2,160 research outputs found

    Exploring Equity Frameworks for a Cross-Jurisdictional Vehicle Miles Traveled Mitigation Program in Santa Clara County

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    The Santa Clara Valley Transportation Authority (VTA) partnered with a Mineta Transportation Institute (MTI) research team and San José State University (SJSU) students for assistance in developing the equity framework for the agency’s proposed Equitable Vehicle Miles Traveled (VMT) Mitigation Program. The goal of the program is to reduce the amount of driving generated from new developments in Santa Clara County through transportation solutions with equity and cross-jurisdictional collaboration in mind. During the Fall 2023 semester, graduate urban planning students from SJSU worked to develop policy recommendations for the program equity framework through a literature review, spatial analysis, community engagement observations, and stakeholder interviews. This report summarizes and builds upon student contributions to present a set of equity-focused recommendations for VTA to consider for program development, implementation, and evaluation. Notable strategies identified for developing the framework include defining VMT equity with local relevance, creating an accountability plan, and embedding equity into key decision-making points. Additionally, a transportation challenge frequently mentioned by stakeholders was a need for improved transit availability, frequency, reliability, and speed. Major recommendations discussed in the report include developing and adopting a localized definition of VMT equity, developing an informative and implementable accountability plan, embedding equity measures into project prioritization and evaluation processes, and prioritizing improvements to public transit. Lessons learned can help other jurisdictions develop and implement equitable VMT mitigation programs and effective community engagement processes. Additionally, the report provides an overview of the factors that go into program development, which can help readers better understand this process and identify areas where they can get involved

    Validation Between Gene Expression Measurement Platforms

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    https://openworks.mdanderson.org/sumexp22/1088/thumbnail.jp

    The Role of Apparent Competition in Facilitating Ecological Release of a Range-expanding Insect

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    Due to anthropogenic climate change, species are expanding their historical natural ranges. However, interacting species will not shift synchronously and range-expanding species are likely to lose interactions and pick up novel ones in their expanded range. If antagonistic interactions, such as with competitors or enemies are lost, range-expanding species may experience “ecological release” and have impacts in their expanded range. Of the parasitoid wasps that attack phytophagous insects, some are specialists and some are generalists attacking alternative hosts (competitors). Range-expanding species may lose enemies if their specialists fail to follow from their native range and if generalist enemies fail to switch from competitors in the expanded range (“release from apparent competition”). We study a poleward range-expansion of a phytophagous gall-forming insect Neuroterus saltatorius that expanded its range from mainland western North America to Vancouver Island, BC, where it is outbreaking on its plant Querucs garryana. N. saltatorius co-occurs with several other gall-formers on its host, including Andricus opertus, throughout its native and expanded range. Here, we ask if A. opertus acts as an apparent competitor (shares enemies) with N. saltatorius, and if apparent competition is weaker in the expanded range. These two host species were collected from 18 sites that span the range of Q. garryana. We reared parasitoid wasps from them and identified parasitoids to morphospecies using taxonomic keys. We identified 16 parasitoids from N. saltatorius and 39 from A. opertus. Of these, 13 species of parasitoids are shared between the two host species in all regions, and we will calculate the rate of shared overlap to see if there are fewer shared species in the expanded range. This result would suggest that release from apparent competition contributes to ecological release. Understanding how biotic interactions change under range expansions is important to predict species responses to climate change.https://orb.binghamton.edu/research_days_posters_2021/1095/thumbnail.jp

    Evaluation of laser-based spectrometers for greenhouse gas flux measurements in coastal marshes

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    © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Limnology and Oceanography: Methods 14 (2016): 466–476, doi:10.1002/lom3.10105.Precise and rapid analyses of greenhouse gases (GHGs) will advance understanding of the net climatic forcing of coastal marsh ecosystems. We examined the ability of a cavity ring down spectroscopy (CRDS) analyzer (Model G2508, Picarro) to measure carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes in real-time from coastal marshes through comparisons with a Shimadzu GC-2014 (GC) in a marsh mesocosm experiment and with a similar laser-based N2O analyzer (Model N2O/CO, Los Gatos Research) in both mesocosm and field experiments. Minimum (analytical) detectable fluxes for all gases were more than one order of magnitude lower for the Picarro than the GC. In mesocosms, the Picarro analyzer detected several CO2, CH4, and N2O fluxes that the GC could not, but larger N2O fluxes (218–409 μmol m−2 h−1) were similar between analyzers. Minimum detectable fluxes for the Picarro were 1 order of magnitude higher than the Los Gatos analyzer for N2O. The Picarro and Los Gatos N2O fluxes (3–132 μmol m−2 h−1) differed in two mesocosm nitrogen addition experiments, but were similar in a mesocosm with larger N2O fluxes (326–491 μmol m−2 h−1). In a field comparison, Picarro and Los Gatos N2O fluxes (13 ± 2 μmol m−2 h−1) differed in plots receiving low nitrogen loads but were similar in plots with higher nitrogen loads and fluxes roughly double in magnitude. Both the Picarro and Los Gatos analyzers offer efficient and precise alternatives to GC-based methods, but the former uniquely enables simultaneous measurements of three major GHGs in coastal marshes.This study was funded by the USDA National Institute of Food and Agriculture (Hatch project # 229286, grant to Moseman-Valtierra) and a Woods Hole Sea Grant award to Moseman-Valtierra and Tang

    Predictive modeling of die filling of the pharmaceutical granules using the flexible neural tree

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    In this work, a computational intelligence (CI) technique named flexible neural tree (FNT) was developed to predict die filling performance of pharmaceutical granules and to identify significant die filling process variables. FNT resembles feedforward neural network, which creates a tree-like structure by using genetic programming. To improve accuracy, FNT parameters were optimized by using differential evolution algorithm. The performance of the FNT-based CI model was evaluated and compared with other CI techniques: multilayer perceptron, Gaussian process regression, and reduced error pruning tree. The accuracy of the CI model was evaluated experimentally using die filling as a case study. The die filling experiments were performed using a model shoe system and three different grades of microcrystalline cellulose (MCC) powders (MCC PH 101, MCC PH 102, and MCC DG). The feed powders were roll-compacted and milled into granules. The granules were then sieved into samples of various size classes. The mass of granules deposited into the die at different shoe speeds was measured. From these experiments, a dataset consisting true density, mean diameter (d50), granule size, and shoe speed as the inputs and the deposited mass as the output was generated. Cross-validation (CV) methods such as 10FCV and 5x2FCV were applied to develop and to validate the predictive models. It was found that the FNT-based CI model (for both CV methods) performed much better than other CI models. Additionally, it was observed that process variables such as the granule size and the shoe speed had a higher impact on the predictability than that of the powder property such as d50. Furthermore, validation of model prediction with experimental data showed that the die filling behavior of coarse granules could be better predicted than that of fine granules
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