Interactive batch process schedule optimization and decision-making using multiobjective genetic algorithms

A multiobjective genetic algorithm (MOGA) is applied to a test batch scheduling problem to optimize five objectives simultaneously. The design of the MOGA allows an emphasis on human interaction with the optimization process, including the ability to change priorities of preferences and plant data interactively, and to allow the MOGA to make decisions regarding batch size and the rule task allocation. Experimental results demonstrate the development of this technique, allowing the combination of human expertise and MOGA optimization power to provide scheduling solutions to a highly complex problem

The M-CAT's out of the bag: A paper-based microfluidic immunoassay for the rapid detection of mephedrone

This paper reports a paper-based microfluidic competitive immunoassay for the detection of mephedrone, a new psychoactive substance (NPS). Using the proposed system, limits of detection of 4.078 μg mL-1 and 1.597 μg mL-1 for aqueous mephedrone and spiked urine samples, respectively, were obtained, with these values enabling the detection of clinically relevant concentrations of mephedrone. The proposed device has the opportunity to provide rapid, on-site testing, within either a forensic or clinical setting, for NPSs

Combining Electro-Osmotic Flow and FTA® Paper for DNA Analysis on Microfluidic Devices

FTA® paper can be used to protect a variety of biological samples prior to analysis, facilitating ease-of-transport to laboratories or long-term archive storage. The use of FTA® paper as a solid phase eradicates the need to elute the nucleic acids from the matrix prior to DNA amplification, enabling both DNA purification and polymerase chain reaction (PCR)-based DNA amplification to be performed in a single chamber on the microfluidic device. A disc of FTA® paper, containing a biological sample, was placed within the microfluidic device on top of wax-encapsulated DNA amplification reagents. The disc containing the biological sample was then cleaned up using Tris-EDTA (TE) buffer, which was passed over the disc, via electro-osmotic flow, in order to remove any potential inhibitors of downstream processes. DNA amplification was successfully performed (from buccal cells, whole blood and semen) using a Peltier thermal cycling system, whereupon the stored PCR reagents were released during the initial denaturing step due to the wax barrier melting between the FTA® disc and PCR reagents. Such a system offers advantages in terms of a simple sample introduction interface and the ability to process archived samples in an integrated microfluidic environment with minimal risk of contamination

Novel detection of provenance in the illegal wildlife trade using elemental data

© 2018, The Author(s). Despite being the fourth largest criminal market in the world, no forensic tools have been sufficiently developed to accurately determine the legal status of seized animals and their parts. Although legal trading is permissible for farmed or captive-bred animals, many animals are illegally removed from the wild and laundered by masquerading them as captive bred. Here we present high-resolution x-ray fluorescence (XRF) as a non-invasive and cost-effective tool for forensic classification. We tested the efficacy of this technique by using machine learning on a training set of zoo specimens and wild-caught individuals of short-beaked echidnas (Tachyglossus aculeatus), a small insectivorous monotreme in Australia. XRF outperformed stable isotope analysis (δ13C, δ15N), reducing overall classification error below 4%. XRF has the added advantage of providing samples every 200 μm on a single quill, enabling 100% classification accuracy by taking the consensus of votes per quill. This accurate and cost-effective forensic technique could provide a much needed in situ solution for combating the illegal laundering of wildlife, and conversely, assist with certification of legally bred animals

Evaluation of an Online Instructional Database Accessed by QR Codes To Support Biochemistry Practical Laboratory Classes

An online instructional database containing information on commonly used pieces of laboratory equipment was created. In order to make the database highly accessible and to promote its use, QR codes were utilized. The instructional materials were available anytime and accessed using QR codes located on the equipment itself and within undergraduate student practical handouts. The database and access mechanism was evaluated during multiple undergraduate practical sessions, and the students were able to provide feedback through completion of a questionnaire. The majority of the participating students reported that the QR Instructor was easy or very easy to use (89%) and made using the laboratory equipment easier or much easier (70%). Just under two-thirds (63%) of the students felt that having used the QR Instructor they were more confident in using the equipment than before, and three-quarters (75%) of students stated that they felt better or much better equipped to use similar equipment in their future employment. Overall, 90% of those students who responded to the questionnaire said that they would recommend the use of the online instructional database. The proposed system therefore has been shown to enable easy access for students to online instructional information as well as enhancing the learning experience with increased student confidence

