What is the scientific basis for climate-smart agriculture?

Climate-smart agriculture (CSA) is a systematic approach to agricultural development. It intends to address climate change and food security challenges simultaneously across levels, from field management to national policy, with goals to 1) improve food security and agricultural productivity, 2) increase the resilience of farming systems to climate change, and 3) mitigate greenhouse gas (GHG) emissions or sequester carbon. After the introduction of the CSA concept in 2010, development organizations, national governments, and donors have quickly adopted a “climate-smart” agenda

Tumors Metastatic to Thyroid Neoplasms: A Case Report and Review of the Literature

Metastasis into a thyroid neoplasm—tumor-to-tumor metastasis—is exceedingly rare. We describe the 28th documented case of a tumor metastatic to a thyroid neoplasm and review the literature on tumor-to-tumor metastasis involving a thyroid neoplasm as recipient. All cases showed a recipient thyroid neoplasm with an abrupt transition to a morphologically distinct neoplasm. Metastasis into primary thyroid neoplasm was synchronous in 33% of cases and metachronous in 67%. Follicular adenoma was the most common recipient thyroid neoplasm overall (16/28), and papillary thyroid carcinoma was the most common malignant recipient neoplasm (9/28). Of the 9 recipient papillary carcinomas, 6 were follicular variants. Renal cell carcinoma was the most common neoplasm to metastasize to a primary thyroid neoplasm (9/28), followed by lung (6/28), breast (5/28), and colon (3/28) carcinoma. Tumor-to-tumor metastasis should be considered whenever a dimorphic pattern is encountered in a thyroid tumor

Exploring the Spectral Space of Low Redshift QSOs

The Karhunen-Loeve (KL) transform can compactly represent the information contained in large, complex datasets, cleanly eliminating noise from the data and identifying elements of the dataset with extreme or inconsistent characteristics. We develop techniques to apply the KL transform to the 4000-5700A region of 9,800 QSO spectra with z < 0.619 from the SDSS archive. Up to 200 eigenspectra are needed to fully reconstruct the spectra in this sample to the limit of their signal/noise. We propose a simple formula for selecting the optimum number of eigenspectra to use to reconstruct any given spectrum, based on the signal/noise of the spectrum, but validated by formal cross-validation tests. We show that such reconstructions can boost the effective signal/noise of the observations by a factor of 6 as well as fill in gaps in the data. The improved signal/noise of the resulting set will allow for better measurement and analysis of these spectra. The distribution of the QSO spectra within the eigenspace identifies regions of enhanced density of interesting subclasses, such as Narrow Line Seyfert 1s (NLS1s). The weightings, as well as the inability of the eigenspectra to fit some of the objects, also identifies "outliers," which may be objects that are not valid members of the sample or objects with rare or unique properties. We identify 48 spectra from the sample that show no broad emission lines, 21 objects with unusual [O III] emission line properties, and 9 objects with peculiar H-beta emission line profiles. We also use this technique to identify a binary supermassive black hole candidate. We provide the eigenspectra and the reconstructed spectra of the QSO sample.Comment: 34 pages, 14 figures, revised version resubmitted to the Astronomical Journa