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Harmful and nuisance algal blooms are becoming a greater concern to public health, riverine ecosystems, and recreational uses of inland waterways. Algal bloom proliferation has increased in the Upper Clark Fork River due to a combination of warming water temperatures, naturally high phosphorus levels, and an influx of nitrogen from various sources. To improve understanding of bloom dynamics and how they affect water quality, often measured as algal biomass measured through pigment standing crops, a UAV-based hyperspectral imaging system was deployed to monitor several locations along the Upper Clark Fork River in western Montana. Image data were collected across the spectral range of 400–1000 nm with 2.1 nm spectral resolution during two field sampling campaigns in 2021. Included are methods to estimate chl a and phycocyanin standing crops using regression analysis of salient wavelength bands, before and after separating the pigments according to their growth form. Estimates of chl a and phycocyanin standing crops generated through a linear regression analysis are compared to in situ data, resulting in a maximum R2 of 0.96 for estimating fila/epip chl-a and 0.94 when estimating epiphytic phycocyanin. Estimates of pigment standing crops from total abundance, epiphytic, and the sum of filamentous and epiphytic sources are also included, resulting in a promising method for remotely estimating algal standing crops. This method addresses the shortcomings of current monitoring techniques, which are limited in spatial and temporal scale, by proposing a method for rapid collection of high-spatial-resolution pigment abundance estimates. 

Although many species shift their phenology with climate change, species vary significantly in the direction and magnitude of these responses (i.e., phenological sensitivity). Studies increasingly detect early phenology or high phenological sensitivity to climate in non-native species, which may favor non-native species over natives in warming climates. Yet relatively few studies explicitly compare phenological responses to climate between native vs. non-native species or between non-native populations in the native vs. introduced range, limiting our ability to quantify the role of phenology in invasion success. Here, we review the empirical evidence for and against differences in phenology and phenological sensitivity to climate in both native vs. non-native species and native and introduced populations of non-native species. Contrary to common assumptions, native and non-native plant species did not consistently differ in mean phenology or phenological sensitivity. However, non-native plant species were often either just as or more sensitive, but rarely less sensitive, to climate as natives. Introduced populations of non-native plant species often show earlier reproduction than native populations of the same species, but there was mixed evidence for differences in phenological sensitivity between introduced and native plant populations. We found very few studies comparing native vs. invasive animal phenology. Future work should characterize phenological sensitivity to climate in native vs. non-native plant and animal species, in native vs. introduced populations of non-native species, and across different stages of invasion, and should carefully consider how differences in phenology might promote invasion success or disadvantage native species under climate change. 

Pharmaceutical cocrystals comprise one active pharmaceutical ingredient (API) and at least one small molecule excipient coformer. While solvent evaporation and mechanochemistry are the preferred methods for their synthesis, some cocrystals are known to form spontaneously at ambient conditions when powders of input materials are mixed—a process not yet fully understood. Aqueous humidity is also known to accelerate spontaneous cocrystal formation. We report here the extent of spontaneous cocrystallization for 14 cocrystal systems, at four levels of humidity. The binary cocrystals in our study consist of a model API (caffeine, theophylline, nicotinamide) and a small chain diacid coformer (oxalic acid, malonic acid, maleic acid, fumaric acid, succinic acid, glutaric acid). The spontaneous cocrystal formation was monitored ex situ by powder X-ray diffraction over several weeks. Our results show cocrystal formation in all 14 systems to varying extent and are consistent with literature reports that higher humidity correlates with more rapid cocrystal formation. We find that cocrystals containing smaller coformers often form faster. Based on our findings, we identify several cocrystals as candidates for future study. 

In this work-in-progress (WIP) study, we begin to identify explicit links between ethics and diversity, equity, and inclusion (DEI) in engineering education and closely related fields. We use systematic literature review procedures coupled with a qualitative content analytic approach to identify these explicit links within engineering education journals and conference papers. Through this WIP, we identify preliminary themes that represent explicit discourses connecting ethics and DEI and we cite associated literature. We unpack four themes that have a prominent presence in the abstracts that we have reviewed: cultural, global, social, and sustainable. These explicit connections will support future systematic review procedures wherein we will aim to identify implicit DEI and ethics connections via an analysis of whole manuscripts. While preliminary, we hope that these four themes can prompt strategies to connect ethics and DEI more purposefully when teaching towards these and related topics. 

Hyperspectral imaging systems are becoming widely used due to their increasing accessibility and their ability to provide detailed spectral responses based on hundreds of spectral bands. However, the resulting hyperspectral images (HSIs) come at the cost of increased storage requirements, increased computational time to process, and highly redundant data. Thus, dimensionality reduction techniques are necessary to decrease the number of spectral bands while retaining the most useful information. Our contribution is two-fold: First, we propose a filter-based method called interband redundancy analysis (IBRA) based on a collinearity analysis between a band and its neighbors. This analysis helps to remove redundant bands and dramatically reduces the search space. Second, we apply a wrapper-based approach called greedy spectral selection (GSS) to the results of IBRA to select bands based on their information entropy values and train a compact convolutional neural network to evaluate the performance of the current selection. We also propose a feature extraction framework that consists of two main steps: first, it reduces the total number of bands using IBRA; then, it can use any feature extraction method to obtain the desired number of feature channels. We present classification results obtained from our methods and compare them to other dimensionality reduction methods on three hyperspectral image datasets. Additionally, we used the original hyperspectral data cube to simulate the process of using actual filters in a multispectral imager. 

The increasing prevalence of three-dimensional (3D) printing of optical housings and mounts necessitates a better understanding of the optical properties of printing materials. This paper describes a method for using multithickness samples of 3D printing materials to measure transmittance spectra at wavelengths from 400 to 2400 nm [visible to short-wave infrared (IR)]. In this method, 3D samples with material thicknesses of 1, 2, 3, and 4 mm were positioned in front of a uniform light source with a spectrometer probe on the opposing side to measure the light transmittance. Transmission depended primarily on the thickness and color of the sample, and multiple scattering prevented the use of a simple exponential model to relate transmittance, extinction, and thickness. A Solidworks file and a 3D printer file are included with the paper to enable measurements of additional materials with the same method.

 

As the applications of hyperspectral imaging rapidly diversify, the need for accurate radiometric calibration of these imaging systems is becoming increasingly important. When performing radiometric measurements, the polarization response of the imaging system can be of particular interest if the scene contains partially polarized objects. For example, when imaging a scene containing water, surface reflections from the water will be partially polarized, possibly affecting the response of the imaging system. In this paper, the polarization response of a Resonon, Inc. visible near-infrared (VNIR) hyperspectral imaging system is assessed across a spectral range of 400nm to 1000 nm, with a spectral resolution of 2.1 nm. Efforts are currently underway to correct for the observed polarization response of the imaging system.