Design and control of an AS/RS

Automated storage/retrieval systems (AS/RSs) are a combination of equipment and controls which automatically handle, store and retrieve materials (components, tools, raw material and subassemblies) with great speed and accuracy. Consequently, they are widely used in industrial companies to manage products with cost-effective utilization of time, space and equipment. This paper presents a multi-parametric dynamic model of a product-to-picker storage system with class based storage allocation of products. Thousands of what-if scenarios are simulated in order to measure the impact of alternative design and operating configurations on the expected system performance and to identify the most critical factors and combinations of factors affecting the response of the system. Class based storage proves to be a very effective way of both reducing the picking cycle time and maximizing the throughput of the system. The rapid effectiveness of visual interactive simulation (VIS) in supporting the design (redesign) and control of new (existing) warehouses emerges, responding to the need for flexibility which modern companies need in order to adapt to strongly changing operating conditions quickly.     

BashDungeon

We present here the first of a series of video-games designed for teaching fundamentals of computer science to university students. We built the game as an adventure inside a dungeon, which aims at reproducing the topology of a Unix file system. Inside the different rooms, the players can learn how to use several Unix commands, from simple file system actions to complex text manipulations, to complete the quests and win the game. We performed a user test on a class of B.Sc. students at the University of Cagliari. The results show a good acceptance of the game metaphor and its effectiveness in supporting the learning process. We plan to expand this game and to design similar games for teaching object-oriented programming and algorithms and data structures.

     

Light Management in Organic Photovoltaics Processed in Ambient Conditions Using ZnO Nanowire and Antireflection Layer with Nanocone Array

Low carrier mobility and lifetime in semiconductor polymers are some of the main challenges facing the field of organic photovoltaics (OPV) in the quest for efficient devices with high current density. Finding novel strategies such as device structure engineering is a key pathway toward addressing this issue. In this work, the light absorption and carrier collection of OPV devices are improved by employment of ZnO nanowire (NW) arrays with an optimum NW length (50 nm) and antireflection (AR) film with nanocone structure. The optical characterization results show that ZnO NW increases the transmittance of the electron transporting layer as well as the absorption of the polymer blend. Moreover, the as‐deposited polymer blend on the ZnO NW array shows better charge transfer as compared to the planar sample. By employing PC70BM:PV2000 as a promising air‐stable active‐layer, power conversion efficiencies of 9.8% and 10.1% are achieved for NW devices without and with an AR film, indicating 22.5% and 26.2% enhancement in PCE as compared to that of planar device. Moreover, it is shown that the AR film enhances the water‐repellent ability of the OPV device.     

HNCR model following robust approach

This paper introduces a new model for Non‐Conformity Management, aimed at overcoming the limitations occurring when dealing with Non‐Conformities through traditional methods like Root Cause Analysis. The need to suggest a new approach to Non‐Conformities Management is connected to those situations where a large variety of Non‐Conformities is recorded, with a significant number of low‐impacting ones; addressing them directly through methods like Root Cause Analysis would often be not economically viable. In this context, the paper discusses Holistic Non‐Conformities Reduction (HNCR) approach as a suitable option to address this kind of business situations. In particular, the contribution of this paper is related to the development of HNCR model and the evaluation of how to properly structure the model and the flow that shall be followed. By clustering Non‐Conformities into flexible categories to be easily modified, expanded and rearranged through time, the HNCR model allows to identify new critical Non‐Conformity families, otherwise hardly detectable. A proof of concept relative to HNCR deployment is presented: 2 different scenarios are introduced, the first being the Non‐Conformities management within the extended supply chain of a large pharmaceutical distribution centre, while the second deals with Non‐Conformities in the context of a company's new programs development.     

Electroactive Ionic Soft Actuators with Monolithically Integrated Gold Nanocomposite Electrodes

Electroactive ionic gel/metal nanocomposites are produced by implanting supersonically accelerated neutral gold nanoparticles into a novel chemically crosslinked ion conductive soft polymer. The ionic gel consists of chemically crosslinked poly(acrylic acid) and polyacrylonitrile networks, blended with halloysite nanoclays and imidazolium‐based ionic liquid. The material exhibits mechanical properties similar to that of elastomers (Young's modulus ≈ 0.35 MPa) together with high ionic conductivity. The fabrication of thin (≈100 nm thick) nanostructured compliant electrodes by means of supersonic cluster beam implantation (SCBI) does not significantly alter the mechanical properties of the soft polymer and provides controlled electrical properties and large surface area for ions storage. SCBI is cost effective and suitable for the scaleup manufacturing of electroactive soft actuators. This study reports the high‐strain electromechanical actuation performance of the novel ionic gel/metal nanocomposites in a low‐voltage regime (from 0.1 to 5 V), with long‐term stability up to 76 000 cycles with no electrode delamination or deterioration. The observed behavior is due to both the intrinsic features of the ionic gel (elasticity and ionic transport capability) and the electrical and morphological features of the electrodes, providing low specific resistance (<100 Ω cm^?2), high electrochemical capacitance (≈mF g^?1), and minimal mechanical stress at the polymer/metal composite interface upon deformation.     

