Design and optimization of an electromagnetic servo braking system combining finite element analysis and weight-based multi-objective genetic algorithms

The purpose of this paper is to show the design and optimization of a novel electromagnetic servo brake incorporating an Antilock brake system (ABS) function by Multi-objective genetic algorithms. To consider different design requirements, three types of Axisymmetric Finite element (FE) models were initially formulated parametrically to determine the braking force and position of the pusher at each instant during operation of the proposed device. Using a combination of the FE models and Weight-based multi-objective genetic algorithms (WBMOGA), the optimal geometry and dimensions of the proposed FE models were determined while maximizing the braking force of the device and minimizing both the current supplied by the battery and the weight of the assembly. Once an optimal configuration for each type of servo brake designed had been achieved, three prototypes were built and validated experimentally on a conventional test bench. Finally, the prototype that performed best of the three prototypes was mounted and tested on a hybrid test bench with a realistic ABS device. The good agreement between the results obtained from the simulations and those measured experimentally, suggests that the combination of FE models and WBMOGA may be used successfully to design and optimize any complex electromechanical device.     

Chemisorption of CO2 in a gas–liquid vortex reactor: An interphase mass transfer efficiency assessment

To develop cost-effective CO₂ capture technology process intensification will play a vital role. In this work, the capabilities of a gas–liquid vortex reactor (GLVR) as novel process intensification equipment are evaluated by studying its interphase mass transfer parameters to build up the fundamentals for its future application to for example, CO₂ capture. The NaOH-CO₂ chemisorption system and Danckwerts' model are applied to obtain the effective interfacial area and liquid-side mass transfer coefficient. Results show that the gas–liquid contact in the GLVR is capable of both generating a large interfacial area in a small reactor volume and creating a region with high-energy dissipation to improve mass transfer. A comparison of the volumetric mass transfer coefficients with data reported in literature for conventional and intensified reactor types confirms a superior mass transfer efficiency and, most importantly, a favorable energetic efficiency of the GLVR.     

Quantum computation with write-only memory

In classical computation, a “write-only memory” (WOM) is little more than an oxymoron, and the addition of WOM to a (deterministic or probabilistic) classical computer brings no advantage. We prove that quantum computers that are augmented with WOM can solve problems that neither a classical computer with WOM nor a quantum computer without WOM can solve, when all other resource bounds are equal. We focus on realtime quantum finite automata, and examine the increase in their power effected by the addition of WOMs with different access modes and capacities. Some problems that are unsolvable by two-way probabilistic Turing machines using sublogarithmic amounts of read/write memory are shown to be solvable by these enhanced automata.     

Production of a high‐protein meal and fermentable sugars from defatted soybean meal,a co‐product of the soybean oil industry

The goal of this research was to produce a high‐protein meal by treating defatted soybean meal, a by‐product of soybean oil production, with dilute acid. Treatments were a mild hydrolysis at 80 °C with sulphuric acid at concentrations ranging from 0.5% to 2.0% (w/v) and times varying from 1 to 16 h that were arranged according to a central composite rotatable experimental design. The end products were an enhanced‐protein meal and a carbohydrate concentrate of fermentable and nonfermentable sugars. The highest protein content rise, from 48% to 58%, was for treatments with concentrations of acid ranging between 1.2% and 1.7% and times between 1.0 and 2.6 h. The maximum yield of fermentable sugar was 21.0% d.b. at 2.0% H₂SO₄ and treatments of at least 6 h. The conditions that provide a highest protein and sugar contents were the treatments with concentrations of sulphuric acid ranging from 0.9 to 1.9% H₂SO₄ for 1–4 h.     

Lead time prediction in unbalanced production systems

Whether job due dates are set internally or externally, it is critical for the shop floor controller to be able to accurately predict job lead times. Previous research has shown that utilizing information on the congestion levels along a job's route is more valuable than overall shop congestion levels when predicting job lead times. While this information is easily attained in a simulation model, in industrial applications the task may be considerably more difficult, especially when lot splitting is used to accelerate material flow. We examine the effectiveness of three lead time estimation procedures which utilize different shop information in bottleneck-constrained production systems where lot splitting is practiced under a variety of experimental conditions. The results indicate that accurate lead time estimates can be obtained using information pertaining solely to the bottleneck work centre when the bottleneck is at an entry work centre. This offers operations managers a substantial ease in implementation over previously reported methods. The results also show that the operations managers interested in accurately estimating job lead times are well advised to take advantage of the excess capacity at non-bottleneck work centres by performing additional setups, and take measures that reduce bottleneck shiftiness.     

