Classification Tree Models for Predicting Distributions of Michigan Stream Fish from Landscape Variables

Traditionally, fish habitat requirements have been described from local‐scale environmental variables. However, recent studies have shown that studying landscape‐scale processes improves our understanding of what drives species assemblages and distribution patterns across the landscape. Our goal was to learn more about constraints on the distribution of Michigan stream fish by examining landscape‐scale habitat variables. We used classification trees and landscape‐scale habitat variables to create and validate presence‐absence models and relative abundance models for Michigan stream fishes. We developed 93 presence‐absence models that on average were 72% correct in making predictions for an independent data set, and we developed 46 relative abundance models that were 76% correct in making predictions for independent data. The models were used to create statewide predictive distribution and abundance maps that have the potential to be used for a variety of conservation and scientific purposes.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141481/1/tafs0976.pd

Comparison between estimation of breeding values and fixed effects using Bayesian and empirical BLUP estimation under selection on parents and missing pedigree information

Bayesian (via Gibbs sampling) and empirical BLUP (EBLUP) estimation of fixed effects and breeding values were compared by simulation. Combinations of two simulation models (with or without effect of contemporary group (CG)), three selection schemes (random, phenotypic and BLUP selection), two levels of heritability (0.20 and 0.50) and two levels of pedigree information (0% and 15% randomly missing) were considered. Populations consisted of 450 animals spread over six discrete generations. An infinitesimal additive genetic animal model was assumed while simulating data. EBLUP and Bayesian estimates of CG effects and breeding values were, in all situations, essentially the same with respect to Spearman's rank correlation between true and estimated values. Bias and mean square error (MSE) of EBLUP and Bayesian estimates of CG effects and breeding values showed the same pattern over the range of simulated scenarios. Methods were not biased by phenotypic and BLUP selection when pedigree information was complete, albeit MSE of estimated breeding values increased for situations where CG effects were present. Estimation of breeding values by Bayesian and EBLUP was similarly affected by joint effect of phenotypic or BLUP selection and randomly missing pedigree information. For both methods, bias and MSE of estimated breeding values and CG effects substantially increased across generations

On the Delta set and catenary degree of Krull monoids with infinite cyclic divisor class group

AbstractLet M be a Krull monoid with divisor class group Z, and let S⊆Z denote the set of divisor classes of M which contain prime divisors. We find conditions on S equivalent to the finiteness of both Δ(M), the Delta set of M, and c(M), the catenary degree of M. In the finite case, we obtain explicit upper bounds on maxΔ(M) and c(M). Our methods generalize and complement a previous result concerning the elasticity of M

Analytical sensitivity of COVID-19 rapid antigen tests: A case for a robust reference standard

Aggressive diagnostic testing remains an indispensable strategy for health and aged care facilities to prevent the transmission of SARS-CoV-2 in vulnerable populations. The preferred diagnostic platform has shifted towards COVID-19 rapid antigen tests (RATs) to identify the most infectious individuals. As such, RATs are being manufactured faster than at any other time in our history yet lack the relevant quantitative analytics required to inform on absolute analytical sensitivity enabling manufacturers to maintain high batch-to-batch reproducibility, and end-users to accurately compare brands for decision making. Here, we describe a novel reference standard to measure and compare the analytical sensitivity of RATs using a recombinant GFP-tagged nucleocapsid protein (NP-GFP). Importantly, we show that the GFP tag does not interfere with NP detection and provides several advantages affording streamlined protein expression and purification in high yields as well as faster, cheaper and more sensitive quality control measures for post-production assessment of protein solubility and stability. Ten commercial COVID-19 RATs were evaluated and ranked using NP-GFP as a reference standard. Analytical sensitivity data of the selected devices as determined with NP-GFP did not correlate with those reported by the manufacturers using the median tissue culture infectious dose (TCID50) assay. Of note, TCID50 discordance has been previously reported. Taken together, our results highlight an urgent need for a reliable reference standard for evaluation and benchmarking of the analytical sensitivity of RAT devices. NP-GFP is a promising candidate as a reference standard that will ensure that RAT performance is accurately communicated to healthcare providers and the public

Impact of Atmospheric Correction on Classification and Quantification of Seagrass Density from WorldView-2 Imagery

