Tracking at LHC

Precise tracking is an indispensable tool for the study of many phenomena at new energy frontier accessible with the CERN Large Hadron Collider (LHC). The tracking detectors of ATLAS and CMS have been designed to cope with the harsh experimental conditions of the LHC interaction region. In this paper, we discuss and compare the tracking performance of these two detectors

A Quantitative Morphological Analysis of Some Hypericum Species

Hypericum perforatum L. (Hypericaceae) is a medicinal plant of considerable interest for the therapeutic potentialities of its biologically active compounds. Due to the presence of hybrids and frequent adulterants from other species of Hypericum, the identification of the drug obtained of this species is difficult. Therefore, a quantitative morphological analysis of the leaf epidermises of H. hircinum L. and H. perfoliatum L. compared with H. perforatum L., carried out by means of scanning electron microscopy and image analysis, was performed to identify phytognostic markers useful for the characterization of these different Hypericum species. Size and shape parameters of the leaf surface cells have permitted a comparative study of the cogeneric species examined, providing a key factor in their recognition and/or selection. Unlike the methods employed so far, the results obtained by means of this innovative kind of analysis supply a valid criterion, not only for the morphological differentiation of the Italian Hypericum species studied, but also for an accurate and reproducible quality control of the commercial samples, often made up of drugs obtained from different species, subspecies and varieties

Identification of DC thermal steady-state differential inductance of ferrite power inductors

In this paper, we propose a method for the identification of the differential inductance of saturable ferrite inductors adopted in DC–DC converters, considering the influence of the operating temperature. The inductor temperature rise is caused mainly by its losses, neglecting the heating contribution by the other components forming the converter layout. When the ohmic losses caused by the average current represent the principal portion of the inductor power losses, the steady-state temperature of the component can be related to the average current value. Under this assumption, usual for saturable inductors in DC–DC converters, the presented experimental setup and characterization method allow identifying a DC thermal steady-state differential inductance profile of a ferrite inductor. The curve is obtained from experimental measurements of the inductor voltage and current waveforms, at different average current values, that lead the component to operate from the linear region of the magnetization curve up to the saturation. The obtained inductance profile can be adopted to simulate the current waveform of a saturable inductor in a DC–DC converter, providing accurate results under a wide range of switching frequency, input voltage, duty cycle, and out-put current values

Data-Driven Constraint Handling in Multi-Objective Inductor Design

This paper analyses the multi-objective design of an inductor for a DC-DC buck converter. The core volume and total losses are the two competing objectives, which should be minimised while satisfying the design constraints on the required differential inductance profile and the maximum overheating. The multi-objective optimisation problem is solved by means of a population-based metaheuristic algorithm based on Artificial Immune Systems (AIS). Despite its effectiveness in finding the Pareto front, the algorithm requires the evaluation of many candidate solutions before converging. In the case of the inductor design problem, the evaluation of a configuration is time-consuming. In fact, a non-linear iterative technique (fixed point) is needed to obtain the differential inductance profile of the configuration, as it may operate in conditions of partial saturation. However, many configurations evaluated during an optimisation do not comply with the design constraint, resulting in expensive and unnecessary calculations. Therefore, this paper proposes the adoption of a data-driven surrogate model in a pre-selection phase of the optimisation. The adopted model should classify newly generated configurations as compliant or not with the design constraint. Configurations classified as unfeasible are disregarded, thus avoiding the computational burden of their complete evaluation. Interesting results have been obtained, both in terms of avoided configuration evaluations and the quality of the Pareto front found by the optimisation procedure

CONTAINER LOCALISATION AND MASS ESTIMATION WITH AN RGB-D CAMERA

In the research area of human-robot interactions, the automatic estimation of the mass of a container manipulated by a person leveraging only visual information is a challenging task. The main challenges consist of occlusions, different filling materials and lighting conditions. The mass of an object constitutes key information for the robot to correctly regulate the force required to grasp the container. We propose a single RGB-D camera-based method to locate a manipulated container and estimate its empty mass i.e., independently of the presence of the content. The method first automatically selects a number of candidate containers based on the distance with the fixed frontal view, then averages the mass predictions of a lightweight model to provide the final estimation. Results on the CORSMAL Containers Manipulation dataset show that the proposed method estimates empty container mass obtaining a score of 71.08% under different lighting or filling conditions

Sarcopenia using muscle mass prediction model and cognitive impairment: A longitudinal analysis from the English longitudinal study on ageing

