Fusing NIR and Process Sensors Data for Polymer Production Monitoring

Process analytical technology and multivariate process monitoring are nowadays the most effective approaches to achieve real-time quality monitoring/control in production. However, their use is not yet a common practice, and industries benefit much less than they could from the outcome of the hundreds of sensors that constantly monitor production in industrial plants. The huge amount of sensor data collected are still mostly used to produce univariate control charts, monitoring one compartment at a time, and the product quality variables are generally used to monitor production, despite their low frequency (offline measurements at analytical laboratory), which is not suitable for real-time monitoring. On the contrary, it would be extremely advantageous to benefit from predictive models that, based on online sensors, will be able to return quality parameters in real time. As a matter of fact, the plant setup influences the product quality, and process sensors (flow meters, thermocouples, etc.) implicitly register process variability, correlation trends, drift, etc. When the available spectroscopic sensors, reflecting chemical composition and structure, consent to monitor the intermediate products, coupling process, and spectroscopic sensor and extracting/fusing information by multivariate analysis from this data would enhance the evaluation of the produced material features allowing production quality to be estimated at a very early stage. The present work, at a pilot plant scale, applied multivariate statistical process control (MSPC) charts, obtained by data fusion of process sensor data and near-infrared (NIR) probes, on a continuous styrene-acrylonitrile (SAN) production process. Furthermore, PLS regression was used for real-time prediction of the Melt Flow Index and percentage of bounded acrylonitrile (%AN). The results show that the MSPC model was able to detect deviations from normal operative conditions, indicating the variables responsible for the deviation, be they spectral or process. Moreover, predictive regression models obtained using the fused data showed better results than models computed using single datasets in terms of both errors of prediction and R2. Thus, the fusion of spectra and process data improved the real-time monitoring, allowing an easier visualization of the process ongoing, a faster understanding of possible faults, and real-time assessment of the final product quality

Real Time Quality Assessment of General Purpose Polystyrene (GPPS) by means of Multiblock-PLS Applied on On-line Sensors Data

In the petrochemical industry, in order to control the final product quality over time and to detect potential plant failures, the amount of lab (off-line) analysis performed every day is very demanding in terms of resources and time. Hence, at/in-line monitoring can be an efficient solution to decrease chemical wastes and operators’ efforts and to perform a fast detection of deviations from normal operative conditions. Moving toward this implementation requires both installation of analytical sensors and the development of models capable to predict in real time the quality parameters of the polymers based on both process and analytical sensors. The primary aim of the current work has been the development of real time monitoring models by advanced chemometric tools for the prediction of a General Purpose PolyStyrene (GPPS) quality property, fusing Near Infrared (NIR) and process sensors data. In the plant considered, in addition to standard process sensors, along the GPPS production line, operating in continuous, two NIR probes are installed in-line. After the arrangement of the available data in different blocks, aiming at studying the specific contribution of the two types of sensors and of the main phases of the process, Multiblock-PLS (MB-PLS) method was employed to fuse the different blocks and to assess which were the most relevant sensors and plant phases for the prediction of the two quality parameters. Good prediction performances were achieved, allowing identifying the most significant data blocks for the GPPS quality prediction. Moreover, prediction errors obtained by models computed without considering blocks of data belonging to the final stages of the process were similar to those involving all the available data blocks. Therefore, a good real time assessment of the GPPS quality can be obtained even before the production is completed, which is very promising in view of minimizing the number of off-line laboratory analyse

Toward a centralized data management center for integrated landslide monitoring in Emilia Romagna Region (Italy)

In Emilia Romagna Region, slope monitoring systems have become more widely used for hazard and risk management. However, they are generally non-interoperable. Moreover dispersion of monitoring data in several local databases have made data sharing among the involved institutional actors quite laborious and often untimely. A centralized database and a web-based portal that integrate infor- mation derived by different types of slope monitoring systems has been developed. The paper illustrates the specific features of the developed “SensorNet” and provides examples of its use for visualizing and analyzing in an integrated manner data from different monitoring systems. In perspective it could serve as an every-day operational tool for a timely reporting of landslide monitoring data for surveillance and warning purposes

