Laser capture microdissection (LCM) is a versatile computer-assisted dissection method that permits collection of tissue samples with a remarkable level of anatomical resolution. LCM's application to the study of human brain pathology is growing, although it is still relatively underutilized, compared with other areas of research. The present study examined factors that affect the utility of LCM, as performed with an Arcturus Veritas, in the study of gene expression in the human brain using frozen tissue sections. LCM performance was ascertained by determining cell capture efficiency and the quality of RNA extracted from human brain tissue under varying conditions. Among these, the relative humidity of the laboratory where tissue sections are stained, handled, and submitted to LCM had a profound effect on the performance of the instrument and on the quality of RNA extracted from tissue sections. Low relative humidity in the laboratory, i.e., 6-23%, was conducive to little or no degradation of RNA extracted from tissue following staining and fixation and to high capture efficiency by the LCM instrument. LCM settings were optimized as described herein to permit the selective capture of astrocytes, oligodendrocytes, and noradrenergic neurons from tissue sections containing the human locus coeruleus, as determined by the gene expression of cell-specific markers. With due regard for specific limitations, LCM can be used to evaluate the molecular pathology of individual cell types in post-mortem human brain.

Thesis. 1977. Ph.D.--Massachusetts Institute of Technology. Dept. of Meteorology. / Microfiche copy available in Archives and Science. / Vita. / Bibliography : leaves 290-293. / Ph.D.

The construction industry is massive but not so advanced in adapting and utilizing technology. Sensors and sensing technology are critical elements that can enhance the digitalization of the construction industry. The need for low-cost sensors is rapidly increasing as the industry steps into the construction 4.0 phase. This research is an exploratory study on the potential of low-cost sensors, concentrating on the temperature and humidity sensors in the production stage of construction. The methodology used in the research is a qualitative approach consisting of literature review and interviews. The literature review identified the state of art of low-cost temperature and humidity sensors. From interviews, the constraints, adaptation factors were identified. The potential application of the low-cost temperature and humidity sensors were identified from the literatures and interviews. The conclusion of the research was that there is a knowledge gap in the field of low-cost temperature and humidity sensors. Furthermore, there is lack of adaptation of sensor technology in the production stage of the construction industry even though it has potential to improve the productivity and quality.

Since methyl bromide is an ozone depleting substance, there is a significant need to find effective alternative compounds to control mite infestations on dry cured hams. Therefore, the objective of this study was to determine the most effective relative humidity and/or temperature to minimize mite reproduction and mold growth on dry cured hams in untreated and food grade ingredient infused nets. Mites on ham slices in untreated nets were reduced from the initial inoculum level of 50 mites per ham slice when exposed to 85% RH at 24, 28, and 32°C. Results indicated that hams should be stored at 85% RH or greater to minimize mite reproduction when xanthan gum and propylene glycol infused nets are used. Nets infused with carrageenan, propylene glycol alginate, and propylene glycol, completely inhibited mite reproduction at 85% RH and were effective at controlling mold growth.

With the growing demand of renewable wind energy, logistics and operations associated with a wind turbine makes for compelling study and analysis. The study entails understanding of transporting a wind turbine nacelle from Denmark till Australia. The methods of transporting the wind turbine nacelle and the modes of transportation that are currently in use have been studied. Factors that are detrimental to efficient shipping have been reviewed with existing literature and analysed for a wind turbine nacelle. The two key factors that influence transportation namely humidity and G-force have been identified. Simple and cost effective solutions such as use of insulation material, use of desiccants to overcome the effects of humidity, use of shock absorber pallets to reduce shock and vibration have been proposed. For the damages caused to a wind turbine nacelle due to random causes, some suggestions to prevent such damages have also been provided.

The study was performed at Billerudkorsnäs at the section Box Lab which offers knowledge and solutions for packaging. Paper that can be used to create packaging interacts with the surrounding environment, but has only been tested for a few climates. This thesis aims to investigate more climates and see how paper is affected by humidity and temperature and try to determine the cause of the results. The methods used to measure this was primary tensile test and moisture content analysis but also a test to evaluate creep was performed in climates with high humidity. From this, the mechanical properties of the paper were calculated. The test was performed in a climate chamber and the choice of methods was limited by what could be performed in the climate chamber. The materials tested were chosen to give a good representation of what is commonly used in the containerboard business. The climates for testing were selected from the ability of the climate chamber as well as interesting climates for the company. The results show that the papers are weakest at high RH, but the results indicate that the temperature solely impacts the properties of the paper. The highest moisture content does not necessarily mean the lowest value for a chosen property. The causes for the results are not clear since the patterns found are not bound to a certain quality but rather to paper in general. Therefore, more research on the area is suggested to try to determine what causes the material to react to temperature.

