Computing Storyline Visualizations with Few Block Crossings

Storyline visualizations show the structure of a story, by depicting the interactions of the characters over time. Each character is represented by an x-monotone curve from left to right, and a meeting is represented by having the curves of the participating characters run close together for some time. There have been various approaches to drawing storyline visualizations in an automated way. In order to keep the visual complexity low, rather than minimizing pairwise crossings of curves, we count block crossings, that is, pairs of intersecting bundles of lines. Partly inspired by the ILP-based approach of Gronemann et al. [GD 2016] for minimizing the number of pairwise crossings, we model the problem as a satisfiability problem (since the straightforward ILP formulation becomes more complicated and harder to solve). Having restricted ourselves to a decision problem, we can apply powerful SAT solvers to find optimal drawings in reasonable time. We compare this SAT-based approach with two exact algorithms for block crossing minimization, using both the benchmark instances of Gronemann et al. and random instances. We show that the SAT approach is suitable for real-world instances and identify cases where the other algorithms are preferable.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

Illuminating Choices for Library Prep: A Comparison of Library Preparation Methods for Whole Genome Sequencing of Cryptococcus neoformans Using Illumina HiSeq.

The industry of next-generation sequencing is constantly evolving, with novel library preparation methods and new sequencing machines being released by the major sequencing technology companies annually. The Illumina TruSeq v2 library preparation method was the most widely used kit and the market leader; however, it has now been discontinued, and in 2013 was replaced by the TruSeq Nano and TruSeq PCR-free methods, leaving a gap in knowledge regarding which is the most appropriate library preparation method to use. Here, we used isolates from the pathogenic fungi Cryptococcus neoformans var. grubii and sequenced them using the existing TruSeq DNA v2 kit (Illumina), along with two new kits: the TruSeq Nano DNA kit (Illumina) and the NEBNext Ultra DNA kit (New England Biolabs) to provide a comparison. Compared to the original TruSeq DNA v2 kit, both newer kits gave equivalent or better sequencing data, with increased coverage. When comparing the two newer kits, we found little difference in cost and workflow, with the NEBNext Ultra both slightly cheaper and faster than the TruSeq Nano. However, the quality of data generated using the TruSeq Nano DNA kit was superior due to higher coverage at regions of low GC content, and more SNPs identified. Researchers should therefore evaluate their resources and the type of application (and hence data quality) being considered when ultimately deciding on which library prep method to use

Oakleaf: an S locus-linked mutation of Primula vulgaris that affects leaf and flower development

•In Primula vulgaris outcrossing is promoted through reciprocal herkogamy with insect-mediated cross-pollination between pin and thrum form flowers. Development of heteromorphic flowers is coordinated by genes at the S locus. To underpin construction of a genetic map facilitating isolation of these S locus genes, we have characterised Oakleaf, a novel S locus-linked mutant phenotype. •We combine phenotypic observation of flower and leaf development, with classical genetic analysis and next-generation sequencing to address the molecular basis of Oakleaf. •Oakleaf is a dominant mutation that affects both leaf and flower development; plants produce distinctive lobed leaves, with occasional ectopic meristems on the veins. This phenotype is reminiscent of overexpression of Class I KNOX-homeodomain transcription factors. We describe the structure and expression of all eight P. vulgaris PvKNOX genes in both wild-type and Oakleaf plants, and present comparative transcriptome analysis of leaves and flowers from Oakleaf and wild-type plants. •Oakleaf provides a new phenotypic marker for genetic analysis of the Primula S locus. We show that none of the Class I PvKNOX genes are strongly upregulated in Oakleaf leaves and flowers, and identify cohorts of 507 upregulated and 314 downregulated genes in the Oakleaf mutant

Integration of genetic and physical maps of the Primula vulgaris S locus and localization by chromosome in situ hybridization

