Combinatorial classification of quantum lens spaces

We answer the question of how large the dimension of a quantum lens space must be, compared to the primary parameter $r$, for the isomorphism class to depend on the secondary parameters. Since classification results in C*-algebra theory reduces this question to one concerning a certain kind of $SL$-equivalence of integer matrices of a special form, our approach is entirely combinatorial and based on the counting of certain paths in the graphs shown by Hong and Szyma\'nski to describe the quantum lens spaces.Comment: 27 pages, 2 figure

Can pathoanatomical pathways of degeneration in lumbar motion segments be identified by clustering MRI findings

Background: Magnetic Resonance Imaging (MRI) is the gold standard for detailed visualisation of spinal pathological and degenerative processes, but the prevailing view is that such imaging findings have little or no clinical relevance for low back pain. This is because these findings appear to have little association with treatment effects in clinical populations, and mostly a weak association with the presence of pain in the general population.However, almost all research into these associations is based on the examination of individual MRI findings, despite its being very common for multiple MRI findings to coexist. Therefore, this proof-of-concept study investigated the capacity of a multivariable statistical method to identify clusters of MRI findings and for those clusters to be grouped into pathways of vertebral degeneration. Methods. This study is a secondary analysis of data from 631 patients, from an outpatient spine clinic, who had been screened for inclusion in a randomised controlled trial. The available data created a total sample pool of 3,155 vertebral motion segments. The mean age of the cohort was 42 years (SD 10.8, range 18-73) and 54% were women.MRI images were quantitatively coded by an experienced musculoskeletal research radiologist using a detailed and standardised research MRI evaluation protocol that has demonstrated high reproducibility. Comprehensive MRI findings descriptive of the disco-vertebral component of lumbar vertebrae were clustered using Latent Class Analysis. Two pairs of researchers, each containing an experienced MRI researcher, then independently categorised the clusters into hypothetical pathoanatomic pathways based on the known histological changes of discovertebral degeneration. Results: Twelve clusters of MRI findings were identified, described and grouped into five different hypothetical pathways of degeneration that appear to have face validity. Conclusions: This study has shown that Latent Class Analysis can be used to identify clusters of MRI findings from people with LBP and that those clusters can be grouped into degenerative pathways that are biologically plausible. If these clusters of MRI findings are reproducible in other datasets of similar patients, they may form a stable platform to investigate the relationship between degenerative pathways and clinically important characteristics such as pain and activity limitation

Degenerative Pathways of Lumbar Motion Segments--A Comparison in Two Samples of Patients with Persistent Low Back Pain

Background: Magnetic resonance imaging (MRI) is used to identify spinal pathoanatomy in people with persistent low back pain. However, the clinical relevance of spinal degenerative MRI findings remains uncertain. Although multiple MRI findings are almost always present at the same time, research into the association with clinical outcomes (such as pain) has predominantly focused on individual MRI findings. This study aimed to: (i) investigate how multiple MRI lumbar spine findings cluster together within two different samples of patients with low back pain, (ii) classify these clusters into hypothetical pathways of degeneration based on scientific knowledge of disco-vertebral degeneration, and (iii) compare these clusters and degenerative pathways between samples. Methods: We performed a secondary cross-sectional analysis on two dissimilar MRI samples collected in a hospital department: (1) data from the spinal MRI reports of 4,162 low back pain patients and (2) data from an MRI research protocol of 631 low back pain patients. Latent Class Analysis was used in both samples to cluster MRI findings from lumbar motion segments. Using content analysis, each cluster was then categorised into hypothetical pathways of degeneration. Results: Six clusters of MRI findings were identified in each of the two samples. The content of the clusters in the two samples displayed some differences but had the same overall pattern of MRI findings. Although the hypothetical degenerative pathways identified in the two samples were not identical, the overall pattern of increasing degeneration within the pathways was the same. Conclusions: It was expected that different clusters could emerge from different samples, however, when organised into hypothetical pathways of degeneration, the overall pattern of increasing degeneration was similar and biologically plausible. This evidence of reproducibility suggests that Latent Class Analysis may provide a new approach to investigating the relationship between MRI findings and clinically important characteristics such as pain and activity limitation

Identification and characterization of a bacterial glutamic peptidase

<p>Abstract</p> <p>Background</p> <p>Glutamic peptidases, from the MEROPS family G1, are a distinct group of peptidases characterized by a catalytic dyad consisting of a glutamate and a glutamine residue, optimal activity at acidic pH and insensitivity towards the microbial derived protease inhibitor, pepstatin. Previously, only glutamic peptidases derived from filamentous fungi have been characterized.</p> <p>Results</p> <p>We report the first characterization of a bacterial glutamic peptidase (pepG1), derived from the thermoacidophilic bacteria <it>Alicyclobacillus </it><it>sp</it>. DSM 15716. The amino acid sequence identity between pepG1 and known fungal glutamic peptidases is only 24-30% but homology modeling, the presence of the glutamate/glutamine catalytic dyad and a number of highly conserved motifs strongly support the inclusion of pepG1 as a glutamic peptidase. Phylogenetic analysis places pepG1 and other putative bacterial and archaeal glutamic peptidases in a cluster separate from the fungal glutamic peptidases, indicating a divergent and independent evolution of bacterial and fungal glutamic peptidases. Purification of pepG1, heterologously expressed in <it>Bacillus subtilis</it>, was performed using hydrophobic interaction chromatography and ion exchange chromatography. The purified peptidase was characterized with respect to its physical properties. Temperature and pH optimums were found to be 60°C and pH 3-4, in agreement with the values observed for the fungal members of family G1. In addition, pepG1 was found to be pepstatin-insensitive, a characteristic signature of glutamic peptidases.</p> <p>Conclusions</p> <p>Based on the obtained results, we suggest that pepG1 can be added to the MEROPS family G1 as the first characterized bacterial member.</p

