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This systematic review aims to evaluate which effects nature exposure has on stress in women and get a more objective viewpoint using measurements of physiological markers of stress to complement the many studies using subjective questionnaires. A search was done on Scopus, Medline EBSCO, and Web of Science for peer-reviewed, published, and original research. Five studies met the inclusion criteria and were included in this review. The outcome measurements included were activity in the autonomic nervous system (ANS) measured with heart-rate variability (HRV) and cerebral activity measured by near-infrared spectroscopy (NIRS). With the definition of Shinrin-Yoku in mind, nature exposure was walking in or watching the natural environment, compared to walking in or watching an urban environment. In this systematic review, four of five studies found significant results that nature exposure alleviated stress in women compared to an urban environment. These findings contribute to a growing body of evidence suggesting that nature is valuable in reducing stress-related illnesses in women. On the individual level, these findings show that nature exposure can be used as an evidence-based intervention to reduce stress in women. Furthermore, these findings clarify the benefits of including elements from nature in urban environments on a societal level.

Hyperspectral imaging is an emerging technology in the field of biomedical engineering which may be used as a non-invasive modality to characterize tumors. In this thesis, a hyperspectral imaging system was used to characterize canine mammary tumors of unknown histopathology (pre-surgery) and correlate the results with the post-surgical histopathology results. The system consisted of a charge coupled device (CCD) camera, a liquid crystal tunable filter in the near infrared range (650-1100 nm), and a controller. Spectral signatures of malignant and benign canine mammary tumors were extracted and analyzed. The reflectance intensities of malignant tumor spectra were generally lower than benign tumor spectra over the wavelength range 650-1100nm. Previous studies have shown that cancerous tissues have a higher hemoglobin and water content, and lower lipid concentration with respect to benign tissues. The decreased reflectance intensity observed for malignant tumors is likely due to the increased microvasculature and, therefore, higher blood content of malignant tissue relative to benign tissue. Second derivative method was applied to the reflectance spectra. Peaks at 700, 840, 900 and 970 nm were observed in the second derivative reflectance spectra. These peaks were attributed to deoxy-hemoglobin, oxy-hemoglobin, lipid and water respectively. A Tissue Optical Index (TOI) was developed that enhances contrast between malignant and benign canine tumors. This index is based on the ratio of the reflectance intensity values corresponding to the wavelengths associated with the four chromophores. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were also applied on the canine spectral dataset and the method was cross-validated. Preliminary results from 22 canine mammary tumors showed that the sensitivity and specificity of the PCA-LDA is method is 86% and 86% respectively. The sensitivity and specificity of the TOI model is 86% and 95% respectively. These results show promise in the non-invasive optical diagnosis of canine mammary cancer. / Electrical and Computer Engineering

Articular cartilage helps in the motion of the diarthroidal joints by providing a near frictionless load bearing surface. Identification of changes in articular cartilage chemical and structural properties that arise from degeneration and suboptimal tissue repair have been the target of many studies. Current methods that evaluate these changes frequently involve destructive specimen preparation. Thus there is a need to develop a method to accurately evaluate changes in cartilage during disease or repair processes. Fourier transform infrared (FTIR) spectroscopy in the mid-infrared (MIR) spectral range is based on molecular vibrations and has been used to study the chemical and structural properties of biological tissues, including cartilage. However, this technique generally requires extensive sample preparation and modification of the intact tissue. An alternative approach is to use near-infrared spectroscopy (NIRS) which does not require sample preparation due to higher depth of penetration. This doctoral dissertation focuses on identification of NIR spectral features to evaluate the major components of cartilage. These NIR spectral features are then used to evaluate compositional changes in engineered and degraded cartilage, and the results validated with histological, biochemical, mechanical and MIR analysis of the same tissue. Together, these studies lay the groundwork for clinical and in situ applications of NIRS. / Bioengineering

