A Flexible Software Framework for Magnetic Measurements at CERN: a Prototype for the new Generation of Rotating Coils

A new software platform named FFMM (Flexible Framework for Magnetic Measurements) is under development at CERN (European Organization for Nuclear Research) in cooperation with the University of Sannio. The FFMM is aimed at facing the new test requirements arising after the production series of the Large Hadron Collider magnets. In particular, the basic concepts of the FFMM, its architecture, and the experimental implementation of a demonstrator are illustrated in order to show how the quality requirements of software flexibility and scalability are met

Fault self-defection of automatic testing systems by means of aspect-oriented programming

An Aspect Oriented approach to implement fault detection in automatic measurement systems is proposed. Faults are handled by means of "aspects", a specific software unit to better modularize issues transversal to many modules ("crosscutting concerns"). In this way, maintainability and reusability of a measurement software are improved: indeed, once a modification of the fault detection policy occurs, only the related aspects have to be modified. As an experimental case study, this technique has been applied to the fault self-detection of a flexible framework for magnetic measurements, developed at the European Organization for Nuclear Research (CERN)

Editorial: Advances and Challenges of RNAi Based Technologies for Plants—Volume 2

Editorial on the Research Topic: Advances and Challenges of RNAi Based Technologies for Plants—Volume

Smart monitoring system based on adaptive current control for superconducting cable test

A smart monitoring system for superconducting cable test is proposed with an adaptive currentcontrol of asuperconductingtransformer secondary. The design, based on Fuzzy Gain Scheduling, allows thecontrollerparameters to adapt continuously, and finely, to the working variations arising fromtransformer nonlineardynamics. The control system is integrated in a fully digital control loop, with all therelated benefits, i.e., high noise rejection, ease of implementation/modification, and soon. In particular, an accurate model of the system,controlled by aFuzzy Gain Scheduler of the superconducting transformer, was achieved by an experimental campaignthrough the working domain at several current ramp rates. The model performance wascharacterized by simulation, under all the main operating conditions, in order to guidethe controllerdesign. Finally, the proposed monitoring system was experimentally validated at EuropeanOrganization for Nuclear Research (CERN) in comparison to the state-of-the-artcontrol system[P. Arpaia, L. Bottura, G. Montenero, and S. LeNaour, “Performance improvement of a measurement station forsuperconductingcable test,” Rev. Sci. Instrum.83, 095111 (2012)] of theFacility for the Research on Superconducting Cables, achieving a significant performanceimprovement: a reduction in the system overshoot by 50%, with a related attenuationof the corresponding dynamic residual error (both absolute and RMS) up to 52%

Assessment of blood perfusion quality in laparoscopic colorectal surgery by means of Machine Learning

An innovative algorithm to automatically assess blood perfusion quality of the intestinal sector in laparoscopic colorectal surgery is proposed. Traditionally, the uniformity of the brightness in indocyanine green-based fluorescence consists only in a qualitative, empirical evaluation, which heavily relies on the surgeon’s subjective assessment. As such, this leads to assessments that are strongly experience-dependent. To overcome this limitation, the proposed algorithm assesses the level and uniformity of indocyanine green used during laparoscopic surgery. The algorithm adopts a Feed Forward Neural Network receiving as input a feature vector based on the histogram of the green band of the input image. It is used to (i) acquire information related to perfusion during laparoscopic colorectal surgery, and (ii) support the surgeon in assessing objectively the outcome of the procedure. In particular, the algorithm provides an output that classifies the perfusion as adequate or inadequate. The algorithm was validated on videos captured during surgical procedures carried out at the University Hospital Federico II in Naples, Italy. The obtained results show a classification accuracy equal to 99.9 % , with a repeatability of 1.9 %. Finally, the real-time operation of the proposed algorithm was tested by analyzing the video streaming captured directly from an endoscope available in the OR