Genomic Prediction and Genome-Wide Association Studies of Flour Yield and Alveograph Quality Traits Using Advanced Winter Wheat Breeding Material

Use of genetic markers and genomic prediction might improve genetic gain for quality traits in wheat breeding programs. Here, flour yield and Alveograph quality traits were inspected in 635 F6 winter wheat breeding lines from two breeding cycles. Genome-wide association studies revealed single nucleotide polymorphisms (SNPs) on chromosome 5D significantly associated with flour yield, Alveograph P (dough tenacity), and Alveograph W (dough strength). Additionally, SNPs on chromosome 1D were associated with Alveograph P and W, SNPs on chromosome 1B were associated with Alveograph P, and SNPs on chromosome 4A were associated with Alveograph L (dough extensibility). Predictive abilities based on genomic best linear unbiased prediction (GBLUP) models ranged from 0.50 for flour yield to 0.79 for Alveograph W based on a leave-one-out cross-validation strategy. Predictive abilities were negatively affected by smaller training set sizes, lower genetic relationship between lines in training and validation sets, and by genotype–environment (G×E) interactions. Bayesian Power Lasso models and genomic feature models resulted in similar or slightly improved predictions compared to GBLUP models. SNPs with the largest effects can be used for screening large numbers of lines in early generations in breeding programs to select lines that potentially have good quality traits. In later generations, genomic predictions might be used for a more accurate selection of high quality wheat lines

Initial experiments to assess short-term survival of discarded plaice (Pleuronectes platessa) caught in trammel nets during winter season

European plaice (Pleuronectes platessa) is a key species in commercial fisheries in the North Sea, Skagerrak, Kattegat, and Baltic Sea. The reformed European Union Common Fisheries Policy includes the possibility of exemptions from the landing obligation for “species for which scientific evidence demonstrates high survival rates”. Discard survival from set-net fisheries is poorly studied. Trials were conducted on two commercial fishing vessels over seven trips from November to February 2017–2018 in the Baltic Sea. The nylon trammel nets had a nominal bar size for the inner/outer wall of 75/350 mm and 85/400 mm. Soaking time was 23–47 h, water depth 7–18 m, and deck temperature was − 0.1–6.0 ◦C. Following commercial practice, the trammel nets were hauled back onto the vessel, after which netting and fish passed through a net hauler onto a steel sorting table where the entire fish catch were manually untangled by the fishers and plaice collected by scientists. We used a storage system for housing the captured fish inside fishing harbours during observations. Catch-damage-index (CDI) and Reflex Action Mortality Predictor (RAMP) scores were used to assess fish condition immediately after capture and at the end of observation periods. All plaice below 40 cm were sampled with a total number of 118 individuals from 13 fleets (several nets joined together). The fish were assessed for short-term survival for 4–10 days with full survival (100%). The majority of fish exhibited no reflex impairments. Minor bruises, fraying, and net marks were frequently observed on captured fish. The overall condition of the fish did not change during observation periods

Completeness for a First-order Abstract Separation Logic

Existing work on theorem proving for the assertion language of separation logic (SL) either focuses on abstract semantics which are not readily available in most applications of program verification, or on concrete models for which completeness is not possible. An important element in concrete SL is the points-to predicate which denotes a singleton heap. SL with the points-to predicate has been shown to be non-recursively enumerable. In this paper, we develop a first-order SL, called FOASL, with an abstracted version of the points-to predicate. We prove that FOASL is sound and complete with respect to an abstract semantics, of which the standard SL semantics is an instance. We also show that some reasoning principles involving the points-to predicate can be approximated as FOASL theories, thus allowing our logic to be used for reasoning about concrete program verification problems. We give some example theories that are sound with respect to different variants of separation logics from the literature, including those that are incompatible with Reynolds's semantics. In the experiment we demonstrate our FOASL based theorem prover which is able to handle a large fragment of separation logic with heap semantics as well as non-standard semantics.Comment: This is an extended version of the APLAS 2016 paper with the same titl

Kinematics of Spiral Arm Streaming in M51

We use CO and H alpha velocity fields to study the gas kinematics in the spiral arms and interarms of M51 (NGC 5194), and fit the 2D velocity field to estimate the radial and tangential velocity components as a function of spiral phase (arm distance). We find large radial and tangential streaming velocities, which are qualitatively consistent with the predictions of density wave theory and support the existence of shocks. The streaming motions are complex, varying significantly across the galaxy as well as along and between arms. Aberrations in the velocity field indicate that the disk is not coplanar, perhaps as far in as 20\arcsec\ (800 pc) from the center. Velocity profile fits from CO and H alpha are typically similar, suggesting that most of the H alpha emission originates from regions of recent star formation. We also explore vortensity and mass conservation conditions. Vortensity conservation, which does not require a steady state, is empirically verified. The velocity and density profiles show large and varying mass fluxes, which are inconsistent with a steady flow for a single dominant global spiral mode. We thus conclude that the spiral arms cannot be in a quasi-steady state in any rotating frame, and/or that out of plane motions may be significant.Comment: 50 pages, including 20 figures; Accepted for publication in ApJ. PDF version with high resolution figures available at http://www.astro.umd.edu/~shetty/Research