Charaterizing soil properties and biogeochemical processes in a mountain peatland

Northern peatlands are important to the global carbon (C) and nitrogen (N) cycles. Peat profiles in Rocky Mountain areas commonly show complex stratigraphy with underlying and/or interbedded mineral sediments, referred to as stratified mineral horizons. Stratified mineral horizons usually have lower hydraulic conductivity and more electron acceptors, which influences biogeochemical processes. To study the effect of mineral sediments on pedological and biogeochemical processes, I conducted a field study and a microcosm study. The field study was located in a mountain peatland in the foothills of the Canadian Rocky Mountains with three different organic soil types: sedge peat/silty sediments/calcareous sediments (PMC), sedge peat/silty sediments/moss peat (PMP) and sedge peat/moss peat (PP). Soil samples were tested for spatial distribution of total organic C (TOC), total N (TN), pH, volumetric water content (θv), C and N cycling rates, C composition and microbial community structure. A microcosm study was designed to mimic climate warming conditions with four temperature-water table treatments: current temperature/current water table, higher temperature/current water table, current temperature/lower water table, and higher temperature/lower water table. In the microcosm study, PMC and PP soils were incubated for 28 days and tested for GHG emissions and concentrations, biogeochemical process rates, apparent enzyme activation energy (Ea) and bacterial community structure. In the field study, results indicated mineral sediments mainly affect pedological and biogeochemical processes in subsurface peat rather than surface peat. Mineral sediments affected the spatial distributions of total organic C (TOC), total N (TN), pH and volumetric water content (θv) via elevating the pH adjacent to calcareous sediments and slowing water infiltration to lower depths. The pH and θv further affected TOC and TN distribution by regulating organic matter decomposition during the peatland’s geomorphic history. At the same time, mineral sediments also affected C and N cycling processes, though depth had an even greater effect. The effect of mineral sediments on N cycling was mainly due to high pH from calcareous sediments, which promoted net nitrification but lowered net ammonification in the PMC. Moreover, mineral sediment mitigated the lag phase of N cycling in deeper layers. The effect of mineral sediments on C cycling was reflected in two aspects, geomorphic history and hydrological conditions. During the peatland’s geomorphic history, mineral horizons promoted decomposition by increasing pH and providing electron acceptors in overlying peat. Enhanced decomposition in the past resulted in more recalcitrant materials in peat at present. This, combined with physicochemical protection of C by mineral sediments, further restricted C mineralization in the PMP and PMC. Hydrologically, stratified mineral horizons slowed water infiltration and resulted in higher θv above the mineral horizon and lower θv below the mineral horizon. This restricted C mineralization in peat above mineral sediment and encouraged C mineralization in peat below mineral sediment in PMP. In addition, these factors also affected microbial community structure, with the highest Stress and Bacteria:Fungi ratio in peat above mineral sediment and different microbial community structure in peat below mineral sediments. In the microcosm study, I found that high temperature increased GHG emission and GHG concentration – especially at depth – in most samples. Soil types affected CO2 and N2O concentrations from subsurface horizons: PP had higher CO2 and N2O than PMC. Importantly, N2O concentration and production rates were affected by interaction of soil types and temperature near the water table: N2O production in PP was more enhanced by high temperature. This was possibly because PP had greater labile C and lower pH. In addition, compared with PP, the Ea for N2O generation in PMC was increased more by high temperature incubation and microbial community structures were quite different in the two soils, especially the lower relative abundance of copiotrophs in PMC. Overall, the findings highlight that stratified mineral sediment affected spatial distribution of key soil properties, which influenced biogeochemical processes in this mountain peatland. Elevated pH due to calcareous sediment promoted nitrification and C mineralization. In addition, stratified mineral sediment affected θv, which then affected microbial community structure and C mineralization. Under a warming climate, compared with a continuous peat profile, peat with mineral sediments tends to have less labile C and higher pH, which could potentially result in less CO2 and N2O emission and mitigate N2O production proximal to the water table

