Differential fitness of Eucalyptus defense phenotypes under altered nutrient and light conditions

Producing defensive chemicals is a cost for a plant. Scientists have hypothesized that there is always a trade-off between investment in chemical defence and plant physiological and developmental growth processes. It has been proposed that plants growing under high resource availability should use their carbon budget for plant growth rather than defence and that when plants are growing under resource-limited environmental conditions plants use their available carbon budget for the differentiation processes such as the production of defensive chemicals, rather than plant growth. Eucalyptus is the dominant genus of trees in Australian forests and their leaves are the main food source for many herbivores including insects and some arboreal marsupials. However, trees from the genus Eucalyptus possess a complex mixture of plant secondary metabolites (PSM), including formylated phloroglucinol compounds such as sideroxylonal, and a range of water-soluble phenolics. These compounds vary qualitatively and quantitatively between species and quantitatively within species. These plants are extensively studied for the great chemical variation they possess. However, few experiments have been conducted to test for the existence of trade-offs between growth and defence in these plants. The defensive chemistry of Eucalyptus species is mainly constitutively determined and phenotypic plasticity across the environmental variation is less well understood. I aimed to find out under which environmental circumstances this proposed trade-off will take place in Eucalyptus and also the nature of such trade-offs, under different conditions of light and nutrient availability. Eucalyptus melliodora and Eucalyptus camaldulensis seeds were grown under three different light conditions and E. melliodora seedlings were grown under two nutrient conditions and changes in growth parameters and sideroxylonal and total phenolic concentrations of seedlings were observed. Plants under different light and nutrient treatments varied greatly in their growth parameters and foliar PSM concentrations as well. Plants that were grown under higher light levels contained more sideroxylonal and more total phenolics than plants under low light conditions. Plants grown under higher nutrient levels possessed higher sideroxylonal but lower total phenolics compared to low nutrient plants. However, no trade-offs were identified between growth parameters and defensive chemical concentrations under any environmental conditions. Contrary to expectations, positive relationships between growth and concentrations of sideroxylonal were identified between and within many environmental treatments

REVIEWS TO RATING CONVERSION AND ANALYSIS USING MACHINE LEARNING TECHNIQUES

With the advent of technology in recent years, people depend more on online reviews to purchase a product. It is hard to determine whether the product is good or bad from hundreds of mixed reviews. Also, it is very time-consuming to read many reviews. So, opinion mining of reviews is necessary. The main aim of this project is to convert the reviews of a product into a rating and to evaluate the ratings using machine learning algorithms such as Naïve Bayes and Support Vector Machine. In the process of converting the reviews to a rating, score words are created using SentiWordNet and transformed into seven categories from highly positive to highly negative

Evaluating the Impact of Land Use Changes, Drivers of TMDL Development, and Green Infrastructure on Stream Impairments

Despite the water quality improvements and regulatory advancements over the last 50 years since the enactment of the Clean Water Act, water bodies within the United States are still impaired for a broad range of contaminants from non-point source pollution. Improving watershed management approaches to meet this challenge will require a greater understanding of (1) how changes within a watershed, such as changing land use, impact stream water quality, (2) what influence socioeconomic, spatial and political factors may have on the progress towards meeting water quality goals, such as those set within Total Maximum Daily Loads (TMDLs), and (3) how specific best management practices can be designed to address water body impairments. First, land use within a watershed is known to have a direct impact on downstream water quality; however, temporal dynamics of these relationships are ill-defined. This is an important gap as management approaches are largely compartmentalized among land use types. Additionally, while management plans can span several decades, the impact of land use changes on water quality is often overlooked. Therefore, this dissertation evaluates land-use changes and their relationship to discharge and water quality trends at stream gages across the U.S. Second, the TMDL program is the primary regulatory lever in the U.S. for addressing non-point source pollution, but its implementation has been uneven across states. This could be due to the diverse socioeconomic, spatial, and political factors of each state. This dissertation therefore seeks to define the influence of these factors on indicators of TMDL progress. Finally, at the site level, management actions to meet regulatory permits include the use of green stormwater infrastructure to capture, treat, and infiltrate runoff at the source. One of the largest sources of impairments in the TMDL program is temperature; however, it is unclear the degree to which green stormwater infrastructure in series mitigates runoff temperatures during summer storms. To address this gap, this dissertation analyzes the temperature mitigation potential of interconnected green infrastructure practices through field observations. Altogether, the outcomes of this dissertation help to advance our understanding of how watershed planning, regulatory, and engineering actions affect downstream water quality

