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Unveiling the existence and ecological hazards of trace organic pollutants in wastewater treatment plant effluents across China
No full textThe presence of trace organic pollutants in the effluent of wastewater treatment plants (WWTPs) poses considerable risks to aquatic organisms and human health. A large-scale survey of 302 trace organic pollutants in the effluent of 46 Chinese WWTPs was conducted to gain an improved understanding of their occurrence and ecological risks. The survey data showed that 216 compounds in 11 chemical classes had been detected in effluents. The sum concentrations of the trace contaminants in effluent ranged from 1,392 ng/L to 35,453 ng/L, with the maximum concentration of perfluoroalkyl substances (PFASs) recorded as the highest (30,573 ng/L), which was markedly less than the reported 185,000 ng/L for the 38 American WWTPs. The concentration of bisphenol analogs (BPs) was up to 4,422 ng/L, significantly higher than those reported in France, Germany, Japan, Korea, and the U.S. PFASs and BPs were the major pollutants, accounting for 59% of the total pollution. Additionally, a total of 119 contaminants were found to have ecological risks (RQ > 0.01). Among these, 23 contaminants (RQ > 1.0) warrant higher attention and should be prioritized for removal. This study lists valuable information for controlling contaminants with higher priority in WWTP effluent in China
Associations between changes in crime and changes in walking for transport with effect measure modification by gender: A fixed-effects analysis of the multilevel longitudinal HABITAT study (2007–2016)
No full textWalking for transport is a potential solution to increasing physical activity in mid to older aged adults however neighbourhood crime may be a barrier. Using data from the How Areas in Brisbane Influence HealTh and AcTivity (HABITAT) study 2007–2016, this study examined associations between changes in crime (perceived crime and objectively measured crime) and changes in transport walking, and whether this association differed by gender. Fixed effects regression modelled associations between changes in crime and changes in transport walking, with interaction terms examining effect modification by gender. Positive associations were found between crimes against person and walking for transport. There was no evidence of effect modification by gender. Understanding the relationship between crime and walking for transport can inform policies aimed at promoting transport walking
Using natural language processing and patient journey clustering for temporal phenotyping of antimicrobial therapies for cat bite abscesses
No full textBackground: Temporal phenotyping of patient journeys, which capture the common sequence patterns of interventions in the treatment of a specific condition, is useful to support understanding of antimicrobial usage in veterinary patients. Identifying and describing these phenotypes can inform antimicrobial stewardship programs designed to fight antimicrobial resistance, a major health crisis affecting both humans and animals, in which veterinarians have an important role to play. Objective: This research proposes a framework for extracting temporal phenotypes of patient journeys from clinical practice data through the application of natural language processing (NLP) and unsupervised machine learning (ML) techniques, using cat bite abscesses as a model condition. By constructing temporal phenotypes from key events, the relationship between antimicrobial administration and surgical interventions can be described, and similar treatment patterns can be grouped together to describe outcomes associated with specific antimicrobial selection. Methods: Cases identified as having a cat bite abscess as a diagnosis were extracted from VetCompass Australia, a database of veterinary clinical records. A classifier was trained and used to label the most clinically relevant event features in each record as chosen by a group of veterinarians. The labeled records were processed into coded character strings, where each letter represents a summary of specific types of treatments performed at a given visit. The sequences of letters representing the cases were clustered based on weighted Levenshtein edit distances with KMeans+ + to identify the main variations of the patient treatment journeys, including the antimicrobials used and their duration of administration. Results: A total of 13,744 records that met the selection criteria was extracted and grouped into 8436 cases. There were 9 clinically distinct event sequence patterns (temporal phenotypes) of patient journeys identified, repres
NeuroDiag: Software for Automated Diagnosis of Parkinson's Disease Using Handwriting
No full textObjective: A change in handwriting is an early sign of Parkinson’s disease (PD). However, significant inter-person differences in handwriting make it difficult to identify pathological handwriting, especially in the early stages. This paper reports the testing of NeuroDiag, a software-based medical device, for the automated detection of PD using handwriting patterns. NeuroDiag is designed to direct the user to perform six drawing and writing tasks, and the recordings are then uploaded onto a server for analysis. Kinematic information and pen pressure of handwriting are extracted and used as baseline parameters. NeuroDiag was trained based on 26 PD patients in the early stage of the disease and 26 matching controls. Methods: Twenty-three people with PD (PPD) in their early stage of the disease, 25 age-matched healthy controls (AMC), and 7 young healthy controls were recruited for this study. Under the supervision of a consultant neurologist or their nurse, the participants used NeuroDiag. The reports were generated in real-time and tabulated by an independent observer. Results: The participants were able to use NeuroDiag without assistance. The handwriting data was successfully uploaded to the server where the report was automatically generated in real-time. There were significant differences in the writing speed between PPD and AMC (P<0.001). NeuroDiag showed 86.96% sensitivity and 76.92% specificity in differentiating PPD from those without PD. Conclusion: In this work, we tested the reliability of NeuroDiag in differentiating between PPD and AMC for real-time applications. The results show that NeuroDiag has the potential to be used to assist neurologists and for telehealth applications. Clinical and Translational Impact Statement — This pre-clinical study shows the feasibility of developing a community-wide screening program for Parkinson’s disease using automated handwriting analysis software, NeuroDiag