Recycling of multilayer packaging waste with switchable anionic surfactants

Switchable Anionic Surfactants (SAS) were used for delaminating flexible packaging waste composed of various plastic layers and aluminium, thereby promoting the recycling of such waste streams from a circular economy perspective. The delamination protocol was optimized on de-pulped food and beverage cartons containing low-density polyethylene (LDPE) and aluminium, varying the carboxylic acid and its counterion constituting the SAS (C8[sbnd]C18 carboxylic acids as the anionic part; inorganic bases and primary, secondary and tertiary amines as the cationic one) their molar ratio (carboxylic acid: base molar ratio from 1:1 to 1:3), SAS concentration (0.15, 0.3 and 0.5 wt%), time (0.5–3 h) and material weight in input (1–10 wt%). High-quality LDPE and aluminium were separated and recovered by using a diluted solution of a surfactant based on lauric acid and triethanolamine (C12-TEA), with performances not achievable with other anionic or cationic surfactants available on the market. The C12-TEA solution was then applied to a large variety of multilayer waste materials composed of polypropylene and aluminium, polyolefins/polyethylene terephthalate/aluminium, giving a material separation dependant on the structure and composition of the material in input. At the end of the process, lauric acid was recovered from the aqueous solution used for washing the separated materials by tuning its water solubility with CO2

Integrating adverse effect analysis into environmental risk assessment for exotic generalist arthropod biological control agents: a three-tiered framework

Environmental risk assessments (ERAs) are required before utilizing exotic arthropods for biological control (BC). Present ERAs focus on exposure analysis (host/prey range) and have resulted in approval of many specialist exotic biological control agents (BCA). In comparison to specialists, generalist arthropod BCAs (GABCAs) have been considered inherently risky and less used in classical biological control. To safely consider exotic GABCAs, an ERA must include methods for the analysis of potential effects. A panel of 47 experts from 14 countries discussed, in six online forums over 12 months, scientific criteria for an ERA for exotic GABCAs. Using four case studies, a three-tiered ERA comprising Scoping, Screening and Definitive Assessments was developed. The ERA is primarily based on expert consultation, with decision processes in each tier that lead to the approval of the petition or the subsequent tier. In the Scoping Assessment, likelihood of establishment (for augmentative BC), and potential effect(s) are qualitatively assessed. If risks are identified, the Screening Assessment is conducted, in which 19 categories of effects (adverse and beneficial) are quantified. If a risk exceeds the proposed risk threshold in any of these categories, the analysis moves to the Definitive Assessment to identify potential non-target species in the respective category(ies). When at least one potential non-target species is at significant risk, long-term and indirect ecosystem risks must be quantified with actual data or the petition for release can be dismissed or withdrawn. The proposed ERA should contribute to the development of safe pathways for the use of low risk GABCAs

Murine Gamma Herpesvirus 68 Hijacks MAVS and IKKβ to Abrogate NFκB Activation and Antiviral Cytokine Production

Upon viral infection, mitochondrial antiviral signaling (MAVS) protein serves as a key adaptor to promote cytokine production. We report here that murine gamma herpesvirus 68 (γHV68), a model virus for oncogenic human gamma herpesviruses, subverts cytokine production via the MAVS adaptor. During early infection, γHV68 hijacks MAVS and IKKβ to induce the site-specific phosphorylation of RelA, a crucial subunit of the transcriptionally active NFκB dimer, which primes RelA for the proteasome-mediated degradation. As such, γHV68 efficiently abrogated NFκB activation and cytokine gene expression. Conversely, uncoupling RelA degradation from γHV68 infection promoted NFκB activation and elevated cytokine production. Loss of MAVS increased cytokine production and immune cell infiltration in the lungs of γHV68-infected mice. Moreover, exogenous expression of the phosphorylation- and degradation-resistant RelA variant restored γHV68-induced cytokine production. Our findings uncover an intricate strategy whereby signaling via the upstream MAVS adaptor is intercepted by a pathogen to nullify the immediate downstream effector, RelA, of the innate immune pathway