Yes / Sensing concrete has the capability to sense its condition and environmental changes, including stress (or force), strain (or deformation), crack, damage, temperature and humidity through incorporating functional fillers. Sensing concrete has recently attracted major research interests, aiming to produce smart infrastructures with elegantly integrated health monitoring abilities. In addition to having highly improved mechanical properties, sensing concrete has multifunctional properties, such as improved ductility, durability, resistance to impact, and most importantly self-health monitoring due to its electrical conductivity capability, allowing damage detection without the need of an external grid of sensors. This tutorial will provide an overview of sensing concrete, with attentions to its principles, properties, and applications. It concludes with an outline of some future opportunities and challenges in the application of sensing concrete in construction industry. / National Science Foundation of China (51978127 and 51908103), the China Postdoctoral Science Fundation (2019M651116) and the Fundamental Research Funds for the Central Universities in China (DUT18GJ203). / National Science Foundation of China (NSFC) (Nos. 51978127 and 51908103), the China Postdoctoral Science Foundation (No. 2019M651116), and the Fundamental Research Funds for the Central Universities in China (No. DUT18GJ203).

Humidity responsive materials sense, respond and adapt to the environment in response to changes in humidity. An important potential application of this material technology is the creation of “smart textiles” that facilitate moisture management in clothing. Materials used for clothing must have characteristics such as elasticity, washability and abrasion resistance, but smart textiles that have been demonstrated to date lack these characteristics. It is the need for improved materials that motivated the present study. Here, we developed spore-cellulose nanofiber composites (CNF) and spore-polyurethane (PU) composites, which are two biologically-based humidity-responsive materials that derive their high energy density humidity responsiveness from spores. We demonstrate the use of these hygromorphing materials for smart textiles by coupling the responsive materials to fabrics to create a textile that vents in humid environments and closes in dry environments. This material can be used in clothing to enable fast evaporation of sweat from the skin and improved comfort. Because the spore-CNF composite is not elastic stretchy or water resistant and therefore is undesirable for real world clothing applications, we also developed a stretchy spore-PU composite that is simultaneously humidity responsive, stretchy and water and abrasion resistant. In addition, we fabricated spore-PU based hygromorphing fabric bilayer actuators to create venting smart textiles with adaptive permeability properties that are compatible with clothing applications. These smart fabrics have the potential to improve the functionality and utility of garments, especially those intended for athleticwear, workwear and protective garments.

