Postponing the choice of penalty parameter and step length

We study, in the context of interior-point methods for linear programming, some possible advantages of postponing the choice of the penalty parameter and the steplength, which happens both when we apply Newton's method to the Karush-Kuhn-Tucker system and when we apply a predictor-corrector scheme. We show that for a Newton or a strictly predictor step the next iterate can be expressed as a linear function of the penalty parameter mu, and, in the case of a predictor-corrector step, as a quadratic function of mu. We also show that this parameterization is useful to guarantee either the non-negativity of the next iterate or the proximity to the central path. Initial computational results of these strategies are shown and compared with PCx, an implementation of Mehotra's predictor-corrector method.241638

Guest-host chemistry with dendrimers: Stable polymer assemblies by rational design

A new type of guest has been designed and synthesized for the exo-type supramol. functionalization of adamantyl-urea-terminated poly(propylene imine) dendrimers. This new type of guest motif features a uriedo methane sulfonic acid moiety that binds very selectively to the surfaces of dendrimers via a combination of noncovalent interactions forming well-defined complexes. The guest-host properties have been examd. for a fifth-generation adamantyl-urea-functionalized poly(propylene imine) dendrimer capable of binding 32 guest mols. and for a model host mol. that can bind only one guest mol. The guest-host chem. has been studied with 1H NMR spectroscopy, nuclear Overhauser enhancement spectroscopy NMR spectroscopy, T1-relaxation NMR expts., and IR spectroscopy. The 1:32 ratio with the dendrimer has been confirmed unambiguously from 1H NMR spectra of the complex after size exclusion chromatog. Competition expts. with guests bearing a carboxylic acid instead of a sulfonic acid in the binding motif have demonstrated that the sulfonic acid has superior binding strength. Also, the importance of a combination of noncovalent interactions has been shown via competition expts. with a guest lacking the uriedo moiety

Anatomical Modeling of Brain Vasculature in Two-Photon Microscopy by Generalizable Deep Learning

Objective and Impact Statement. Segmentation of blood vessels from two-photon microscopy (2PM) angiograms of brains has important applications in hemodynamic analysis and disease diagnosis. Here, we develop a generalizable deep learning technique for accurate 2PM vascular segmentation of sizable regions in mouse brains acquired from multiple 2PM setups. The technique is computationally efficient, thus ideal for large-scale neurovascular analysis. Introduction. Vascular segmentation from 2PM angiograms is an important first step in hemodynamic modeling of brain vasculature. Existing segmentation methods based on deep learning either lack the ability to generalize to data from different imaging systems or are computationally infeasible for large-scale angiograms. In this work, we overcome both these limitations by a method that is generalizable to various imaging systems and is able to segment large-scale angiograms. Methods. We employ a computationally efficient deep learning framework with a loss function that incorporates a balanced binary-cross-entropy loss and total variation regularization on the network’s output. Its effectiveness is demonstrated on experimentally acquired in vivo angiograms from mouse brains of dimensions up to 808×808×702 μm. Results. To demonstrate the superior generalizability of our framework, we train on data from only one 2PM microscope and demonstrate high-quality segmentation on data from a different microscope without any network tuning. Overall, our method demonstrates 10× faster computation in terms of voxels-segmented-per-second and 3× larger depth compared to the state-of-the-art. Conclusion. Our work provides a generalizable and computationally efficient anatomical modeling framework for brain vasculature, which consists of deep learning-based vascular segmentation followed by graphing. It paves the way for future modeling and analysis of hemodynamic response at much greater scales that were inaccessible before

Taxonomic review of the orders mysida and stygiomysida (Crustacea, Peracarida)

The order Mysida (2 families, 178 genera, 1132 species) contains species across a broad range of habitats, such as subterranean, fresh, brackish, coastal, and surface to deep-sea habitats. The Stygiomysida (2 families, 2 genera, 16 species), however, are found primarily in subterranean waters, but always in waters with a marine influence. The Mysida and Stygiomysida body is divided into three main regions: cephalon, thorax, and abdomen. They are shrimp-like in appearance, containing morphological features earlier referred to as defining a "caridoid facies". The shrimp-like morphology was to some extent diagnostic for the historic Decapod taxon Schizopoda, containing the Nebalia, Mysida, Lophogastrida, and Euphausiacea. In 1904 the concept of Schizopoda was abandoned, and the Mysidacea (Mysida and Lophogastrida) along with Cumacea, Amphipoda, Isopoda, and Tanaidacea were placed in a new taxon, the Peracarida. Later discoveries of groundwater mysids led to the establishment of Stygiomysida, but placement to either Lophogastrida or Mysida remained unclear. The presence of oostegites and absence of podobranchiae, coupled with non-statocyst bearing uropods have been used to classify the Stygiomysida as a primitive Mysida family, comparable to Petalophthalmidae. On the other hand, equally suggestive characters, but for a Lophogastrida affiliation, was suggested for the archaic foregut characters and again, non-statocyst bearing uropods. With the inclusion of DNA sequence data of ribosomal genes, sister group relationships between Stygiomysida, Lophogastrida, and Mictacea within the Peracarida are observed, which supports a classification of the Stygiomysida as a separate order removed from the Mysida