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Micro nikkor 105 mm f 2.8 lens

Manufactured by Nikon
Sourced in Japan, United States

The Micro Nikkor 105mm f/2.8 lens is a prime lens designed for close-up photography and macro work. It features a fixed focal length of 105mm and a maximum aperture of f/2.8. The lens is capable of focusing on subjects as close as 1:1 magnification ratio, allowing for detailed, high-quality macro captures.

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Lab products found in correlation

2 protocols using micro nikkor 105 mm f 2.8 lens

1

Trachoma Grading in Children

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Clinical grading of trachoma (TF and/or TI) of the right everted superior tarsal conjunctiva was done using the WHO simplified grading system.[2 (link)] Clinical graders were allowed to grade for the study if they attained a chance corrected agreement k ≥ 0.6 with an experienced grader (BDG, JDK or TML) over the scoring signs of clinically active trachoma (TF and TI) during validation exercises with 200 previously graded photographic examples from children 1–9 years. Following grading and prior to any sample collection, at least 2 photographs of the upper tarsal conjunctiva were taken with a Nikon D-series camera and a Micro Nikkor 105 mm f/2.8 lens (Nikon, Tokyo, Japan) for subsequent auditing.
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2

Studying Samara Descent Dynamics

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To determine the natural descent properties of all samaras tested, artificial and natural, we dropped the samaras in a still air setting, as in [30 (link)]. Samaras were released from rest, with the blade pointing downward, from a height of 3.05 m, and allowed to fall freely. Tests were conducted in a laboratory (a growth chamber) without active ventilation, to minimize air currents that could disrupt the measurements. Each individual samara was tested 3 times (i.e., 90 samaras, each dropped 3 times, giving 270 total drops). A Photron FASTCAM Mini UX100 camera (Photron, San Diego, CA, USA) with a micro-Nikkor 105 mm f/28 lens (Nikon, New York, NY, USA) was used to record video data at 2000 frames per second (0.5 ms between frames) with a resolution of 1280 × 800 pixels. The resulting images were analyzed to determine the mean descent speed and rotational velocity at steady state, as illustrated in Figure 3a. Video frames were processed using a combination of background subtraction, median filtering, and thresholding with scikit-image and opencv for Python to track samara position and orientation.
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