Improvement of random vibration theory site response analysis

Random Vibration Theory (RVT) site response analysis is a standard in seismic hazard analysis for nuclear facilities to compute the dynamic response of soil deposits. However, studies have shown that the RVT analysis predicts site amplification at natural site frequencies that are considerably larger than the time series (TS) analysis. The objectives of this research are to identify improvements to the current approaches used in RVT site response analysis and to incorporate these improvements so that the discrepancy between RVT and TS site amplification are reduced. This research first investigates a critical part of the RVT approach – the peak factor, defined as the peak to root-mean-square (rms) ratio of a signal. It is shown that by accounting for the statistical dependence between peaks, the peak factor model developed by Vanmarcke (1975) is superior to the model developed by Cartwright and Longuet-Higgins (1956) when applied to seismic site response analysis. The use of the Vanmarcke peak factor model reduces the RVT site amplification at the natural site frequencies and makes the RVT amplification more similar to the TS analysis. This research also investigates the duration used in the computation of the rms value from the Fourier Amplitude Spectrum. It is shown that by accounting for the influence of the dynamic site response on the duration of the oscillator response, the RVT analysis generally predicts site amplification within +/- 10% of TS analysis. To apply the modification of duration to RVT without the use of time series, a duration model is developed that empirically predicts the change of duration at the ground surface due to site response. In the last part of the research, the improved RVT approach, which utilizes the Vanmarcke (1975) peak factor and incorporates the change in duration due to site response, is applied to more complex and realistic shear wave velocity profiles and for strain-compatible properties associated with equivalent-linear analysis. The site amplification results indicate that the improved RVT site response analysis generally works well to reduce the discrepancy between RVT and TS amplification for a wide range of situations.Civil, Architectural, and Environmental Engineerin

Influência de características culturais na decisão de marketing: o caso de marcas chinesas de automóveis em Portugal e no Brasil

Dissertação de mestrado em Estudos Interculturais Português/Chinês: Tradução, Formação e Comunicação EmpresarialUma empresa que pretenda operar em mercados externos deve ter uma estratégia de marketing adequada para cada mercado-alvo, que considere as variáveis chave: produto, preço, canal de distribuição e promoção. O contexto do mercado-alvo é igualmente importante, com destaque para o ambiente cultural. Tomando como exemplo a marca de automóveis Chery, analisa-se a importância que as marcas chinesas dão ao contexto cultural e o que poderão fazer na altura de tomarem decisões de marketing internacional. Neste contexto, caracterizou-se em traços gerais o setor automóvel em Portugal e na China - incluindo o ambiente macro do mercado - comparando as preferências dos consumidores no momento de escolherem e comprarem automóvel. Considerando as teorias e análises expostas no primeiro e segundo capítulos, apontam-se as vantagens e desvantagens da marca para o mercado português, adaptações que deve fazer para atender à procura, bem como as diferenças e semelhanças entre o mercado português e o chinês. No final, são apresentadas algumas conclusões e sugestões às marcas chinesas que tenham interesse no mercado nacional, baseadas na experiência da Chery no Brasil.A company wishing to operate in foreign markets must have a proper marketing strategy for each target market, considering the 4 P’s of marketing: product, price, placing and promotion. Furthermore, the environment of the target market is also important, especially the cultural environment. Taking the Chinese automobile brand Chery as an example, we aim to analyse the importance of cultural environment for Chinese brands and what they can do to make proper decisions of international marketing. In this context, we will characterized, in a broad sense, the automobile sector in Portugal and China - including the macro market's environment - comparing consumer preferences when choosing and buying cars. Considering the theories and analysis exposed in the first and second chapters, we point up the brand's advantages and disadvantages to the Portuguese market, adaptations one must make to meet the demand as well as the differences and similarities between the Portuguese and Chinese markets. In the end, we present some conclusions and suggestions to the Chinese brands with interest in the Portuguese market, based on the experience that Chery had in Brazil

DORIS-MAE: Scientific Document Retrieval using Multi-level Aspect-based Queries

In scientific research, the ability to effectively retrieve relevant documents based on complex, multifaceted queries is critical. Existing evaluation datasets for this task are limited, primarily due to the high cost and effort required to annotate resources that effectively represent complex queries. To address this, we propose a novel task, Scientific DOcument Retrieval using Multi-level Aspect-based quEries (DORIS-MAE), which is designed to handle the complex nature of user queries in scientific research. We developed a benchmark dataset within the field of computer science, consisting of 100 human-authored complex query cases. For each complex query, we assembled a collection of 100 relevant documents and produced annotated relevance scores for ranking them. Recognizing the significant labor of expert annotation, we also introduce Anno-GPT, a scalable framework for validating the performance of Large Language Models (LLMs) on expert-level dataset annotation tasks. LLM annotation of the DORIS-MAE dataset resulted in a 500x reduction in cost, without compromising quality. Furthermore, due to the multi-tiered structure of these complex queries, the DORIS-MAE dataset can be extended to over 4,000 sub-query test cases without requiring additional annotation. We evaluated 17 recent retrieval methods on DORIS-MAE, observing notable performance drops compared to traditional datasets. This highlights the need for better approaches to handle complex, multifaceted queries in scientific research. Our dataset and codebase are available at https://github.com/Real-Doris-Mae/Doris-Mae-Dataset.Comment: To appear in NeurIPS 2023 Datasets and Benchmarks Trac

