C-Ring Contaminate Identification by Spectroscopy and Elemental Mapping

A silver plated steel c-ring used to seal two steel pieces together was found to have contamination upon disassembly. Auger and x-ray fluorescence spectroscopy and mapping were used to identify the contaminate as molybdenum disulfide lubricant. Recommendations were made to avoid such contamination in the future

Fecal lactoferrin predicts primary non-response to biologic agents in inflammatory bowel disease

3INTRODUCTION: Fecal Lactoferrin (FL) is a timely and accurate marker of inflammation in ulcerative colitis (UC) and Crohn's disease (CD). Aim of this study was to verify whether FL can predict primary non-response (PNR) to biologic agents during induction.METHODS: Retrospective outcome review in 27 patients (13 with CD and 14 with UC) tested for baseline FL and re-tested within a week after the first and second induction doses. Clinical/biochemical outcomes were evaluated at end of induction and at follow up (3-24 months).RESULTS: Compared to baseline, changes of the Harvey-Bradshaw (CD) and Partial Mayo Scoring (UC) indices at end of induction separated responders (18/27 or 67%) from non-responders (9/17 or 33%). In all patients the initial FL value at induction decreased compared to baseline, continuing to decrease after the following dose in clinical responders while bouncing back in the others. Models targeting the two consecutively decreased FL values or the second FL value compared to baseline or the second FL value compared to the first were able to accurately predict response at end of induction. Follow-up assessment confirmed clinical remission in initial responders (with FL values reduced on the average by 94±10% compared to baseline).CONCLUSIONS: In CD and UC patients during induction with biologic agents early FL measurements accurately separate clinical responders from those experiencing PNR. The method described here offers several potential advantages over other strategies to assess and manage these patients.openopenSorrentino, Dario; Nguyen, Vu Q; Love, KimSorrentino, Dario; Nguyen, Vu Q; Love, Ki

Capturing the Biologic Onset of Inflammatory Bowel Diseases: Impact on Translational and Clinical Science

While much progress has been made in the last two decades in the treatment and the management of inflammatory bowel diseases (IBD)-both ulcerative colitis (UC) and Crohn's Disease (CD)-as of today these conditions are still diagnosed only after they have become symptomatic. This is a major drawback since by then the inflammatory process has often already caused considerable damage and the disease might have become partially or totally unresponsive to medical therapy. Late diagnosis in IBD is due to the lack of accurate, non-invasive indicators that would allow disease identification during the pre-clinical stage-as it is often done in many other medical conditions. Here, we will discuss what is known about the biologic onset and pre-clinical CD with an emphasis on studies conducted in patients' first degree relatives. We will then review the possible strategies to diagnose IBD very early in time including screening, available disease markers and imaging, and the possible clinical implications of treating these conditions at or close to their biologic onset. Later, we will review the potential impact of conducting translational research in IBD during the pre-clinical stage, especially focusing on the role of the microbiome in disease etiology and pathogenesis. Finally, we will highlight possible future developments in the field and how they can impact IBD management and our scientific knowledge of these conditions

A Deep Learning Approach to Network Intrusion Detection

Software Defined Networking (SDN) has recently emerged to become one of the promising solutions for the future Internet. With the logical centralization of controllers and a global network overview, SDN brings us a chance to strengthen our network security. However, SDN also brings us a dangerous increase in potential threats. In this paper, we apply a deep learning approach for flow-based anomaly detection in an SDN environment. We build a Deep Neural Network (DNN) model for an intrusion detection system and train the model with the NSL-KDD Dataset. In this work, we just use six basic features (that can be easily obtained in an SDN environment) taken from the forty-one features of NSL-KDD Dataset. Through experiments, we confirm that the deep learning approach shows strong potential to be used for flow-based anomaly detection in SDN environments

Accurate Phase Calibration for Digital Beam-Forming in Multi-Transceiver HF Radar System

The TIGER-3 radar is being developed as an “all digital” radar with 20 integrated digital transceivers, each connected to a separate antenna. Using phased array antenna techniques, radiated power is steered towards a desired direction based on the relative phases within the array elements. This paper proposes an accurate phase measurement method to calibrate the phases of the radio output signals using Field Programmable Gate Array (FPGA) technology. The method sequentially measures the phase offset between the RF signal generated by each transceiver and a reference signal operated at the same frequency. Accordingly, the transceiver adjusts its phase in order to align to the reference phase. This results in accurately aligned phases of the RF output signals and with the further addition of appropriate phase offsets, digital beamforming (DBF) can be performed steering the beam in a desired direction. The proposed method is implemented on a Virtex-5 VFX70T device. Experimental results show that the calibration accuracy is of 0.153 degrees with 14 MHz operating frequency

Factors governing microalgae harvesting efficiency by flocculation using cationic polymers.

This study aims to elucidate the mechanisms governing the harvesting efficiency of Chlorella vulgaris by flocculation using a cationic polymer. Flocculation efficiency increased as microalgae culture matured (i.e. 35-45, 75, and > 97% efficiency at early, late exponential, and stationary phase, respectively. Unlike the negative impact of phosphate on flocculation in traditional wastewater treatment; here, phosphorous residue did not influence the flocculation efficiency of C. vulgaris. The observed dependency of flocculation efficiency on growth phase was driven by changes in microalgal cell properties. Microalgal extracellular polymeric substances (EPS) in both bound and free forms at stationary phase were two and three times higher than those at late and early exponential phase, respectively. Microalgae cells also became more negatively charged as they matured. Negatively charged and high EPS content together with the addition of high molecular weight and positively charged polymer could facilitate effective flocculation via charge neutralisation and bridging