Plasmonic polymer nanocomposites contain plasmonic nanoparticles that are dispersed within a polymer. The polymer matrix strongly influences the optical properties of plasmonic nanoparticles. It is imperative to understand the interaction between plasmonic nanoparticles and polymers so that one can develop functional devices using nanocomposites. The utilization of plasmonic nanoparticles as fillers has great potential to transform critical nanotechnologies where light management is crucial, such as refractive index based nanosensors, optical coatings, and light actuated devices. Despite the great potential, effective integration of plasmonic nanoparticles with polymers remains challenging. This dissertation presents i) the effects of dielectric media on the optical properties of plasmonic nanoparticles, ii) the sensing of polymer brush formation on nanoparticles, iii) the fabrication of plasmonic nanocomposite thin-films with controlled optical properties, and iv) the development of electrically conductive membranes for electrostatic speakers. The optical response of plasmonic nanoparticles (referred to as wavelength of localized surface plasmon resonance, λLSPR) is sensitive to changes in refractive index of the medium. The sensitivity (S) plays a critical role in determining the performance of nanoparticles in sensing applications. In this dissertation, I have conducted a systematic study on the sensitivity of plasmonic nanoparticles as a function of various parameters: shape, size, composition, initial plasmonic resonance wavelength, cross-sectional area, and aspect ratio. Among the parameters investigated, aspect ratio (R) is determined to be the key parameter that controls S, following an empirical equation, S = 46.87 R + 109.37. This relationship provides a guideline for selecting fillers in plasmonic polymer nanocomposites, and it predicts the final effect of plasmonic nanoparticles on the optical properties of polymer nanocomposites. Plasmonic nanoparticles are employed to probe polymer grafting on the surfaces of metal nanoparticles. Using ultraviolet-visible (UV-vis) spectroscopy, I have demonstrated the quantification of polymer grafting density on the surface of plasmonic nanoparticles. The λLSPR of plasmonic nanoparticles red-shifts as the polymer concentration near the nanoparticle surface increases. I have investigated the formation of polymer brush by grafting the nanoparticles with thiolated polyethylene glycol (PEG-SH) and revealed the three–regime kinetics in situ. Importantly, this study suggests that a latent regime arises due to fast polymer adsorption and prolonged chain rearrangement on nanoparticle surfaces. When the polymer chains rearrange and chemically tether to the surface, they contract and allow more polymer chains to graft onto the particle surface until saturation. This analytical method provides a new surface probing technique for polymer brush analysis, complementary to conventional methods such as quartz crystal microbalance, atomic force microscope, and microcantilivers. Commercial tinted glass employs expensive metalized films to reduce light transmittance but has limited spectral selectivity. To reduce the cost of metalized films and to improve the spectral selectivity, I have employed plasmonic nanoparticles in polymers to fabricate spectral-selective tinted films. First, I have synthesized two-dimensional (2D) plasmonic silver nanoparticles (AgNPs) using multi-step growth. The nanoparticles have a tunable plasmon resonance and provide spectral selectivity. The multi-step growth forgoes polymeric ligands such as poly(vinylpyrrolidone) (PVP) and solely relies on a small molecule sodium citrate. Briefly, small citrate-capped Ag seeds are first grown into small 2D AgNPs. The small 2D AgNPs are then used to grow large 2D AgNPs via multiple growth steps. The PVP-free method allows for fast synthesis of 2D AgNPs with large sizes and tunable plasmon resonance across the visible and NIR region. The 2D AgNPs are integrated with polymers to produce thin-film plasmonic nanocomposites. By controlling the planar orientation of the 2D AgNPs through layer-by-layer assembly, the polymer nancomposites have achieved reduced light transmittance and enhanced reflectance across the visible and NIR range. In contrast to conventional polymer nanocomposites where the AgNPs are randomly oriented, the thin-film polymer nanocomposites exhibit excellent control over nanoparticle density and hence the optical properties, that is, tunable light transmittance and reflectance across the visible and NIR. Lastly, graphene is used to prepare conductive free-standing polymer thin-films. Graphene, an ultralight weight 2D material with excellent electrical and mechanical properties, has potential for use in thin-film composites essential for photovoltaics, electrostatic speakers, sensors, and touch displays. Current graphene-based composite films contain graphene flakes randomly mixed in a polymer matrix and usually possess poor mechanical and electrical properties. In this dissertation, I have developed thin-film nanocomposites comprised of chemical vapor deposited (CVD) graphene and high-performance polyetherimide (PI). The CVD-grown graphene is polycrystalline, and it cannot be used as a free-standing film. By enforcing the polycrystalline graphene with a thin layer of PI, I have prepared free-standing thin-film composites with a high aspect ratio of 105. Mechanical and electrical property characterization reveals a Young's modulus of 3.33 GPa and a resistance of 200 - 500 Ω across the membrane. A typical spring constant of the membrane is ~387 N/m. Dynamic electromechanical actuation shows that the membrane vibrates at various input frequencies. The polymer/graphene film has excellent acoustic properties, and when used as a speaker membrane, it reduces the electrical power consumption by a factor of 10-100 over the frequency range of 600–10,000 Hz. / Doctor of Philosophy / Nanomaterials such as plasmonic nanoparticles and graphene have optical, electrical, and mechanical properties that are important for light filters, sensors, printing, photovoltaics, touch screens, speakers, and biomedical devices. To fully employ the nanomaterials, a support such as polymer is often required. However, when the nanomaterials and polymers are combined, their optical, electrical, and mechanical properties drastically change. Therefore, it is imperative to understand the interactions between nanomaterials and polymers, as well as the resulting properties. Towards this goal, I have studied the sensitivity of plasmonic nanoparticles in a dielectric media and then utilized the sensitivity to investigate polymer brush formation on nanoparticle surfaces. In addition, I have investigated the integration of plasmonic nanoparticles and graphene with polymers to develop thin-film nanocomposites for window coatings and audio speakers, respectively. Plasmonic nanoparticles can detect trace amounts of chemicals, biomolecules, toxics, warfare agents, and environmental pollutants. Sensitivity is the key criterion that determines the performance of nanoparticles for such applications. Firstly, I have conducted a detailed and comprehensive study of the plasmonic sensitivity as a function of various nanoparticle parameters including shape, size, composition, cross-sectional area, initial plasmonic resonance wavelength, and aspect ratio. I have found that the sensitivity scaled linearly with aspect ratio. The strong dependence of sensitivity on aspect ratio provides insight into designing effective plasmonic sensors. Based on the sensitivity study, I have used plasmonic nanoparticles as sensors to probe and understand the mechanism of polymer brush formation in situ. When the concentration of polymer increases on the nanoparticle surfaces, the optical response of the nanoparticle changes. Through functionalizing the plasmonic nanoparticles with polymers, I have confirmed the three different regimes of polymer brush formation. Plasmonic nanoparticles resonating in the visible and near infrared have a great potential in designing polymer nanocomposites for window coatings. Among different exotic shapes, two-dimensional nanoplates are the most important as their optical properties can be easily tuned across a wide range of wavelengths. However, most of the current methods require polymers, long hours of reaction time, and multiple purification steps. I have developed a new multi-step strategy to synthesize Ag nanoplates which absorb in the range of 500–1660 nm. Utilizing the plasmonic nanoparticles, the spectral-selective plasmonic nanocomposites comprised of polymers and planarly oriented Ag nanoparticles of judiciously selected sizes and compositions were prepared. The plasmonic polymer nanocomposites spectral-selectively reflect, scatter, and filter light of any desired wavelength. The nanocomposites will impact on the tinted glass in modern energy-efficient buildings. The outstanding electrical and mechanical properties of graphene have stirred a large volume of research in the last 15 years. Most graphene-based technologies focus on graphene at the nano or micro scale. To further the practicality of graphene in large devices like audio speakers, large areas and thin films are needed to reduce energy consumption. Graphene on its own cannot be used over large areas due to the inherent defects arising during the growth. Here I present results on combining suspended sheets of single layer graphene with a mechanically strong polymer thin film. The acoustic properties of speakers made of polymer/graphene thin films are similar to those of conventional electrodynamic speakers in modern cellphones. The energy consumption, however, reduces sharply by a factor of 10-100 for the polymer/graphene based speakers. This sharp decrease in energy is attributed to the lightweight, flexibility, and excellent electrical conductivity. Apart from speakers, the membrane designed here also has huge potential in other devices like touch panels, capacitive sensors, and photovoltaics.

