Miniature bioreactors: current practices and future opportunities

This review focuses on the emerging field of miniature bioreactors (MBRs), and examines the way in which they are used to speed up many areas of bioprocessing. MBRs aim to achieve this acceleration as a result of their inherent high-throughput capability, which results from their ability to perform many cell cultivations in parallel. There are several applications for MBRs, ranging from media development and strain improvement to process optimisation. The potential of MBRs for use in these applications will be explained in detail in this review. MBRs are currently based on several existing bioreactor platforms such as shaken devices, stirred-tank reactors and bubble columns. This review will present the advantages and disadvantages of each design together with an appraisal of prototype and commercialised devices developed for parallel operation. Finally we will discuss how MBRs can be used in conjunction with automated robotic systems and other miniature process units to deliver a fully-integrated, high-throughput (HT) solution for cell cultivation process development

In Vivo Human-Like Robotic Phenotyping of Leaf and Stem Traits in Maize and Sorghum in Greenhouse

In plant phenotyping, the measurement of morphological, physiological and chemical traits of leaves and stems is needed to investigate and monitor the condition of plants. The manual measurement of these properties is time consuming, tedious, error prone, and laborious. The use of robots is a new approach to accomplish such endeavors, which enables automatic monitoring with minimal human intervention. In this study, two plant phenotyping robotic systems were developed to realize automated measurement of plant leaf properties and stem diameter which could reduce the tediousness of data collection compare to manual measurements. The robotic systems comprised of a four degree of freedom (DOF) robotic manipulator and a Time-of-Flight (TOF) camera. Robotic grippers were developed to integrate an optical fiber cable (coupled to a portable spectrometer) for leaf spectral reflectance measurement, a thermistor for leaf temperature measurement, and a linear potentiometer for stem diameter measurement. An Image processing technique and deep learning method were used to identify grasping points on leaves and stems, respectively. The systems were tested in a greenhouse using maize and sorghum plants. The results from the leaf phenotyping robot experiment showed that leaf temperature measurements by the phenotyping robot were correlated with those measured manually by a human researcher (R2 = 0.58 for maize and 0.63 for sorghum). The leaf spectral measurements by the phenotyping robot predicted leaf chlorophyll, water content and potassium with moderate success (R2 ranged from 0.52 to 0.61), whereas the prediction for leaf nitrogen and phosphorus were poor. The total execution time to grasp and take measurements from one leaf was 35.5±4.4 s for maize and 38.5±5.7 s for sorghum. Furthermore, the test showed that the grasping success rate was 78% for maize and 48% for sorghum. The experimental results from the stem phenotyping robot demonstrated a high correlation between the manual and automated stem diameter measurements (R2 \u3e 0.98). The execution time for stem diameter measurement was 45.3 s. The system could successfully detect and localize, and also grasp the stem for all plants during the experiment. Both robots could decrease the tediousness of collecting phenotypes compare to manual measurements. The phenotyping robots can be useful to complement the traditional image-based high-throughput plant phenotyping in greenhouses by collecting in vivo morphological, physiological, and biochemical trait measurements for plant leaves and stems. Advisors: Yufeng Ge, Santosh Pitl

Mass Spectrometry as a Workhorse for Preclinical Drug Discovery: Special Emphasis on Drug Metabolism and Pharmacokinetics

Mass spectrometry as an instrument is popular, given its sensitivity, selectivity, speed and robustness. In this chapter, we have briefly deliberated on various mass spec platforms, their hardware components and specific applications in preclinical drug discovery with a special emphasis on drug metabolism and pharmacokinetic assays. Basic principle of operation of mass spectrometer and various ionization techniques/mass analyzers was explicitly discussed. Compatibility of mass spectrometers with ultrafast LC and various throughput techniques, enabled evaluation of thousands of compounds with quick turnaround times. Faster generation of results corresponding to in vitro ADME and in vivo pharmacokinetic assays, aid medicinal chemists to refine their combinatorial synthetic chemistry efforts and expedite the lead optimization and identification phases of drug discovery. Mass spectrometer is a powerful tool for both qualitative and quantitative applications. While quantitative applications include measurement of absolute/relative concentrations, qualitative features assist in identification of molecular structures of metabolites and putative biotransformation pathways. Qualitative inputs are more precise and accurate, with the advent of high-resolution mass spectrometry technology. Although, mass spectrometry has many built-in advantages, it also suffers from matrix effects, as the samples analyzed are mostly of biological origin and are complex in nature. In this chapter, we have defined the nature of matrix effects and various approaches by which these matrix effects can be mitigated