Background: Literature on the association between sarcopenia and cognitive impairment is largely unclear and mainly limited to non-European populations. Therefore, the aim of this study is to explore if the presence of sarcopenia at the baseline could increase the risk of cognitive impairment in a large cohort of older people participating to the English Longitudinal Study of Ageing (ELSA), over ten years of follow-up. Methods: Sarcopenia was diagnosed as having low handgrip strength and low skeletal muscle mass index at the baseline, using a muscle mass prediction model; cognitive function was evaluated in the ELSA through several tests. The results are reported in the whole sample adjusted for potential baseline confounders and after matching sarcopenic and non-sarcopenic participants with a propensity score. Results: 2738 people (mean age: 68.7 years, 54.4% males) were included. During the ten years of follow-up, sarcopenia was associated with significantly lower scores in memory (p < 0.001), verbal fluency (p < 0.001), immediate word recall (p <0.001), delayed word recall (p = 0.018), and in recall summary score (p < 0.001). After adjusting for eight potential confounders, the presence of sarcopenia was significantly associated with poor verbal fluency (odds ratio, OR= 1.417, 95% confidence intervals, CI= 1.181–1.700) and in propensity-score matched analyses (OR=1.272, 95%CI= 1.071- 1.511). Conclusions and implications: Sarcopenia was found to be associated with a significantly higher incidence of poor cognitive status in a large population of elderly people followed up for 10 years, suggesting it may be an important potential risk factor for dementia

Botulinum toxin type A combined with neurodynamic mobilization for upper limb spasticity after stroke: a case report

Objective: The purpose of this study is to report a case in which combinatory therapy of botulinum toxin type A (BoNT-A) and neurodynamic mobilization (NM) was used as treatment for a patient with severe upper limb spasticity and pain after stroke. Clinical Features: A 76-year-old male patient had spastic muscles in the upper limb 10 months after an ischemic stroke. Intervention and Outcome: The patient underwent combined treatment with BoNT-A and NM of the upper limb in 6 monthly applications. Evaluation was performed pretreatment, 3 months after the first injection, 3 months after the second injection, and at a follow-up session 9 months after starting the treatment. The following outcomes were measured: pain by using a numeric rating scale, spasticity by the Modified Ashworth Scale for Grading Spasticity, acceptance and emotional reaction to the treatment by the Hospital Anxiety and Depression Scale, and functionality by ranges of motion. The patient improved in all outcomes after treatment, and results were maintained during the follow-up sessions. Conclusion: The combined NM and BoNT-A treatment appeared to decrease pain and improve joint ranges of motion during treatment for this patient. The patient showed decreased anxiety and depression during and after the treatment.Fil: Villafañe, Jorge Hugo. Universidad Rey Juan Carlos; EspañaFil: Silva, Guillermo Benjamin. Universidad Católica de Córdoba. Facultad de Ciencias Químicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Chiarotto, Alessandro. Universidad Rey Juan Carlos; EspañaFil: Ragusa, Orazio L. F.. No especifíca

Magnetic loss analysis in coaxial magnetic gears

This paper proposes a procedure for computing magnetic losses in coaxial magnetic gears. These magnetic structures are made of permanent magnets and ferromagnetic poles in relative motion transferring torque between two shafts in a contactless way. The loss computation in magnetic materials is crucial to define the system performance. The flux distribution inside the iron parts is computed by means of the finite element method and a model of iron losses taking into account the rotational nature of the flux loci is applied. The procedure highlights where the major loss sources are present and gives the opportunity to evaluate some corrective measures to reduce their effects. Particular attention is devoted to the 2D modeling in presence of permanent magnets segmentatio

Investigation on the composition of agarose–collagen i blended hydrogels as matrices for the growth of spheroids from breast cancer cell lines

Three-dimensional (3D) cell culture systems mimic the structural complexity of the tissue microenvironment and are gaining increasing importance as they resemble the extracellular matrix (ECM)–cell and cell–cell physical interactions occurring in vivo. Several scaffold-based culture systems have been already proposed as valuable tools for large-scale production of spheroids, but they often suffer of poor reproducibility or high costs of production. In this work, we present a reliable 3D culture system based on collagen I-blended agarose hydrogels and show how the variation in the agarose percentage affects the physical and mechanical properties of the resulting hydrogel. The influence of the different physical and mechanical properties of the blended hydrogels on the growth, size, morphology, and cell motility of the spheroids obtained by culturing three different breast cancer cell lines (MCF-7, MDA-MB-361, and MDA-MB-231) was also evaluated. As proof of concept, the cisplatin penetration and its cytotoxic effect on the tumor spheroids as function of the hydrogel stiffness were also investigated. Noteworthily, the possibility to recover the spheroids from the hydrogels for further processing and other biological studies has been considered. This feature, in addition to the ease of preparation, the lack of cross-linking chemistry and the high re-producibility, makes this hydrogel a reliable biomimetic matrix for the growth of 3D cell structures