•Heteromorphic flower development in Primula is controlled by the S locus. The S locus genes, which control anther position, pistil length and pollen size in pin and thrum flowers, have not yet been characterized. We have integrated S-linked genes, marker sequences and mutant phenotypes to create a map of the P. vulgaris S locus region that will facilitate the identification of key S locus genes. We have generated, sequenced and annotated BAC sequences spanning the S locus, and identified its chromosomal location. •We have employed a combination of classical genetics and three-point crosses with molecular genetic analysis of recombinants to generate the map. We have characterized this region by Illumina sequencing and bioinformatic analysis, together with chromosome in situ hybridization. •We present an integrated genetic and physical map across the P. vulgaris S locus flanked by phenotypic and DNA sequence markers. BAC contigs encompass a 1.5-Mb genomic region with 1 Mb of sequence containing 82 S-linked genes anchored to overlapping BACs. The S locus is located close to the centromere of the largest metacentric chromosome pair. •These data will facilitate the identification of the genes that orchestrate heterostyly in Primula and enable evolutionary analyses of the S locus

Nanoantenna-enhanced ultrafast nonlinear spectroscopy of a single gold nanoparticle

Optical nanoantennas are a novel tool to investigate previously unattainable dimensions in the nanocosmos. Just like their radio-frequency equivalents, nanoantennas enhance the light-matter interaction in their feed gap. Antenna enhancement of small signals promises to open a new regime in linear and nonlinear spectroscopy on the nanoscale. Without antennas especially the nonlinear spectroscopy of single nanoobjects is very demanding. Here, we present for the first time antenna-enhanced ultrafast nonlinear optical spectroscopy. In particular, we utilize the antenna to determine the nonlinear transient absorption signal of a single gold nanoparticle caused by mechanical breathing oscillations. We increase the signal amplitude by an order of magnitude which is in good agreement with our analytical and numerical models. Our method will find applications in linear and nonlinear spectroscopy of nanoobjects, ranging from single protein binding events via nonlinear tensor elements to the limits of continuum mechanics

Comparison of computed tomography image features extracted by radiomics, self-supervised learning and end-to-end deep learning for outcome prediction of oropharyngeal cancer

Background and purpose: To compare the prediction performance of image features of computed tomography (CT) images extracted by radiomics, self-supervised learning and end-to-end deep learning for local control (LC), regional control (RC), locoregional control (LRC), distant metastasis-free survival (DMFS), tumor-specific survival (TSS), overall survival (OS) and disease-free survival (DFS) of oropharyngeal squamous cell carcinoma (OPSCC) patients after (chemo)radiotherapy.Methods and materials: The OPC-Radiomics dataset was used for model development and independent internal testing and the UMCG-OPC set for external testing. Image features were extracted from the Gross Tumor Volume contours of the primary tumor (GTVt) regions in CT scans when using radiomics or a self-supervised learning-based method (autoencoder). Clinical and combined (radiomics, autoencoder or end-to-end) models were built using multivariable Cox proportional-hazard analysis with clinical features only and both clinical and image features for LC, RC, LRC, DMFS, TSS, OS and DFS prediction, respectively.Results: In the internal test set, combined autoencoder models performed better than clinical models and combined radiomics models for LC, RC, LRC, DMFS, TSS and DFS prediction (largest improvements in C-index: 0.91 vs. 0.76 in RC and 0.74 vs. 0.60 in DMFS). In the external test set, combined radiomics models performed better than clinical and combined autoencoder models for all endpoints (largest improvements in LC, 0.82 vs. 0.71). Furthermore, combined models performed better in risk stratification than clinical models and showed good calibration for most endpoints.Conclusions: Image features extracted using self-supervised learning showed best internal prediction performance while radiomics features have better external generalizability.</p

Electronic Stopping and Momentum Density of Diamond Obtained from First-Principles Calculations

We calculate the "head" element or the (0,0)-element of the wave-vector and frequency-dependent dielectric matrix of bulk crystals via first-principles, all-electron Kohn-Sham states in the integral of the irreducible polarizability in the random phase approximation. We approximate the macroscopic "head" element of the inverse matrix by its reciprocal value, and integrate over frequencies and momenta to obtain the electronic energy loss of protons at low velocities. Numerical evaluation for diamond targets predicts that the band gap causes a strong non-linear reduction of the electronic stopping power at ion velocities below 0.2 atomic units.Comment: 8 pages, 6 figures, REVTeX

Towards reference values of pericoronary adipose tissue attenuation:impact of coronary artery and tube voltage in coronary computed tomography angiography

