traits