Experimental dataset on electrolyte mixtures containing fluoroethylene carbonate and lithium bis(trifluoromethanesulfonyl)imide

These data and analyses support the research article “Low-flammable electrolytes with fluoroethylene carbonate based solvent mixtures and lithium bis(trifluoromethanesulfonyl)-imide (LiTFSI) for lithium-ion batteries” [1]. The data and analyses presented here include fitted data for density measurements, temperature dependence of density and specific volume of the mixtures, detailed viscosity measurements and conductivity data, current density plots with respect to anodic aluminum dissolution, half-cell C-rate capability of mixtures with the additives used in research article as well as the SEM images and EDX data of the full-cell with the electrolyte selected and controlled

Adaptive backstepping control of quadrotors with neural-network

A quadrotor is a type of unmanned aerial vehicles. It has been widely used in aerial photography. The quadrotor has the capability of vertical takeoff and landing, which is very useful in small or narrow areas. The mechanical structure of a quadrotor is also simple, which makes it easy to produce and maintain. It is a strong candidate for a future means of transportation. In practical applications, it is commonly controlled by a proportional integral derivative controller. In this thesis, two nonlinear controllers are designed to control the attitude and the position of a quadrotor by using the backstepping technique. The attitude is estimated by a nonlinear attitude estimator, which is based on a nonlinear explicit complementary filter. It uses data from a six axis inertial measurement unit and a three axis magnetometer to calculate the estimated attitude. To avoid the singularity problem like "gimbal lock" in Euler angle attitude representation, the unit quaternion attitude representation is applied in the controller derivation. However, the Euler angle representation is easier for people to imagine the actual attitude of a quadrotor. To make it more readable, the results of the experiments are converted to the Euler angle representation. During the derivation of a backstepping controller, a neural-network is applied to estimate the nonlinear terms in the system. The universal approximation theorem is the principle for the estimation of nonlinear terms. Besides, a two step controller is derived by modifying the backstepping controller with four steps. The two step controller is developed by an adaptive method for both the nonlinear terms and the moment of inertia. Analysis shows the boundedness of the closed-loop system with both controllers. Finally, the proposed controllers are tested on a true quadrotor system. Experimental results show the effectiveness of the two proposed controllers. Also, comparison between two controllers are carried out. In addition, some future works are discussed

InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images

We present a method for learning to generate unbounded flythrough videos of natural scenes starting from a single view, where this capability is learned from a collection of single photographs, without requiring camera poses or even multiple views of each scene. To achieve this, we propose a novel self-supervised view generation training paradigm, where we sample and rendering virtual camera trajectories, including cyclic ones, allowing our model to learn stable view generation from a collection of single views. At test time, despite never seeing a video during training, our approach can take a single image and generate long camera trajectories comprised of hundreds of new views with realistic and diverse content. We compare our approach with recent state-of-the-art supervised view generation methods that require posed multi-view videos and demonstrate superior performance and synthesis quality.Comment: ECCV 2022 (Oral Presentation

Imipramine blue sensitively and selectively targets FLT3-ITD positive acute myeloid leukemia cells.

Aberrant cytokine signaling initiated from mutant receptor tyrosine kinases (RTKs) provides critical growth and survival signals in high risk acute myeloid leukemia (AML). Inhibitors to FLT3 have already been tested in clinical trials, however, drug resistance limits clinical efficacy. Mutant receptor tyrosine kinases are mislocalized in the endoplasmic reticulum (ER) of AML and play an important role in the non-canonical activation of signal transducer and activator of transcription 5 (STAT5). Here, we have tested a potent new drug called imipramine blue (IB), which is a chimeric molecule with a dual mechanism of action. At 200-300 nM concentrations, IB is a potent inhibitor of STAT5 through liberation of endogenous phosphatase activity following NADPH oxidase (NOX) inhibition. However, at 75-150 nM concentrations, IB was highly effective at killing mutant FLT3-driven AML cells through a similar mechanism as thapsigargin (TG), involving increased cytosolic calcium. IB also potently inhibited survival of primary human FLT3/ITD+ AML cells compared to FLT3/ITDneg cells and spared normal umbilical cord blood cells. Therefore, IB functions through a mechanism involving vulnerability to dysregulated calcium metabolism and the combination of fusing a lipophilic amine to a NOX inhibiting dye shows promise for further pre-clinical development for targeting high risk AML

DynIBaR: Neural Dynamic Image-Based Rendering

We address the problem of synthesizing novel views from a monocular video depicting a complex dynamic scene. State-of-the-art methods based on temporally varying Neural Radiance Fields (aka dynamic NeRFs) have shown impressive results on this task. However, for long videos with complex object motions and uncontrolled camera trajectories, these methods can produce blurry or inaccurate renderings, hampering their use in real-world applications. Instead of encoding the entire dynamic scene within the weights of an MLP, we present a new approach that addresses these limitations by adopting a volumetric image-based rendering framework that synthesizes new viewpoints by aggregating features from nearby views in a scene-motion-aware manner. Our system retains the advantages of prior methods in its ability to model complex scenes and view-dependent effects, but also enables synthesizing photo-realistic novel views from long videos featuring complex scene dynamics with unconstrained camera trajectories. We demonstrate significant improvements over state-of-the-art methods on dynamic scene datasets, and also apply our approach to in-the-wild videos with challenging camera and object motion, where prior methods fail to produce high-quality renderings. Our project webpage is at dynibar.github.io.Comment: Project page: dynibar.github.i

Small Molecule Inhibitors of Programmed Cell Death Ligand 1 (PD-L1):A Patent Review (2019–2021)

Introduction: The blockade of immune checkpoints, especially the PD-1/PD-L1 pathway with therapeutic antibodies, has shown success in treating cancers in recent years. Seven monoclonal antibodies (mAbs) targeting PD-1 or PD-L1 have been approved by FDA. However, mAbs exhibit several disadvantages as compared to small molecules such as poor permeation, high manufacturing costs, immunogenicity as well as lacking oral bioavailability. Recently, small-molecule inhibitors targeting PD-L1 have been disclosed with the ability to modulate the PD-1/PD-L1 pathway. Areas covered: The authors reviewed small molecules targeting PD-L1 that block the PD-1/PD-L1 protein–protein interaction for the treatment of various diseases. Expert opinion: Compared with mAbs, PD-1/PD-L1 small-molecule inhibitors show several advantages such as improved tissue penetration, low immunogenicity, well-understood formulation and lower manufacturing costs. They can serve as complementary or synergistically with mAbs for immune therapy. However, at this time most of the reported inhibitors are still inferior to therapeutic antibodies in their inhibitory activities due to smaller molecular weight. Therefore, better small molecules need to be developed to improve their potencies. Moreover, although several PD-L1 small-molecule inhibitors have shown excellent preclinical results, their safety and efficacy in the clinic still awaits further validation