80 research outputs found

    Should State Land in Southern California Be Allocated to Warehousing Goods or Housing People? Analyzing Transportation, Climate, and Unintended Consequences of Supply Chain Solutions

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    In response to COVID-19 pandemic supply chain issues, the State of California issued Executive Order (EO) N-19-21 to use state land to increase warehousing capacity. This highlights a land-use paradox between economic and environmental goals: adding warehouse capacity increases climate pollution and traffic congestion around the ports and warehouses, while there is a deficit of affordable housing and high homeless rates in port-adjacent underserved communities. This study aims to inform regional policymakers and community stakeholders about these trade-offs by identifying current and future supply of and demand for warehousing and housing in Southern California through 2040. The study uses statistical analysis and forecasting, and evaluates across numerous scenarios the environmental impact of meeting demand for both with the Community LINE Source Model. Warehousing and housing are currently projected to be in high demand across Southern California in future decades, despite short-run adjustments in the post-pandemic period of inflation and net declines in population. Using state land for warehousing creates environmental justice concerns, as the number of air pollution hotspots increases even with electrifying trucking fleets, especially when compared against low-impact affordable housing developments. However, low-income housing demand appears to be positively correlated with unemployment, suggesting that the jobs provided by warehousing development might help to ameliorate that concern

    The effect of waste engine oil and waste polyethylene on UV aging resistance of asphalt.

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    Waste engine oil (WEO) and waste polyethylene (WPE) are two common wastes, which are easy to pollute the environment. As the primary material in road construction, natural asphalt is a non-renewable energy source and asphalt is vulnerable to ultraviolet (UV) radiation during the service life. It results in degradation of asphalt pavement performance. In this paper, 22 wt % to 82 wt % of WEO and WPE were used to modify asphalts and the UV aging simulation experiment was carried out. The physical parameters of asphalts before the UV aging experiment show that the asphalt containing 42 wt % WPE and 62 wt % WEO mixture (42 wt % WPE + 62 wt % WEO) has similar physical properties with that of the matrix asphalt. Besides, gel permeation chromatography (GPC) verifies that the molecular weight distribution of the asphalt containing 42 wt % WPE + 62 wt % WEO is close to that of the matrix asphalt. The storage stability test shows that 42 wt % WPE + 62 wt % WEO has good compatibility with the matrix asphalt. The functional groups and micro-morphology of asphalts before and after the UV aging experiment were investigated by Fourier transform infrared spectroscopy (FTIR) and atomic force microscopy (AFM). FTIR results display that 42 wt % WPE + 62 wt % WEO can effectively reduce the formation of carbonyl and sulfoxide functional groups. AFM shows that 42 wt % WPE + 62 wt % WEO can also retard the formation of a bee-like structure in asphalt after the UV aging experiment. Based on the above results, it can be concluded that WEO and WPE mixture can replace part of asphalt and improve the UV aging resistance of asphalt

    Crowdsourcing geospatial data for Earth and human observations: a review

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    The transformation from authoritative to user-generated data landscapes has garnered considerable attention, notably with the proliferation of crowdsourced geospatial data. Facilitated by advancements in digital technology and high-speed communication, this paradigm shift has democratized data collection, obliterating traditional barriers between data producers and users. While previous literature has compartmentalized this subject into distinct platforms and application domains, this review offers a holistic examination of crowdsourced geospatial data. Employing a narrative review approach due to the interdisciplinary nature of the topic, we investigate both human and Earth observations through crowdsourced initiatives. This review categorizes the diverse applications of these data and rigorously examines specific platforms and paradigms pertinent to data collection. Furthermore, it addresses salient challenges, encompassing data quality, inherent biases, and ethical dimensions. We contend that this thorough analysis will serve as an invaluable scholarly resource, encapsulating the current state-of-the-art in crowdsourced geospatial data, and offering strategic directions for future interdisciplinary research and applications across various sectors

    Antipsychotics-induced improvement of cool executive function in individuals living with schizophrenia

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    Cool executive dysfunction is a crucial feature in people living with schizophrenia which is related to cognition impairment and the severity of the clinical symptoms. Based on electroencephalogram (EEG), our current study explored the change of brain network under the cool executive tasks in individuals living with schizophrenia before and after atypical antipsychotic treatment (before_TR vs. after_TR). 21 patients with schizophrenia and 24 healthy controls completed the cool executive tasks, involving the Tower of Hanoi Task (THT) and Trail-Marking Test A-B (TMT A-B). The results of this study uncovered that the reaction time of the after_TR group was much shorter than that of the before_TR group in the TMT-A and TMT-B. And the after_TR group showed fewer error numbers in the TMT-B than those of the before_TR group. Concerning the functional network, stronger DMN-like linkages were found in the before_TR group compared to the control group. Finally, we adopted a multiple linear regression model based on the change network properties to predict the patient’s PANSS change ratio. Together, the findings deepened our understanding of cool executive function in individuals living with schizophrenia and might provide physiological information to reliably predict the clinical efficacy of schizophrenia after atypical antipsychotic treatment

    Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

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    Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049
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