A Simple yet Effective Self-Debiasing Framework for Transformer Models

Current Transformer-based natural language understanding (NLU) models heavily rely on dataset biases, while failing to handle real-world out-of-distribution (OOD) instances. Many methods have been proposed to deal with this issue, but they ignore the fact that the features learned in different layers of Transformer-based NLU models are different. In this paper, we first conduct preliminary studies to obtain two conclusions: 1) both low- and high-layer sentence representations encode common biased features during training; 2) the low-layer sentence representations encode fewer unbiased features than the highlayer ones. Based on these conclusions, we propose a simple yet effective self-debiasing framework for Transformer-based NLU models. Concretely, we first stack a classifier on a selected low layer. Then, we introduce a residual connection that feeds the low-layer sentence representation to the top-layer classifier. In this way, the top-layer sentence representation will be trained to ignore the common biased features encoded by the low-layer sentence representation and focus on task-relevant unbiased features. During inference, we remove the residual connection and directly use the top-layer sentence representation to make predictions. Extensive experiments and indepth analyses on NLU tasks show that our framework performs better than several competitive baselines, achieving a new SOTA on all OOD test sets

Measuring the Quality of Service for High Occupancy Toll Lanes Operations

AbstractHigh Occupancy Toll (HOT) lane systems have been proposed as one of the most applicable countermeasures against freeway congestion. Under HOT lane operational scheme, a Single Occupancy Vehicle (SOV) can pay to access HOT lanes in exchange of travel time saving or enhanced trip reliability when excess HOT lane capacity is available. Compared with regular freeway facilities, HOT lane systems demonstrate unique characteristics in facility capacity, driver behavior, travel pattern, demand modeling, and trip reliability. This study aims at conducting a comprehensive performance analysis on two representative HOT lane systems of State Route 167 in Washington and I-394 MnPass in Minnesota based on the field data collected from traffic sensors and transponder toll tags. Performance measurements are proposed to quantify the quality of service for HOT lane operations. Three critical issues are addressed in this study: 1) the speed-flow relationships in HOT lane systems, 2) quantified system-wide travel time savings and travel time reliability achieved, 3) SOVs tolling incentives. Based on the empirical analysis and evaluation results for the SR 167 and I-394 MnPass HOT lane systems, operational problems and challenges are also identified. Although the HOT lane system preserves favorable travel reliability, under-utilized HOT lane capacities were observed. The existing tolling strategies may be modified for better SOV allocation for HOT lane usages and further optimize the overall HOT system operations. The research findings greatly advance our understanding on HOT lane system operation mechanisms and are complementary to the freeway facility performance analysis provided by Highway Capacity Manual 2000

DDMM-Synth: A Denoising Diffusion Model for Cross-modal Medical Image Synthesis with Sparse-view Measurement Embedding

Reducing the radiation dose in computed tomography (CT) is important to mitigate radiation-induced risks. One option is to employ a well-trained model to compensate for incomplete information and map sparse-view measurements to the CT reconstruction. However, reconstruction from sparsely sampled measurements is insufficient to uniquely characterize an object in CT, and a learned prior model may be inadequate for unencountered cases. Medical modal translation from magnetic resonance imaging (MRI) to CT is an alternative but may introduce incorrect information into the synthesized CT images in addition to the fact that there exists no explicit transformation describing their relationship. To address these issues, we propose a novel framework called the denoising diffusion model for medical image synthesis (DDMM-Synth) to close the performance gaps described above. This framework combines an MRI-guided diffusion model with a new CT measurement embedding reverse sampling scheme. Specifically, the null-space content of the one-step denoising result is refined by the MRI-guided data distribution prior, and its range-space component derived from an explicit operator matrix and the sparse-view CT measurements is directly integrated into the inference stage. DDMM-Synth can adjust the projection number of CT a posteriori for a particular clinical application and its modified version can even improve the results significantly for noisy cases. Our results show that DDMM-Synth outperforms other state-of-the-art supervised-learning-based baselines under fair experimental conditions.Comment: llncs.cls v2.20,12 pages with 6 figure

Experimental Investigation on Vibration Reduction Performance of Fiber Metal Laminate Beams with MRE Core

The vibration reduction characteristics of composite beams filled with magnetorheological elastomer core are studied experimentally. The fiber metal laminates with magnetorheological elastomers core is self-designed and prepared. Internal magnetic field is applied to the beam to explore its action of damping vibration performance under the magnetic field for the first time. The composite elements test system with controllable magnetic field intensity is designed and the function of each part is introduced. Then, a set of reasonable and standard vibration test flow of this type of composite beam under different magnetic field intensity is clarified, and the practical test is conducted. It has been found that the composite beam has excellent damping performance with the first 4 damping ratios being greater than 10%. Moreover, after the magnetic field is applied, its damping results can be further improved to meet the active control purpose