Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach

Recent years have witnessed the rapid development of human activity recognition (HAR) based on wearable sensor data. One can find many practical applications in this area, especially in the field of health care. Many machine learning algorithms such as Decision Trees, Support Vector Machine, Naive Bayes, K-Nearest Neighbor, and Multilayer Perceptron are successfully used in HAR. Although these methods are fast and easy for implementation, they still have some limitations due to poor performance in a number of situations. In this paper, we propose a novel method based on the ensemble learning to boost the performance of these machine learning methods for HAR

Adaptive Genetic Algorithm for Crystal Structure Prediction

We present a genetic algorithm (GA) for structural search that combines the speed of structure exploration by classical potentials with the accuracy of density functional theory (DFT) calculations in an adaptive and iterative way. This strategy increases the efficiency of the DFT-based GA by several orders of magnitude. This gain allows considerable increase in size and complexity of systems that can be studied by first principles. The method's performance is illustrated by successful structure identifications of complex binary and ternary inter-metallic compounds with 36 and 54 atoms per cell, respectively. The discovery of a multi-TPa Mg-silicate phase with unit cell containing up to 56 atoms is also reported. Such phase is likely to be an essential component of terrestrial exoplanetary mantles.Comment: 14 pages, 4 figure

QUANTITATIVE DETERMINATION AND PREPARATIVE ISOLATION OF TWO MAJOR ALKALOIDS FROM THE VIETNAMESE MEDICINAL HERB EVODIAE FRUCTUS

Objective: To develop a simple and accurate HPLC-DAD method for simultaneous determination, the content of major components: limonin, evodiamine, and rutaecarpine in Evodiae fructus and evaluation the quality of Evodiae fructus sold in markets. Methods: Open column chromatography was used to separate and purify rutaecarpine and evodiamine, the two major alkaloids from Evodiae fructus extract as a laboratory standard. Chromatographic separation was achieved using a Germini C18 column (150 mm × 4.6 mm I.D., 5 µm), detected at 210 nm. The mobile phase consisted of acetonitrile (A), methanol (B), and water (C). The validated method simultaneously determined alkaloid content in 40 batches of samples collected from markets in different regions of Vietnam. Results: In one-step purification, our method yielded 326 mg of rutaecarpine and 128 mg of evodiamine from 3.2 g of crude extract, with purities of 98.9 and 98.5%, respectively. The structures of these compounds were identified using 1H NMR and 13C NMR. There was a significant correlation between alkaloid content and fruit size, with a Spearman correlation coefficient of>0.5 (p<0.001), and there was a large difference in alkaloid contents between three maturity degrees of the fruit. Open-mouth fruits and fruits with average sizes of 4 to 6 mm had the highest alkaloid contents, whereas closed-mouth fruits had the lowest. Conclusion: This study provided information on the standardization and quality control of evodiamine and rutaecarpine in Evodiae fructus, as well as a foundation for further pharmacological and toxicological studies

Fulminant Cerebral Malaria in a Swiss Patient

Abstract : Malaria remains the most important parasitic disease worldwide. Falciparum malaria is a medical emergency and requires immediate diagnosis and treatment. Cerebral malaria is a rapidly progressive, potentially fatal complication of Plasmodium falciparum infection. This case, including post-mortem observations, histology, and laboratory diagnosis, emphasizes the necessity of appropriate advice regarding malaria prophylaxis before travel to an endemic area. Malaria should always be considered in the differential diagnosis of patients presenting with fever and/or nonspecific flu-like symptoms after traveling to endemic countrie

Cryo-EM structure of a fungal mitochondrial calcium uniporter.

