Scenarios for the Third National Climate Assessment (NCA3) were produced for physical climate and sea level rise with substantial input from disciplinary and regional experts. These scenarios underwent extensive review and were published as NOAA Technical Reports. For land use/cover and socioeconomic conditions, scenarios already developed by other agencies were specified for use in the NCA3. Efforts to enhance participatory scenario planning as an assessment activity were pursued, but with limited success. Issues and challenges included the timing of availability of scenarios, the need for guidance in use of scenarios, the need for approaches to nest information within multiple scales and sectors, engagement and collaboration of end users in scenario development, and development of integrated scenarios. Future assessments would benefit from an earlier start to scenarios development, the provision of training in addition to guidance documents, new and flexible approaches for nesting information, ongoing engagement and advice from both scientific and end user communities, and the development of consistent and integrated scenarios.
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http://dx.doi.org/10.1007/s10584-015-1494-z | DOI Listing |
Biomed Phys Eng Express
January 2025
Applied Sciences, Indian Institute of Information Technology Allahabad, Deoghat, Jhalwa, Allahabad, 211012, INDIA.
Photoacoustic tomography (PAT) is a non-destructive, non-ionizing, and rapidly expanding hybrid biomedical imaging technique, yet it faces challenges in obtaining clear images due to limited data from detectors or angles. As a result, the methodology suffers from significant streak artifacts and low-quality images. The integration of deep learning (DL), specifically convolutional neural networks (CNNs), has recently demonstrated powerful performance in various fields of PAT.
View Article and Find Full Text PDFPurpose: Although publicly available cancer-related information online and offline could help patients make informed decisions, it also poses challenges due to prevalent misinformation. Patients need proper provider guidance to ensure they use valid and relevant information in decisions. We identify effective communication approaches for providers when (1) discussing patient-identified information and (2) disagreeing with it.
View Article and Find Full Text PDFJ Agric Food Chem
January 2025
Yibin Academy of Southwest University, Yibin 644000, China.
Consumer concerns regarding food nutrition and quality are becoming increasingly prevalent. High-resolution mass spectrometry (HRMS)-based metabolomics stands as a cutting-edge and widely embraced technique in the realm of food component analysis and detection. It boasts the capability to identify character metabolites at exceedingly low abundances, which remain undetectable by conventional platforms.
View Article and Find Full Text PDFIntegr Environ Assess Manag
January 2025
Syngenta Proteção de Cultivos Ltda, São Paulo, São Paulo, Brazil.
Estimating pesticide concentrations in paddy rice systems is challenging due to unique cultivation methods and water management practices. Various models, ranging from simple exposure calculators to complex scenario-dependent tools, have been developed globally to address this issue (PADDY, MED-Rice, RICEWQ, PFAM). In Brazil, pesticides are used in paddy rice production, and there is a potential risk of these compounds reaching waterbodies.
View Article and Find Full Text PDFBioinformatics
January 2025
Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI 53726, United States.
Motivation: Clustering patients into subgroups based on their microbial compositions can greatly enhance our understanding of the role of microbes in human health and disease etiology. Distance-based clustering methods, such as partitioning around medoids (PAM), are popular due to their computational efficiency and absence of distributional assumptions. However, the performance of these methods can be suboptimal when true cluster memberships are driven by differences in the abundance of only a few microbes, a situation known as the sparse signal scenario.
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