Transition from synchronous to asynchronous superfluid phase slippage in an aperture array

We have investigated the dynamics of superfluid phase slippage in an array of apertures. The magnitude of the dissipative phase slips shows that they occur simultaneously in all the apertures when the temperature is around 10 mK below the superfluid transition, and subsequently lose their simultaneity as the temperature is lowered. We find that when periodic synchronous phase slippage occurs, the synchronicity exists from the very first phase slip, and therefore is not due to mode locking of interacting oscillators. When the system is allowed to relax freely from a given initial energy, the total number of phase slips that occur and the energy left in the system after the last phase slip depends reproducibly on the initial energy. We find the energy remaining after the final phase slip is a periodic function of the initial system energy. This dependence directly reveals the discrete and dissipative nature of the phase slips and is a powerful diagnostic for investigation of synchronicity in the array. When the array slips synchronously, this periodic energy function is a sharp sawtooth. As the temperature is lowered and the degree of synchronicity drops, the peak of this sawtooth becomes rounded, suggesting a broadening of the time interval over which the array slips. The underlying mechanism for the higher temperature synchronous behavior and the following loss of synchronicity at lower temperatures is not yet understood. We discuss the implications of our measurements and pose several questions that need to be resolved by a theory explaining the synchronous behavior in this quantum system. An understanding of the array phase slip process is essential to the optimization of superfluid `dc-SQUID' gyroscopes and interferometers.Comment: 10 pages, 4 figure

The Impact of Soil Sampling Errors on Variable Rate Fertilization

Variable rate fertilization of an agricultural field is done taking into account spatial variability in the soil’s characteristics. Most often, spatial variability in the soil’s fertility is the primary characteristic used to determine the differences in fertilizers applied from one point to the next. For several years the Idaho National Engineering and Environmental Laboratory (INEEL) has been developing a Decision Support System for Agriculture (DSS4Ag) to determine the economically optimum recipe of various fertilizers to apply at each site in a field, based on existing soil fertility at the site, predicted yield of the crop that would result (and a predicted harvest-time market price), and the current costs and compositions of the fertilizers to be applied. Typically, soil is sampled at selected points within a field, the soil samples are analyzed in a lab, and the lab-measured soil fertility of the point samples is used for spatial interpolation, in some statistical manner, to determine the soil fertility at all other points in the field. Then a decision tool determines the fertilizers to apply at each point. Our research was conducted to measure the impact on the variable rate fertilization recipe caused by variability in the measurement of the soil’s fertility at the sampling points. The variability could be laboratory analytical errors or errors from variation in the sample collection method. The results show that for many of the fertility parameters, laboratory measurement error variance exceeds the estimated variability of the fertility measure across grid locations. These errors resulted in DSS4Ag fertilizer recipe recommended application rates that differed by up to 138 pounds of urea per acre, with half the field differing by more than 57 pounds of urea per acre. For potash the difference in application rate was up to 895 pounds per acre and over half the field differed by more than 242 pounds of potash per acre. Urea and potash differences accounted for almost 87% of the cost difference. The sum of these differences could result in a $34 per acre cost difference for the fertilization. Because of these differences, better analysis or better sampling methods may need to be done, or more samples collected, to ensure that the soil measurements are truly representative of the field’s spatial variability

A Phase transition in acoustic propagation in 2D random liquid media

Acoustic wave propagation in liquid media containing many parallel air-filled cylinders is considered. A self-consistent method is used to compute rigorously the propagation, incorporating all orders of multiple scattering. It is shown that under proper conditions, multiple scattering leads to a peculiar phase transition in acoustic propagation. When the phase transition occurs, a collective behavior of the cylinders appears and the acoustic waves are confined in a region of space in the neighborhood of the transmission source. A novel phase diagram is used to describe such phase transition. Originally submitted on April 6, 99.Comment: 5 pages, 5 color figure

Multilocation Corn Stover Harvest Effects on Crop Yields and Nutrient Removal

Corn (Zea mays L.) stover was identified as an important feedstock for cellulosic bioenergy production because of the extensive area upon which the crop is already grown. This report summarizes 239 site-years of field research examining effects of zero, moderate, and high stover removal rates at 36 sites in seven different states. Grain and stover yields from all sites as well as N, P, and K removal from 28 sites are summarized for nine longitude and six latitude bands, two tillage practices (conventional vs no tillage), two stover-harvest methods (machine vs calculated), and two crop rotations {continuous corn (maize) vs corn/soybean [Glycine max (L.) Merr.]}. Mean grain yields ranged from 5.0 to 12.0 Mg ha−1 (80 to 192 bu ac−1). Harvesting an average of 3.9 or 7.2 Mg ha−1(1.7 or 3.2 tons ac−1) of the corn stover resulted in a slight increase in grain yield at 57 and 51 % of the sites, respectively. Average no-till grain yields were significantly lower than with conventional tillage when stover was not harvested, but not when it was collected. Plant samples collected between physiological maturity and combine harvest showed that compared to not harvesting stover, N, P, and K removal was increased by 24, 2.7, and 31 kg ha−1, respectively, with moderate (3.9 Mg ha−1) harvest and by 47, 5.5, and 62 kg ha−1, respectively, with high (7.2 Mg ha−1) removal. This data will be useful for verifying simulation models and available corn stover feedstock projections, but is too variable for planning site-specific stover harvest

Development of a Novel ex vivo Nasal Epithelial Cell Model Supporting Colonization With Human Nasal Microbiota

The nasal mucosa provides first line defense against inhaled pathogens while creating a unique microenvironment for bacterial communities. Studying the impact of microbiota in the nasal cavity has been difficult due to limitations with current models including explant cultures, primary cells, or neoplastic cell lines. Most notably, none have been shown to support reproducible colonization by bacterial communities from human donors. Therefore, to conduct controlled studies of the human nasal ecosystem, we have developed a novel ex vivo mucosal model that supports bacterial colonization of a cultured host mucosa created by immortalized human nasal epithelial cells (NEC). For this model, immortalized NEC established from 5 male and 5 female donors were cultured with an air-interfaced, apical surface on a porous transwell membrane. NEC were grown from nasal turbinate tissues harvested from willed bodies or from discarded tissue collected during sinonasal procedures. Immortalized cells were evaluated through molecular verification of cell type, histological confirmation of tissue differentiation including formation of tight junctions, NEC multilayer viability, metabolism, physiology and imaging of the luminal surface by scanning electron microscopy. Results showed proper differentiation and multilayer formation at seven to 10 days after air interface that was maintained for up to 3 weeks. The optimized mucosal cultures created an environment necessary to sustain colonization by nasal microbiomes (NMBs) that were collected from healthy volunteers, cryogenically preserved and characterized with customized quantitative polymerase chain reaction (qPCR) arrays. Polymicrobial communities of nasal bacteria associated with healthy and inflamed states were consistently reproduced in matured NEC co-cultures by transplant of NMBs from multiple community types. The cultured NMBs were stable after an initial period of bacterial replication and equilibration. This novel ex vivo culture system is the first model that supports controlled cultivation of NMBs, allowing for lab-based causation studies and further experimentation to explore the complexities of host-microbe and microbe-microbe interactions

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson\u27s disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia