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Source Origins of Hunter-Harvested Waterfowl in Arkansas and Louisiana
No full textUnderstanding variability in breeding origins of harvested waterfowl is important for effective population management and regional conservation. Band-recovery data are often used to estimate harvest derivation and inform resource allocation for cross-seasonal conservation. However, uneven spatial and temporal banding effort across species\u27 breeding ranges may result in an incomplete understanding of summer origins and recruitment, particularly if portions of the breeding range are inaccessible. Analysis of stable-hydrogen isotope ratios in duck feathers (δ2Hf) provides an alternative method for identifying source origins of unmarked populations since environmental deuterium values follow a predictable latitudinal gradient across North America. I collected \u3e1800 feather samples from cohorts of male and female adult and juvenile blue-winged teal (Spatula discors), gadwall (Mareca strepera), green-winged teal (Anas crecca carolinensis), lesser scaup (Aythya affinis), mallards (Anas platyrhynchos), and northern pintail (Anas acuta) harvested across Louisiana during the 2022–2023 waterfowl hunting season, and \u3e2200 samples during the 2023–2024 season. In Arkansas, I collected \u3e800 samples from green-winged teal and mallards in the 2022–2023 season, and \u3e900 in the 2023–2024 season. In Chapter 1, I evaluated how δ2Hf and inferred geographic origins differed by sex, age, harvest region, and harvest date across two years for each species. While I found statistical differences in δ2Hf across each parameter, these differences were not large enough to detect interpretable differences in inferred origins. However, results revealed that high proportions of individuals likely originated from more northern geographies within their breeding range. In Chapter 2, I paired δ2Hf sampling with informative Bayesian priors (spatial relative abundance and proportional band returns), to compare the origins of waterfowl harvested in Louisiana to geographic areas of banding effort and band recovery. I found that while there is variation by species, many harvested individuals originated from latitudes underrepresented by long-term banding efforts. Together, my results suggest that while pre-season banding efforts are essential for informing population vital rates, they may not completely represent source origins if individuals move post-hatch or after molt prior to capture. Additionally, these findings improve our understanding of migratory connectivity and could aid strategic conservation initiatives targeting specific breeding geographies
The Operational Performance of Buildings in a Humid Subtropical Climate: Insights from Empirical Data and Assessment Models
Get PDFThis thesis evaluates the operational performance of residential and non-residential buildings in a humid subtropical climate, emphasizing Indoor Environmental Quality (IEQ) and energy performance through empirical data and assessment models. Motivated by the increasing need for integrated sustainability evaluations, this study combines a systematic review with multi-method field investigations to advance understanding in this domain. The systematic review critically analyzed 99 case study articles, identifying dominant IEQ assessment methodologies and highlighting methodological inconsistencies that hinder cross-study comparability. Emerging computational approaches, although promising, remain underutilized. The review advocates for standardized, climate-responsive, and feedback-oriented evaluation frameworks. Field investigations assessed IEQ and energy performance across residential college lounges, public assembly buildings, and residential college buildings in Louisiana.
An extended IEQ model integrating subjective, objective, and energy performance components was developed, providing a holistic tool for facility management and sustainability planning. Findings underscore the importance of continuous operational evaluations, targeted interventions, and climate-sensitive strategies to enhance occupant comfort and building sustainability. This research contributes to the advancement of operational performance assessment by integrating occupant well-being and energy efficiency considerations.
It also lays the groundwork for developing an operational sustainability index through a proposed shift from additive to product-based integration of IEQ and energy performance metrics, offering new insights for the green certification industry and sustainable building practices in humid subtropical climates
Variation in Hydraulic Vulnerability Among Tree Species in a Bottomland Hardwood Forest
No full textDrought is a threat to forests globally, with severe impacts on ecosystem structure and function predicted this century. Tree hydraulic traits are useful predictors of drought responses. However, hydraulic-trait data remain limited in floodplain ecosystems like bottomland hardwood (BLH) forests of the Southeastern U.S.A. These systems may be especially vulnerable to drought due to trade-offs between flood- and drought tolerance, yet hydraulic diversity within BLH tree species remains poorly understood. Empirical assessments of hydraulic traits, trade-offs, and alignment with drought tolerance indices in this ecosystem can help predict BLH forests response to future drought.
To address this, I measured hydraulic traits for 20 species in a Louisiana BLH forest, including the water potential at 50% loss of maximum stem hydraulic conductivity (P50), minimum leaf water potential (Ѱmin), Ѱmin hydraulic safety margin (HSMѰmin), and turgor loss point hydraulic safety margin (HSMTLP). I tested the following hypotheses: (1) BLH species exhibit less negative P50 values than upland-temperate species; (2) HSMѰmin values are like those observed in upland-forests globally; (3) species with more negative P50 and wider HSMѰmin have higher drought tolerance scores and slower growth-rates; and (4) HSMѰmin is correlated with HSMTLP.
Results revealed wide interspecific variation in hydraulic traits (P50: -4.6 to -1.09 MPa, Ѱmin: -3.60 to -1.23 MPa, HSMѰmin: -1.4 to 1.9 MPa, HSMTLP: -0.88 to 2.6 MPa). Contrary to expectations, BLH species showed similar P50 values to upland-temperate species. While the species-level average HSMѰmin was narrow (-0.11 MPa), it was consistent with other forest biomes, indicating potential drought vulnerability. However, high community-level variability (0.61 MPa, i.e., the standard deviation of community-weighted HSMѰmin) suggests that species diversity may improve the forest potential to buffer against drought. No significant relationship between hydraulic traits and drought tolerance scores, likely reflecting the influence of other traits such as deep root or deciduousness. No fast-slow trade-off was detected possibly due to the limitations in growth-rate classification. Lastly, HSMѰmin and HSMTLP were strongly correlated, primarily driven by P50. Despite frequent water availability, the BLH forest exhibits hydraulic traits comparable to upland systems, and high hydraulic diversity may enhance the forest\u27s ability to withstand water stress
Soft Hexapod Robot with Tendon-Driven Continuum Legs for Internal Infrastructure Inspection
No full textThe need for robotic systems capable of operating in confined, hazardous, or complex environments has driven interest in soft and legged platforms for industrial inspection and structural integrity assessment. This thesis presents the design and fabrication of a tentacle-like, soft-legged hexapod robot, which uses six cable-stiffened, pre-curved, tendon-driven continuum robot (TDCR) legs. These biologically inspired legs are designed to offer a balance between compliance and control, enabling the robot to navigate unstructured terrains and potentially grasp cylindrical structures such as pipes. The design phase involved the development and comparison of multiple leg geometries using CAD modeling and finite element analysis (FEA) to optimize mechanical performance. The final leg design was fabricated using a combination of thermoplastic polyurethane (TPU) for flexibility and polylactic acid (PLA) for structural rigidity. Additional mechanical innovations, including tip-mounted tendon tensioners inspired by guitar tuners, were implemented to control leg stiffness. While the hexapod system was under development, a stiffness characterization study was conducted on a separate 2D tendon-driven robot. A UR5 robotic arm with a custom voltage-based force sensor applied precise displacements while a 3D camera system tracked deformation. Tests were performed under different cable configurations, including actuation-only and various stiffnesses of cosine cable patterns. The results — force-displacement curves, stiffness slopes, and hysteresis loop areas — provided valuable insights into how tendon routing and cable pretension influence stiffness behavior. These experimental methods and findings serve as a reference framework for future stiffness evaluation on the hexapod robot. This work demonstrates a novel approach to integrating stiffness modulation into soft-legged robots and sets the stage for developing fully untethered, terrain-adaptive inspection systems. The hexapod’s modular design, mechanical flexibility, and the foundation laid by earlier stiffness studies contribute to the broader field of soft robotics, especially in applications requiring compliant locomotion and safe interaction with sensitive or irregular environments
EFFICIENT SMALL TOOL DETECTION IN CONSTRUCTION VIA LIGHTWEIGHT DEEP NEURAL NETWORKS
Get PDFConstruction sites are dynamic and inherently hazardous environments, where small hand tools—although essential—pose serious safety risks due to their frequent use, portability, and tendency to be misplaced or dropped. This study introduces a novel and lightweight deep learning-based architecture, Lightweight Small Tool Detection (LSTD), specifically designed for fast detection of small tools in unstructured and challenging construction environments. Recognizing that small object detection remains a persistent limitation in existing computer vision models, particularly under poor lighting or cluttered backgrounds, LSTD integrates advanced modules for enhanced feature extraction, fusion, and classification. It achieves notable improvements in accuracy, recall, and computational efficiency compared to existing methods. The core architecture of LSTD is built upon YOLOv5 but is augmented with three significant components: Dynamic Feature Extraction (DFE), Integrated Feature Fusion (IFF), and Accurate Separated Head (ASH). These modules are tailored to improve the detection of small tools by capturing fine-grained details with fewer parameters. The DFE module focuses on preserving critical visual cues despite the limited size of target objects, while the IFF module ensures robust multi-scale feature representation without excessive computation. The ASH module decouples regression and classification to enhance convergence and precision. Together, these innovations lead to a substantial 73% reduction in model parameters and a 28% drop in computational load, while achieving a mean Average Precision (mAP) of 87.3%. To evaluate the robustness and generalizability of the LSTD model, the research utilized a comprehensive dataset of over 34,700 images of 12 commonly used construction tools. The dataset incorporated diverse conditions such as occlusions, varying illumination levels, and realistic construction site backgrounds. Experiments included ablation studies, comparisons with state-of-the-art models, and stress testing under misty and low-light scenarios. The LSTD model consistently outperformed other lightweight detectors like YOLOv6-Small, YOLOv7-Tiny,and YOLOv8-Small, demonstrating high detection accuracy across different environmental challenges. Moreover, the integration of Convolutional Block Attention Module (CBAM) proved critical in enabling the model to effectively distinguish tools from visually complex backgrounds. Ultimately, this research contributes a compact yet powerful detection model that supports real-time applications on edge devices, paving the way for smarter and safer construction practices. By enabling accurate detection of misplaced, dropped, or unauthorized tools, LSTD offers a proactive mechanism to reduce tripping hazards, improve inventory tracking, and support robotic monitoring systems. Its lightweight design makes it particularly suited for deployment in mobile platforms and embedded construction site monitoring systems. Future work may explore edge implementation, integration with autonomous robotics, and real-time adaptive learning in dynamic construction environments. This work marks a significant step forward in aligning modern computer vision technologies with the urgent safety needs of the construction industry
A novel disinfection technology for onsite wastewater treatment using UV-LEDs
No full textThe edaphic characteristics of Louisiana particularly in Tangipahoa parish make the suitability of onsite wastewater treatment systems a challenge. Sewage runoff through ditches from failed aerobic treatment units (ATUs) during intense rainfall impacting nearby water bodies. The Yellow Water and the Natalbany Rivers in the Tangipahoa parish are such rivers that have been impacted by fecal contamination posing potential risks to humans and the aquatic biota. Germicidal ultraviolet (UVC) light-emitting diodes (LEDs) technology offers exciting advancements for water and wastewater disinfection. Although UV disinfection of ATU effluent is a promising solution, cellular repair is triggered which includes dark, or photo-repair post-UVC exposure. A novel disinfection technology for onsite treatment systems has been assembled. The reactor was tested for UVC doses achieved using chemical actinometry (potassium ferrioxalate) and with over 5-log reduction using a fluence of 15.2 mJ/cm2 and rate constant of 0.299 ±0.037 cm2/mJ. Disinfection experiments were performed under varied turbid conditions to test the effects of full and pulsed illumination (50% and 25% duty cycle) and a flow-through process using Escherichia coli ATCC 15597. Particle size and type influenced UV disinfection efficiency. The results indicated a decline in disinfection efficiency, as turbidity (amount of silica particles) increased with respect to the particle sizes. Further, photo-repair experiments were performed obtaining the highest survival fraction of 2.159 ± 0.67 % and SUVA at 3.6 NTU suggesting high humic or aromatic hydrophobic matter which absorbs photons and aggregates out of solution providing a shield and source of attachment for microorganisms. Micro-toxicity and residual chlorine experiments were performed obtaining minimal toxic levels (peak level: 3.61%) and residual chlorine levels of ~0.5 mg/L. Additionally, the novel UV/Cl technology addresses the drawbacks of traditional ATU designs with a decrease in thermotolerant coliform count to ~ 2 log when the retention time and water depth within the reactor were optimized. Absorption coefficient at 278 nm obtained a 13.3% higher fluence per unit power. Also, the UV-LED reactor made up of 101.6 cm long polypropylene plastic (ADR-002) was the most energy efficient. Smart reactor design with optimum water depth might suppress turbidity impact on UV disinfection efficiency
Identification of Pathogenic Vibrio Species Associated with Eastern Oyster Crassostrea virginica Larval Mortality Events and Assessment of Potential Therapeutic Approach
No full textAs the aquaculture industry continues to grow it is imperative to identify potential pathogens and find treatments for stock diseases that are both effective and environmentally friendly. The aquaculture of Eastern oysters is plagued by outbreaks of vibriosis during summer months and hatcheries are at risk of larval mortality if pathogenic Vibrio concentrations get too high. Given the success of Bdellovibrio and like organisms (BALOs) in treating V. parahaemolyticus infections in shrimp, we investigated whether BALOs could reduce larval oyster mortality. We collected water samples during two larval mortality events of the Eastern oyster, Crassostrea virginica, in July, 2022, and August, 2024 to isolate Vibrio spp. We purified these isolates and classified them using 16S rDNA sequencing techniques at the LSU Genomics Core Lab. Multiple Vibrio isolates from the two mortality events were selected for pathogenicity screening, LD50 determination, and BALOs treatment trials based on the sequencing results and a literature review. Two additional Vibrio strains from a previous collection stored in our lab were also included in the studies. These selected isolates belonged to V. tubiashii, V. parahaemolyticus, and V. cidicii, V. harveyi, V. azureus, and P. chinensis. V. cidicii isolates LT28 and SW1-15 stood out as highly pathogenic to larvae. Larval mortality was reduced when Vibrio spp. was treated with BALOs. In two pathogenicity studies, LT28 caused 84.17% and 100% mortality, respectively. V. tubiashii (BS10 isolate) was the most pathogenic Vibrio in LD50 assays with a 24-hour LD50 of 2.13 ± 0.3 x 104 CFU/mL. Other Vibrio spp. did not surpass 6.07 x 104 CFU/mL in 24-hour LD50 studies. In challenge studies, BALOs treatment reduced V. cidicii (LT28) mortalities by 18.98% over 48 hours (p\u3c 0.05). V. cidicii (SW1-15) also responded positively to BALOs treatment; mortality was reduced by 18.38% and 27.67% over 24 and 48 hours, respectively (p\u3c 0.05 and p\u3c 0.005 respectively). Our studies indicate the potential for BALOs to be used as a probiotic additive for larval oyster systems in the Northern Gulf of America
Protecting Cultural Heritage in a Changing Climate: A Risk Assessment Model for Galleries, Libraries, Archives, and Museums in Florida, United States
No full textThe aim of this research is to develop a climate threat risk assessment scale for galleries, libraries, archives, and museums within the State of Florida. Current research neglects the localized impact of tropical cyclones, inland flash flooding, and exposure to SLR on cultural institutions. Tropical cyclone events bring in flooding, intense wind speeds, and power outages which affect these institutions. Tropical cyclone data from the National Hurricane Center are used to represent historical wind occurrence. Finally, flash flood warning data are used to represent the flooding likelihood in each county. Each threat is assessed individually across Florida counties. The range of possible values forms a total scale, which is then translated into an academic grade (4.0). Each individual grade is then added together to provide a combined threat scale. Understanding how each of these threats exist within a space can better inform these institutions on how to prepare in a changing climate. These institutions often exist in regions where they can act as social hubs post an event like a hurricane where people can go for resources. Understanding their role alongside understanding their risk is incredibly important. This research aims to tackle the risk that these cultural institutions in face of various climate risk
Cesium Lead Bromide-Coated Fiber Bragg Grating Sensors for Gamma Radiation Environments
No full textThis study presents the development and characterization of CsPbBr3 (CPB) and CPB-poly(methyl methacrylate) (CPB-PMMA) composite coatings on Fiber Bragg Grating (FBGs)-based sensors for high-sensitivity gamma radiation sensing. CPB precipitates were synthesized using a solvent-based method and uniformly deposited onto the FBGs. The incorporation of PMMA into the CPB matrix enhanced both mechanical stability and adhesion to the FBG surface. Spectral analysis revealed significant Bragg wavelength shifts in response to gamma radiation exposures, indicating strain-optic variations induced by radiation-matter interactions. Comparative investigations between uncoated, CPB-coated, and CPB-PMMA-coated FBGs confirmed that the coatings significantly enhance strain sensitivity and stability. The incorporation of PMMA modified the mechanical response, influencing residual stress and strain attenuation. The advantage of using fiber optic sensors includes the ability to enable multiplexed sensing across large areas, immunity to electromagnetic interference (EMI), and operability in high-temperature environments. Additionally, CPB and CPB-PMMA coatings demonstrated enhanced sensitivity under UV exposure, further highlighting their potential for advanced optical sensing applications in both radiation and UV-intensive environments. These results demonstrate the potential of CPB-based coatings for radiation monitoring in extreme environments, including in nuclear facilities, space missions, and near medical instruments using radiation sources. The findings provide a foundation for further optimization of perovskite-polymer composites to enhance sensor performance and long-term durability in radiation-intensive applications
