Heavy-tailed statistics in short-message communication

Short-message (SM) is one of the most frequently used communication channels in the modern society. In this Brief Report, based on the SM communication records provided by some volunteers, we investigate the statistics of SM communication pattern, including the interevent time distributions between two consecutive short messages and two conversations, and the distribution of message number contained by a complete conversation. In the individual level, the current empirical data raises a strong evidence that the human activity pattern, exhibiting a heavy-tailed interevent time distribution, is driven by a non-Poisson nature.Comment: 4 pages, 4 figures and 1 tabl

Cultural differences in neurocognitive mechanisms underlying believing

Believing as a fundamental mental process influences other cognitive/affective processes and behavior. However, it is unclear whether believing engages distinct neurocognitive mechanisms in people with different cultural experiences. We addressed this issue by scanning Chinese and Danish adults using functional MRI during believing judgments on personality traits of oneself and a celebrity. Drift diffusion model analyses of behavioral performances revealed that speed/quality of information acquisition varied between believing judgments on positive and negative personality traits in Chinese but not in Danes. Chinese adopted a more conservative strategy of decision-making during celebrity- than self-believing judgments whereas an opposite pattern was observed in Danes. Non-decisional processes were longer for celebrity- than for self-believing in Danes but not in Chinese. Believing judgments activated the medial prefrontal cortex (mPFC) in both cultural groups but elicited stronger left anterior insular and ventral frontal activations in Chinese. Greater mPFC activity in Chinese was associated with longer duration of non-decision processes during believing-judgments, which predicted slower retrieval of self-related information in a memory test. Greater mPFC activity in Danes, however, was associated with a less degree of adopting a conservative strategy during believing judgments, which predicted faster retrieval of self-related information. Our findings highlight different neurocognitive processes engaged in believing between individuals from East Asian and Western cultures

An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification

While deep learning methods are increasingly being applied to tasks such as computer-aided diagnosis, these models are difficult to interpret, do not incorporate prior domain knowledge, and are often considered as a "black-box." The lack of model interpretability hinders them from being fully understood by target users such as radiologists. In this paper, we present a novel interpretable deep hierarchical semantic convolutional neural network (HSCNN) to predict whether a given pulmonary nodule observed on a computed tomography (CT) scan is malignant. Our network provides two levels of output: 1) low-level radiologist semantic features, and 2) a high-level malignancy prediction score. The low-level semantic outputs quantify the diagnostic features used by radiologists and serve to explain how the model interprets the images in an expert-driven manner. The information from these low-level tasks, along with the representations learned by the convolutional layers, are then combined and used to infer the high-level task of predicting nodule malignancy. This unified architecture is trained by optimizing a global loss function including both low- and high-level tasks, thereby learning all the parameters within a joint framework. Our experimental results using the Lung Image Database Consortium (LIDC) show that the proposed method not only produces interpretable lung cancer predictions but also achieves significantly better results compared to common 3D CNN approaches

A unique distant submillimeter galaxy with an X-ray-obscured radio-luminous active galactic nucleus

We present a multiwavelength study of an atypical submillimeter galaxy in the GOODS-North field, with the aim to understand its physical properties of stellar and dust emission, as well as the central AGN activity. Although it is shown that the source is likely an extremely dusty galaxy at high redshift, its exact position of submillimeter emission is unknown. With the new NOEMA interferometric imaging, we confirm that the source is a unique dusty galaxy. It has no obvious counterpart in the optical and even NIR images observed with HST at lambda~<1.4um. Photometric-redshift analyses from both stellar and dust SED suggest it to likely be at z~>4, though a lower redshift at z~>3.1 cannot be fully ruled out (at 90% confidence interval). Explaining its unusual optical-to-NIR properties requires an old stellar population (~0.67 Gyr), coexisting with a very dusty ongoing starburst component. The latter is contributing to the FIR emission, with its rest-frame UV and optical light being largely obscured along our line of sight. If the observed fluxes at the rest-frame optical/NIR wavelengths were mainly contributed by old stars, a total stellar mass of ~3.5x10^11Msun would be obtained. An X-ray spectral analysis suggests that this galaxy harbors a heavily obscured AGN with N_H=3.3x10^23 cm^-2 and an intrinsic 2-10 keV luminosity of L_X~2.6x10^44 erg/s, which places this object among distant type 2 quasars. The radio emission of the source is extremely bright, which is an order of magnitude higher than the star-formation-powered emission, making it one of the most distant radio-luminous dusty galaxies. The combined characteristics of the galaxy suggest that the source appears to have been caught in a rare but critical transition stage in the evolution of submillimeter galaxies, where we are witnessing the birth of a young AGN and possibly the earliest stage of its jet formation and feedback.Comment: 13 pages in printer format, 10 figures, 1 table, accepted for publication in the A&