Bioprocess applications of model-based estimation techniques

The last decade has seen the development of a number of approaches for estimating those variables which are difficult to measure on-line in industrial process situations. Whilst a range of techniques is available, a common element is the use of process knowledge in the form of a system model. In the case of bioprocess systems, although a large range of models has been presented in the literature, their use in estimation schemes on an industrial scale has been limited. A number of reasons can be identified for their low level of utilisation. Of particular significance is the uncertainty which exists in quantifying system performance and the process-model mismatch which inevitably results. The level of ‘pre-defined model’ uncertainty, together with the knowledge gained during the course of the fermentation, serves to dictate estimator structure. The paper considers a range of estimation strategies and contrasts, through industrial applications, their performance characteristics and utility.     

Flow regime, hydrodynamics, floc size distribution and sludge properties in activated sludge bubble column, air-lift and aerated stirred reactors

This paper presents a comparative study how reactor configuration, sludge loading and air flowrate affect flow regimes, hydrodynamics, floc size distribution and sludge solids-liquid separation properties. Three reactor configurations were studied in bench scale activated sludge bubble column reactor (BCR), air-lift reactor (ALR) and aerated stirred reactor (ASR). The ASR demonstrated the highest capacity of gas holdup and resistance, and homogeneity in flow regimes and shearing forces, resulting in producing large numbers of small and compact flocs. The fluid dynamics in the ALR created regularly directed recirculation forces to enhance the gas holdup and sludge flocculation. The BCR distributed a high turbulent flow regime and non-homogeneity in gas holdup and mixing, and generated large numbers of larger and looser flocs. The sludge size distributions, compressibility and settleability were significantly influenced by the reactor configurations associated with the flow regimes and hydrodynamics.     

Microaerophilic conditions support elevated mixed culture polyhydroxyalkanoate (PHA) yields, but result in decreased PHA production rates

For commercial polyhydroxyalkanoate (PHA) production the objective is to maximise the fraction of feedstock that ends up as polymer, and minimise biomass growth. In this paper, oxygen limitation was applied to achieve this. Intracellular PHA content in mixed cultures in batch systems operated with low and high DO was compared. It is shown that in microaerophilic conditions a higher fraction of substrate is accumulated as PHA in comparison to high DO conditions, evidenced by elevated intracellular PHA content: in the order of 50% higher in the early stages of accumulation. However, the accumulation capacity is not affected by DO. The PHA content in biomass in both the low and high DO systems reached approximately 35%. The time taken for the PHA content in the low DO system to reach capacity was three times longer than in the high DO system.     

A Novel Technique for Early Detection of COVID-19

COVID-19 is a global pandemic disease, which results from a dangerous coronavirus attack, and spreads aggressively through close contacts with infected people and artifacts. So far, there is not any prescribed line of treatment for COVID-19 patients. Measures to control the disease are very limited, partly due to the lack of knowledge about technologies which could be effectively used for early detection and control the disease. Early detection of positive cases is critical in preventing further spread, achieving the herd immunity, and saving lives. Unfortunately, so far we do not have effective toolkits to diagnose very early detection of the disease. Recent research findings have suggested that radiology images, such as X-rays, contain significant information to detect the presence of COVID-19 virus in early stages. However, to detect the presence of the disease in in very early stages from the X-ray images by the naked eye is not possible. Artificial Intelligence (AI) techniques, machine learning in particular, are known to be very helpful in accurately diagnosing many diseases from radiology images. This paper proposes an automatic technique to classify COVID-19 patients from their computerized tomography (CT) scan images. The technique is known as Advanced Inception based Recurrent Residual Convolution Neural Network (AIRRCNN), which uses machine learning techniques for classifying data. We focus on the Advanced Inception based Recurrent Residual Convolution Neural Network, because we do not find it being used in the literature. Also, we conduct principal component analysis, which is used for dimensional deduction. Experimental results of our method have demonstrated an accuracy of about 99%, which is regarded to be very efficient.     

Review of weld repair procedures for low alloy steels designed to minimise the risk of future cracking

Weld repairs to aged and degenerated materials are prone to early failure on return to service unless strict preparation and controlled welding procedures are followed. This paper reviews and appraises the practical weld repair procedures, which have been developed or are currently being considered, for low alloy ferritic steels used within the Power, Petrochemical and Refinery Industries. The half-bead and temper-bead approaches both manual and automatic are considered in detail. The alternative use of high nickel weld fills for repair welding of low alloy ferritic base materials are also considered. Some conclusions about the expected life of repair welds are drawn from recently sponsored projects.     

Polymers for dye transfer inhibition in laundry applications

The deposition of dyes onto lightly colored garments, or onto lighter sections of multicolored garments, during laundry results in fabric discoloration. In particular, there is a requirement to restrict indigo dye transfer between garments. Polymers may be added to detergent formulations as dye transfer inhibitors to prevent dye transfer by blocking the deposition of fugitive dyes in aqueous solution. This article reports the generation of a range of dye transfer inhibitors produced by condensation reactions that are effective in preventing the transfer of unbound indigo dye to a variety of fiber types. Key design rules relating to polymer hydrophilicity and pendant polymer functionality were established for the creation of effective dye transfer inhibitors. Remarkably, polymers at concentrations as low as 0.1 mg/ml were found to be effective in inhibiting indigo deposition on a variety of fiber types, offering great promise for their inclusion within laundry detergent formulations as dye transfer inhibitors.     

Involvement of the dorsal paratrigeminal nucleus in visceral pain-related phenomena

Cyclophosphamide is an antitumor agent that generates evolving cystitis through the release of toxic urinary by-products, mostly acrolein, that attack the bladder walls. Using c-fos expression, which permits quantitative analysis of neural activity, we demonstrated that the paratrigeminal nucleus is involved in processing the inputs that this disease generates. c-Fos staining in the paratrigeminal nucleus increases regularly reaching a plateau over the 4 h postinjection period during which the disease develops. The degree of staining is directly correlated with that of the subnucleus medialis of the nucleus of the solitary tract, which is one of the main structures that processes cystitis-related inputs at the supraspinal level.     

Migraine and mitochondrial dysfunction

Like many others neurological diseases, mitochondrial involvement, by means of abnormalities in cerebral oxidative metabolism, may play a role in migraine. This review summarizes clinical data, in vivo magnetic resonance spectroscopy studies, biochemical assays and therapeutic results that support the "mitochondrial hypothesis of migraine".     

Impacts of structural characteristics on activated sludge floc stability

Activated sludge samples from seven full-scale plants were investigated in order to determine the relationship between floc structure and floc stability. Floc stability was determined by shear sensitivity and floc strength. Floc structure was considered in terms of two size scales, the micro- and macrostructure. The microstructure refers to the organization of the floc components, such as the individual microorganisms. The macrostructure refers to the overall floc. The floc macrostructure was characterized by filament index, sludge volume index, size, and fractal dimension. It had a significant impact on floc stability. Large and open flocs with low fractal dimensions containing large number of filaments were more shear sensitive and had lower floc strength compared to small and dense flocs. Fluorescent in situ hybridization analysis indicated that the organization of the bacterial cells might also have an effect on the floc stability.