Antiferromagnetic Inverse Spinel Oxide LiCoVO4 with Spin-Polarized Channels for Water Oxidation

Exploring highly efficient catalysts for the oxygen evolution reaction (OER) is essential for water electrolysis. Cost-effective transition-metal oxides with reasonable activity are raising attention. Recently, OER reactants' and products' differing spin configurations have been thought to cause slow reaction kinetics. Catalysts with magnetically polarized channels could selectively remove electrons with opposite magnetic moment and conserve overall spin during OER, enhancing triplet state oxygen molecule evolution. Herein, antiferromagnetic inverse spinel oxide LiCoVO₄ is found to contain d⁷ Co²⁺ ions that can be stabilized under active octahedral sites, possessing high spin states S = 3/2 (t_2g⁵e_g²). With high spin configuration, each Co²⁺ ion has an ideal magnetic moment of 3 µ_B, allowing the edge-shared Co²⁺ octahedra in spinel to be magnetically polarized. Density functional theory simulation results show that the layered antiferromagnetic LiCoVO₄ studied contains magnetically polarized channels. The average magnetic moment (µ_ave) per transition-metal atom in the spin conduction channel is around 2.66 µ_B. Such channels are able to enhance the selective removal of spin-oriented electrons from the reactants during the OER, which facilitates the accumulation of appropriate magnetic moments for triplet oxygen molecule evolution. In addition, the LiCoVO₄ reported has been identified as an oxide catalyst with excellent OER activity.     

One-year persistence of neutralizing anti-SARS-CoV-2 antibodies in dialysis patients recovered from COVID-19

The immunological mechanisms that modulate immune response to SARS-CoV-2 infection remain elusive. Little is known on the magnitude and the durability of antibody response against COVID-19. There is consensus that patients with immune dysfunction, such as dialysis patients, may be unable to mount a robust and durable humoral immunity after infections. Recent studies showed that dialysis patients seroconverted after COVID-19, but data on the durability of the immune response are missing. We reported the data of a durable anti-spike protein seroconversion after natural SARS-CoV-2 infection in three patients on hemodialysis with a mean age of 67.2 ± 13.8 years. A mean antibody titer of 212.6 ± 174.9 UA/ml (Liaison®, DiaSorin) was found after one year (range, 366–374 days) from the diagnosis of COVID-19. In conclusion, this case series provided evidence that patients receiving hemodialysis who recovered from severe COVID-19 were able to mount a long-lasting immune response against SARS-CoV-2. Although the protective capacity of this long-term immunity remains to be determined, these patients did not report signs of reinfection after recovery from COVID-19.     

Anatomy of Skyrmionic Textures in Magnetic Multilayers

Room temperature magnetic skyrmions in magnetic multilayers are considered as information carriers for future spintronic applications. Currently, a detailed understanding of the skyrmion stabilization mechanisms is still lacking in these systems. To gain more insight, it is first and foremost essential to determine the full real‐space spin configuration. Here, two advanced X‐ray techniques are applied, based on magnetic circular dichroism, to investigate the spin textures of skyrmions in [Ta/CoFeB/MgO]_n multilayers. First, by using ptychography, a high‐resolution diffraction imaging technique, the 2D out‐of‐plane spin profile of skyrmions with a spatial resolution of 10 nm is determined. Second, by performing circular dichroism in resonant elastic X‐ray scattering, it is demonstrated that the chirality of the magnetic structure undergoes a depth‐dependent evolution. This suggests that the skyrmion structure is a complex 3D structure rather than an identical planar texture throughout the layer stack. The analyses of the spin textures confirm the theoretical predictions that the dipole–dipole interactions together with the external magnetic field play an important role in stabilizing sub‐100 nm diameter skyrmions and the hybrid structure of the skyrmion domain wall. This combined X‐ray‐based approach opens the door for in‐depth studies of magnetic skyrmion systems, which allows for precise engineering of optimized skyrmion heterostructures.     

PointProNets: Consolidation of Point Clouds with Convolutional Neural Networks

With the widespread use of 3D acquisition devices, there is an increasing need of consolidating captured noisy and sparse point cloud data for accurate representation of the underlying structures. There are numerous algorithms that rely on a variety of assumptions such as local smoothness to tackle this ill‐posed problem. However, such priors lead to loss of important features and geometric detail. Instead, we propose a novel data‐driven approach for point cloud consolidation via a convolutional neural network based technique. Our method takes a sparse and noisy point cloud as input, and produces a dense point cloud accurately representing the underlying surface by resolving ambiguities in geometry. The resulting point set can then be used to reconstruct accurate manifold surfaces and estimate surface properties. To achieve this, we propose a generative neural network architecture that can input and output point clouds, unlocking a powerful set of tools from the deep learning literature. We use this architecture to apply convolutional neural networks to local patches of geometry for high quality and efficient point cloud consolidation. This results in significantly more accurate surfaces, as we illustrate with a diversity of examples and comparisons to the state‐of‐the‐art.