The Enhanced Definition and Control of Downstream Processing Operations

Monitoring product and contaminants is critically important at all stages of bioprocess operation, development and control. The availability of rapid measurements on product and key contaminants will yield a higher resolution of data points and will allow for more intelligent operation of a process and thereby enhance the definition and characterisation of a bioprocess. The need to control a bioseparation process is due to the variable nature of upstream conditions, process additives and sub-optimal performance of processing equipment which may lead to different requirements for the operating conditions either within batches or on batch to batch basis. Potential operations for downstream processing of intracellular proteins are the selective flocculation, packed bed and expanded bed chromatographic operations. These processes involve the removal of a large number of contaminants in a single dynamic step and hence are difficult unit operations to characterise and operate in an efficient and reproducible manner. In order to achieve rapid charactensation and control of these processes some form of rapid monitoring was required. A sampling and monitoring system for analysis of an enzyme produced intracellularly in S.cerevisiae, alcohol dehydrogenase (ADH), cell debris, protein and RNA contaminants has been constructed, with a measurement cycle time of 135 s. Both an extended Kalman filter and the Levenberg-Marquardt nonlinear least squares model parameter identification technique have been implemented for rapid process characterisation. Estimation of model parameters from at-line data enabled process performance predictions to be represented in an optimum graphical manner and the subsequent determination of ideal operating conditions in a feedback model based control configuration. The application of such a control strategy for the batch flocculation process yielded on average 92% accuracy in achieving optimum operating conditions. A structured and intelligent use of the at-line data would improve process characterisation in terms of speed and stability. It was demonstrated that rapid monitoring of the packed and expanded bed chromatographic operations yielded improved characterisation in terms of higher resolution data points, enabled real time process analysis and control of the load cycle. For the control of the expanded bed operation a predictive technique was applied to compensate for the large dead volume associated with this unit operation. The feedback control resulted in approximately 80% accurate breakthrough setpoint regulation

Therapeutic Applications of Monte Carlo Calculations in Nuclear Medicine

This book examines the applications of Monte Carlo (MC) calculations in therapeutic nuclear medicine, from basic principles to computer implementations of software packages and their applications in radiation dosimetry and treatment planning. It is written for nuclear medicine physicists and physicians as well as radiation oncologists, and can serve as a supplementary text for medical imaging, radiation dosimetry and nuclear engineering graduate courses in science, medical and engineering faculties. With chapters is written by recognised authorities in that particular field, the book covers the entire range of MC applications in therapeutic medical and health physics, from its use in imaging prior to therapy to dose distribution modelling targeted radiotherapy. The contributions discuss the fundamental concepts of radiation dosimetry, radiobiological aspects of targeted radionuclide therapy and the various components and steps required for implementing a dose calculation and treatment planning methodology in radioimmunotherapy. Some computer programmes (for example MIRDOSE, MABDOS, 3D-ID) are described and illustrated with some useful features and clinical applications. Other potential applications of MC techniques are also discussed together with computing aspects of radiation transport calculations Key Features - Contributions from leading experts in their field - Several introductory chapters to introduce the Monte Carlo method and nuclear medical imaging techniques as well as radiation biology concepts to allow a better understanding. - Many chapters in the book summarise scientific developments in the last couple of decades and others deal with completely new techniques fully developed in recent years. Readership Medical and health physicists, computationa

Supplemental peri-operative intravenous crystalloids for postoperative nausea and vomiting: an abridged Cochrane systematic review.

We conducted a Cochrane systematic review on the effectiveness of supplemental intravenous crystalloid administration in preventing postoperative nausea and vomiting. We included randomised controlled trials of patients undergoing surgery under general anaesthesia and given supplemental peri-operative intravenous crystalloid. Our primary outcomes were the risk of postoperative nausea and the risk of postoperative vomiting. We assessed the risk of bias for each included study and applied the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework for the certainty of evidence. We included 41 studies. We found that the intervention probably reduces the overall risk of postoperative nausea, the risk ratio (95%CI) being 0.62 (0.51-0.75) (I2  = 57%, p < 0.00001, 18 studies; 1766 participants; moderate-certainty evidence). It also probably reduces the risk of postoperative nausea within 6 h of surgery, with a risk ratio (95%CI) of 0.67 (0.58 to 0.78) (I2  = 9%, p < 0.00001, 20 studies; 2310 participants; moderate-certainty evidence) and by around 24 h, the risk ratio (95%CI) being 0.47 (0.32-0.69) (I2  = 38%, p = 0.0001, 17 studies; 1682 participants; moderate-certainty evidence). Supplemental intravenous crystalloid probably also reduces the overall risk of postoperative vomiting, with a risk ratio (95%CI) of 0.50 (0.40-0.63) (I2  = 31%, p < 0.00001, 20 studies; 1970 participants; moderate-certainty evidence). The beneficial effect on vomiting was seen both within 6 h and by around 24 h postoperatively

Presence analytics: density-based social clustering for mobile users

We demonstrate how social density-based clustering of WLAN traces can be utilised to detect granular social groups of mobile users within a university campus. Furthermore, the ability to detect such social groups, which can be linked to the learning activities taking place at target locations, provides an invaluable opportunity to understand the presence and movement of people within such an environment. For example, the proposed density-based clustering procedure, which we call Social-DBSCAN, has real potential to support human mobility studies such as the optimisation of space usage strategies. It can automatically detect the academic term period, the classes, and the attendance data. From a large Eduroam log of an academic site, we chose as a proof concept, selected locations with known capacity for the evaluation of our proposed method, which we successfully utilise to detect the regular learning activities at those locations, and to provide accurate estimates about the attendance levels over the academic term period

Constructing a unique profile for mobile user identification in location recommendation systems

It has been established in previous research that only a small number of spatio-temporal points are enough to uniquely identify an individual [1]. This means, if a user u visited the set of locations {a,b,...,z} then only a smal

Presence analytics: discovering meaningful patterns about human presence using WLAN digital imprints

In this paper we illustrates how aggregated WLAN activity traces provide anonymous information that reveals invaluable insight into human presence within a university campus. We show how technologies supporting pervasive services, such as WLAN, which have the potential to generate vast amounts of detailed information, provide an invaluable opportunity to understand the presence and movement of people within such an environment. We demonstrate how these aggregated mobile network traces offer the opportunity for human presence analytics in several dimensions: social, spatial, temporal and semantic dimensions. These analytics have real potential to support human mobility studies such as the optimisation of space use strategies. The analytics presented in this paper are based on recent WLAN traces collected at Birkbeck College of University of London, one of the participants in the Eduroam network

Virtual Reality Feedback Cues for Improvement of Gait in Patients with Parkinson's Disease

Background: Our aim was to study the effects of visual feedback cues, responding dynamically to patient's self‐motion and provided through a portable see‐through virtual reality apparatus, on the walking abilities of patients with Parkinson's disease. Methods: Twenty patients participated. On‐line and residual effects on walking speed and stride length were measured. Results Attaching the visual feedback device to the patient with the display turned off showed a negligible effect of about 2%. With the display turned on, 56% of the patients improved either their walking speed, or their stride length, or both, by over 20%. After device removal, and waiting for 15 minutes, the patients were instructed to walk again: 68% of the patients showed over 20% improvement in either walking speed or stride length or both. One week after participating in the first test, 36% of the patients showed over 20% improvement in baseline performance with respect to the previous test. Some of the patients reported that they still walked on the tiles in their minds. Discussion: Improvements in walking abilities were measured in patients with Parkinson's disease using virtual reality visual feedback cues. Residual effects suggest the examination of this approach in a comprehensive therapy program