Mapping the seagrass distribution and density in the underwater landscape can improve global Blue Carbon estimates. However, atmospheric absorption and scattering introduce errors in space-based sensors’ retrieval of sea surface reflectance, affecting seagrass presence, density, and above-ground carbon (AGCseagrass) estimates. This study assessed atmospheric correction’s impact on mapping seagrass using WorldView-2 satellite imagery from Saint Joseph Bay, Saint George Sound, and Keaton Beach in Florida, USA. Coincident in situ measurements of water-leaving radiance (Lw), optical properties, and seagrass leaf area index (LAI) were collected. Seagrass classification and the retrieval of LAI were compared after empirical line height (ELH) and dark-object subtraction (DOS) methods were used for atmospheric correction. DOS left residual brightness in the blue and green bands but had minimal impact on the seagrass classification accuracy. However, the brighter reflectance values reduced LAI retrievals by up to 50% compared to ELH-corrected images and ground-based observations. This study offers a potential correction for LAI underestimation due to incomplete atmospheric correction, enhancing the retrieval of seagrass density and above-ground Blue Carbon from WorldView-2 imagery without in situ observations for accurate atmospheric interference correction

Orientifolds and the Refined Topological String

We study refined topological string theory in the presence of orientifolds by counting second-quantized BPS states in M-theory. This leads us to propose a new integrality condition for both refined and unrefined topological strings when orientifolds are present. We define the SO(2N) refined Chern-Simons theory which computes refined open string amplitudes for branes wrapping Seifert three-manifolds. We use the SO(2N) refined Chern-Simons theory to compute new invariants of torus knots that generalize the Kauffman polynomials. At large N, the SO(2N) refined Chern-Simons theory on the three-sphere is dual to refined topological strings on an orientifold of the resolved conifold, generalizing the Gopakumar-Sinha-Vafa duality. Finally, we use the (2,0) theory to define and solve refined Chern-Simons theory for all ADE gauge groups

Observational evidence for self-interacting cold dark matter

Cosmological models with cold dark matter composed of weakly interacting particles predict overly dense cores in the centers of galaxies and clusters and an overly large number of halos within the Local Group compared to actual observations. We propose that the conflict can be resolved if the cold dark matter particles are self-interacting with a large scattering cross-section but negligible annihilation or dissipation. In this scenario, astronomical observations may enable us to study dark matter properties that are inaccessible in the laboratoryComment: 4 pages, no figures; added references, pedagogical improvements, to appear in PR

Existence of long-lasting experience-dependent plasticity in endocrine cell networks

Experience-dependent plasticity of cell and tissue function is critical for survival by allowing organisms to dynamically adjust physiological processes in response to changing or harsh environmental conditions. Despite the conferred evolutionary advantage, it remains unknown whether emergent experience-dependent properties are present in cell populations organized as networks within endocrine tissues involved in regulating body-wide homeostasis. Here we show, using lactation to repeatedly activate a specific endocrine cell network in situ in the mammalian pituitary, that templates of prior demand are permanently stored through stimulus-evoked alterations to the extent and strength of cell–cell connectivity. Strikingly, following repeat stimulation, evolved population behaviour leads to improved tissue output. As such, long-lasting experience-dependent plasticity is an important feature of endocrine cell networks and underlies functional adaptation of hormone release

BC4GO: a full-text corpus for the BioCreative IV GO task

Gene function curation via Gene Ontology (GO) annotation is a common task among Model Organism Database groups. Owing to its manual nature, this task is considered one of the bottlenecks in literature curation. There have been many previous attempts at automatic identification of GO terms and supporting information from full text. However, few systems have delivered an accuracy that is comparable with humans. One recognized challenge in developing such systems is the lack of marked sentence-level evidence text that provides the basis for making GO annotations. We aim to create a corpus that includes the GO evidence text along with the three core elements of GO annotations: (i) a gene or gene product, (ii) a GO term and (iii) a GO evidence code. To ensure our results are consistent with real-life GO data, we recruited eight professional GO curators and asked them to follow their routine GO annotation protocols. Our annotators marked up more than 5000 text passages in 200 articles for 1356 distinct GO terms. For evidence sentence selection, the inter-annotator agreement (IAA) results are 9.3% (strict) and 42.7% (relaxed) in F1-measures. For GO term selection, the IAAs are 47% (strict) and 62.9% (hierarchical). Our corpus analysis further shows that abstracts contain ∼10% of relevant evidence sentences and 30% distinct GO terms, while the Results/Experiment section has nearly 60% relevant sentences and >70% GO terms. Further, of those evidence sentences found in abstracts, less than one-third contain enough experimental detail to fulfill the three core criteria of a GO annotation. This result demonstrates the need of using full-text articles for text mining GO annotations. Through its use at the BioCreative IV GO (BC4GO) task, we expect our corpus to become a valuable resource for the BioNLP research community