Oscillatory, Computational, and Behavioral Evidence for Impaired GABAergic Inhibition in Schizophrenia

The dysconnection hypothesis of schizophrenia (SZ) proposes that psychosis is best understood in terms of aberrant connectivity. Specifically, it suggests that dysconnectivity arises through aberrant synaptic modulation associated with deficits in GABAergic inhibition, excitation-inhibition balance and disturbances of high-frequency oscillations. Using a computational model combined with a graded-difficulty visual orientation discrimination paradigm, we demonstrate that, in SZ, perceptual performance is determined by the balance of excitation-inhibition in superficial cortical layers. Twenty-eight individuals with a DSM-IV diagnosis of SZ, and 30 age- and gender-matched healthy controls participated in a psychophysics orientation discrimination task, a visual grating magnetoencephalography (MEG) recording, and a magnetic resonance spectroscopy (MRS) scan for GABA. Using a neurophysiologically informed model, we quantified group differences in GABA, gamma measures, and the predictive validity of model parameters for orientation discrimination in the SZ group. MEG visual gamma frequency was reduced in SZ, with lower peak frequency associated with more severe negative symptoms. Orientation discrimination performance was impaired in SZ. Dynamic causal modeling of the MEG data showed that local synaptic connections were reduced in SZ and local inhibition correlated negatively with the severity of negative symptoms. The effective connectivity between inhibitory interneurons and superficial pyramidal cells predicted orientation discrimination performance within the SZ group; consistent with graded, behaviorally relevant, disease-related changes in local GABAergic connections. Occipital GABA levels were significantly reduced in SZ but did not predict behavioral performance or oscillatory measures. These findings endorse the importance, and behavioral relevance, of GABAergic synaptic disconnection in schizophrenia that underwrites excitation-inhibition balance

Associations between data-driven lifestyle profiles and cognitive function in the AusDiab study

Background: Mounting evidence highlights the importance of combined modifiable lifestyle factors in reducing risk of cognitive decline and dementia. Several a priori additive scoring approaches have been established; however, limited research has employed advanced data-driven approaches to explore this association. This study aimed to examine the association between data-driven lifestyle profiles and cognitive function in community-dwelling Australian adults. Methods: A cross-sectional study of 4561 Australian adults (55.3% female, mean age 60.9 ± 11.3 years) was conducted. Questionnaires were used to collect self-reported data on diet, physical activity, sedentary time, smoking status, and alcohol consumption. Cognitive testing was undertaken to assess memory, processing speed, and vocabulary and verbal knowledge. Latent Profile Analysis (LPA) was conducted to identify subgroups characterised by similar patterns of lifestyle behaviours. The resultant subgroups, or profiles, were then used to further explore associations with cognitive function using linear regression models and an automatic Bolck, Croon & Hagenaars (BCH) approach. Results: Three profiles were identified: (1) “Inactive, poor diet” (76.3%); (2) “Moderate activity, non-smokers” (18.7%); and (3) “Highly active, unhealthy drinkers” (5.0%). Profile 2 “Moderate activity, non-smokers” exhibited better processing speed than Profile 1 “Inactive, poor diet”. There was also some evidence to suggest Profile 3 “Highly active, unhealthy drinkers” exhibited poorer vocabulary and verbal knowledge compared to Profile 1 and poorer processing speed and memory scores compared to Profile 2. Conclusion: In this population of community-dwelling Australian adults, a sub-group characterised by moderate activity levels and higher rates of non-smoking had better cognitive function compared to two other identified sub-groups. This study demonstrates how LPA can be used to highlight sub-groups of a population that may be at increased risk of dementia and benefit most from lifestyle-based multidomain intervention strategies