Modified versus standard intention-to-treat reporting: Are there differences in methodological quality, sponsorship, and findings in randomized trials? A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Randomized controlled trials (RCTs) that use the modified intention-to-treat (mITT) approach are increasingly being published. Such trials have a preponderance of post-randomization exclusions, industry sponsorship, and favourable findings, and little is known whether in terms of these items mITT trials are different with respect to trials that report a standard intention-to-treat.</p> <p>Methods</p> <p>To determine differences in the methodological quality, sponsorship, authors' conflicts of interest, and findings among trials with different "types" of intention-to-treat, we undertook a cross-sectional study of RCTs published in 2006 in three general medical journals (the Journal of the American Medical Association, the New England Journal of Medicine and the Lancet) and three specialty journals (Antimicrobial Agents and Chemotherapy, the American Heart Journal and the Journal of Clinical Oncology). Trials were categorized based on the "type" of intention-to-treat reporting as follows: ITT, trials reporting the use of standard ITT approach; mITT, trials reporting the use of a "modified intention-to-treat" approach; and "no ITT", trials not reporting the use of any intention-to-treat approach. Two pairs of reviewers independently extracted the data in duplicate. The strength of the associations between the "type" of intention-to-treat reporting and the quality of reporting (sample size calculation, flow-chart, lost to follow-up), the methodological quality of the trials (sequence generation, allocation concealment, and blinding), the funding source, and the findings was determined. Odds ratios (OR) were calculated with 95% confidence intervals (CI).</p> <p>Results</p> <p>Of the 367 RCTs included, 197 were classified as ITT, 56 as mITT, and 114 as "no ITT" trials. The quality of reporting and the methodological quality of the mITT trials were similar to those of the ITT trials; however, the mITT trials were more likely to report post-randomization exclusions (adjusted OR 3.43 [95%CI, 1.70 to 6.95]; <it>P </it>< 0.001). We found a strong association between trials classified as mITT and for-profit agency sponsorship (adjusted OR 7.41 [95%CI, 3.14 to 17.48]; <it>P </it>< .001) as well as the presence of authors' conflicts of interest (adjusted OR 5.14 [95%CI, 2.12 to 12.48]; <it>P </it>< .001). There was no association between mITT reporting and favourable results; in general, however, trials with for-profit agency sponsorship were significantly associated with favourable results (adjusted OR 2.30; [95%CI, 1.28 to 4.16]; <it>P </it>= 0.006).</p> <p>Conclusion</p> <p>We found that the mITT trials were significantly more likely to perform post-randomization exclusions and were strongly associated with industry funding and authors' conflicts of interest.</p

A Multiblock Approach to Fuse Process and Near-Infrared Sensors for On-Line Prediction of Polymer Properties

Petrochemical companies aim at assessing final product quality in real time, in order to rapidly deal with possible plant faults and to reduce chemical wastes and staff effort resulting from the many laboratory analyses performed every day. In order to answer these needs, the main purpose of the current work is to explore the feasibility of multiblock regression methods to build real-time monitoring models for the prediction of two quality properties of Acrylonitrile-Butadiene-Styrene (ABS) by fusing near-infrared (NIR) and process sensors data. Data come from a production plant, which operates continuously, and where four NIR probes are installed on-line, in addition to standard process sensors. Multiblock-PLS (MB-PLS) and Response-Oriented Sequential Alternation (ROSA) methods were here utilized to assess which of such sensors and plant areas were the most relevant for the quality parameters prediction. Several prediction models were constructed exploiting measurements provided by sensors active at different ABS production process stages. Both methods provided good prediction performances and permitted identification of the most relevant data blocks for the quality parameters’ prediction. Moreover, models built without considering recordings from the final stage of the process yielded prediction errors comparable to those involving all available data blocks. Thus, in principle, allowing final ABS quality to be estimated in real-time before the end of the process itself

Increased expression of interleukin-22 in patients with giant cell arteritis

GCA is characterized by arterial remodelling driven by inflammation. IL-22 is an attractive cytokine which acts at the crosstalk between immune and stromal cells. We hypothesized that IL-22 might be induced in GCA and might be involved in disease pathogenesis

Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering.

Neuroprostheses are neuroengineering devices that have an interface with the nervous system and supplement or substitute functionality in people with disabilities. In the collective imagination, neuroprostheses are mostly used to restore sensory or motor capabilities, but in recent years, new devices directly acting at the brain level have been proposed. In order to design the next-generation of neuroprosthetic devices for brain repair, we foresee the increasing exploitation of closed-loop systems enabled with neuromorphic elements due to their intrinsic energy efficiency, their capability to perform real-time data processing, and of mimicking neurobiological computation for an improved synergy between the technological and biological counterparts. In this manuscript, after providing definitions of key concepts, we reviewed the first exploitation of a real-time hardware neuromorphic prosthesis to restore the bidirectional communication between two neuronal populations in vitro. Starting from that 'case-study', we provide perspectives on the technological improvements for real-time interfacing and processing of neural signals and their potential usage for novel in vitro and in vivo experimental designs. The development of innovative neuroprosthetics for translational purposes is also presented and discussed. In our understanding, the pursuit of neuromorphic-based closed-loop neuroprostheses may spur the development of novel powerful technologies, such as 'brain-prostheses', capable of rewiring and/or substituting the injured nervous system