Sustainability is inherently a complex problem that requires new ways of thinking. To solve grand challenges such as climate change, environmental degradation, and poverty, engineers cannot rely on the same models of thinking that were used to create these problems. Engineering education is therefore critical to advance sustainable engineering solutions. Improving education relies on understanding of cognition of thinking and designing for sustainability. In this thesis, a nascent neuroimaging technology called functional near-infrared spectroscopy (fNIRS) was used to measure cognition among engineering students thinking about sustainability. fNIRS provides an opportunity to investigate how sustainability in design influences cognition, and how different concept generation techniques help students consider many aspects related to sustainability. The first manuscript provides evidence that engineering students perceive sustainability in design as a constraint, limiting the number of solutions for design and decreasing the cognitive efficiency to generate solutions. Senior engineering students generated fewer solutions than freshmen, however, seniors were better able to cognitively manage the sustainability parameter with higher cognitive efficiency. The second manuscript investigates the cognitive difference when generating concepts using concept listing or concept mapping. The results indicate that concept mapping (i.e. intentionally drawing relationships between concepts) leads to more concepts generated. An increase in concepts during concept mapping was also observed to shift cognitive load in the brain from regions associated with process sequencing to regions associated with cognitive flexibility. This research demonstrates the feasibility of fNIRS applied in engineering research and provides more understanding of the cognitive requirements for sustainability thinking. / M. S.

Described is the development of a multispectral image labeling system with emphasis on Unmanned Ground Vehicles(UGVs). UGVs operating in unstructured environments face significant problems detecting viable paths when LIDAR is the sole source for perception. Promising advances in computer vision and machine learning has shown that multispectral imagery can be effective at detecting materials in unstructured environments [1][2][3][4][5][6]. This thesis seeks to extend previous work[6][7] by performing pixel level classification with multispectral features and texture. First the images are spatially registered to create a multispectral image cube. Visual, near infrared, shortwave infrared, and visible/near infrared polarimetric data are considered. The aligned images are then used to extract features which are fed to machine learning algorithms. The class list includes common materials present in rural and urban scenes such as vehicles, standing water, various forms of vegetation, and concrete. Experiments are conducted to explore the data requirement for a desired performance and the selection of a hyper-parameter for the textural features. A complete system is demonstrated, progressing from the data collection and labeling to the analysis of the classifier performance. / Master of Science