Combined Self-consistent-field And Spin-flip Tamm-dancoff Density Functional Approach To Potential Energy Surfaces For Photochemistry

We present a new approach to calculating potential energy surfaces for photochemical reactions by combining self-consistent-field calculations for single-reference ground and excited states with symmetry-corrected spin-flip Tamm-Dancoff approximation calculations for multireference electronic states. The method is illustrated by an application with the M05-2X exchange-correlation functional to cis-trans isomerization of the penta-2,4-dieniminium cation, which is a model (with three conjugated double bonds) of the protonated Schiff base of retinal. We find good agreement with multireference configuration interaction-plus-quadruples (MRCISD+Q) wave function calculations along three key paths in the strong-interaction region of the ground and first excited singlet states

Intramolecular and water mediated tautomerism of solvated glycine

The understanding of prototropic tautomerism in water and the characterization of solvent effects on protomeric equilibrium pose significant challenges. Using molecular dynamics simulations based on state-of-the-art deep learning potential and enhanced sampling methods, we provide a comprehensive description of all configurational transformations in glycine solvated in water and determine accurate free energy profiles of these processes. We observe that the tautomerism between the neutral and zwitterionic forms of solvated glycine can occur by both intramolecular proton transfer in glycine and intermolecular proton transfer in the contact ion pair (anionic glycine and hydronium ion) or the separated ion pair (cationic glycine and hydroxide ion)

Best Possible Approximation Algorithms for Single Machine Scheduling with Increasing Linear Maintenance Durations

We consider a single machine scheduling problem with multiple maintenance activities, where the maintenance duration function is of the linear form ft=a+bt with a≥0 and b>1. We propose an approximation algorithm named FFD-LS2I with a worst-case bound of 2 for problem. We also show that there is no polynomial time approximation algorithm with a worst-case bound less than 2 for the problem with b≥0 unless P=NP, which implies that the FFD-LS2I algorithm is the best possible algorithm for the case b>1 and that the FFD-LS algorithm, which is proposed in the literature, is the best possible algorithm for the case b≤1 both from the worst-case bound point of view

Design and synthesis of active heparan sulfate-based probes

A chemoenzymatic approach for synthesizing heparan sulfate oligosaccharides with a reactive diazoacetyl saccharide residue is reported. The resultant oligosaccharides were demonstrated to serve as specific inhibitors for heparan sulfate sulfotransferases, offering a new set of tools to probe the structural selectivity for heparan sulfate-binding proteins

Learning to Construct 3D Building Wireframes from 3D Line Clouds

Line clouds, though under-investigated in the previous work, potentially encode more compact structural information of buildings than point clouds extracted from multi-view images. In this work, we propose the first network to process line clouds for building wireframe abstraction. The network takes a line cloud as input , i.e., a nonstructural and unordered set of 3D line segments extracted from multi-view images, and outputs a 3D wireframe of the underlying building, which consists of a sparse set of 3D junctions connected by line segments. We observe that a line patch, i.e., a group of neighboring line segments, encodes sufficient contour information to predict the existence and even the 3D position of a potential junction, as well as the likelihood of connectivity between two query junctions. We therefore introduce a two-layer Line-Patch Transformer to extract junctions and connectivities from sampled line patches to form a 3D building wireframe model. We also introduce a synthetic dataset of multi-view images with ground-truth 3D wireframe. We extensively justify that our reconstructed 3D wireframe models significantly improve upon multiple baseline building reconstruction methods. The code and data can be found at https://github.com/Luo1Cheng/LC2WF.Comment: 10 pages, 6 figure

Anticancer effect of a combination of cisplatin and matrine on cervical cancer U14 cells and U14 tumor-bearing mice, and possible mechanism of action involved

Purpose: To investigate the anticancer effects of cisplatin (DDP) in combination with matrine on cervical cancer U14 cell tumor-bearing mice. Methods: The cell proliferation of cervical cancer U14 cells treated with DDP (25, 20, 15, 10 and 5 μg/mL); matrine (2.5, 2.0, 1.5, 1.0 and 0.5 mg/mL); or DDP (15 μg/mL) + matrine (2.5, 2.0, 1.5, 1.0 and 0.5 mg/mL) was determined with MTT assay. The anticancer effect of DDP + matrine in U14 tumor-bearing mice was also investigated, based on expression of tumor suppressor lung cancer 1 (TSLC1) using quantitative real time-polymerase chain reaction (qRT-PCR) and immunohistochemistry. Results: The inhibition of proliferation of U14 cells ranged from 26.68–70.25, 10.20–61.73, and 51.89–89.75 % for DDP, matrine and DDP + matrine, respectively. In mice with U14 solid tumors, the DDP group had 12.3 % weight loss (p < 0.05). Treatment with DDP, matrine, and DDP + matrine reduced tumor growth by 64.56, 42.22–56.67, and 67.78–81.11 %, respectively (p < 0.01). Results from RT-qPCR and immunohistochemistry showed corresponding increases in expression levels of TSLC1. Conclusion: These results indicate that the anticancer activity of DDP + matrine is higher than that of a single treatment with either DPP or matrine. The likely mechanism of action might be related to promotion of TSLC1 expression. This finding provides a potential strategy for the management of cervical cancer