Ammonia-oxidizing bacteria (AOB) have long been considered key to the removal of nitrogen in activated sludge bioreactors. Culture-independent molecular analyses established that AOB lineages bioreactors are dynamic, but underlying operational or environmental factors unclear. Furthermore, contribution ammonia-oxidizing archaea (AOA) has not studied. To this end, we investigated abundance AOA and as well correlations between dynamics parameters at a municipal wastewater treatment plant...

Abstract The observation and detection of the microplastic pollutants generated by industrial manufacturing require use precise optical systems. Digital holography is well suited for this task because its non-contact non-invasive features ability to generate information-rich holograms. However, traditional digital usually requires post-processing steps, which time-consuming may not achieve final object performance. In work, we develop a deep learning-based holographic classification method,...

We devise an inline digital holographic imaging system equipped with a lightweight deep learning network, termed CompNet, and develop the transfer for classification analysis. It has compression block consisting of concatenated rectified linear unit (CReLU) activation to reduce channels, class-balanced cross-entropy loss training. The method is particularly suitable small imbalanced datasets, we apply it detection microplastics. Our results show good improvements both in feature extraction,...

Microplastic (MP) pollution poses severe environmental problems. Developing effective imaging tools for the identification and analysis of MPs is a critical step to curtail their proliferation. Digital holographic can record morphological refractive index information such small plastic fragments, yet due heterogeneous sampling environments variations in MP shapes, traditional supervised learning methods are limited use. In this work, we pioneer zero-shot method that combines images with...

A search in ancient Chinese medicinal literature and modern phytochemical reference indicates that the therapeutic value of Leonurus artemisia (I-mu ts'ao, motherwort) might reside a uterotonic principle present leaves. Leonurine (4-guanidino-n-butyl syringate) was isolated from fresh dry leaves artemisia. The effect leonurine demonstrated rat uterus vitro. Results this study suggest functional phytochemistry based on ethnobotanical experience could lead to development new effective drugs medicine.

Micro-objects, such as microplastics and particulate pollution, need to be accurately observed detected by high-precision optical systems. Digital holography is a powerful tool detect microscopic objects. However, traditional digital requires additional image processing phase unwrapping, de-noising, refocusing, which costs lot of time does not have consistently better performance in micro-object detection. Here, we propose an intelligent holographic classifier, deep learning-based lensless...

An inline digital holography with deep learning is developed to detect microplastics automatically from the raw holograms, without any additional image processing and analysis.

Microplastics, which are a major source of pollution in the ocean, need to be accurately detected and monitored. However, current detection approaches often require complex optical instrumentation long time for image processing. Furthermore, because difficulties particle sampling, it is hard collect dataset with sufficient images balanced distribution. Digital holography, non-destructive imaging method, suitable situ imaging. In this work, we propose novel digital holography microplastics...

Detecting and quantifying microplastic particles have become important problems in environmental monitoring recent years. In the natural environment, nanoplastic are often mixed with large pieces of plastic, microalgae, microorganisms, leaf fragments, etc., making them difficult to be distinguished. addition, microplastics themselves made different materials various shapes. As a result, conventional classification methods based mostly on morphological characteristics cannot accurately...

Underwater imaging is often affected by light scattering, which leads to a significant degradation in image quality and resolution. We propose digital holographic microscopy method with polarization multiplexing for underwater descattering. Our based on single laser source, so that the reference different states can interfere object at same time, required information be extracted frequency spectrum. Combined formation model, we achieve descattering one step. The experimental results...

Water scattering is a significant limiting factor for underwater imaging quality. It changes the transportation direction of original light path, causes attenuation intensity, and so on. In this work, we use synthetic polarizing camera to capture images with different polarization states reduce impact water in one step propagation model Stokes vector. addition, an untrained deep network designed complete image descattering processing. Compared methods based on learning or physical prior, it...

A zero-shot learning method with attribute embedding is developed for holographic image analysis and microplastics probing. Experimental results show its efficacy in identifying the unknown alleviating need manual dataset class annotation.

We propose a novel digital holographic microscope system with synthetic polarization. It can obtain the light intensity of different polarization states in single shot and achieve descattering underwater imaging through polarity calculation.