Accurate Reconstruction of Molecular Phylogenies for Proteins Using Codon and Amino Acid Unified Sequence Alignments (CAUSA)

Based on molecular clock hypothesis, and neutral theory of molecular evolution, molecular phylogenies have been widely used for inferring evolutionary history of organisms and individual genes. Traditionally, alignments and phylogeny trees of proteins and their coding DNA sequences are constructed separately, thus often different conclusions were drawn. Here we present a new strategy for sequence alignment and phylogenetic tree reconstruction, codon and amino acid unified sequence alignment (CAUSA), which aligns DNA and protein sequences and draw phylogenetic trees in a unified manner. We demonstrated that CAUSA improves both the accuracy of multiple sequence alignments and phylogenetic trees by solving a variety of molecular evolutionary problems in virus, bacteria and mammals. Our results support the hypothesis that the molecular clock for proteins has two pointers existing separately in DNA and protein sequences. It is more accurate to read the molecular clock by combination (additive) of these two pointers, since the ticking rates of them are sometimes consistent, sometimes different. CAUSA software were released as Open Source under GNU/GPL license, and are downloadable free of charge from the website www.dnapluspro.com

MonoNeRF: Learning Generalizable NeRFs from Monocular Videos without Camera Pose

We propose a generalizable neural radiance fields - MonoNeRF, that can be trained on large-scale monocular videos of moving in static scenes without any ground-truth annotations of depth and camera poses. MonoNeRF follows an Autoencoder-based architecture, where the encoder estimates the monocular depth and the camera pose, and the decoder constructs a Multiplane NeRF representation based on the depth encoder feature, and renders the input frames with the estimated camera. The learning is supervised by the reconstruction error. Once the model is learned, it can be applied to multiple applications including depth estimation, camera pose estimation, and single-image novel view synthesis. More qualitative results are available at: https://oasisyang.github.io/mononerf .Comment: ICML 2023 camera ready version. Project page: https://oasisyang.github.io/mononer

Frequency analysis of urban runoff quality in an urbanizing catchment of Shenzhen, China

Copyright © 2013 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Hydrology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Hydrology Vol. 496 (2013), DOI: 10.1016/j.jhydrol.2013.04.053This paper investigates the frequency distribution of urban runoff quality indicators using a long-term continuous simulation approach and evaluates the impacts of proposed runoff control schemes on runoff quality in an urbanizing catchment in Shenzhen, China. Four different indicators are considered to provide a comprehensive assessment of the potential impacts: total runoff depth, event pollutant load, Event Mean Concentration, and peak concentration during a rainfall event. The results obtained indicate that urban runoff quantity and quality in the catchment have significant variations in rainfall events and a very high rate of non-compliance with surface water quality regulations. Three runoff control schemes with the capacity to intercept an initial runoff depth of 5 mm, 10 mm, and 15 mm are evaluated, respectively, and diminishing marginal benefits are found with increasing interception levels in terms of water quality improvement. The effects of seasonal variation in rainfall events are investigated to provide a better understanding of the performance of the runoff control schemes. The pre-flood season has higher risk of poor water quality than other seasons after runoff control. This study demonstrates that frequency analysis of urban runoff quantity and quality provides a probabilistic evaluation of pollution control measures, and thus helps frame a risk-based decision making for urban runoff quality management in an urbanizing catchment.Open Research Fund Program of State Key Laboratory of Hydroscience and EngineeringNational Natural Science Foundation of ChinaNational Water Pollution Control and Management Technology Major Project

Phosphorylated AKT1 is associated with poor prognosis in esophageal squamous cell carcinoma

BACKGROUND: The epidermal growth factor receptor (EGFR) signaling pathway is important in regulating biological behaviors in many malignancies. We explored whether expression and activation of EGFR and several components on its downstream pathways have prognostic significance in patients with esophageal squamous cell carcinoma (ESCC). METHODS: Expression of EGFR, phosphorylated (p)-EGFR, AKT1, p-AKT1, AKT2, p-AKT2, ERK1, ERK2, p-ERK1/2, STAT3, and p-STAT3 was assessed by immunohistochemical analysis of tissue microarrays for 275 ESCC patients who had undergone complete three-field lymphadenectomy. Spearman rank correlation tests were used to determine the relationships among protein expression, and Cox regression analyses were performed to determine the prognostic factors on overall survival (OS). RESULTS: p-EGFR expression was correlated statistically with all of the other phosphorylated markers. Gender, N stage, and p-AKT1 expression were found to be independent prognostic factors for OS. Increased expression of p-AKT1 was associated with decreased patient survival. EGFR and p-EGFR expression was not significantly associated with patient survival. CONCLUSION: Activation of AKT1 was associated with poor prognosis in ESCC

FRED Navigation & Communication Subsystem

Clear Blue Sea (CBS), a non-profit organization, has focused on removing the plastic from the Great Pacific Garbage Patch by designing and piloting a Floating Robot for Eliminating Debris (FRED). The goal for this project is to design and prototype two subsystems; a navigation and communication subsystem and a power subsystem. The navigation and communication subsystem will allow for tracking location, remote control of the vehicle, operational status and environmental conditions monitoring. The power subsystem will use solar power to operate the overall FRED system. Our objective is to integrate these subsystems with the other USD Clear Blue Sea team?s final prototype. This report discusses our objectives, requirements and functions of our subsystems. After extensive research on different components, we decided on utilizing high-quality and low-cost autopilot hardware. Rather than build from scratch our subteam switched gears and unanimously decided on using a flight controller and open drone software. This flight controller would then manage all the sensors and motors on the FRED unit itself, as well as allow for communication between the FRED system, a computer, and a handheld controller for manual inputs. For the power subsystem, it consists of 3 main parts: a solar panel, a battery and two motors. Solar panel converts solar energy into electric current, then power the thruster and the motor. Part of the generated electric power is stored into the battery for later use

Topology optimization of microstructures with perturbation analysis and penalty methods

Topology optimization at the continuum nano/microscale is of wide interest in designing and developing more efficient micro/nano electromechanical systems. This paper presents a new methodology for topology optimization of microstructures that is based on perturbation analysis and the penalty methods. The homogenized material coefficients are numerically computed based on perturbation analysis, and periodic boundary conditions are imposed by the penalty methods. The sensitivity analysis is implemented directly without the adjoint method. The extension of the proposed method to the design of components for multi-field analysis is straightforward. The capability and performance of the presented methodology are demonstrated through several numerical examples

Topology optimization of microstructures with perturbation analysis and penalty methods

Topology optimization at the continuum nano/microscale is of wide interest in designing and developing more efficient micro/nano electromechanical systems. This paper presents a new methodology for topology optimization of microstructures that is based on perturbation analysis and the penalty methods. The homogenized material coefficients are numerically computed based on perturbation analysis, and periodic boundary conditions are imposed by the penalty methods. The sensitivity analysis is implemented directly without the adjoint method. The extension of the proposed method to the design of components for multi-field analysis is straightforward. The capability and performance of the presented methodology are demonstrated through several numerical examples