The Design of International Trade Agreements: Introducing a New Dataset

Preferential trade agreements (PTAs) have been proliferating for the last twenty years. A large literature has studied various aspects of this phenomenon. Until recently, however, many large-N studies have paid only scant attention to variation across PTAs in terms of content and design. Our contribution to this literature is a new dataset on the design of trade agreements that is the most comprehensive in terms of both variables coded and agreements covered. We illustrate the dataset’s usefulness in re-visiting the questions if and to what extent PTAs impact trade flows. The analysis shows that on average PTAs increase trade flows, but that this effect is largely driven by deep agreements. In addition, we provide evidence that provisions that tackle behind-the-border regulation matter for trade flows. The dataset’s contribution is not limited to the PTA literature, however. Broader debates on topics such as institutional design and the legalization of international relations will also benefit from the novel data.

Warm Conveyor Belts in the ERA-Interim Dataset (1979–2010): Part I: Climatology and Potential Vorticity Evolution

A global climatology of warm conveyor belts (WCBs) is presented for the years 1979–2010, based on trajectories calculated with Interim ECMWF Re-Analysis (ERA-Interim) data. WCB trajectories are identified as strongly ascending air parcels (600 hPa in 2 days) near extratropical cyclones. Corroborating earlier studies, WCBs are more frequent during winter than summer and they ascend preferentially in the western ocean basins between 25° and 50° latitude. Before ascending, WCB trajectories typically approach from the subtropics in summer and from more midlatitude regions in winter. Considering humidity, cloud water, and potential temperature along WCBs confirms that they experience strong condensation and integrated latent heating during the ascent (typically >20 K). Liquid and ice water contents along WCBs peak at about 700 and 550 hPa, respectively. The mean potential vorticity (PV) evolution shows typical tropospheric values near 900 hPa, followed by an increase to almost 1 potential vorticity unit (PVU) at 700 hPa, and a decrease to less than 0.5 PVU at 300 hPa. These low PV values in the upper troposphere constitute significant negative anomalies with amplitudes of 1–3 PVU, which can strongly influence the downstream flow. Considering the low-level diabatic PV production, (i) WCBs starting at low latitudes (<40°) are unlikely to attain high PV (due to weak planetary vorticity) although they exhibit the strongest latent heating, and (ii) for those ascending at higher latitudes, a strong vertical heating gradient and high absolute vorticity are both important. This study therefore provides climatological insight into the cloud diabatic formation of significant positive and negative PV anomalies in the extratropical lower and upper troposphere, respectively.

Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features.

Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.