Application of Artificial Intelligence in predicting earthquakes: state-of-the-art and future challenges

Predicting the time, location and magnitude of an earthquake is a challenging job as an earthquake does not show specific patterns resulting in inaccurate predictions. Techniques based on Artificial Intelligence (AI) are well known for their capability to find hidden patterns in data. In the case of earthquake prediction, these models also produce a promising outcome. This work systematically explores the contributions made to date in earthquake prediction using AI-based techniques. A total of 84 scientific research papers, which reported the use of AI-based techniques in earthquake prediction, have been selected from different academic databases. These studies include a range of AI techniques including rule-based methods, shallow machine learning and deep learning algorithms. Covering all existing AI-based techniques in earthquake prediction, this paper provides an account of the available methodologies and a comparative analysis of their performances. The performance comparison has been reported from the perspective of used datasets and evaluation metrics. Furthermore, using comparative analysis of performances the paper aims to facilitate the selection of appropriate techniques for earthquake prediction. Towards the end, it outlines some open challenges and potential research directions in the field

Crystal Structures of the structure-selective nuclease Mus81-Eme1 bound to flap DNA substrates

The Mus81-Eme1 complex is a structure-selective endonuclease with a critical role in the resolution of recombination intermediates during DNA repair after interstrand cross-links, replication fork collapse, or double-strand breaks. To explain the molecular basis of 3 ' flap substrate recognition and cleavage mechanism by Mus81-Eme1, we determined crystal structures of human Mus81-Eme1 bound to various flap DNA substrates. Mus81-Eme1 undergoes gross substrate-induced conformational changes that reveal two key features: (i) a hydrophobic wedge of Mus81 that separates pre- and post-nick duplex DNA and (ii) a 5 ' end binding pocket that hosts the 5 ' nicked end of post-nick DNA. These features are crucial for comprehensive protein-DNA interaction, sharp bending of the 3 ' flap DNA substrate, and incision strand placement at the active site. While Mus81-Eme1 unexpectedly shares several common features with members of the 5 ' flap nuclease family, the combined structural, biochemical, and biophysical analyses explain why Mus81-Eme1 preferentially cleaves 3 ' flap DNA substrates with 5 ' nicked ends.X11119Ysciescopu

Consecutive junction-induced efficient charge separation mechanisms for high-performance MoS2/quantum dot phototransistors

Phototransistors that are based on a hybrid vertical heterojunction structure of two-dimensional (2D)/quantum dots (QDs) have recently attracted attention as a promising device architecture for enhancing the quantum efficiency of photodetectors. However, to optimize the device structure to allow for more efficient charge separation and transfer to the electrodes, a better understanding of the photophysical mechanisms that take place in these architectures is required. Here, we employ a novel concept involving the modulation of the built-in potential within the QD layers for creating a new hybrid MoS2/PbS QDs phototransistor with consecutive type II junctions. The effects of the built-in potential across the depletion region near the type II junction interface in the QD layers are found to improve the photoresponse as well as decrease the response times to 950 μs, which is the faster response time (by orders of magnitude) than that recorded for previously reported 2D/QD phototransistors. Also, by implementing an electric-field modulation of the MoS2 channel, our experimental results reveal that the detectivity can be as large as 1 × 1011 jones. This work demonstrates an important pathway toward designing hybrid phototransistors and mixed-dimensional van der Waals heterostructures

A QoS-Aware Data Collection Protocol for LLNs in Fog-Enabled Internet of Things

© 2004-2012 IEEE. Improving quality of service (QoS) of low power and lossy networks (LLNs) in Internet of things (IoT) is a major challenge. Cluster-based routing technique is an effective approach to achieve this goal. This paper proposes a QoS-Aware clustering-based routing (QACR) mechanism for LLNs in Fog-enabled IoT which provides a clustering, a cluster head (CH) election, and a routing path selection technique. The clustering adopts the community detection algorithm that partitions the network into clusters with available nodes' connectivity. The CH election and relay node selection both are weighted by the rank of the nodes which take node's energy, received signal strength, link quality, and number of cluster members into consideration as the ranking metrics. The number of CHs in a cluster is adaptive and varied according to a cluster state to balance the energy consumption of nodes. Besides, the protocol uses the CH role handover technique during CH election that decreases the control messages for the periodic election and cluster formation in detail. An evaluation of the QACR has performed through simulations for various scenarios. The obtained results show that the QACR improves the QoS in terms of packet delivery ratio, latency, and network lifetime compared to the existing protocols

Adipose triglyceride lipase (ATGL) expression in human skeletal muscle is type I (oxidative) fiber specific

Accumulation of triacylglycerol (TAG) and lipid intermediates in skeletal muscle plays an important role in the etiology of insulin resistance and type 2 diabetes mellitus. Disturbances in skeletal muscle lipid turnover and lipolysis may contribute significantly to this. So far, knowledge on the regulation of muscle lipolysis is limited. Recently the identification of a new lipase was reported: adipose triglyceride lipase (ATGL). ATGL deficient animals show significant lipid accumulation in skeletal muscle, which may indicate that ATGL plays a pivotal role in skeletal muscle lipolysis. However, until now, it is still unknown whether ATGL protein is expressed in human skeletal muscle. Therefore, the aim of the present study was to investigate whether ATGL is expressed at the protein level in human skeletal muscle, and to examine whether its expression is fiber-type specific. To accomplish this, we established an imunohistochemical and immunofluorescent staining procedure to study ATGL protein expression in relation to fiber type in human vastus lateralis muscle of eight male subjects (BMI range: 21.0–34.5 kg/m2 and age: 38–59 years). In the present paper we report for the first time that ATGL protein is indeed expressed in human skeletal muscle. Moreover, ATGL is exclusively expressed in type I (oxidative) muscle fibers, suggesting a pivotal role for ATGL in intramuscular fatty acid handling, lipid storage and breakdown