Control loop diagnosis with ambiguous historical operating modes: Part 1. A proportional parametrization approach

Control-loop performance assessment methods have been evolving over the past two decades, with many different monitor algorithms being used to single out specific problems and determine the operating mode. However, a change in operating mode may affect multiple monitors, resulting in the possibility of conflicting assessments. Data-driven Bayesian methods were previously proposed which use multiple monitors to yield probabilistic assessments; however, training data for Bayesian methods requires complete knowledge of underlying operational modes. This paper proposes an approach based on proportionality parameters θ to address the problem of incomplete mode information in the training data; values in θ can be used to fill in missing information, and by varying θ one can determine the boundaries on a probabilistic diagnosis. Two diagnostic approaches are considered: the first type is direct probability approach, which can only be applied when historical data on the operation mode is sufficient and representative. The second type is the likelihood approach which can be applied to more general cases, including when the historical data is too limited to adequately represent mode frequency. In order to represent mode frequency, the likelihood approach takes into account prior probabilities of operating modes. The proposed methods are evaluated in two simulated chemical processes.     

Nanometrology in Emerging Economies: The Case of Mexico

Nanotechnology is a global phenomenon already impacting, in some way, the scientific, technological, economic and social development, and the culture, of emerging economies, like Mexico’s. As any new technology, on one hand it has the potential to be one of the main sources of productivity growth for these economies, but on the other it can also be the origin of drawbacks if no appropriate actions are taken about. The effects of such impact depend on how the country prepares itself concerning the aforementioned aspects of development. Metrology constitutes a discipline which is transversal to all of these aspects. It has to move forward in order to face the challenges derived from nanotechnology, in proportion to the particular status of the country. Metrology has to be seen as an essential part of nanotechnologies. Any activity within science and technology must be accompanied by reliable measurements. The current paper describes issues and challenges in metrology to be faced in Mexico concerning this technology.     

Vacuum insulation panels for building applications: A review and beyond

Vacuum insulation panels (VIPs) are regarded as one of the most promising high performance thermal insulation solutions on the market today. Thermal performances three to six times better than still-air are achieved by applying a vacuum to an encapsulated micro-porous material, resulting in a great potential for combining the reduction of energy consumption in buildings with slim constructions. However, thermal bridging due to the panel envelope and degradation of thermal performance through time occurs with current technology. Furthermore, VIPs cannot be cut on site and the panels are fragile towards damaging. These effects have to be taken into account for building applications as they may diminish the overall usability and thermal performance.This paper is as far as the authors know the first comprehensive review on VIPs. Properties, requirements and possibilities of foil encapsulated VIPs for building applications are studied based on available literature, emphasizing thermal bridging and degradation through time. An extension is made towards gas-filled panels and aerogels, showing that other high performance thermal insulation solutions do exist. Combining the technology of these solutions and others may lead to a new leap forward. Feasible paths beyond VIPs are investigated and possibilities such as vacuum insulation materials (VIMs) and nano insulation materials (NIMs) are proposed.     

A Collection of Designed Peptides to Target SARS-CoV-2 Spike RBD—ACE2 Interaction

The angiotensin-converting enzyme 2 (ACE2) is the receptor used by SARS-CoV and SARS-CoV-2 coronaviruses to attach to cells via the receptor-binding domain (RBD) of their viral spike protein. Since the start of the COVID-19 pandemic, several structures of protein complexes involving ACE2 and RBD as well as monoclonal antibodies and nanobodies have become available. We have leveraged the structural data to design peptides to target the interaction between the RBD of SARS-CoV-2 and ACE2 and SARS-CoV and ACE2, as contrasting exemplar, as well as the dimerization surface of ACE2 monomers. The peptides were modelled using our original method: PiPreD that uses native elements of the interaction between the targeted protein and cognate partner(s) that are subsequently included in the designed peptides. These peptides recapitulate stretches of residues present in the native interface plus novel and highly diverse conformations surrogating key interactions at the interface. To facilitate the access to this information we have created a freely available and dedicated web-based repository, PepI-Covid19 database, providing convenient access to this wealth of information to the scientific community with the view of maximizing its potential impact in the development of novel therapeutic and diagnostic agents.     

Cold Atmospheric Plasma Does Not Affect Stellate Cells Phenotype in Pancreatic Cancer Tissue in Ovo

Pancreatic ductal adenocarcinoma (PDAC) is a challenging neoplastic disease, mainly due to the development of resistance to radio- and chemotherapy. Cold atmospheric plasma (CAP) is an alternative technology that can eliminate cancer cells through oxidative damage, as shown in vitro, in ovo, and in vivo. However, how CAP affects the pancreatic stellate cells (PSCs), key players in the invasion and metastasis of PDAC, is poorly understood. This study aims to determine the effect of an anti-PDAC CAP treatment on PSCs tissue developed in ovo using mono- and co-cultures of RLT-PSC (PSCs) and Mia PaCa-2 cells (PDAC). We measured tissue reduction upon CAP treatment and mRNA expression of PSC activation markers and extracellular matrix (ECM) remodelling factors via qRT-PCR. Protein expression of selected markers was confirmed via immunohistochemistry. CAP inhibited growth in Mia PaCa-2 and co-cultured tissue, but its effectiveness was reduced in the latter, which correlates with reduced ki67 levels. CAP did not alter the mRNA expression of PSC activation and ECM remodelling markers. No changes in MMP2 and MMP9 expression were observed in RLT-PSCs, but small changes were observed in Mia PaCa-2 cells. Our findings support the ability of CAP to eliminate PDAC cells, without altering the PSCs.