Microfluidic passive samplers for in situ collection of live aquatic protists

2014 ◽  
Vol 6 (20) ◽  
pp. 8350-8357 ◽  
Author(s):  
Grant M. Bouchillon ◽  
Jessica Furrer Chau ◽  
George B. McManus ◽  
Leslie M. Shor
Keyword(s):  
High Resolution ◽  
Passive Samplers ◽  
Aquatic Habitats ◽  
Long Term Observation ◽  
In Situ Collection

Examples of microfluidic passive samplers for collecting live protists from aquatic habitats. The samplers allow high-resolution, long-term observation of unstained protists by concentrating and isolating them in nanoliter-scale galleries.

scholarly journals A case of ALM in situ under long-term observation.

Skin Cancer ◽  
2002 ◽  
Vol 17 (2) ◽  
pp. 141-143
Author(s):  
Katsunori MORI ◽  
Takako SHISHIBA
Keyword(s):  
Long Term Observation

scholarly journals LGHAP: a Long-term Gap-free High-resolution Air Pollutants concentration dataset derived via tensor flow based multimodal data fusion

2021 ◽  
Author(s):  
Kaixu Bai ◽  
Ke Li ◽  
Mingliang Ma ◽  
Kaitao Li ◽  
Zhengqiang Li ◽  
...  
Keyword(s):  
Environmental Management ◽  
High Resolution ◽  
Data Fusion ◽  
Air Pollutants ◽  
Big Data Analytics ◽  
Quality Data ◽  
Haze Pollution ◽  
Pm2.5 And Pm10

Abstract. Developing a big data analytics framework for generating a Long-term Gap-free High-resolution Air Pollutants concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and earth system science analysis. By synergistically integrating multimodal aerosol data acquired from diverse sources via a tensor flow based data fusion method, a gap-free aerosol optical depth (AOD) dataset with daily 1-km resolution covering the period of 2000–2020 in China was generated. Specifically, data gaps in daily AOD imageries from MODIS aboard Terra were reconstructed based on a set of AOD data tensors acquired from satellites, numerical analysis, and in situ air quality data via integrative efforts of spatial pattern recognition for high dimensional gridded image analysis and knowledge transfer in statistical data mining. To our knowledge, this is the first long-term gap-free high resolution AOD dataset in China, from which spatially contiguous PM2.5 and PM10 concentrations were estimated using an ensemble learning approach. Ground validation results indicate that the LGHAP AOD data are in a good agreement with in situ AOD observations from AERONET, with R of 0.91 and RMSE equaling to 0.21. Meanwhile, PM2.5 and PM10 estimations also agreed well with ground measurements, with R of 0.95 and 0.94 and RMSE of 12.03 and 19.56 μg m−3, respectively. Overall, the LGHAP provides a suite of long-term gap free gridded maps with high-resolution to better examine aerosol changes in China over the past two decades, from which three distinct variation periods of haze pollution were revealed in China. Additionally, the proportion of population exposed to unhealthy PM2.5 was increased from 50.60 % in 2000 to 63.81 % in 2014 across China, which was then drastically reduced to 34.03 % in 2020. Overall, the generated LGHAP aerosol dataset has a great potential to trigger multidisciplinary applications in earth observations, climate change, public health, ecosystem assessment, and environmental management. The daily resolution AOD, PM2.5, and PM10 datasets can be publicly accessed at https://doi.org/10.5281/zenodo.5652257 (Bai et al., 2021a), https://doi.org/10.5281/zenodo.5652265 (Bai et al., 2021b), and https://doi.org/10.5281/zenodo.5652263 (Bai et al., 2021c), respectively. Meanwhile, monthly and annual mean datasets can be found at https://doi.org/10.5281/zenodo.5655797 (Bai et al., 2021d) and https://doi.org/10.5281/zenodo.5655807 (Bai et al., 2021e), respectively. Python, Matlab, R, and IDL codes were also provided to help users read and visualize these data.

scholarly journals Evaluation of snow extent time series derived from Advanced Very High Resolution Radiometer global area coverage data (1982–2018) in the Hindu Kush Himalayas

2021 ◽  
Vol 15 (9) ◽  
pp. 4261-4279
Author(s):  
Xiaodan Wu ◽  
Kathrin Naegeli ◽  
Valentina Premier ◽  
Carlo Marin ◽  
Dujuan Ma ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Land Cover ◽  
Snow Cover ◽  
Area Coverage ◽  
Slope Aspect ◽  
Hindu Kush ◽  
Very High

Abstract. Long-term monitoring of snow cover is crucial for climatic and hydrological studies. The utility of long-term snow-cover products lies in their ability to record the real states of the earth's surface. Although a long-term, consistent snow product derived from the ESA CCI+ (Climate Change Initiative) AVHRR GAC (Advanced Very High Resolution Radiometer global area coverage) dataset dating back to the 1980s has been generated and released, its accuracy and consistency have not been extensively evaluated. Here, we extensively validate the AVHRR GAC snow-cover extent dataset for the mountainous Hindu Kush Himalayan (HKH) region due to its high importance for climate change impact and adaptation studies. The sensor-to-sensor consistency was first investigated using a snow dataset based on long-term in situ stations (1982–2013). Also, this includes a study on the dependence of AVHRR snow-cover accuracy related to snow depth. Furthermore, in order to increase the spatial coverage of validation and explore the influences of land-cover type, elevation, slope, aspect, and topographical variability in the accuracy of AVHRR snow extent, a comparison with Landsat Thematic Mapper (TM) data was included. Finally, the performance of the AVHRR GAC snow-cover dataset was also compared to the MODIS (MOD10A1 V006) product. Our analysis shows an overall accuracy of 94 % in comparison with in situ station data, which is the same with MOD10A1 V006. Using a ±3 d temporal filter caused a slight decrease in accuracy (from 94 % to 92 %). Validation against Landsat TM data over the area with a wide range of conditions (i.e., elevation, topography, and land cover) indicated overall root mean square errors (RMSEs) of about 13.27 % and 16 % and overall biases of about −5.83 % and −7.13 % for the AVHRR GAC raw and gap-filled snow datasets, respectively. It can be concluded that the here validated AVHRR GAC snow-cover climatology is a highly valuable and powerful dataset to assess environmental changes in the HKH region due to its good quality, unique temporal coverage (1982–2019), and inter-sensor/satellite consistency.

