Surface ocean microbiota determine cloud precursors.

One pathway by which the oceans influence climate is via the emission of sea spray that may subsequently influence cloud properties. Sea spray emissions are known to be dependent on atmospheric and oceanic physicochemical parameters, but the potential role of ocean biology on sea spray fluxes remains poorly characterized. Here we show a consistent significant relationship between seawater nanophytoplankton cell abundances and sea-spray derived Cloud Condensation Nuclei (CCN) number fluxes, generated using water from three different oceanic regions. This sensitivity of CCN number fluxes to ocean biology is currently unaccounted for in climate models yet our measurements indicate that it influences fluxes by more than one order of magnitude over the range of phytoplankton investigated.

Multi-Task Deep Learning for Real-Time 3D Human Pose Estimation and Action Recognition.

Human pose estimation and action recognition are related tasks since both problems are strongly dependent on the human body representation and analysis. Nonetheless, most recent methods in the literature handle the two problems separately. In this article, we propose a multi-task framework for jointly estimating 2D or 3D human poses from monocular color images and classifying human actions from video sequences. We show that a single architecture can be used to solve both problems in an efficient way and still achieves state-of-the-art or comparable results at each task while running with a throughput of more than 100 frames per second. The proposed method benefits from high parameters sharing between the two tasks by unifying still images and video clips processing in a single pipeline, allowing the model to be trained with data from different categories simultaneously and in a seamlessly way. Additionally, we provide important insights for end-to-end training the proposed multi-task model by decoupling key prediction parts, which consistently leads to better accuracy on both tasks. The reported results on four datasets (MPII, Human3.6M, Penn Action and NTU RGB+D) demonstrate the effectiveness of our method on the targeted tasks. Our source code and trained weights are publicly available at https://github.com/dluvizon/deephar.

Deepzzle: Solving Visual Jigsaw Puzzles with Deep Learning and Shortest Path Optimization.

We tackle the image reassembly problem with wide space between the fragments, in such a way that the patterns and colors continuity is mostly unusable. The spacing emulates the erosion of which the archaeological fragments suffer. We crop-square the fragments borders to compel our algorithm to learn from the content of the fragments. We also complicate the image reassembly by removing fragments and adding pieces from other sources. We use a two-step method to obtain the reassemblies: 1) a neural network predicts the positions of the fragments despite the gaps between them; 2) a graph that leads to the best reassemblies is made from these predictions. In this paper, we notably investigate the effect of branch-cut in the graph of reassemblies. We also provide a comparison with the literature, solve complex images reassemblies, explore at length the dataset, and propose a new metric that suits its specificities.

Corrigendum: Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition.

This corrects the article DOI: 10.1038/sdata.2017.3.

Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition.

Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment.

A standardized transcutaneous electric acupoint stimulation for relieving tobacco urges in dependent smokers.

The efficacy of acupuncture in smoking cessation, and its effect on the urge to smoke are unclear. We evaluated the effect of a standardized protocol of transcutaneous electric acupoint stimulations (TEAS) on alleviating the urge to smoke. Ninety-eight smokers were recruited in two double-blind studies. Participants abstained from smoking for 26 h, and were randomized to receive TEAS alternating between 2 and 100 Hz at four acupoints (LI4 and PC8, PC6 and TE5) at four different intensities (10, 5, Intermittent 5 or 0 mA). The urge to smoke was assessed by the Questionnaire of Smoking Urges (QSU-Brief). In Experiment 1, the 10 mA group (n = 20) was compared with the 5 mA group (n = 20); the increase in smoking urges did not differ significantly. Considering the possibility that 5 mA may be an active intervention, in Experiment 2, a true placebo (0 mA), and a proxy of placebo [Intermittent 5 mA (i5 mA)] were compared with 10 mA TEAS. In this experiment, 10 mA (n = 20) TEAS showed a tendency to alleviate smoking urges compared with 0 mA (n = 16), and i5 mA (n = 19) TEAS. Only when the data of smokers with Fagerstöm Test for Nicotine Dependence score ≥5 were analyzed that the difference between the 10 mA group and the control group (0 and i5 mA) became significant. Based on these preliminary findings, we conclude that TEAS applied on the skin may antagonize the increase in urge to smoke in abstinent-dependent smokers. It seems warranted to assess the efficacy of TEAS in smoking cessation clinical trials involving a larger population of dependent smokers.

Danqi Piantang Jiaonang (DJ), a traditional Chinese medicine, in poststroke recovery.

BACKGROUND AND PURPOSE: Stroke is a leading cause of death and disability worldwide. Despite improvements in acute stroke treatment, many patients only make a partial or poor recovery. Therefore, there is a need for treatments that would further improve outcome. Danqi Piantang Jiaonang (DJ; NeuroAid), a traditional Chinese medicine widely used in China to improve recovery after stroke, has been compared with another traditional Chinese medicine in 2 unpublished randomized clinical trials. The results of these studies were pooled and reanalyzed to assess efficacy and safety. METHODS: Six hundred five subjects were randomized in 2 randomized double-blinded, controlled trials to receive either DJ or Buchang Naoxintong Jiaonang. Subjects were treated for 1 month. Inclusion criteria were: (1) patients with recent (from 10 days to 6 months) ischemic stroke; (2) patients satisfying Western diagnostic standards for stroke and traditional Chinese medicine standards for diagnosis of apoplexy; and (3) Diagnostic Therapeutic Effects of Apoplexy score >/=10. RESULTS: The functional outcome, measured by the Comprehensive Function Score component of the Diagnostic Therapeutic Effects of Apoplexy scale, showed a statistically significant superiority of DJ over the control treatment group (relative risk, 2.4; 95% CI, 1.28 to 4.51; P=0.007). Tolerance was excellent in both groups. CONCLUSIONS: The pooled analysis of 2 unpublished trials of DJ, a traditional Chinese medicine currently approved in China to improve neurological recovery after stroke, shows good tolerability and superiority of DJ over another traditional Chinese medicine also approved for stroke. A large double-blind randomized clinical trial is required to further assess the safety and efficacy of DJ.