Solving Set Cover with Pairs Problem using Quantum Annealing

Here we consider using quantum annealing to solve Set Cover with Pairs (SCP), an NP-hard combinatorial optimization problem that plays an important role in networking, computational biology, and biochemistry. We show an explicit construction of Ising Hamiltonians whose ground states encode the solution of SCP instances. We numerically simulate the time-dependent Schrödinger equation in order to test the performance of quantum annealing for random instances and compare with that of simulated annealing. We also discuss explicit embedding strategies for realizing our Hamiltonian construction on the D-wave type restricted Ising Hamiltonian based on Chimera graphs. Our embedding on the Chimera graph preserves the structure of the original SCP instance and in particular, the embedding for general complete bipartite graphs and logical disjunctions may be of broader use than that the specific problem we deal with

Intensification of liquid mixing and local turbulence using a fractal injector with staggered conformation

Two self-similar, tree-like injectors of the same fractal dimension are compared, demonstrating that other geometric parameters besides dimension play a crucial role in determining mixing performance. In one injector, when viewed from the top, the conformation of branches is eclipsed; in the other one, it is staggered. The flow field and the fractal injector induced mixing performance are investigated through computational fluid dynamics (CFD) simulations. The finite rate/eddy dissipation model (FR/EDM) is modified for fast liquid-phase reactions involving local micromixing. Under the same operating conditions, flow field uniformity and micromixing are improved when a staggered fractal injector is used. This is because of enhanced jet entrainment and local turbulence around the spatially distributed nozzles. Compared with a traditional double-ring sparger, a larger reaction region volume and lower micromixing time are obtained with fractal injectors. Local turbulence around the spatially distributed nozzles in fractal injectors improves reaction efficiency

Improving the Total Organic Carbon Estimation of the Eagle Ford Shale with Density Logs by Considering the Effect of Pyrite

Pyrite is a common mineral with a higher density than most other minerals in the Eagle Ford Shale formation. Hence, if pyrite is not considered in the total organic carbon (TOC) estimation, based on density logs, it may lead to errors. In order to improve the accuracy of the TOC estimation, we propose an updated TOC estimation method that incorporates the concentration of pyrite and organic porosity. More than 15 m of Eagle Ford Shale samples were analyzed using Rock-Eval pyrolysis, X-ray fluorescence (XRF), and X-ray diffraction (XRD). TOC, elemental concentration, and mineralogical data were analyzed for a better understanding of the relationship between the concentration of TOC and pyrite content in the Eagle Ford formation. An updated petrophysical model—including parameters such as organic pores, solid organic matter, inorganic pores, pyrite, and inorganic rock matrix without pyrite—was built using the sample data from the Eagle Ford. The model was compared with Schmoker’s model and validated with the Eagle Ford field data. The results showed that the updated model had a lower root mean square error (RMSE) than Schmoker’s model. Therefore, it could be used in the future estimation of TOC in pyrite-rich formations

AMatFormer: Efficient Feature Matching via Anchor Matching Transformer

Learning based feature matching methods have been commonly studied in recent years. The core issue for learning feature matching is to how to learn (1) discriminative representations for feature points (or regions) within each intra-image and (2) consensus representations for feature points across inter-images. Recently, self- and cross-attention models have been exploited to address this issue. However, in many scenes, features are coming with large-scale, redundant and outliers contaminated. Previous self-/cross-attention models generally conduct message passing on all primal features which thus lead to redundant learning and high computational cost. To mitigate limitations, inspired by recent seed matching methods, in this paper, we propose a novel efficient Anchor Matching Transformer (AMatFormer) for the feature matching problem. AMatFormer has two main aspects: First, it mainly conducts self-/cross-attention on some anchor features and leverages these anchor features as message bottleneck to learn the representations for all primal features. Thus, it can be implemented efficiently and compactly. Second, AMatFormer adopts a shared FFN module to further embed the features of two images into the common domain and thus learn the consensus feature representations for the matching problem. Experiments on several benchmarks demonstrate the effectiveness and efficiency of the proposed AMatFormer matching approach.Comment: Accepted by IEEE Transactions on Multimedia (TMM) 202

Possible Roles of Membrane Trafficking Components for Lipid Droplet Dynamics in Higher Plants and Green Algae

Lipid droplets are ubiquitous dynamic organelles that contain neutral lipids surrounded by a phospholipid monolayer. They can store and supply lipids for energy metabolism and membrane synthesis. In addition, protein transport and lipid exchange often occur between LDs and various organelles to control lipid homeostasis in response to multiple stress responses and cellular signaling. In recent years, multiple membrane trafficking proteins have been identified through LD proteomics and genetic analyses. These membrane trafficking machineries are emerging as critical regulators to function in different LD-organelle interactions, e.g., for LD dynamics, biogenesis and turnover. In this review, we will summarize recent advances in regard to LD-related membrane trafficking proteins and discuss future investigations in higher plants and green algae

Reconstitution of Mammary Epithelial Morphogenesis by Murine Embryonic Stem Cells Undergoing Hematopoietic Stem Cell Differentiation

