585 research outputs found

    Flux-based classification of reactions reveals a functional bow-tie organization of complex metabolic networks

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    Unraveling the structure of complex biological networks and relating it to their functional role is an important task in systems biology. Here we attempt to characterize the functional organization of the large-scale metabolic networks of three microorganisms. We apply flux balance analysis to study the optimal growth states of these organisms in different environments. By investigating the differential usage of reactions across flux patterns for different environments, we observe a striking bimodal distribution in the activity of reactions. Motivated by this, we propose a simple algorithm to decompose the metabolic network into three sub-networks. It turns out that our reaction classifier which is blind to the biochemical role of pathways leads to three functionally relevant sub-networks that correspond to input, output and intermediate parts of the metabolic network with distinct structural characteristics. Our decomposition method unveils a functional bow-tie organization of metabolic networks that is different from the bow-tie structure determined by graph-theoretic methods that do not incorporate functionality.Comment: 11 pages, 6 figures, 1 tabl

    Bioassay-directed isolation and identification of phytotoxic terpenoids from horseweed (Conyza Canadensis).

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    Horseweed [Conyza canadensis (L.) Cronquist, syn. Erigeron canadensis L.], Asteraceae, is a common weed with known allelopathic effects but few studies on the isolation and identification of the phytotoxic compounds have been reported [1]. C. canadensis infests orchards, vineyards, field crops such as corn, soybean and cotton, particularly in herbicide-resistant crops where conservation tillage or no-till systems are used. The objective of this study was to identify the phytotoxic compounds present by systematically performing bioassay-directed isolation and subsequent identification of the bioactive constituents according to Dayan et al. [2]. No significant phytotoxic activity against Lactuca sativa or Agrostis stolonifera was detected in methanol, or water extracts when tested at 1.0mg·mL-1; however, the dichloromethane extract was active. Further fractionation using liquid-liquid partitioning with hexane, chloroform, ethyl acetate and water was performed with the DCM extract. The most active extract (chloroform) was subjected to preparative HPLC and the fractions were tested again. The active compounds were isolated and identified by GC-MS and 1H- and 13C-NMR. The isolated compounds (Figure 1) were identified as (2Z,8Z)-matricaria acid methyl ester, (4Z,8Z)-matricarialactone and (4Z)-lachnophyllumlactone. Compound 3 shows similar activity a

    A Series of Financial Accounting Case Studies

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    This thesis was completed during the 2021-2022 academic year consists of eleven accounting case studies. The topics from these cases cover a wide variety of topics both related and external to accounting. The first five pertain to topics such as 9/11, the impact of COVID-19 on Pfizer, an interview with a business professional, and an Excel certification course. One of the cases also pertains to the city we desire to start our career in. Following case 5, myself and several other honors students worked together to complete the next six cases, which involved a multiple-week analysis of Goldman Sachs. Topics include the business structure of Goldman Sachs, audit risks and controls, tax-saving strategies, advisory opinions, and an overall threat assessment. After completing these cases, they were compiled and presented to a panel of accounting professionals, who then were able to make further inquiries about the presented material

    An Area-Based Calculation of the Analysis of Roof Bolt Systems (ARBS)

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    The objective of this research is to develop a software tool, which will assist in the area-wide calculation of ARBS while incorporating more detailed/accurate stress, varying CMRR and intersection span inputs. This tool imports the overburden, abutment and multiple-seam stresses as obtained by the boundary-element program LaModel and is converts them to a pseudo-depth which is used as the depth input to the ARBS calculations. In addition, available geologic data at the mine can be used to determine an area-based CMRR, and mine design information can be used to determine an area-based intersection span for input to the calculation. This tool is incorporated in the recently modified Stability Mapping program (StabMap) which, as part of this development effort, has been upgraded to readily accept area-based inputs from: SurvCADD\u27s geologic grids for calculating an area-based CMRR, LaModel\u27s stress grids for determining an area-based pseudo-depth, and user defined grids for specifying an area-based intersection span. Finally, the StabMap program is now designed to take the appropriate pseudo-depth, CMRR, and intersection span grids to calculate an area-based ARBS support intensity. This final area-based ARBS grid can then be plotted, analyzed and overlaid on the mine map for optimum presentation to production personnel

    Exploring RoBERTa model for cross-domain suggestion detection in online reviews

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    Detecting suggestions in online review requires contextual understanding of review text, which is an important real-world application of natural language processing. Given the disparate text domains found in product reviews, a common strategy involves fine-tuning bidirectional encoder representations from transformers (BERT) models using reviews from various domains. However, there hasn't been an empirical examination of how BERT models behave across different domains in tasks related to detecting suggestion sentences from online reviews. In this study, we explore BERT models for suggestion classification that have been fine-tuned using single-domain and cross-domain Amazon review datasets. Our results indicate that while single-domain models achieved slightly better performance within their respective domains compared to cross-domain models, the latter outperformed single-domain models when evaluated on cross-domain data. This was also observed for single-domain data not used for fine-tuning the single-domain model and on average across all tests. Although fine-tuning single-domain models can lead to minor accuracy improvements, employing multi-domain models that perform well across domains can help in cold start problems and reduce annotation costs

    Federal agency perspectives and funding opportunities for weed and invasive plant research

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    Weeds and invasive plants know no borders and have collectively impacted many ecosystems worldwide, including croplands, forests, grasslands, rangelands, wetlands, and riparian areas. Losses continue to mount, affecting yield and productivity, species diversity, and ecosystem services, with both short- and long-term repercussions on the sustainability of plant and animal communities and the livelihoods of many. New and emerging invasive plants, along with many of the most intractable weeds, have undermined even the best control efforts, serving as a reminder of the constant need for improvements in science, application, and technology. One of the main reasons for the success of weeds and invasive plants is their ability to adapt to abiotic and biotic conditions, and research suggests that this will continue with minimal change. Despite the challenges posed by weeds and invasive plants, integrated management techniques, several effective chemistries, and the development of new technology are a signal that ongoing and renewed efforts are worthwhile. National coordination is needed across the sectors of weed and invasive plant sciences to achieve common goals. Federal agencies have the largest land holdings—which are infested with weeds and invasive plants—and work with a diverse group of stakeholders comprising managers, researchers, and regulators. Thus, there is an urgent and pressing need to facilitate dialogue between federal agencies specific to weed and invasive plant science to (1) serve as a starting point for summarizing current knowledge and identifying information gaps and (2) re-engage national program leaders and representatives to better coordinate programs in addressing common challenges. Federal departments and agencies with expertise in weed and invasive plant science were brought together at a symposium held during the Weed Science Society of America’s 63rd Annual Meeting in Washington, DC. Individuals from the Animal and Plant Health Inspection Service (APHIS), Agricultural Research Service (ARS), National Institute of Food and Agriculture (NIFA), Office of Pest Management Policy (OPMP), Natural Resources Conservation Service (NRCS), U.S. Forest Service (USFS), Bureau of Land Management (BLM), U.S. Geological Survey (USGS), National Park Service (NPS), Department of Defense (DOD), Army Corps of Engineers (ACOE), National Aeronautics and Space Administration (NASA), and National Science Foundation (NSF) shared current research and management efforts and participated in a discussion focused on the identification of funding opportunities and other issues pertaining to research gaps and management needs among this society’s membership
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