scholarly journals Long-term observation of in situ seismic velocity and attenuation

2003 ◽  
Vol 108 (B6) ◽  
Author(s):  
Keiko Yamamura ◽  
Osam Sano ◽  
Hisashi Utada ◽  
Yasuko Takei ◽  
Shigeru Nakao ◽  
...  
Keyword(s):  
Seismic Velocity ◽  
Long Term Observation

scholarly journals On the Relation of Net Balance, Ice Flow, and Surface Lowering of Lewis Glacier, Mount Kenya, East Africa, 1982–86

1987 ◽  
Vol 33 (115) ◽  
pp. 315-318 ◽  
Author(s):  
Stefan Hastenrath
Keyword(s):  
Vertical Flow ◽  
Glacier Surface ◽  
Ice Flow ◽  
Ice Surface ◽  
Mass Redistribution ◽  
Observation Program ◽  
Glacier Ice ◽  
Long Term Observation

AbstractThe second 4 year phase of a long-term observation program on Lewis Glacier, Mount Kenya, was completed in March 1986. As for the 1978–82 interval, net-balance results at a stake network and repeated mapping of the ice-surface topography allowed assessment of the mass economy by both “glaciological” and “geodetic” methods.The general findings from the 1978–82 observations are confirmed: the vertical flow component is directed downward in the upper glacier, and upward in the lower glacier; surface lowering and negative net balance increase down-glacier; ice flow mitigates surface lowering by the negative net balance in the lower glacier, but enhances it in the upper glacier. However, the major difference between the 1982–86 and 1978–82 periods is the progressive slow-down of ice flow. This entails a reduction of mass redistribution, in consequence of which the surface lowering becomes increasingly dependent on thein-situnet balance. It is expected that this circumstance will simplify any inference on future glacier behavior.

scholarly journals In-situ Real-time Field Imaging and Monitoring of Leaf Stomata by High-resolution Portable Microscope

2019 ◽  
Author(s):  
Prashant Purwar ◽  
Junghoon Lee
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Stomatal Opening ◽  
Objective Lens ◽  
Lower Epidermis ◽  
Plant Hydraulics ◽  
Small Depth ◽  
Field Imaging

ABSTRACTStomata, functionally specialized micrometer-sized pores on the epidermis of leaves (mainly on the lower epidermis), control the flow of gases and water between the interior of the plant and atmosphere. Real-time monitoring of stomatal dynamics can be used for predicting the plant hydraulics, photosensitivity, and gas exchanges effectively. To date, several techniques offer the direct or indirect measurement of stomatal dynamics, yet none offer real-time, long-term persistent measurement of multiple stomal apertures simultaneously of an intact leaf in a field under natural conditions. Here, we report a high-resolution portable microscope-based technique for in situ real-time field imaging and monitoring of stomata. Our technique is capable of analyzing and quantifying the multiple lower epidermis stomal pore dynamics simultaneously and does not require any physical or chemical manipulation of a leaf. An upward facing objective lens in our portable microscope allows the imaging of lower epidermis stomatal opening of a leaf while upper epidermis being exposed to the natural environment. Small depth of field (~ 1.3 μm) of a high-magnifying objection lens assists in focusing the stomatal plane in highly non-planar tomato leaf having a high density of trichome (hair-like structures). For long-term monitoring, the leaf is fixed mechanically by a novel designed leaf holder providing freedom to expose the upper epidermis to the sunlight and lower epidermis to the wind simultaneously. In our study, a direct relation between the stomatal opening and the intensity of sunlight illuminating on the upper epidermis has been observed in real-time. In addition, real-time porosity of leaf (ratio between the areas of stomatal opening to the area of a leaf) and stomatal aspect ratio (ratio between the major axis and minor axis of stomatal opening) along with stomatal density have been quantified.

scholarly journals Solid optical clearing agents based through-Intact-Skull (TIS) window technique for long-term observation of cortical structure and function in mice

2021 ◽  
Author(s):  
Dongyu Li ◽  
Zhengwu Hu ◽  
Hequn Zhang ◽  
Liang Zhu ◽  
Yin Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Basic Research ◽  
Neuron Activity ◽  
Optical Clearing ◽  
Non Invasive ◽  
Clearing Technique ◽  
Long Term Observation ◽  
And Function

In vivo cortical optical imaging needs to overcome the scattering of skull. Compared to the traditional transcranial surgery-based open-skull glass window and thinned-skull preparation, chemical tissue optical clearing techniques can provide a skull-remained optical access to the brain while maintaining its original environment. However, previously demonstrated skull optical clearing windows could only maintain transparency for a couple of hours and hardly capable for high-resolution monitoring of awake animals. Here, we developed a convenient and easy-handling chronic skull optical clearing technique, named "Through-Intact-Skull (TIS) window", which was compatible with long-term observation at high resolution, and yielded large imaging depth of 900 μm for cortical neurovascular visualization. In addition, our TIS window could monitor neuron activity in awake mice for a long term. Therefore, our bio-compatible and non-invasive TIS window is a new promising approach for intravital brain microscopy with great potential for basic research in neuroscience.

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