Multi-task Neural Network for Non-discrete Attribute Prediction in Knowledge Graphs

Many popular knowledge graphs such as Freebase, YAGO or DBPedia maintain a list of non-discrete attributes for each entity. Intuitively, these attributes such as height, price or population count are able to richly characterize entities in knowledge graphs. This additional source of information may help to alleviate the inherent sparsity and incompleteness problem that are prevalent in knowledge graphs. Unfortunately, many state-of-the-art relational learning models ignore this information due to the challenging nature of dealing with non-discrete data types in the inherently binary-natured knowledge graphs. In this paper, we propose a novel multi-task neural network approach for both encoding and prediction of non-discrete attribute information in a relational setting. Specifically, we train a neural network for triplet prediction along with a separate network for attribute value regression. Via multi-task learning, we are able to learn representations of entities, relations and attributes that encode information about both tasks. Moreover, such attributes are not only central to many predictive tasks as an information source but also as a prediction target. Therefore, models that are able to encode, incorporate and predict such information in a relational learning context are highly attractive as well. We show that our approach outperforms many state-of-the-art methods for the tasks of relational triplet classification and attribute value prediction.Comment: Accepted at CIKM 201

Extreme long-lifetime self-assembled monolayer for air-stable molecular junctions

The molecular electronic devices based on self-assembled monolayer (SAM) on metal surfaces demonstrate novel electronic functions for device minimization yet are unable to realize in practical applications, due to their instability against oxidation of the sulfur-metal bond. This paper describes an alternative to the thiolate anchoring group to form stable SAMs on gold by selenides anchoring group. Because of the formation of strong selenium-gold bonds, these stable SAMs allow us to incorporate them in molecular tunnel junctions to yield extremely stable junctions for over 200 days. A detailed structural characterization supported by spectroscopy and first-principles modeling shows that the oxidation process is much slower with the selenium-gold bond than the sulfur-gold bond, and the selenium-gold bond is strong enough to avoid bond breaking even when it is eventually oxidized. This proof of concept demonstrates that the extraordinarily stable SAMs derived from sel-enides are useful for long-lived molecular electronic devices and can possibly become important in many air-stable applications involving SAMs.</p

Chinese Expert Consensus on Critical Care Ultrasound Applications at COVID-19 Pandemic

The spread of new coronavirus (SARS-Cov-2) follows a different pattern than previous respiratory viruses, posing a serious public health risk worldwide. World Health Organization (WHO) named the disease as COVID-19 and declared it a pandemic. COVID-19 is characterized by highly contagious nature, rapid transmission, swift clinical course, profound worldwide impact, and high mortality among critically ill patients. Chest X-ray, computerized tomography (CT), and ultrasound are commonly used imaging modalities. Among them, ultrasound, due to its portability and non-invasiveness, can be easily moved to the bedside for examination at any time. In addition, with use of 4G or 5G networks, remote ultrasound consultation can also be performed, which allows ultrasound to be used in isolated medial areas. Besides, the contact surface of ultrasound probe with patients is small and easy to be disinfected. Therefore, ultrasound has gotten lots of positive feedbacks from the frontline healthcare workers, and it has played an indispensable role in the course of COVID-19 diagnosis and follow up

Mechanical-force-induced non-local collective ferroelastic switching in epitaxial lead-titanate thin films.

Ferroelastic switching in ferroelectric/multiferroic oxides plays a crucial role in determining their dielectric, piezoelectric, and magnetoelectric properties. In thin films of these materials, however, substrate clamping is generally thought to limit the electric-field- or mechanical-force-driven responses to the local scale. Here, we report mechanical-force-induced large-area, non-local, collective ferroelastic domain switching in PbTiO3 epitaxial thin films by tuning the misfit-strain to be near a phase boundary wherein c/a and a1/a2 nanodomains coexist. Phenomenological models suggest that the collective, c-a-c-a ferroelastic switching arises from the small potential barrier between the degenerate domain structures, and the large anisotropy of a and c domains, which collectively generates much larger response and large-area domain propagation. Large-area, non-local response under small stimuli, unlike traditional local response to external field, provides an opportunity of unique response to local stimuli, which has potential for use in high-sensitivity pressure sensors and switches

The evaluation of acoustic characteristic performance on natural sound absorbing materials from cogon grass waste

In the past few decades, synthetic fibers are been used widely in the field of sound absorption due to their superior characteristics such as durable and chemical resistant. However, there are several disadvantages of synthetic fibers such as non-biodegradability and hazards to the health of human. In this research, the natural sound absorber from cogon grass was investigated. The objective of the research was to evaluate the performance of cogon grass physical characteristics on its acoustical behavior, to evaluate the effect of sodium hydroxide (NaOH) treatment times on physical and acoustical characteristics of cogon grass, to investigate the decay effects after it was left over for twelve months and lastly to compare and verify the acoustical results with theoretical models based on (Delany-Bazley and Miki Model). The measurement of acoustical characteristics which are sound absorption coefficient (SAC) and noise reduction coefficient (NRC) were done by using impedance tube method (ITM). The samples of cogon grass were tested in a way of the untreated and treated with NaOH in varied soaked hours which are one, two, three, four and five hours. Scanning electron microscope (SEM) and density kit were used to investigate physical characteristics. The research confirmed that physical characteristics of tortuosity and airflow resistivity values tend to increase with the increment of treatment times, but the density and porosity tend to decrease. Untreated samples were tested with varied thicknesses of 10, 20, 30, 40 and 50mm. The results show SAC value increases when the thickness of the sample was increased. Treated samples results show the least treated sample (1 hour) reached the maximum SAC value and indicated the highest value of NRC which is 0.50. The results also show a reduction in sound absorption value after the samples were left for twelve months. Verification parts demonstrated that Delany-Bazley and Miki Model can predict approximately pattern compared with ITM results because of the theoretical models are developed by a simple empirical model approach. Overall, cogon grass samples have the good characteristics to be an acoustic material component

An outbreak of rotavirus-related acute gastroenteritis of childcare center in Guangzhou, southern China

Rotavirus is the most common cause of severe diarrhea in children under 5 y old in the world. The study aims to explore the relationship between rotavirus vaccination and infection in the outbreak of rotavirus gastroenteritis in a childcare center. Earlier immunization and high vaccination rate should be encouraged

Has the establishment of green finance reform and innovation pilot zones improved air quality? Evidence from China

Abstract The role of finance in environmental sustainability is becoming increasingly important. This study conducts a quasi-natural experiment using a sample of 146 prefecture-level cities from 2015 to 2019. It adopts difference-in-differences to examine the impact of China’s green finance reform and innovations pilot zones (GFRIs) on urban air quality. The findings show that air quality has improved after the establishment of GFRIs, indicating that GFRIs have the potential to control air pollution levels. The mechanism tests indicate that the GFRIs are conducive to improving air quality through industrial structure upgrading and green innovation. Furthermore, the heterogeneity analyses show that the air quality in the south of the Qinling Mountains-Huaihe River line, in large and well-developed financially scaled cities, has improved significantly after the establishment of GFRIs