Because of the considerable uncertainties associated with modeling complex ecosystem processes, it is essential that every effort be made to test model performance prior to relying on model projections for assessment of future surface water chemical response to environmental perturbation. Unfortunately, long-term chemical data with which to validate model performance are seldom available. The authors present here an evaluation of historical acidification of lake waters in the northeastern United States, and compare historical changes in a set of lakes to hindcasts from the same watershed model (MAGIC) used to estimate future changes in response to acidic deposition. The historical analyses and comparisons with MAGIC model hindcasts and forecasts of acid-base response demonstrate that the acidic and low-ANC lakes in this region are responsive to strong acid inputs. However, the model estimates suggest lakewater chemistry is more responsive to atmospheric inputs of sulfur than do the estimates based on paleolimnological historical analyses. A 'weight-of-evidence approach' that incorporates all available sources of information regarding acid-base response provides a more reasonable estimate of future change than an approach based on model projections alone. The results of these analyses have important implications for predicting future surface water chemical change in response to acidic deposition, establishing critical loads of atmospheric pollutants, and other environmental assessment activities where natural variation often exceeds the trends under investigation (high noise-to-signal ratio). Under these conditions, it is particularly important to evaluate future model projections in light of historical trends data.
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http://dx.doi.org/10.1016/0269-7491(92)90084-n | DOI Listing |
Sci Rep
December 2024
Earth Observatory of Singapore, Nanyang Technological University, Singapore, 639798, Singapore.
Coastal populations are susceptible to relative sea-level (RSL) rise and accurate local projections are necessary for coastal adaptation. Local RSL rise may deviate from global mean sea-level rise because of processes such as geoid change, glacial isostatic adjustment (GIA), and vertical land motion (VLM). Amongst all factors, the VLM is often inadequately estimated.
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December 2024
School of Management Science and Engineering, Shandong Jianzhu University, Jinan, 250101, China.
This study seeks to improve urban supply chain management and collaborative governance in the context of public health emergencies (PHEs) by integrating fuzzy theory with the Back Propagation Neural Network (BPNN) algorithm. By combining these two approaches, an early warning mechanism for supply chain risks during PHEs is developed. The study employs Matlab software to simulate supply chain risks, incorporating fuzzy inference techniques with the adaptive data modeling capabilities of neural networks for both training and testing.
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December 2024
Programa de Pós-Graduação em Ecologia, Instituto de Ciência Biológicas, Universidade Federal do Pará, Belém, Brazil.
The negative effects of land-use changes on biodiversity significantly contribute to climate change. Primates are among the animals most affected by these changes, because of their high dependence on forest cover where a lack of forest connectivity can limit their dispersal and segregate their populations. In this sense, protected areas (PAs) are crucial for conserving endangered primates, especially endemic species.
View Article and Find Full Text PDFInt J Antimicrob Agents
December 2024
Department of Pharmacy, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510163, China. Electronic address:
Despite the widespread use of voriconazole in antifungal treatment, its high pharmacokinetic and pharmacodynamic variability may lead to suboptimal efficacy, especially in intensive care unit (ICU) patients. Machine learning (ML), an artificial intelligence modeling approach, is increasingly being applied to personalized medicine. The effectiveness of ML models for predicting voriconazole blood concentrations in ICU patients, compared to traditional population pharmacokinetics (popPK) models, has been uncertain until now.
View Article and Find Full Text PDFSurgery
December 2024
Department of Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China; Molecular Medicine Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China; Department of Gastrointestinal Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. Electronic address:
Background: Duodenal stump leakage is one of the most critical complications following gastrectomy surgery, with a high mortality rate. The present study aimed to establish a predictive model based on machine learning for forecasting the occurrence of duodenal stump leakage in patients who underwent laparoscopic gastrectomy for gastric cancer.
Materials And Methods: The present study included the data of 4,070 patients with gastric adenocarcinoma who received laparoscopic gastrectomy.
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