H-mode transition in the TJ-II stellarator plasmas.

Since the first H-mode transitions were observed in TJ-II plasmas in 2008, an extensive experimental effort has been done aiming at better physics understanding of confinement transitions. In this article, an overview of the main findings related to the L-H transition in TJ-II is presented including how the radial electric field is driven, what are the possible mechanisms for turbulence suppression and what are the related temporal and spatial scales that can impact the transition. The trigger of the L-H transition in TJ-II plasmas is found to be more correlated with the development of fluctuating [Formula: see text] flows than with steady-state [Formula: see text] effects, pointing to the role played by zonal flows in mediating the transition.

Does preoperative neoadjuvant chemotherapy impact short-term surgical outcomes in patients with locally advanced colon cancer?

Background: Preoperative neoadjuvant chemotherapy (NAC) for colon cancer in advanced stages is associated with improved outcomes and tumor regression. The aim of our study was to identify outcomes in patients with colon cancer who received preoperative NAC.

Methods: A 4-year analysis of the American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) was performed.

Cuprous or cupric? How substrate polarity can select for different phases of copper sulfide films in chemical bath deposition.

Copper sulfides have many applications from thermoelectrics to biotechnology. While the properties of different copper sulfide phases are well understood, controlling the deposited copper sulfide stoichiometry remains a significant challenge, especially in solution-phase synthesis techniques. In this work, we investigate the chemical bath deposition of CuS on functionalized self-assembled monolayers (SAMs).

Girasol, a sky imaging and global solar irradiance dataset.

The energy available in a microgrid that is powered by solar energy is tightly related to the weather conditions at the moment of generation. A very short-term forecast of solar irradiance provides the microgrid with the capability of automatically controlling the dispatch of energy. We propose a dataset to forecast Global Solar Irradiance (GSI) using a data acquisition system (DAQ) that simultaneously records sky imaging and GSI measurements, with the objective of extracting features from clouds and use them to forecast the power produced by a Photovoltaic (PV) system.

Diabetic Peripheral Neuropathy Risk Assessment using Digital Fundus Photographs and Machine Learning.

In this work, we demonstrate a novel approach to assessing the risk of Diabetic Peripheral Neuropathy (DPN) using only the retinal images of the patients. Our methodology consists of convolutional neural network feature extraction, dimensionality reduction and feature selection with random projections, combination of image features to case-level representations, and the training and testing of a support vector machine classifier. Using clinical diagnosis as ground truth for DPN, we achieve an overall accuracy of 89% on a held-out test set, with sensitivity reaching 78% and specificity reaching 95%.