Objectives: To determine normal pericoronary adipose tissue mean attenuation (PCATMA) values for left the anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) in patients without plaques on coronary CT angiography (cCTA), taking into account tube voltage influence. Methods: This retrospective study included 192 patients (76 (39.6%) men; median age 49 years (range, 19–79)) who underwent cCTA with third-generation dual-source CT for the suspicion of CAD between 2015 and 2017. We selected patients without plaque on cCTA. PCATMA was measured semi-automatically on cCTA images in the proximal segment of the three main coronary arteries with 10 mm length. Paired t-testing was used to compare PCATMA between combinations of two coronary arteries within each patient, and one-way ANOVA testing was used to compare PCATMA in different kV groups. Results: The overall mean ± standard deviation (SD) PCATMA was − 90.3 ± 11.1 HU. PCATMA in men was higher than that in women: − 88.5 ± 10.5 HU versus − 91.5 ± 11.3 HU (p = 0.001). PCATMA of LAD, LCX, and RCA was − 92.4 ± 11.6 HU, − 88.4 ± 9.9 HU, and − 90.2 ± 11.4 HU, respectively. Pairwise comparison of the arteries showed significant difference in PCATMA: LAD and LCX (p < 0.001), LAD and RCA (p = 0.009), LCX and RCA (p = 0.033). PCATMA of the 70 kV, 80 kV, 90 kV, 100 kV, and 120 kV groups was − 95.6 ± 9.6 HU, − 90.2 ± 11.5 HU, − 87.3 ± 9.9 HU, − 82.7 ± 6.2 HU, and − 79.3 ± 6.8 HU, respectively (p < 0.001). Conclusions: In patients without plaque on cCTA, PCATMA varied by tube voltage, with minor differences in PCATMA between coronary arteries (LAD, LCX, RCA). PCATMA values need to be interpreted taking into account tube voltage setting. Key Points: • In patients without plaque on cCTA, PCATMAdiffers slightly by coronary artery (LAD, LCX, RCA). • Tube voltage of cCTA affects PCATMAmeasurement, with mean PCATMAincreasing linearly with increasing kV. • For longitudinal cCTA analysis of PCATMA, the use of equal kV setting is strongly recommended

Focal pericoronary adipose tissue attenuation is related to plaque presence, plaque type, and stenosis severity in coronary CTA

Objectives To investigate the association of pericoronary adipose tissue mean attenuation (PCAT(MA)) with coronary artery disease (CAD) characteristics on coronary computed tomography angiography (CCTA). Methods We retrospectively investigated 165 symptomatic patients who underwent third-generation dual-source CCTA at 70kVp: 93 with and 72 without CAD (204 arteries with plaque, 291 without plaque). CCTA was evaluated for presence and characteristics of CAD per artery. PCAT(MA) was measured proximally and across the most severe stenosis. Patient-level, proximal PCAT(MA) was defined as the mean of the proximal PCAT(MA) of the three main coronary arteries. Analyses were performed on patient and vessel level. Results Mean proximal PCAT(MA) was -96.2 +/- 7.1 HU and -95.6 +/- 7.8HU for patients with and without CAD (p = 0.644). In arteries with plaque, proximal and lesion-specific PCAT(MA) was similar (-96.1 +/- 9.6 HU, -95.9 +/- 11.2 HU, p = 0.608). Lesion-specific PCAT(MA) of arteries with plaque (-94.7 HU) differed from proximal PCAT(MA) of arteries without plaque (-97.2 HU, p = 0.015). Minimal stenosis showed higher lesion-specific PCAT(MA) (-94.0 HU) than severe stenosis (-98.5 HU, p = 0.030). Lesion-specific PCAT(MA) of non-calcified, mixed, and calcified plaque was -96.5 HU, -94.6 HU, and -89.9 HU (p = 0.004). Vessel-based total plaque, lipid-rich necrotic core, and calcified plaque burden showed a very weak to moderate correlation with proximal PCAT(MA). Conclusions Lesion-specific PCAT(MA) was higher in arteries with plaque than proximal PCAT(MA) in arteries without plaque. Lesion-specific PCAT(MA) was higher in non-calcified and mixed plaques compared to calcified plaques, and in minimal stenosis compared to severe; proximal PCAT(MA) did not show these relationships. This suggests that lesion-specific PCAT(MA) is related to plaque development and vulnerability