This thesis estimates the ecosystem evaporation response to two forms of aridity: (1) atmospheric aridity in the form of vapor pressure deficit (Chapter 2), and (2) soil moisture aridity (Chapter 4). We also develop new methods to estimate the ecosystem response to aridity. For the response to atmospheric aridity (Chapter 2), we build a theoretical framework that allows us to derive an analytical expression for the ecosystem evaporation response to vapor pressure deficit with all environmental conditions held fixed (Chapter 2). For the response to soil moisture aridity, we develop a method to estimate the response of evaporation to interventions on soil moisture using only passive data generated in a simulated reality (Chapter 4). To guide the development of this data-driven approach, we review and analyze causal inference’s applications in the Earth system, considering generic scenarios that are applicable to the land-atmosphere system as well as many other subdomains of the Earth system (Chapter 3). The subsections below elaborate more on the contents of each Chapter. Chapter 2: When does vapor pressure deficit drive or reduce evaporation? Increasingvapor pressure deficit increases atmospheric demand for water. While increased evaporation in response to increased atmospheric demand seems intuitive, plants are capable of reducing evaporation in response to increased vapor pressure deficit by closing their stomata. We examine which effect dominates the response to increasing vapor pressure deficit: atmospheric demand and increases in evaporation, or plant response (stomata closure) and decreases in evaporation. We use Penman-Monteith, combined with semi-empirical optimal stomatal regulation theory and underlying water use efficiency, to develop a theoretical framework for assessing evaporation response to vapor pressure deficit. The theory suggests that depending on the environment and plant characteristics, evaporation response to increasing vapor pressure deficit can vary from strongly decreasing to increasing, highlighting the diversity of plant water regulation strategies. The evaporation response varies due to: 1) climate, with tropical and temperate climates more likely to exhibit a positive evaporation response to increasing vapor pressure deficit than boreal and arctic climates; 2) photosynthesis strategy, with C3 plants more likely to exhibit a positive evaporation response than C4 plants; and 3) plant type, with crops more likely to exhibit a positive evaporation response, and shrubs and gymniosperm trees more likely to exhibit a negative evaporation response. These results, derived from previous literature connecting plant parameters to plant and climate characteristics, highlight the utility of our simplified framework for understanding complex land atmosphere systems in terms of idealized scenarios in which evaporation responds to vapor pressure deficit only. This response is otherwise challenging to assess in an environment where many processes co-evolve together. Chapter 3: Causal inference for process understanding in Earth sciences There is growinginterest in the study of causal methods in the Earth sciences. However, most applications have focused on causal discovery, i.e. inferring the causal relationships and causal structure from data. This paper instead examines causality through the lens of causal inference and how expert-defined causal graphs, a fundamental from causal theory, can be used to clarify assumptions, identify tractable problems, and aid interpretation of results and their causality in Earth science research. We apply causal theory to generic graphs of the Earth system to identify where causal inference may be most tractable and useful to address problems in Earth science, and avoid potentially incorrect conclusions. Specifically, causal inference may be useful when: (1) the effect of interest is only causally affected by the observed portion of the state space; or: (2) the cause of interest can be assumed to be independent of the evolution of the system’s state; or: (3) the state space of the system is reconstructable from lagged observations of the system. However, we also highlight through examples that causal graphs can be used to explicitly define and communicate assumptions and hypotheses, and help to structure analyses, even if causal inference is ultimately challenging given the data availability, limitations and uncertainties. Chapter 4: Estimating the ecosystem evaporation response to interventions on soilmoisture: confounding and causal modeling in a simulated world We build a simulated reality using a numerical model designed to represent feedbacks in the land atmosphere system, and observational boundary conditions that are confounded by the real world’s underlying climate state. Although no simulation can reproduce the real land-atmosphere system’s complexity and any simulation’s predictions will deviate from the real world, this simulated reality does share the same characteristics of the real world that make causal inference challenging: it contains feedbacks, non-linearity, and the real world’s confounding-induced covariations between boundary conditions. We use this simulated reality to estimate confounding’s impact on relationships between soil moisture and ecosystem evaporation, and also to validate a method for calculating ecosystem evaporation response to interventions on soil moisture from passive observations. We repeat this analysis at 12 sites spanning a range of humid and arid climates in western North American and Europe, and find that: • Confounding bias is largest at the more humid sites, and lower at the more arid sites where soil moisture limits evaporation and decouples the response from other environmental factors (Section 4.3.1). • At the more humid sites, bias due to confounding is of a larger magnitude than model specification bias, even when the specified model is a linear model applied to a known non-linear process. This highlights the importance of accounting for confounding. (Section4.3.1). • Statistically adjusting for potential sources of confounding improves causal estimates at the highly confounded sites without degrading causal estimates at arid, soil moisture-limited sites characterized by less confounding bias (Section 4.3.2). • The estimated causal effects appear to differentiate true variations in the causal effects across climates and ecosystems. (Section 4.3.2).

An optical fiber humidity sensor has been devised using a porous sol-gel silica (PSGS) coating as a transducer. Evanescent wave scattering (EWS) in the PSGS coating. PSGS particles are highly hydrophilic and have a strong tendency to absorb water molecules from the surrounding environment. The absorbed water molecules form a thin layer on the inner surface of the pores inside the porous silica and enhance EWS, from which an indicatory signal can be obtained. The humidity sensor presented in this thesis has a fast response, is reversible, low cost, and has a broad dynamic relative humidity range from 3.6?0-6% to 100% or humidity range from 1.2ppm to 30000ppm. Because of its multiple advantages, including immunity to electromagnetic interference, resistance to corrosive environments, and high sensitivity, this humidity sensor has various applications. In soil moisture sensing, this humidity sensor can avoid the interference caused by compounds in soil water. For electrical transformer moisture sensing, this humidity sensor can avoid the effect of electromagnetic fields.