Integrated Access and Backhaul for 5G and Beyond (6G)

Enabling network densification to support coverage-limited millimeter wave (mmWave) frequencies is one of the main requirements for 5G and beyond. It is challenging to connect a high number of base stations (BSs) to the core network via a transport network. Although fiber provides high-rate reliable backhaul links, it requires a noteworthy investment for trenching and installation, and could also take a considerable deployment time. Wireless backhaul, on the other hand, enables fast installation and flexibility, at the cost of data rate and sensitivity to environmental effects. For these reasons, fiber and wireless backhaul have been the dominant backhaul technologies for decades. Integrated access and backhaul (IAB), where along with celluar access services a part of the spectrum available is used to backhaul, is a promising wireless solution for backhauling in 5G and beyond. To this end, in this thesis we evaluate, analyze and optimize IAB networks from various perspectives. Specifically, we analyze IAB networks and develop effective algorithms to improve service coverage probability. In contrast to fiber-connected setups, an IAB network may be affected by, e.g., blockage, tree foliage, and rain loss. Thus, a variety of aspects such as the effects of tree foliage, rain loss, and blocking are evaluated and the network performance when part of the network being non-IAB backhauled is analysed. Furthermore, we evaluate the effect of deployment optimization on the performance of IAB networks.First, in Paper A, we introduce and analyze IAB as an enabler for network densification. Then, we study the IAB network from different aspects of mmWave-based communications: We study the network performance for both urban and rural areas considering the impacts of blockage, tree foliage, and rain. Furthermore, performance comparisons are made between IAB and networks of which all or part of small BSs are fiber-connected. Following the analysis, it is observed that IAB may be a good backhauling solution with high flexibility and low time-to-market. The second part of the thesis focuses on improving the service coverage probability by carrying out topology optimization in IAB networks focusing on mmWave communication for different parameters, such as blockage, tree foliage, and antenna gain. In Paper B, we study topology optimization and routing in IAB networks in different perspectives. Thereby, we design efficient Genetic algorithm (GA)-based methods for IAB node distribution and non-IAB backhaul link placement. Furthermore, we study the effect of routing in the cases with temporal blockages. Finally, we briefly study the recent standardization developments, i.e., 3GPP Rel-16 as well as the\ua0Rel-17 discussions on routing. As the results show, with a proper planning on network deployment, IAB is an attractive solution to densify the networks for 5G and beyond. Finally, we focus on improving the performance of IAB networks with constrained deployment optimization. In Paper C, we consider various IAB network models while presenting different algorithms for constrained deployment optimization. Here, the constraints are coming from either inter-IAB distance limitations or geographical restrictions. As we show, proper network planning can considerably improve service coverage probability of IAB networks with deployment constraints

Orion+: Automated Problem Diagnosis in Computing Systems by Mining Metric Data

Nowadays, distributed systems are a necessity of almost all big enterprises. It is a programmers nightmare to encounter a bug which causes failures in the system and leads to a crash on such a large infrastructure. With the ever increasing code sizes and processing needs, a tool is required that is able to assist a programmer in figuring out potential causes of a bug and minimizing time taken for debugging, hence rectifying it quickly. We present our solution Orion+, which compares the system metrics at various levels, namely, hardware, OS, middleware and application layer. It then makes use of the association information provided by the stack traces of the normal and abnormal runs to narrow down the specified buggy code region to a particular sequence of function calls that contain the bug or are most affected by the bug. We benchmarked our work against already established bugs in open source software which have been fixed and find that Orion+ is able to provide root cause analysis for all the benchmark bugs

A rare case report on cauda equina syndrome

Cauda Equina Syndrome (CES) is a rare but serious neurologic condition in which neurological dysfunction affects the lumbar and sacral nerve roots within the vertebral canal. CES is a clinical entity consisting of low back ache, bilateral leg pain with motor and sensory deficits, genitourinary dysfunction, saddle anaesthesia and faecal incontinence. It is a rare condition with a prevalence in the general population estimated between 1:100000 and 1:33000. The presentation of CES may vary, especially in the early stages of compression. Magnetic Resonance Imaging (MRI) is the accepted gold standard modality of choice for diagnosing CES which identifies potential mimics such as aortic dissection or spinal infarction. Here we discuss a rare and unique case of CES with atypical presentation, knowledge of which is essential for early diagnosis, treatment and prevention of permanent neurological dysfunction