Deep Multi-view Models for Glitch Classification

Non-cosmic, non-Gaussian disturbances known as "glitches", show up in gravitational-wave data of the Advanced Laser Interferometer Gravitational-wave Observatory, or aLIGO. In this paper, we propose a deep multi-view convolutional neural network to classify glitches automatically. The primary purpose of classifying glitches is to understand their characteristics and origin, which facilitates their removal from the data or from the detector entirely. We visualize glitches as spectrograms and leverage the state-of-the-art image classification techniques in our model. The suggested classifier is a multi-view deep neural network that exploits four different views for classification. The experimental results demonstrate that the proposed model improves the overall accuracy of the classification compared to traditional single view algorithms.Comment: Accepted to the 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'17

Theory of mind in bilingual and monolingual preschool children

This research examined whether theory of mind (ToM) development differs in bilingual and monolingual preschool children. Three false belief tasks were given to 163 Kurdish-Persian bilingual and Persian monolingual preschool children. Bilingual children performed significantly better than monolingual children in their ToM. Hierarchical multiple regression analysis revealed that, bilingualism contributed significantly to the prediction of preschoolers’ ToM development when age and verbal ability were controlled

The spiritual experiences of students of Iran University of Medical Sciences in 2020

Background: Psychologists consider the acceptance of spirituality as a cultural reality and by acknowledging the positive effects of spirituality on mental health, the World Health Organization also considers the spiritual dimension as the physical, social and emotional dimensions of human existence. Spirituality is a genuine and inner experience that It lies in the nature of every human being. The purpose of this study was to investigate the spiritual experiences of students of Iran University of Medical Sciences in 2020. Methods: The present study was descriptive-analytical. The sample size of 500 students of Iran University of Medical Sciences in 2020 was estimated. For sampling, a list of students was prepared from the faculty education and the sample was selected by regular random sampling method through random number generation software. The data collection tool was a questionnaire with demographic questions and spiritual experiences. The collected data were analyzed after completion with SPSS 20 software. A significance level of 0.05 was considered. Results: The mean score of the meaning-finding component in life was obtained at 57.98. There was a significant relationship between spiritual experiences and gender, age and educational level of students, while no significant relationship was found between spiritual experiences and marital status and residence. Conclusion: In order to ensure the spiritual health of students, it is necessary to plan properly to create a meaningful atmosphere in universities for different age and gender groups

Theory of mind, birth order, and siblings among preschool children.

This research investigated whether the number of siblings in the family facilitatesthe development of theory of mind (ToM) in preschool children. A battery of tests was administered to measure the ToM and verbal ability of one hundred and sixty three 3.6 to5.6 year-old children. No significant difference was found between ToM and siblings. Incontrast, a significant difference was found between ToM and birth order. Additionally, onundertaking a hierarchical multiple regression analysis, it was found that, over and aboveage and verbal ability, a significant contribution for birth order to ToM development wasobserved

Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science

(abridged for arXiv) With the first direct detection of gravitational waves, the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) has initiated a new field of astronomy by providing an alternate means of sensing the universe. The extreme sensitivity required to make such detections is achieved through exquisite isolation of all sensitive components of LIGO from non-gravitational-wave disturbances. Nonetheless, LIGO is still susceptible to a variety of instrumental and environmental sources of noise that contaminate the data. Of particular concern are noise features known as glitches, which are transient and non-Gaussian in their nature, and occur at a high enough rate so that accidental coincidence between the two LIGO detectors is non-negligible. In this paper we describe an innovative project that combines crowdsourcing with machine learning to aid in the challenging task of categorizing all of the glitches recorded by the LIGO detectors. Through the Zooniverse platform, we engage and recruit volunteers from the public to categorize images of glitches into pre-identified morphological classes and to discover new classes that appear as the detectors evolve. In addition, machine learning algorithms are used to categorize images after being trained on human-classified examples of the morphological classes. Leveraging the strengths of both classification methods, we create a combined method with the aim of improving the efficiency and accuracy of each individual classifier. The resulting classification and characterization should help LIGO scientists to identify causes of glitches and subsequently eliminate them from the data or the detector entirely, thereby improving the rate and accuracy of gravitational-wave observations. We demonstrate these methods using a small subset of data from LIGO's first observing run.Comment: 27 pages, 8 figures, 1 tabl