Advancing the additive manufacturing of PLA-ZnO nanocomposites by fused filament fabrication
No full textPoly(lactic acid)-zinc oxide (PLA-ZnO) nanocomposites for fused filament fabrication have potential applications in the biomedical field as they combine the bio-compatibility of PLA with the antibacterial properties of ZnO. This work investigates the effects of masterbatch mixing strategy, ZnO concentration and ZnO surface treatment (silanisation) on the printability and the mechanical performance of the nanocomposites as a pre-requirement to the wider uptake of these materials. The results showed that the printability decreased as the filler loading increased. However, the surface treatment of the ZnO powder enhanced the matrix-filler interfacial interactions and reduced the thermal degradation of PLA. This ameliorated the printability and the tensile properties of the nanocomposites filled with up to 5 wt.% of ZnO. Moreover, despite the additional thermal treatment, melt-mixing prevented the degradative effect induced by the solvent used for solvent mixing. Future work will focus on assessing the antibacterial properties of the nanocomposite FFF parts
Semi-analytical solutions for the consolidation of unsaturated composite ground with floating permeable columns under equal strain condition
No full textThis study focuses on the mathematical interpretation and consolidation behavior of unsaturated composite ground with floating permeable columns (FPC). By combining the axisymmetric consolidation model with the equal strain assumption, the consolidation problem of unsaturated composite ground with FPC is transformed into a one-dimensional consolidation problem of an equivalent double-layer ground. The consolidation governing equations of the reinforced zone and the underlying stratum are derived respectively. The Laplace transformation and Gauss elimination method are used to obtain solutions for the average excess pore pressure and settlement in the Laplace transform domain. The semi-analytical solutions for the consolidation of composite ground in the time domain are obtained by implementing the Crump numerical method for the inverse Laplace transformation. A comparison with the existing literature and numerical simulation results from Finite Element Methods (FEM) confirms the correctness of the proposed semi-analytical solutions. Based on these solutions, the consolidation behavior of an unsaturated composite ground with FPC under instantaneous loading is investigated. The results indicate that the penetration ratio of the permeable column is the most significant factor affecting the consolidation of composite ground. Furthermore, the consolidation rate and settlement of the composite ground also highly depend on the unsaturated soil in the underlying stratum
Transferrable contextual feature clusters for parking occupancy prediction
No full textRecently, real-time parking availability prediction has attracted much attention since the rapid development of sensor technologies and urbanisation. Most existing works have applied various models to predict long and short-term parking occupancy using historical records. However, historical records are not available for many real-world scenarios, such as new urban areas, where parking lots are fast adjusted and extended. In this paper, we aim to predict parking occupancy using historical data in other areas and contextual information within the targeted area that lacks historical data. We propose a two-step framework to first learn the important contextual features from areas where parking records already existed. Then we transfer these features to the other new areas without historical data records. Through conducting a real-world dataset with various clustering methods combined with different regression models, we observe that multiple contextual features are likely to influence parking availability prediction. We find the best combination (i.e., k-shape clustering algorithm and LSTM regression model) to build parking occupancy prediction model based on the subsequent quantitative correlation analysis between contextual features and parking occupancy. The experimental results show that (1) the conventional internal clustering evaluation does not work well for spatio-temporal data clustering for the prediction purpose; (2) our proposed approach achieves approximately 3% error rate in 30 minutes of prediction, which is significantly better than the estimation of the occupancy rate using the rate in the adjacent regions (13.3%)
Accountabilities and stakeholder expectations regarding asbestos-free building materials supply chain: an actor-network theory perspective