Assessing the potential of autonomous submarine gliders for ecosystem monitoring across multiple trophic levels (plankton to cetaceans) and pollutants in shallow shelf seas

A combination of scientific, economic, technological and policy drivers is behind a recent upsurge in the use of marine autonomous systems (and accompanying miniaturized sensors) for environmental mapping and monitoring. Increased spatial–temporal resolution and coverage of data, at reduced cost, is particularly vital for effective spatial management of highly dynamic and heterogeneous shelf environments. This proof-of-concept study involves integration of a novel combination of sensors onto buoyancy-driven submarine gliders, in order to assess their suitability for ecosystem monitoring in shelf waters at a variety of trophic levels. Two shallow-water Slocum gliders were equipped with CTD and fluorometer to measure physical properties and chlorophyll, respectively. One glider was also equipped with a single-frequency echosounder to collect information on zooplankton and fish distribution. The other glider carried a Passive Acoustic Monitoring system to detect and record cetacean vocalizations, and a passive sampler to detect chemical contaminants in the water column. The two gliders were deployed together off southwest UK in autumn 2013, and targeted a known tidal-mixing front west of the Isles of Scilly. The gliders’ mission took about 40 days, with each glider travelling distances of >1000 km and undertaking >2500 dives to depths of up to 100 m. Controlling glider flight and alignment of the two glider trajectories proved to be particularly challenging due to strong tidal flows. However, the gliders continued to collect data in poor weather when an accompanying research vessel was unable to operate. In addition, all glider sensors generated useful data, with particularly interesting initial results relating to subsurface chlorophyll maxima and numerous fish/cetacean detections within the water column. The broader implications of this study for marine ecosystem monitoring with submarine gliders are discussed

Surface and Sub-Surface Analyses for Bridge Inspection

The development of bridge inspection solutions has been discussed in the recent past. In this dissertation, significant development and improvement on the state-of-the-art in the field of bridge inspection using multiple sensors (e.g. ground penetrating radar (GPR) and visual sensor) has been proposed. In the first part of this research (discussed in chapter 3), the focus is towards developing effective and novel methods for rebar detection and localization for sub-surface bridge inspection of steel rebars. The data has been collected using Ground Penetrating Radar (GPR) sensor on real bridge decks. In this regard, a number of different approaches have been successively developed that continue to improve the state-of-the-art in this particular research area. The second part (discussed in chapter 4) of this research deals with the development of an automated system for steel bridge defect detection system using a Multi-Directional Bicycle Robot. The training data has been acquired from actual bridges in Vietnam and validation is performed on data collected using Bicycle Robot from actual bridge located in Highway-80, Lovelock, Nevada, USA. A number of different proposed methods have been discussed in chapter 4. The final chapter of the dissertation will conclude the findings from the different parts and discuss ways of improving on the existing works in the near future

Underwater Glider Modelling And Analysis For Variable Control Parameters

Underwater glider is a type of autonomous underwater vehicle that can glide by controlling their buoyancy and attitude using internal actuators. By changing the vehicle’s buoyancy intermittently, forward motion can be achieved. Deriving the mathematical model directly from the system can be too complicated due to time constraints in prototyping development processes. This thesis presents the early development of the USM underwater glider platform consist of prototype development involves vehicle concept design using SolidworksTM, vehicle simulations by Computational Fluid Dynamics (CFD) and alternative way of modelling known as system identification in order to obtain the underwater glider system model. The appropriate control parameters for underwater glider control were determined by selecting the ballast rate as the input. Three aspects of the dynamics of a glider will be observed, i.e. net buoyancy, depth of the glider and pitching angle. The best three parametric models that are able to estimate the system correctly are chosen, and the fit between measured and estimated outputs is presented in order to get an optimal underwater glider vehicle model for USM underwater glider platform