Adherence to a Paleolithic Diet in Combination With Lifestyle Factors Reduces the Risk for the Presence of Non-Alcoholic Fatty Liver Disease: A Case-Control Study

BackgroundEvidence suggests the role of changing traditional lifestyle patterns, such as Paleolithic, to the modern lifestyle in the incidence and epidemic of chronic diseases. The purpose of this study was to investigate the associations between the Paleolithic diet (PD) and the Paleolithic-like lifestyle and the risk of non-alcoholic fatty liver disease (NAFLD) among an adult population.Materials and MethodsThis case-control study was carried out among 206 patients with NAFLD and 306 healthy subjects aged >18 years. PD score was evaluated using a validated 168-item quantitative food frequency questionnaire. In addition, to calculate the Paleolithic-like lifestyle score, the components of physical activity, body mass index (BMI), and smoking status of the participants were combined with the score of the PD.ResultsThe mean PD and Paleolithic-like lifestyle scores were 38.11 ± 5.63 and 48.92 ± 6.45, respectively. After adjustment for potential confounders, higher scores of adherence to the PD diet conferred a protection for the presence of NAFLD [odds ratio (OR): 0.53; 95% confidence interval (CI): 0.28–0.98; P for trend = 0.021]. Furthermore, PD and healthy lifestyle habits were negatively associated with NAFLD (OR = 0.42, 95% CI 0.23–0.78; P for trend = 0.007).ConclusionOur data suggest that the PD alone and in combination with lifestyle factors was associated with decreased risk of NAFLD in a significant manner in the overall population. However, prospective studies are needed to further investigate this association

Neural Networks for Modeling Neural Spiking in S1 Cortex

Somatosensation is composed of two distinct modalities: touch, arising from sensors in the skin, and proprioception, resulting primarily from sensors in the muscles, combined with these same cutaneous sensors. In contrast to the wealth of information about touch, we know quite less about the nature of the signals giving rise to proprioception at the cortical level. Likewise, while there is considerable interest in developing encoding models of touch-related neurons for application to brain machine interfaces, much less emphasis has been placed on an analogous proprioceptive interface. Here we investigate the use of Artificial Neural Networks (ANNs) to model the relationship between the firing rates of single neurons in area 2, a largely proprioceptive region of somatosensory cortex (S1) and several types of kinematic variables related to arm movement. To gain a better understanding of how these kinematic variables interact to create the proprioceptive responses recorded in our datasets, we train ANNs under different conditions, each involving a different set of input and output variables. We explore the kinematic variables that provide the best network performance, and find that the addition of information about joint angles and/or muscle lengths significantly improves the prediction of neural firing rates. Our results thus provide new insight regarding the complex representations of the limb motion in S1: that the firing rates of neurons in area 2 may be more closely related to the activity of peripheral sensors than it is to extrinsic hand position. In addition, we conduct numerical experiments to determine the sensitivity of ANN models to various choices of training design and hyper-parameters. Our results provide a baseline and new tools for future research that utilizes machine learning to better describe and understand the activity of neurons in S1

Strange Animals and Creatures in Islamic Miniatures: Focusing on Miniatures of the Conference of the Birds

Strange animals and creatures have always existed in every mythological culture. In Iran's pre-Islamic and post-Islamic miniatures and reliefs, there are many strange animals and creatures such as dragons and phoenix which were associated with the Iranian culture and civilization. Because of presence of these strange creatures, particularly human life, these creatures are first used in mythological life and then symbolically to express human ideas. However, these animals were present in both mythology and epics and, later in the Islamic era, in the mystical stories, educational stories and admonishing anecdotes like Sanai, Attar, and Rumi. This study tends to investigate genealogy of strange animals and creatures in ancient Iranian reliefs and their continued presence in miniatures of Islamic era as well as presence of these creatures in miniatures which are based on Attar’s Conference of the Birds. In fact, this study reviews elements and symbolic concepts of animals, allowing a deeper understanding of function of elements and symbolism in works of Iranian miniaturists. Contemplation of miniatures, icons and the relationship between literature and miniatures will lead to many results in recognition of mystical intellectual foundations. Therefore, this study tends to investigate mysterious and unknown aspects of Iranian miniatures and find their relationship with culture and stories