Background: Mammary stem cells are maintained within specific microenvironments and recruited throughout lifetime to reconstitute de novo the mammary gland. Mammary stem cells have been isolated through the identification of specific cell surface markers and in vivo transplantation into cleared mammary fat pads. Accumulating evidence showed that during the reformation of mammary stem cell niches by dispersed epithelial cells in the context of the intact epithelium-free mammary stroma, non-mammary epithelial cells may be sequestered and reprogrammed to perform mammary epithelial cell functions and to adopt mammary epithelial characteristics during reconstruction of mammary epithelium in regenerating mammary tissue in vivo. Methodology/Principal Findings: To examine whether other types of progenitor cells are able to contribute to mammary branching morphogenesis, we examined the potential of murine embryonic stem (mES) cells, undergoing hematopoietic differentiation, to support mammary reconstitution in vivo. We observed that cells from day 14 embryoid bodies (EBs) under hematopoietic differentiation condition, but not supernatants derived from these cells, when transplanted into denuded mammary fat pads, were able to contribute to both the luminal and myoepithelial lineages in branching ductal structures resembling the ductal-alveolar architecture of the mammary tree. No teratomas were observed when these cells were transplanted in vivo. Conclusions/Significance: Our data provide evidence for the dominance of the tissue-specific mammary stem cell niche and its role in directing mES cells, undergoing hematopoietic differentiation, to reprogram into mammary epithelial cells and to promote mammary epithelial morphogenesis. These studies should also provide insights into regeneration of damaged mammary gland and the role of the mammary microenvironment in reprogramming cell fate. © 2010 Jiang et al

Slit2N and Robo4 regulate lymphangiogenesis through the VEGF-C/VEGFR-3 pathway

Background: Signaling through vascular endothelial growth factor C (VEGF–C) and VEGF receptor 3 (VEGFR-3) plays a central role in lymphangiogenesis and the metastasis of several cancers via the lymphatics. Recently, the Slit2/Robo4 pathway has been recognized as a modulator of vascular permeability and integrity. Signaling via the Robo receptor inhibits VEGF-mediated effects; however, its effects on lymphatic endothelial cell function have not been well characterized. Results: We found that pretreatment with Slit2N, an active fragment of Slit2, inhibited VEGF-C-mediated lung-derived lymphatic endothelial cell (L-LEC) proliferation, migration, and in vitro tube formation. Slit2N induced the internalization of VEGFR-3, which blocked its activation, and inhibited the activation of the PI3K/Akt pathway by VEGF-C in L-LECs. Moreover, we found that inhibition of VEGF-C-induced effects by Slit2N was Robo4-dependent. Conclusion: These results indicate that Slit2N/Robo4 modulates several key cellular functions, which contribute to lymphangiogenesis, and identify this ligand-receptor pair as a potential therapeutic target to inhibit lymphatic metastasis of VEGF-C-overexpressing cancers and manage lymphatic dysfunctions characterized by VEGF-C/VEGFR-3 activation

Consensus under Misaligned Orientations

This paper presents a consensus algorithm under misaligned orientations, which is defined as (i) misalignment to global coordinate frame of local coordinate frames, (ii) biases in control direction or sensing direction, or (iii) misaligned virtual global coordinate frames. After providing a mathematical formulation, we provide some sufficient conditions for consensus or for divergence. Besides the stability analysis, we also conduct some analysis for convergence characteristics in terms of locations of eigenvalues. Through a number of numerical simulations, we would attempt to understand the behaviors of misaligned consensus dynamics.Comment: 23 pages, 9 figure

Expression and Function of Cannabinoid Receptors CB1 and CB2 and Their Cognate Cannabinoid Ligands in Murine Embryonic Stem Cells

Background: Characterization of intrinsic and extrinsic factors regulating the self-renewal/division and differentiation of stem cells is crucial in determining embryonic stem (ES) cell fate. ES cells differentiate into multiple hematopoietic lineages during embryoid body (EB) formation in vitro, which provides an experimental platform to define the molecular mechanisms controlling germ layer fate determination and tissue formation. Methods and Findings: The cannabinoid receptor type 1 (CB1) and cannabinoid receptor type 2 (CB2) are members of the G-protein coupled receptor (GPCR) family, that are activated by endogenous ligands, the endocannabinoids. CB1 receptor expression is abundant in brain while CB2 receptors are mostly expressed in hematopoietic cells. However, the expression and the precise roles of CB1 and CB2 and their cognate ligands in ES cells are not known. We observed significant induction of CB1 and CB2 cannabinoid receptors during the hematopoietic differentiation of murine ES (mES)-derived embryoid bodies. Furthermore, mES cells as well as ES-derived embryoid bodies at days 7 and 14, expressed endocannabinoids, the ligands for both CB1 and CB2. The CB1 and CB2 antagonists (AM251 and AM630, respectively) induced mES cell death, strongly suggesting that endocannabinoids are involved in the survival of mES cells. Treatment of mES cells with the exogenous cannabinoid ligand $\Delta^9$-THC resulted in the increased hematopoietic differentiation of mES cells, while addition of AM251 or AM630 blocked embryoid body formation derived from the mES cells. In addition, cannabinoid agonists induced the chemotaxis of ES-derived embryoid bodies, which was specifically inhibited by the CB1 and CB2 antagonists. Conclusions: This work has not been addressed previously and yields new information on the function of cannabinoid receptors, CB1 and CB2, as components of a novel pathway regulating murine ES cell differentiation. This study provides insights into cannabinoid system involvement in ES cell survival and hematopoietic differentiation