From a local community to a global influence. How elBulli restaurant created a new epistemic movement in the world of haute cuisine

Location plays a major role in the building of artistic, technological or scientific movements that emerge in specific locations before achieving a worldwide reach. However, a deeper understanding is needed about the interplay of local/global knowledge dynamics in the epistemic construction of a movement. Based on an in-depth longitudinal study of a critical case, this article sheds light on these issues by analysing the case of ‘techno-emotional cuisine’, a global gastronomic movement initiated and led by chef Ferran Adrià and his team at the restaurant elBulli in Catalonia (in Northern Spain). The results suggest that the dynamics of formation of a new epistemic movement depend on the form and nature of the interactions between the local buzz and global pipelines, and on the capacity of the originating community to develop and diffuse the new rules and ‘episteme’ on a global scale while consolidating them locally.     

Experimental investigation and numerical modelling of density-driven segregation in an annular shear cell

Granular materials segregate spontaneously due to differences in particle size, shape, density and flow behaviour. In this paper we experimentally investigate density-difference-driven segregation for a range of density ratios and a range of heavy particle concentrations. The experiments are conducted in an annular shear cell with rotating bumpy bottom that yields an exponential shear profile. The cell is initially filled with a layer of light particles and an upper layer of heavier grains and, on top, a load provides confinement. The segregation process is filmed through the transparent side-wall with a camera, and the evolution of particle concentration in space and time is evaluated by means of post-processing image analysis. We also propose a continuum-approach to model density-driven segregation. We use a segregation-diffusion transport equation, constitutive relations for effective viscosity and friction coefficient, and a segregation velocity analogous to the Stokes’ law. The model, which is validated by comparison with experimental findings, can successfully predict density-driven segregation at different density ratios and volumetric fraction.     

Construction of a polynomial invariant annihilation attack of degree 7 for T-310

Abstract

Cryptographic attacks are typically constructed by black-box methods and combinations of simpler properties, for example in [Generalised] Linear Cryptanalysis. In this article, we work with a more recent white-box algebraic-constructive methodology. Polynomial invariant attacks on a block cipher are constructed explicitly through the study of the space of Boolean polynomials which does not have a unique factorisation and solving the so-called Fundamental Equation (FE). Some recent invariant attacks are quite symmetric and exhibit some sort of clear structure, or work only when the Boolean function is degenerate. As a proof of concept, we construct an attack where a highly irregular product of seven polynomials is an invariant for any number of rounds for T-310 under certain conditions on the long term key and for any key and any IV. A key feature of our attack is that it works for any Boolean function which satisfies a specific annihilation property. We evaluate very precisely the probability that our attack works when the Boolean function is chosen uniformly at random.     

POD Evaluation: The Key Performance Indicator for NDE 4.0

The magnified images of thin wires, plastic, steel and lead plates which were obtained using linear microfocus hard bremsstrahlung generated through interaction of an 18 MeV electron beam with a 13 μm thick Ta foil oriented along the internal beam of a B-18 betatron are presented. The images indicate high absorption contrast of the objects due to a small horizontal size of the radiation source the width of which is 115-fold smaller than the diameter of the electron beam. Some results have shown a few peculiarities in the images which were not earlier observed. Several results were compared with the ones obtained earlier using the microfocus bremsstrahlung generated by the 18 MeV electron beam of B-18 in a narrow Si target.

     

Liquid phase exfoliated WS2 nanosheet-based gas sensor for room temperature NO2 detection

Journal of Materials Science: Materials in Electronics - Layered transition metal dichalcogenide (TMD) materials possess novel and unique semiconducting properties when exfoliated into thin sheets...     

Estimating joint kinematics of a whole body chain model with closed-loop constraints

Computer simulation and optimal control requiring actual joint kinematics and based on the definition of a chain model become more used in biomechanics for studying the musculo-skeletal coordination or optimizing the performance. For this purpose, numerical optimization methods using a chain model have been developed and showed promising results to estimate joint kinematics for open-loop movements. The aim of this study was to exhaustively compare the type of method and closed-loop constraint with four criteria: (i) reconstruction quality, (ii) loop closure respect, (iii) regularity of joint kinematics, and (iv) computational time. Five algorithms were tested to estimate the whole body joint kinematics of 10 elite athletes paddling an ergometer: global optimization (GO) without closed-loop constraints, with soft closed-loop constraints and with strict closed-loop constraints, and Kalman filter (KF) without closed-loop constraints and with soft closed-loop constraints. Each athlete was modelled using a personalized 17-segment 42-degree of freedom chain model. Input data were measured by a 10-camera motion capture system sampled at 250 Hz. ANOVAs were performed on the four criteria to identify differences between the five algorithms. Marker residuals were slightly increased by about 2–3 mm using GO under strict constraints and KF with soft constraints. Closed-loop errors were five times reduced when introducing constraints (10 to 2 mm). KF algorithms gave significantly smoother joint kinematics than the three GO algorithms. Computational time was largely increased by introducing closed-loop constraints in GO algorithm (from 21 to 200 ms per frame) while it remained unchanged in KF algorithm (about 60 ms per frame). To conclude, KF with soft constraints represents the best compromise between the four criteria.     

New Peptide-Conjugated Chlorin-Type Photosensitizer Targeting Neuropilin-1 for Anti-Vascular Targeted Photodynamic Therapy

Photodynamic therapy (PDT) is a cancer treatment modality that requires three components, namely light, dioxygen and a photosensitizing agent. After light excitation, the photosensitizer (PS) in its excited state transfers its energy to oxygen, which leads to photooxidation reactions. In order to improve the selectivity of the treatment, research has focused on the design of PS covalently attached to a tumor-targeting moiety. In this paper, we describe the synthesis and the physico-chemical and photophysical properties of six new peptide-conjugated photosensitizers designed for targeting the neuropilin-1 (NRP-1) receptor. We chose a TPC (5-(4-carboxyphenyl)-10,15, 20-triphenyl chlorine as photosensitizer, coupled via three different spacers (aminohexanoic acid, 1-amino-3,6-dioxaoctanoic acid, and 1-amino-9-aza-3,6,12,15-tetraoxa-10-on-heptadecanoic acid) to two different peptides (DKPPR and TKPRR). The affinity towards the NRP-1 receptor of the conjugated chlorins was evaluated along with in vitro and in vivo stability levels. The tissue concentration of the TPC-conjugates in animal model shows good distribution, especially for the DKPPR conjugates. The novel peptide–PS conjugates proposed in this study were proven to have potential to be further developed as future NRP-1 targeting photodynamic therapy agent.