No full textThe purpose of this paper is to explore issues relating to imposing a ban on the importation of asbestos-contaminated building materials (ACBMs) in the Australian context to better understand the multiple accountabilities and consequences. This study undertakes a qualitative content analysis of the multiple accountabilities and stakeholder expectations using the lens of actor-network theory. This study further explores the weaknesses and complexities associated with implementing a complete ban on asbestos, ensuring that only asbestos-free building materials are imported to Australia. This study uses data collected from 15 semi-structured interviews with stakeholders, responses from the Australian Border Force to a questionnaire and 215 counter accounts from the media, the Australian Government, industry organizations, non-governmental organizations and social group websites during the period from 2003 to 2021. This study reveals that stakeholders' expectations of zero tolerance for asbestos have not been met. This assertion has been backed by evidence of asbestos contamination in imported building materials throughout recent years. Stakeholders say that the complete prevention of the importation of ACBMs has been delayed because of issues in policy implementations, opaque supply chain activities, lack of transparency and non-adherence to mandatory and self-regulated guidelines. Stakeholders expect public and private sector organizations to meet their accountabilities through mandatory adoption of the given policy framework. This research provides a road map to identify the multiple accountabilities, their related weaknesses and the lack of implementation of the necessary protocol, which prevents a critical aspect of legislation from being effectively implemented
Australian housing markets, the COVID-19 pandemic and black swan events
No full textPurpose: This study aims to examine the impact of lending liquidity on house prices especially during black swan events such as the Global Financial Crisis of 2007-08 and COVID-19. Homeownership is an important goal for many, and house prices are a significant driver of household wealth and the wider economy. This study argues that excessive liquidity from central banks may be driving house price increases, despite negative changes to fundamental drivers. This study contributes to the literature by examining lending liquidity as a driver of house prices and evaluating the efficacy of fiscal policies aimed at boosting liquidity during black swan events. Design/methodology/approachThis study aims to examine the impact of quantitative easing on Australian house prices during back swan events using data from 2004 to 2021. All macroeconomic and financial data are freely available from official sources such as the Australian Bureau of Statistics and the nation's Central Bank. Methodology wise, given the problematic nature of the data such as a mixed order of integration and the possibility of cointegration among some of the I(1) variables, the auto-regressive distributed lag model was selected given its flexibility and relative lack of assumptions. FindingsThe Australian housing market continued to perform well during the COVID-19 pandemic, with the house price index reaching an unprecedented high towards the end of 2021. Research using data from 2004 to 2021 found a consistent positive relationship between house prices and housing finance, as well as population growth and the value of work commenced on residential properties. Other traditional drivers such as the unemployment rate, economic activity, stock prices and income levels were found to be less significant. This study suggests that quantitative easing implemented during the pandemic played a significant role in the housing market's performance. Originality/valueGiven the severity of COVID-19, policymakers have responded with fiscal and monetary measures that are unprecedented in scale and scope. The full implications of these responses are yet to be completely understood. In Australia, the policy interest rate was reduced to a historic low of 0.1%. In the following periods house prices appreciated by over 20%. The efficacy of quantitative easing and associated fiscal policies aimed at boosting liquidity to mitigate the impact of black swan events such as the pandemic has yet to be tested empirically. This study aims to address that paucity in literature by providing such evidence
Socio-economic disparities in greenspace quality: insights from the city of Melbourne
No full textPurpose: This paper takes a prudent approach to assessing the quality of greenspace in low- and high socio-economic status (SES) settings. Socio-economic data from deprivation indexes were used to systematically define low- and high-SES suburbs. A Geographical Information System (GIS) observation of greenspaces was used to score spaces according to a scoring criterion contingent on six quality facets. Statistics were then synthesised, producing a Cohen effect score highlighting disparities in each criterion between the two SES groups. Design/methodology/approach: As the phenomena of locational prejudice and meritocratic inequality continue to garner global attention, this paper extrapolates this to a world-renown metropolis, Melbourne. This paper endeavours to provide invaluable insights into the environmental injustice paradigm within greenspace and its respective quality. Findings: Conclusive results affirmed a concerning disparity in the quality of greenspace between Melbourne's low- and high-SES settings. Cohen's effect size found that on average, there was a “medium” distinction between the spaces, whilst an individual focus on the quality facets concluded diverse findings. Research limitations/implications: The core of study adopted a meticulous virtual assessment to critique the quality of selected greenspaces opposed to an in-person-real world assessment which could garner more nuanced findings. Originality/value: Existing literature on Melbourne has prioritised distribution, proximity and accessibility domains when assessing inequitable greenspace and, consequently, has catalysed a research gap in greenspace quality. This is also one of the first papers to provide insight into the “Plan Melbourne” policy regarding urban regeneration and ameliorating public open spaces