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Characteristics and Applications of Micro Fluidized Beds (MFBs)
No full textFluidized beds (FBs) are commonly employed by many practical applications, and continuous optimization of FBs is necessary to improve their application performance. However, it is uneconomical and impractical to conduct the parametric investigation and kinetic studies based on a large-scale FB. Accordingly, the micro fluidized beds (MFBs), with excellent mass/heat transfer and sufficient mixing between phases, serve as the suitable platform for understanding the reaction behaviors and extracting kinetics on a laboratory scale. In this review, a global view of the properties of the whole MFBs family (including gas-solid, liquid-solid and gas-liquid-solid MFBs) are comprehensively presented. The differences and correlations of hydrodynamics (e.g. enhanced wall effect) between MFBs and full-scale FBs are discussed, and modified correlations for predicting the minimum fluidization velocity (umf) and hydrodynamic features (e.g. flow regimes and residence time) of MFBs are summarized. Additionally, the application of MFBs in the areas of kinetic studies, rapid reactions and pharmaceutical engineering are also discussed. Finally, the parameter correlation between MFBs and full-scale FBs is discussed critically, and scaling up/scaling out strategies for guiding the design of industrial FBs are proposed. The conclusions of this review serve the purpose of a bridge to link the findings from lab-scale MFBs with the design and optimization of industrial FB reactors
Evidential Reasoning for Preprocessing Uncertain Categorical Data for Trustworthy Decisions: An Application on Healthcare and Finance
No full textThe uncertainty attributed by discrepant data in AI-enabled decisions is a critical challenge in highly regulated domains such as health care and finance. Ambiguity and incompleteness due to missing values in output and input attributes, respectively, is ubiquitous in these domains. It could have an adverse impact on a certain unrepresented set of people in the training data without a developer’s intention to discriminate. The inherently non-numerical nature of categorical attributes than numerical attributes and the presence of incomplete and ambiguous categorical attributes in a dataset increases the uncertainty in decision-making. This paper addresses the challenges in handling categorical attributes as it is not addressed comprehensively in previous research. Three sources of uncertainties in categorical attributes are recognised in this research. The informational uncertainty, unforeseeable uncertainty in the decision task environment, and the uncertainty due to lack of pre-modelling explainability in categorical attributes are addressed in the proposed methodology on maximum likelihood evidential reasoning (MAKER). It can transform and impute incomplete and ambiguous categorical attributes into interpretable numerical features. It utilises a notion of weight and reliability to include subjective expert preference over a piece of evidence and the quality of evidence in a categorical attribute, respectively. The MAKER framework strives to integrate the recognised uncertainties in the transformed input data that allow a model to perceive data limitations during the training regime and acknowledge doubtful predictions by supporting trustworthy pre-modelling and post modelling explainability. The ability to handle uncertainty and its impact on explainability is demonstrated on a real-world healthcare and finance data for different missing data scenarios in three types of AI algorithms: deep-learning, tree-based, and rule-based model
Striving for evidence-based management of food allergies
No full textThis Issue of the Journal highlights several advances in Food Allergy diagnosis and management. It comes seven years after Du Toit et al’s seminal randomized, double-blinded, clinical trial Learning Early About Peanut (LEAP) that has led to a revolution in our thinking about food allergy prevention.1 The LEAP study clearly demonstrated that at least in high-risk infants and young children with eczema and egg allergy, food avoidance increases the prevalence of peanut allergy. The aim of this theme editorial is to highlight key take home messages and ongoing challenges presented in this Issue’s Rostrum and Review articles that clinicians currently face regarding the diagnosis and management of patients with suspected food allergies
Multivariate batch to batch optimisation of fermentation processes to improve productivity
No full textIncreasing the productivity of batch processes presents a complex challenge, with difficulties resulting from, amongst other things, the time-varying and non-linear characteristics that such processes exhibit. This paper presents an innovative optimisation technique which utilises a data-driven Gaussian process regression model, built on time-varying and non-linear historical process data, to iteratively increase batch productivity from one cycle to the next. Specifically, productivity is increased by making appropriate adjustments to batch cycle time and the trajectory of a manipulated variable. The capabilities of the proposed method are demonstrated using two benchmark fermentation simulations, Penicillin production (Pensim) and Saccharomyces Cerevisiae, where it is shown to achieve increases in productivity of between 60% and 97% compared with what was achieved using ‘golden batch’ conditions
The impact of glitches on young pulsar rotational evolution
No full textWe report on a timing programme of 74 young pulsars that have been observed by the Parkes 64-m radio telescope over the past decade. Using modern Bayesian timing techniques, we have measured the properties of 124 glitches in 52 of these pulsars, of which 74 are new. We demonstrate that the glitch sample is complete to fractional increases in spin-frequency greater than 90% g � 9:3 10􀀀9. We measure values of the braking index, n, in 33 pulsars. In most of these pulsars, their rotational evolution is dominated by episodes of spin-down with n > 10, punctuated by step changes in the spin-down rate at the time of a large glitch. The step changes are such that, averaged over the glitches, the long-term n is small. We find a near one-to-one relationship between the inter-glitch value of n and the change in spin-down of the previous glitch divided by the inter-glitch time interval. We discuss the results in the context of a range of physical models