The mitochondrial calcium uniporter (MCU) is a highly selective calcium channel localized to the inner mitochondrial membrane. Here, we describe the structure of an MCU orthologue from the fungus Neosartorya fischeri (NfMCU) determined to 3.8 Å resolution by phase-plate cryo-electron microscopy. The channel is a homotetramer with two-fold symmetry in its amino-terminal domain (NTD) that adopts a similar structure to that of human MCU. The NTD assembles as a dimer of dimers to form a tetrameric ring that connects to the transmembrane domain through an elongated coiled-coil domain. The ion-conducting pore domain maintains four-fold symmetry, with the selectivity filter positioned at the start of the pore-forming TM2 helix. The aspartate and glutamate sidechains of the conserved DIME motif are oriented towards the central axis and separated by one helical turn. The structure of NfMCU offers insights into channel assembly, selective calcium permeation, and inhibitor binding

In Search of the Vortex Loop Blowout Transition for a type-II Superconductor in a Finite Magnetic Field

The 3D uniformly frustrated XY model is simulated to search for a predicted "vortex loop blowout" transition within the vortex line liquid phase of a strongly type-II superconductor in an applied magnetic field. Results are shown to strongly depend on the precise scheme used to trace out vortex line paths. While we find evidence for a transverse vortex path percolation transition, no signal of this transition is found in the specific heat.Comment: 11 pages, 17 figure

Nell-1 Is a Key Functional Modulator in Osteochondrogenesis and Beyond

Neural EGFL-like 1 (Nell-1) is a well-studied osteogenic factor that has comparable osteogenic potency with the Food and Drug Administration–approved bone morphogenic protein 2 (BMP-2). In this review, which aims to summarize the advanced Nell-1 research in the past 10 y, we start with the correlation of structural and functional relevance of the Nell-1 protein with the identification of a specific receptor of Nell-1, contactin-associated protein-like 4 (Cntnap4), for osteogenesis. The indispensable role of Nell-1 in normal craniofacial and appendicular skeletal development and growth was also defined by using the newly developed tissue-specific Nell-1 knockout mouse lines in addition to the existing transgenic mouse models. With the achievements on Nell-1’s osteogenic therapeutic evaluations from multiple preclinical animal models for local and systemic bone regeneration, the synergistic effect of Nell-1 with BMP-2 on osteogenesis, as well as the advantages of Nell-1 as an osteogenic protein with antiadipogenic, anti-inflammatory, and provascularized characteristics over BMP-2 in bone tissue engineering, is highlighted, which lays the groundwork for the clinical trial approval of Nell-1. At the molecular level, besides the mitogen-activated protein kinase (MAPK) signaling pathway, we emphasize the significant involvement of the Wnt/β-catenin pathway as well as the key regulatory molecules Runt-related transcription factor 2 (Runx2) in Nell-1-induced osteogenesis. In addition, the involvement of Nell-1 in chondrogenesis and its relevant pathologies have been revealed with the participation of the nuclear factor of activated T cells 1 (Nfatc1), Runx3, and Indian hedgehog (Ihh) signaling pathways, although the mechanistic insights of Nell-1’s osteochondrogenic property will be continuously evolving. With this perspective, we elucidate some emerging and novel functional properties of Nell-1 in oral-dental and neural tissues that will be the frontiers of future Nell-1 studies beyond the context of bone and cartilage. As such, the therapeutic potential of Nell-1 continues to evolve and grow with continuous pursuit. © International & American Associations for Dental Research 2019

Industrial Internet of Things, Big Data, and Artificial Intelligence in the Smart Factory: a survey and perspective

International audienceThanks to the rapid development and applications of advanced technologies, we are experiencing the fourth industrial revolution, or Industry 4.0, which is a revolution towards smart manufacturing. The wide use of cyber physical systems and Internet of Things leads to the era of Big Data in industrial manufacturing. Artificial Intelligence algorithms emerge as powerful analytics tools to process and analyze the Big Data. These advanced technologies result in the introduction of a new concept in the Industry 4.0: the smart Factory. In order to fully understand this new concept in the context of the Industry 4.0, this paper provides a survey on the key components of a smart factory and the link between them, including the Industrial Internet of Things, Big Data and Artificial Intelligence. Several studies and techniques that are used to enable smart manufacturing are reviewed. Finally, we discuss some perspectives for further researches