Urban Neighbourhood Environments, Cardiometabolic Health and Cognitive Function: A National Cross-Sectional Study of Middle-Aged and Older Adults in Australia

Population ageing and urbanisation are global phenomena that call for an understanding of the impacts of features of the urban environment on older adults’ cognitive function. Because neighbourhood characteristics that can potentially have opposite effects on cognitive function are interdependent, they need to be considered in conjunction. Using data from an Australian national sample of 4141 adult urban dwellers, we examined the extent to which the associations of interre-lated built and natural environment features and ambient air pollution with cognitive function are explained by cardiometabolic risk factors relevant to cognitive health. All examined environmental features were directly and/or indirectly related to cognitive function via other environmental features and/or cardiometabolic risk factors. Findings suggest that dense, interconnected urban environments with access to parks, blue spaces and low levels of air pollution may benefit cognitive health through cardiometabolic risk factors and other mechanisms not captured in this study. This study also high-lights the need for a particularly fine-grained characterisation of the built environment in research on cognitive function, which would enable the differentiation of the positive effects of destination-rich neighbourhoods on cognition via participation in cognition-enhancing activities from the negative effects of air pollutants typically present in dense, destination-rich urban areas

Machine Learning for Prediction of Cognitive Health in Adults Using Sociodemographic, Neighbourhood Environmental, and Lifestyle Factors

The environment we live in, and our lifestyle within this environment, can shape our cognitive health. We investigated whether sociodemographic, neighbourhood environment, and lifestyle variables can be used to predict cognitive health status in adults. Cross-sectional data from the AusDiab3 study, an Australian cohort study of adults (34–97 years) (n = 4141) was used. Cognitive function was measured using processing speed and memory tests, which were categorized into distinct classes using latent profile analysis. Sociodemographic variables, measures of the built and natural environment estimated using geographic information system data, and physical activity and sedentary behaviours were used as predictors. Machine learning was performed using gradient boosting machine, support vector machine, artificial neural network, and linear models. Sociodemographic variables predicted processing speed (r2 = 0.43) and memory (r2 = 0.20) with good accuracy. Lifestyle factors also accurately predicted processing speed (r2 = 0.29) but weakly predicted memory (r2 = 0.10). Neighbourhood and built environment factors were weak predictors of cognitive function. Sociodemographic (AUC = 0.84) and lifestyle (AUC = 0.78) factors also accurately classified cognitive classes. Sociodemographic and lifestyle variables can predict cognitive function in adults. Machine learning tools are useful for population-level assessment of cognitive health status via readily available and easy-to-collect data

A Microfluidic Device for Nucleic Acid-Based Analysis of Helicobacter pylori and Antibiotic Susceptibility Testing

© 2020, Springer Nature Singapore Pte Ltd. Rapid diagnosis of bacterial infections enables earlier implementation of appropriate and effective treatment regimens, therefore improving patient outcomes. We have previously demonstrated a microfluidic device for nucleic acid-based analysis of Helicobacter pylori, which can cause peptic ulcers and increase the risk of stomach cancer. One of the major challenges to overcome has been the use of challenging real-world samples, e.g. stool, and urine allowing use at the point-of-care. Here we present results for bacterial identification as well as initial studies on the use of screen-printed electrodes (SPE) for miniaturised electrochemical detection for determining antibiotic susceptibility of pathogenic Escherichia coli. Resazurin was used as an indicator of bacterial viability, with reduction of resazurin demonstrating continued cell growth. Differential pulse voltammetry was used to measure potential reduction and showed measurement at −0.58 V or −0.38 V to be the most discriminatory. A fixed voltage of −0.58 V was then used to monitor current changes as a function of increasing gentamycin (antibiotic) concentration, with the results showing a significant reduction in current with increasing amounts of gentamycin (ANOVA, p < 0.001), within 90 min. The ability to integrate diagnosis with antibiotic susceptibility testing would allow administration of timely and specific treatment to patients with serious infections in low-resource settings