Offset Learning based Channel Estimation for Intelligent Reflecting Surface-Assisted Indoor Communication
No full textThe emerging intelligent reflecting surface (IRS) can significantly improve the system capacity, and it has been regarded as a promising technology for the beyond fifth-generation (B5G) communications. For IRS-assisted multiple input multiple output (MIMO) systems, accurate channel estimation is a critical challenge. This severely restricts practical applications, particularly for resource-limited indoor scenario as it contains numerous scatterers and parameters to be estimated, while the number of pilots is limited. Prior art tackles these issues and associated optimization using mathematical-based statistical approaches, but are difficult to solve as the number of scatterers increase. To estimate the indoor channels with an affordable piloting overhead, we propose an offset learning (OL)-based neural network for channel estimation. The proposed OL-based estimator can dynamically trace the channel state information (CSI) without any prior knowledge of the IRS-assisted channel structure as well as indoor statistics. In addition, inspired by the powerful learning capability of convolutional neural network (CNN), CNN-based inversion blocks are developed in the offset estimation module to build the offset estimation operator. Numerical results show that the proposed OL-based estimator can achieve more accurate indoor CSI with a lower complexity as compared to the benchmark schemes
Enhancement-Mode Ga<sub>2</sub>O<sub>3</sub> FET With High Mobility Using p-Type SnO Heterojunction
No full textMechanically exfoliated gallium oxide (Ga2O3) nano sheets based filed-effect-transistors (FETs) with Al2O3/Ga2O3, indium gallium zinc oxide (IGZO)/Ga2O3 n-n, and SnO/Ga2O3 p-n heterojunctions in the back-channel were fabricated. In contrast to that Al2O3/Ga2O3 heterojunction induces negative threshold voltage (VTH) shift, both IGZO/Ga2O3 n-n and SnO/Ga2O3 p-n heterojunctions shift VTH positively. The Ga2O3 FET with 12 nm p-type SnO realizes enhanced-mode operation with VTH of 5.3 V by significantly shifting VTH of 40.3 V, high on current density of 14.1 mA/mm, and high electron mobility of 191 cm2V-1s-1, which is, to the best of our knowledge, the highest among the reported Ga2O3 FETs measured at room temperature.Index Terms—gallium oxide (Ga2O3), filed-effect-transistors (FETs), heterojunction, threshold voltage (VTH), p-type SnO,mobility (μ
Novel eco-efficient process for methyl methacrylate production
No full textMethyl methacrylate (MMA) is an essential chemical used as raw material for the production of other methacrylates and poly-MMA. There are various chemistry routes, available or not at industrial scale, to produce MMA. These routes use the same or different raw materials, and present common chemistry and processing steps. Many of these routes though, have as final step the esterification of methacrylic acid (MAA) with methanol (MeOH) to obtain MMA. However, there is no complete process described in the literature for this final esterification step. This paper is the first to propose a solid-based catalytic process for MMA production starting from MAA and MeOH, in a continuous reaction-separation-recycle (RSR) system. In this specific case, the RSR system is more suitable than reactive distillation due to the unfavorable ranking of boiling points and also due to the presence of several potentially hindering azeotropes. This work also provides an original framework for simulation of other MMA processes, by deriving detailed equilibrium and kinetic parameters based on literature experimental data. Rigorous process simulations are carried out in Aspen Plus and Aspen Plus Dynamics for the design and control of the new process. The flowsheet consists mainly of a fixed-bed tubular reactor followed by a sequence of three distillation columns coupled with a decanter. The results show that the process is technically feasible, cost effective in terms of total annualized costs, and with excellent sustainability metrics, requiring only 2.05 MJ/kg of MMA produced
Group Decision Making with Hesitant Fuzzy Linguistic Preference Relations Based on Modified Extent Measurement
No full textImmune Response and Safety of Viral Vaccines in Children with Autoimmune Diseases on Immune Modulatory Drug Therapy
No full textIntroduction: Children with autoimmune diseases often require treatment with systemic immunosuppressives. There are ongoing concerns regarding the efficacy and safety of vaccination, particularly live-attenuated viral vaccines in these patients.Areas covered: To evaluate the immunogenicity and safety of viral vaccines in children and young people treated with systemic immunosuppressive drugs for autoimmune diseases. A systemic literature review was performed using Pubmed and the following terms: virus, vaccination, autoimmune diseases, immunogenicity. English papers in subjects less than 21 years old were included. A total of 37 original articles were available, 25 on inactivated vaccines (influenza; hepatitis A virus; hepatitis B virus; human papillomavirus), and 12 on live-attenuated vaccines (varicella zoster virus; measles, mumps, and rubella). Viral vaccines were generally immunogenic and safe in children receiving immunosuppressive drugs including biologics. Use of low-dose glucocorticosteroids, disease-modifying antirheumatic drugs did not have a significant detrimental effect on vaccine immunogenicity, although there was anecdotal evidence of reduced immunogenicity in patients receiving high dose glucocorticoids and pulse cyclophosphamide. Patients on biologics mounted adequate seroprotective responses, but antibody titres tended to be lower. Both live-attenuated and inactivated vaccines were well tolerated and did not cause serious adverse events. Autoimmune disease activity was not adversely affected by vaccination.Expert commentary: Current evidence indicates that administration of viral vaccines to children and young people with autoimmune diseases receiving most systemic immunosuppressive drugs are immunogenic and safe. Patients on biologicals tend to have lower antibody titres. Those on high-dose glucocorticoids and pulse cyclophosphamide should avoid live viral vaccines