Review of Student-Built Spectroscopy Instrumentation Projects

Copyright © 2020 American Chemical Society and Division of Chemical Education, Inc. One challenge of teaching chemical analysis is the proliferation of sophisticated, but often impenetrable, instrumentation in the modern laboratory. Complex instruments, and the software that runs them, distance students from the physical and chemical processes that generate the analytical signal. A solution to this challenge is the introduction of a student-driven instrument-building project. Visible absorbance spectroscopy is well-suited to such a project due to its relative simplicity and the ubiquity of absorbance measurements. This Article reviews simple instructor- A nd student-built instruments for spectroscopy, providing an overview of common designs, components, and applications. This comprehensive summary includes options that are suitable for in-person or remote learning with K-12 students and undergraduates in general chemistry, analytical chemistry, instrumental analysis, and electronics courses

Hemoglobin determination with paired emitter detector diode

Two ordinary green light-emitting diodes used as light emitter and detector coupled with simple voltmeter form a complete, cost-effective prototype of a photometric hemoglobinometer. The device has been optimized for cuvette assays of total hemoglobin (Hb) in diluted blood using three different chemical methods recommended for the needs of clinical analysis (namely Drabkin, lauryl sulfate, and dithionite methods). The utility of developed device for real analytics has been validated by the assays of total Hb content in human blood. The results of analysis are fully compatible with those obtained using clinically recommended method and clinical analyzer

Analysis of the relationships between vegetation water content obtained from field measurements and vegetation indices

Monitoring the plant moisture has a significant role in geographical research. It may be used, among the others, for climate modelling, agricultural predicting, rational water management, drought monitoring and determining vulnerability to the occurrence of the fire. Traditional methods, based on field measurements, are the most accurate, but also time-consuming. Therefore these methods can be applied only in a limited area. In order to explore bigger areas remote sensing methods are useful. To analyse plant condition and water content vegetation indices can be used. Their calculations are based on the reflectance in different bands. Despite many studies conducted on the development of remote sensing indices, still there is a need for verification of their accuracy and usefulness by comparing the results obtained through remote sensing tools with the results of field measurements. In this paper three indices are used: Moisture Stress Index (MSI), Normalized Difference Infrared Index (NDII) and transformation Tasseled Cap (the Wetness band). The aim of this study was to compare the value of vegetation indices calculated using images from Landsat 5 Thematic Mapper with the results of field measurement from five test areas of different type of land cover: cereal crops, non-cereal crops, forests, meadows and pastures. Research was carried out in province Ontario (Canada) and consisted of two stages. The first stage was the fi eld measurements, where the specified number of plant samples was collected and water content was calculated. The second stage consisted of the preparation of relevant satellite images (atmospheric correction and making the mosaic) and the calculation of vegetation indices. The study has shown, that statistical relationships between data sets obtained through remote sensing indices and calculated on the basis of field measurements are diverse for different indices. MSI and NDII values are significantly correlated with the water content in plants (R= -0.62 and 0.56, respectively). The correlation of TCW was rated as moderate (R=0.30). Spatial distribution of water content based on maps created using NDII and MSI is similar. It was noticed that TC Wetness transformation overestimates water content in cereal plants (smaller water content) and underestimates it in natural green plant ecosystems, which generally have higher water content. As a result, the range of water content values obtained from TCW is more narrow (dominates the class of 60-70% water in plants) than the range of values calculated using NDII and MSI. Both indices have more uniform distribution dominated by the classes of moderate water content (50-60%), rather wet plants (60-70%) and very wet plants (70-80%). Each index is characterized by different distribution of the water content. In general values calculated on the basis of NDII and MSI are higher than calculated using TCW. In order to perform more accurate analysis between values calculated using satellite images and the results of field measurements, the values of particular types of land cover should be compared

Tofacitinib in Combination With Methotrexate in Patients With Rheumatoid Arthritis: Clinical Efficacy, Radiographic, and Safety Outcomes From a Twenty-Four-Month, Phase III Study

Pathophysiology and treatment of rheumatic disease