A Modified Oil Refining Loss Method

In certain research studies involving the determination of the refining loss of vegetable oils, such as soybean, the 500-gram samples required by the official method may not be available. The chromatographic method, while giving consistent results on a given sample, does not give results which check the official method. A modification of the official cup method was developed using a cup of special design with a 50-gram sample. Good checks with the official method were obtained. It was found that variations in evaporation losses were more important than mixing speeds in affecting results

Bio-Inspired Micromachined Volumetric Flow Sensor with a Big Dynamic Range for Intravenous Systems

Real-time monitoring of drug delivery in an intravenous infusion system can prevent injury caused by improper drug doses. As the medicine must be administered into the vein at different rates and doses in different people, an ideal intravenous infusion system requires both a low flow rate and large dynamic range monitoring. In this study, a bio-inspired and micromachined volumetric flow sensor is presented for the biomedical application of an intravenous system. This was realized by integrating two sensing units with different sensitivities on one silicon die to achieve a large dynamic range of the volumetric flow rate. The sensor was coated with a parylene layer for waterproofing and biocompatibility purposes. A new packaging scheme incorporating a silicon die into a flow channel was employed to demonstrate the working prototype. The test results indicate that the sensor can detect a volumetric flow rate as low as 2 mL/h, and its dynamic range is from 2 mL/h to 200 mL/h. The sensor performed better than the other two commercial sensors for low-flow detection. The high sensitivity, low cost, and small size of this flow sensor make it promising for intravenous applications

On-Policy Pixel-Level Grasping Across the Gap Between Simulation and Reality

Grasp detection in cluttered scenes is a very challenging task for robots. Generating synthetic grasping data is a popular way to train and test grasp methods, as is Dex-net and GraspNet; yet, these methods generate training grasps on 3D synthetic object models, but evaluate at images or point clouds with different distributions, which reduces performance on real scenes due to sparse grasp labels and covariate shift. To solve existing problems, we propose a novel on-policy grasp detection method, which can train and test on the same distribution with dense pixel-level grasp labels generated on RGB-D images. A Parallel-Depth Grasp Generation (PDG-Generation) method is proposed to generate a parallel depth image through a new imaging model of projecting points in parallel; then this method generates multiple candidate grasps for each pixel and obtains robust grasps through flatness detection, force-closure metric and collision detection. Then, a large comprehensive Pixel-Level Grasp Pose Dataset (PLGP-Dataset) is constructed and released; distinguished with previous datasets with off-policy data and sparse grasp samples, this dataset is the first pixel-level grasp dataset, with the on-policy distribution where grasps are generated based on depth images. Lastly, we build and test a series of pixel-level grasp detection networks with a data augmentation process for imbalance training, which learn grasp poses in a decoupled manner on the input RGB-D images. Extensive experiments show that our on-policy grasp method can largely overcome the gap between simulation and reality, and achieves the state-of-the-art performance. Code and data are provided at https://github.com/liuchunsense/PLGP-Dataset

ctDNA Detection Based on DNA Clutch Probes and Strand Exchange Mechanism

Circulating tumor DNA (ctDNA), originating directly from the tumor or circulating tumor cells, may reflect the entire tumor genom and has gained considerable attention for its potential clinical diagnosis and prognosis throughout the treatment regimen. However, the reliable and robust ctDNA detection remains a key challenge. Here, this work designs a pair of DNA clutch separation probes and an ideal discrimination probes based on toehold-mediated strand displacement reaction (TSDR) to specifically recognize ctDNA. First, the ctDNAs were denatured to form ssDNAs, the pair of DNA clutch separation probes [one of which modified onto the magnetic nanoparticles (MNPs)] are used to recognize and hybridize with the complemental chains and prevent reassociation of denatured ssDNAs. The complemental chains are removed in magnetic field and left the wild and mutant ssDNA chains in the supernatant. Then, the TSDR specificity recognizes the target mutant sequence to ensure only the mutated strands to be detection. The proposed assay exhibited good sensitivity and selectivity without any signal amplification. The proposed assay displayed a linear range from 2 to100 nM with a limit of detection (LOD) of 0.85 nM, and it was useful for ctDNA biomedical analysis and clinic theranostic

Display Device

Apparatus, methods, systems and devices for a low driving voltage, high transmittance blue phase liquid crystal display device having first and second substrates each with polarizer on the exterior surface thereof and a LC material and patterned electrodes on both substrates. The device outputs different light transmissions from the electrically controllable induced birefringence of the blue phase LC material

In vivo photoacoustic imaging of breast cancer tumor with HER2-targeted nanodiamonds

Radiation-damaged nanodiamonds (NDs) are ideal optical contrast agents for photoacoustic (PA) imaging in biological tissues due to their good biocompatibility and high optical absorbance in the near-infrared (NIR) range. Acid treated NDs are oxidized to form carboxyl groups on the surface, functionalized with polyethylene glycol (PEG) and human epidermal growth factor receptor 2 (HER2) targeting ligand for breast cancer tumor imaging. Because of the specific binding of the ligand conjugated NDs to the HER2-overexpressing murine breast cancer cells (4T1.2 neu), the tumor tissues are significantly delineated from the surrounding normal tissue at wavelength of 820 nm under the PA imaging modality. Moreover, HER2 targeted NDs (HER2-PEG-NDs) result in higher accumulation in HER2 positive breast tumors as compared to non-targeted NDs after intravenous injection (i.v.). Longer retention time of HER-PEG-NDs is observed in HER2 overexpressing tumor model than that in negative tumor model (4T1.2). This demonstrates that targeting moiety conjugated NDs have great potential for the sensitive detection of cancer tumors and provide an attractive delivery strategy for anti-cancer drugs