Higher Frequencies of Lymphocytes Expressing the Natural Killer Group 2D Receptor in Patients With Behçet Disease

Behçet disease (BD) is an inflammatory systemic disease with a fluctuating course, which can affect the skin, eyes, central nervous system, musculoskeletal, gastrointestinal, and vascular systems. No laboratory tests are currently available for the diagnosis of BD and monitoring disease activity. Moreover there is a lack of knowledge on BD pathogenesis. This study focused on circulating Natural Killer (NK), NKT and T cells evaluated as CD3neg CD56pos, CD3pos CD56pos, and CD3pos CD56neg. Peripheral blood mononuclear cells (PBMCs) were collected from 38 BD patients and 20 healthy controls (HC). The frequencies of NK, NKT, and T cells expressing CD16, CD69, NKG2D, Nkp30, Nkp46, and NKG2A were assessed by flow cytometry. Cytotoxic potential of NK cells was evaluated by flow cytometry as the percentage of cells expressing the degranulation marker CD107a after incubation with K562 cells. The levels of 27 cytokines were determined in plasma with a multiplex bead-based assay. Higher percentages of NK, NKT, and T cells expressing NKG2D were detected in PBMCs of BD patients than HC. ROC curve analysis showed that the evaluation of NKG2Dpos NK, NKT, and T cell percentages discriminated between BD patients and HC. Moreover, there was a positive correlation between the BD Current Activity Form (BDCAF) scores and the frequencies of NKG2Dpos NK and NKT cells. A higher frequency of NK cells expressing CD107a was induced in PBMCs from BD patients than HC after incubation with K562 cells. Concentrations of IL-5, IL-6, IL-10, IL-13, IP-10, and MIP-1β were higher in plasma of BD patients than HC. Monitoring the frequencies of NKG2Dpos lymphocytes could help the clinicians in BD patients management. In addition, the increased expression of NKG2D in BD patients is likely involved in disease pathogenesis

Randomised controlled trials for evaluating the prescribing impact of information meetings led by pharmacists and of new information formats, in General Practice in Italy

<p>Abstract</p> <p>Background</p> <p>Suboptimal translation of valid and relevant information in clinical practice is a problem for all health systems. Lack of information independent from commercial influences, limited efforts to actively implement evidence-based information and its limited comprehensibility are important determinants of this gap and may influence an excessive variability in physicians' prescriptions. This is quite noticeable in Italy, where the philosophy and methods of Evidence-Based Medicine still enjoy limited diffusion among practitioners. Academic detailing and pharmacist outreach visits are interventions of proven efficacy to make independent and evidence-based information available to physicians; this approach and its feasibility have not yet been tested on a large scale and, moreover, they have never been formally tested in Italy.</p> <p>Methods/Design</p> <p>Two RCTs are planned:</p> <p>1) a two-arm cluster RCT, carried out in Emilia-Romagna and Friuli Venezia Giulia, will evaluate the effectiveness of small group meetings, randomising about 150 Primary Care Groups (corresponding to about 2000 GPs) to pharmacist outreach visits on two different topics. Physicians' prescriptions (expressed as DDD per 1000 inhabitants/day), knowledge and attitudes (evaluated through the answers to a specific questionnaire) will be compared for target drugs in the two groups (receiving/not receiving each topic).</p> <p>2) A three-arm RCT, carried out in Sardinia, will evaluate both the effectiveness of one-to-one meetings (one pharmacist visiting one physician per time) and of a 'new' information format (compared to information already available) on changing physicians' prescription of specific drugs. About 900 single GPs will be randomised into three groups: physicians receiving a visit supported by "traditional" information material, those receiving a visit with "new" information material on the same topic and those not receiving any visit/material.</p> <p>Discussion</p> <p>The two proposed RCTs aim to evaluate the organisational feasibility and barriers to the implementation of independent information programs led by NHS pharmacists. The objective to assess a 10 or 15% decreases in the prescription of the targeted drugs is quite ambitious in such 'natural' settings, which will be minimally altered by the interventions themselves; this in spite of the quite large sample sizes used comparing to other studies of these kind. Complex interventions like these are not easy to evaluate, given the many different variables into play. Anyway, the pragmatic nature of the two RCTs appears to be also one of their major strengths, helping to provide a deeper insight on what is possible to achieve – in terms of independent information – in a National Health System, with special reference to Italy.</p> <p>Trial registration</p> <p>ISRCTN05866587 (cluster RCT) and ISRCTN28525676 (single GPs RCT)</p