The −675 4G/5G Polymorphism in Plasminogen Activator Inhibitor-1 Gene Is Associated with Risk of Asthma: A Meta-Analysis

BACKGROUND: A number of studies assessed the association of -675 4G/5G polymorphism in the promoter region of plasminogen activator inhibitor (PAI)-1 gene with asthma in different populations. However, most studies reported inconclusive results. A meta-analysis was conducted to investigate the association between polymorphism in the PAI-1 gene and asthma susceptibility. METHODS: Databases including Pubmed, EMBASE, HuGE Literature Finder, Wanfang Database, China National Knowledge Infrastructure (CNKI) and Weipu Database were searched to find relevant studies. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association in the dominant model, recessive model, codominant model, and additive model. RESULTS: Eight studies involving 1817 cases and 2327 controls were included. Overall, significant association between 4G/5G polymorphism and asthma susceptibility was observed for 4G4G+4G5G vs. 5G5G (OR = 1.56, 95% CI 1.12-2.18, P = 0.008), 4G/4G vs. 4G/5G+5G/5G (OR = 1.38, 95% CI 1.06-1.80, P = 0.02), 4G/4G vs. 5G/5G (OR = 1.80, 95% CI 1.17-2.76, P = 0.007), 4G/5G vs. 5G/5G (OR = 1.40, 95% CI 1.07-1.84, P = 0.02), and 4G vs. 5G (OR = 1.35, 95% CI 1.08-1.68, P = 0.008). CONCLUSIONS: This meta-analysis suggested that the -675 4G/5G polymorphism of PAI-1 gene was a risk factor of asthma

Determination of EGFR Endocytosis Kinetic by Auto-Regulatory Association of PLD1 with mu 2

Background: Upon ligand binding, cell surface signaling receptors are internalized through a process tightly regulated by endocytic proteins and adaptor protein 2 (AP2) to orchestrate them. Although the molecular identities and roles of endocytic proteins are becoming clearer, it is still unclear what determines the receptor endocytosis kinetics which is mainly regulated by the accumulation of endocytic apparatus to the activated receptors. Methodology/Principal Findings: Here we employed the kinetic analysis of endocytosis and adaptor recruitment to show that ??2, a subunit of AP2 interacts directly with phospholipase D (PLD)1, a receptor-associated signaling protein and this facilitates the membrane recruitment of AP2 and the endocytosis of epidermal growth factor receptor (EGFR). We also demonstrate that the PLD1-??2 interaction requires the binding of PLD1 with phosphatidic acid, its own product. Conclusions/Significance: These results suggest that the temporal regulation of EGFR endocytosis is achieved by auto-regulatory PLD1 which senses the receptor activation and triggers the translocation of AP2 near to the activated receptor.open3

Dynamical Boson Stars

The idea of stable, localized bundles of energy has strong appeal as a model for particles. In the 1950s John Wheeler envisioned such bundles as smooth configurations of electromagnetic energy that he called {\em geons}, but none were found. Instead, particle-like solutions were found in the late 1960s with the addition of a scalar field, and these were given the name {\em boson stars}. Since then, boson stars find use in a wide variety of models as sources of dark matter, as black hole mimickers, in simple models of binary systems, and as a tool in finding black holes in higher dimensions with only a single killing vector. We discuss important varieties of boson stars, their dynamic properties, and some of their uses, concentrating on recent efforts.Comment: 79 pages, 25 figures, invited review for Living Reviews in Relativity; major revision in 201

Efficacy of an Educational Material on Second Primary Cancer Screening Practice for Cancer Survivors: A Randomized Controlled Trial

<div><h3>Background</h3><p>Cancer surivors have limited knowledge about second primary cancer (SPC) screening and suboptimal rates of completion of screening practices for SPC. Our objective was to test the efficacy of an educational material on the knowledge, attitudes, and screening practices for SPC among cancer survivors.</p> <h3>Methods</h3><p>Randomized, controlled trial among 326 cancer survivors from 6 oncology care outpatient clinics in Korea. Patients were randomized to an intervention or an attention control group. The intervention was a photo-novel, culturally tailored to increase knowledge about SPC screening. Knowledge and attitudes regarding SPC screening were assessed two weeks after the intervention, and screening practices were assessed after one year.</p> <h3>Results</h3><p>At two weeks post-intervention, the average knowledge score was significantly higher in the intervention compared to the control group (0.81 vs. 0.75, P<0.01), with no significant difference in their attitude scores (2.64 vs. 2.57, P = 0.18). After 1 year of follow-up, the completion rate of all appropriate cancer screening was 47.2% in both intervention and control groups.</p> <h3>Conclusion</h3><p>While the educatinal material was effective for increasing knowledge of SPC screening, it did not promote cancer screening practice among cancer survivors. More effective interventions are needed to increase SPC screening rates in this population.</p> <h3>Trial Registration</h3><p>ClinicalTrial.gov <a href="http://clinicaltrials.gov/ct2/show/NCT00948337">NCT00948337</a></p> </div