300 research outputs found
Holographic opto-fluidic microscopy.
Over the last decade microfluidics has created a versatile platform that has significantly advanced the ways in which micro-scale organisms and objects are controlled, processed and investigated, by improving the cost, compactness and throughput aspects of analysis. Microfluidics has also expanded into optics to create reconfigurable and flexible optical devices such as reconfigurable lenses, lasers, waveguides, switches, and on-chip microscopes. Here we present a new opto-fluidic microscopy modality, i.e., Holographic Opto-fluidic Microscopy (HOM), based on lensless holographic imaging. This imaging modality complements the miniaturization provided by microfluidics and would allow the integration of microscopy into existing on-chip microfluidic devices with various functionalities. Our imaging modality utilizes partially coherent in-line holography and pixel super-resolution to create high-resolution amplitude and phase images of the objects flowing within micro-fluidic channels, which we demonstrate by imaging C. elegans, Giardia lamblia, and Mulberry pollen. HOM does not involve complicated fabrication processes or precise alignment, nor does it require a highly uniform flow of objects within microfluidic channels
Existence and Global Uniform Asymptotic Stability of Pseudo Almost Periodic Solutions for Cohen-Grossberg Neural Networks with Discrete and Distributed Delays
This paper studies the existence and uniform asymptotic stability of pseudo almost periodic solutions to Cohen-Grossberg neural networks (CGNNs) with discrete and distributed delays by applying Schauder fixed point theorem and constructing a suitable Lyapunov functional. An example is given to show the effectiveness of the main results
Zhongjing: Enhancing the Chinese Medical Capabilities of Large Language Model through Expert Feedback and Real-world Multi-turn Dialogue
Recent advances in Large Language Models (LLMs) have achieved remarkable
breakthroughs in understanding and responding to user intents. However, their
performance lag behind general use cases in some expertise domains, such as
Chinese medicine. Existing efforts to incorporate Chinese medicine into LLMs
rely on Supervised Fine-Tuning (SFT) with single-turn and distilled dialogue
data. These models lack the ability for doctor-like proactive inquiry and
multi-turn comprehension and cannot always align responses with safety and
professionalism experts. In this work, we introduce Zhongjing, the first
Chinese medical LLaMA-based LLM that implements an entire training pipeline
from pre-training to reinforcement learning with human feedback (RLHF).
Additionally, we introduce a Chinese multi-turn medical dialogue dataset of
70,000 authentic doctor-patient dialogues, CMtMedQA, which significantly
enhances the model's capability for complex dialogue and proactive inquiry
initiation. We define a refined annotation rule and evaluation criteria given
the biomedical domain's unique characteristics. Results show that our model
outperforms baselines in various capacities and matches the performance of
ChatGPT in a few abilities, despite having 50x training data with previous best
model and 100x parameters with ChatGPT. RLHF further improves the model's
instruction-following ability and safety.We also release our code, datasets and
model for further research
Roles of plant growth substance in callus induction of Achyranthes bidentata
   In this research, callus from leaves, petioles and stems of Achyranthes bidentata was evidently initiated by plant growth substance, in which 2,4-dichlorophenoxyacetic acid (2,4-D) was very important to callus induction, but effects of other plant growth substances were various, and the optimum combination of plant growth substances for callus induction from leaves, petioles and stems was respectively obtained. Compared with callus induction from leaves and petioles, callus induction from stems was easier, and the higher induction rate and bigger mass of callus from stems were obtained. This study showed that the dedifferentiation capacity of various explants from Achyranthes bidentata was obviously different, and effects of plant growth substance on callus induction from various explants of Achyranthes bidentata were significantly diverse
Oral Immunization with Recombinant Lactobacillus acidophilus Expressing espA-Tir-M Confers Protection against Enterohemorrhagic Escherichia coli O157:H7 Challenge in Mice
Study on evaporation drainage of deep coal seam gas wells
Targeting the problem of a small amount of fluid accumulation in deep coal seam gas (CSG) wells during flowing production stage, the evaporation drainage method is proposed to discharge the liquid accumulation. Based on the Dalton evaporation model and wind speed function, a calculation model of evaporation drainage was established for deep CSG wells, which was verified by laboratory experiments. Taking a CSG well in the western Ordos Basin as an example to analyze the evaporation drainage capacity, the influence of temperature, daily gas production, bottomhole flowing pressure (BHFP), formation gas water saturation on the evaporation drainage capacity was investigated. The results show that the maximum evaporation water production is 2,533.8 kg/d at a bottomhole temperature of 80°C and a gas production rate of 30 × 103 m3/d. It is found that the temperature and pressure have a marked influence on the evaporation drainage. By improving the gas production and bottomhole temperature, and reducing the BHFP can effectively promote the evaporation drainage capacity. The initial moisture content of CSG in the reservoir are inversely proportional to the evaporation drainage capacity. By adjusting the BHFP and daily gas production, the evaporation drainage capacity can match the liquid production rate of the formation. Evaporation drainage can effectively extend the flowing production time of deep CSG wells and reduce the costs of production
Segment Anything Model (SAM) for Radiation Oncology
In this study, we evaluate the performance of the Segment Anything Model
(SAM) model in clinical radiotherapy. We collected real clinical cases from
four regions at the Mayo Clinic: prostate, lung, gastrointestinal, and head \&
neck, which are typical treatment sites in radiation oncology. For each case,
we selected the OARs of concern in radiotherapy planning and compared the Dice
and Jaccard outcomes between clinical manual delineation, automatic
segmentation using SAM's "segment anything" mode, and automatic segmentation
using SAM with box prompt. Our results indicate that SAM performs better in
automatic segmentation for the prostate and lung regions, while its performance
in the gastrointestinal and head \& neck regions was relatively inferior. When
considering the size of the organ and the clarity of its boundary, SAM displays
better performance for larger organs with clear boundaries, such as the lung
and liver, and worse for smaller organs with unclear boundaries, like the
parotid and cochlea. These findings align with the generally accepted
variations in difficulty level associated with manual delineation of different
organs at different sites in clinical radiotherapy. Given that SAM, a single
trained model, could handle the delineation of OARs in four regions, these
results also demonstrate SAM's robust generalization capabilities in automatic
segmentation for radiotherapy, i.e., achieving delineation of different
radiotherapy OARs using a generic automatic segmentation model. SAM's
generalization capabilities across different regions make it technically
feasible to develop a generic model for automatic segmentation in radiotherapy
The mechanism of chlorogenic acid inhibits lipid oxidation: An investigation using multi-spectroscopic methods and molecular docking
Endogenous lipase and lipoxygenase play important roles in accelerating lipid oxidation. Polyphenols are a series of commonly used chemicals for preserving fish and seafood products, due to their positive inhibitory effects on lipid oxidation. However, the mechanism involved is still unknown. The inhibitory effects of chlorogenic acid (CGA) on lipase and lipoxygenase were investigated and explored with multi- spectroscopic and molecular docking approaches. Results showed that CGA could inhibit the activities of lipase and lipoxygenase with concentration increased in a highly dose-dependent manner. CGA quenched intrinsic fluorescence intensities of enzymes by static quenching and binding with CGA which led to changes in 3D structures of enzymes. Results of the molecular docking confirmed binding modes, binding sites and major interaction forces between CGA and enzymes, which reduced the corresponding activity. Thus, this study could provide basic mechanisms of the inhibitory effects of polyphenols on lipid oxidation during food preservation
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