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A Monte Carlo fuzzy logistic regression framework against imbalance and separation
No full textThis article proposes a new fuzzy logistic regression framework with high classification performance against imbalance and separation while keeping the interpretability of classical logistic regression. Separation and imbalance are two core problems in logistic regression, which can result in biased coefficient estimates and inaccurate predictions. Existing research on fuzzy logistic regression primarily focuses on developing possibilistic models instead of using a logit link function that converts log-odds ratios to probabilities. At the same time, little consideration is given to issues of separation and imbalance. Our study aims to address these challenges by proposing new methods of fuzzifying binary variables and classifying subjects based on a comparison against a fuzzy threshold. We use combinations of fuzzy and crisp predictors, output, and coefficients to understand which combinations perform better under imbalance and separation. Numerical experiments with synthetic and real datasets are conducted to demonstrate the usefulness and superiority of the proposed framework. Seven crisp machine learning models are implemented for benchmarking in the numerical experiments. The proposed framework shows consistently strong performance results across datasets with imbalance or separation and performs equally well when such issues are absent. Meanwhile, the considered machine learning methods are significantly impacted by the imbalanced datasets
Noninvasive biosensing 3D scaffold to monitor degradation: The potential of fluorescent PCL and PLGA for tissue engineering
No full textThe nondestructive localization and traceability of polymers by fluorescent tagging has become a valuable tool for biomedical applications. Integration of fluorescent molecule to the pristine polymers could modify polymers' degradation rate which is still unpredictable from a scaffold application standpoint. The current study focused to understand the material perspective of fluorescently tagged biodegradable polymers such as polycaprolactone (PCL) and poly (d,l-lactide-co-glycolide) (PLGA) with fluorescein amine isomer I (FITC). PCL-FITC and PLGA-FITC were characterized using FTIR for surface chemistry analysis and rheology for their mechanical properties. The grafted materials were utilized to form 3-dimentional scaffolds, and their degradation was monitored under accelerated degradation conditions triggered by pH. It was found that PCL and PCL-FITC had a very slow degradation rate, when compared to PLGA and PLGA-FITC. Both the FITC tagged materials displayed a faster degradation rate compared to their respective pristine material. Biocompatibility of the FITC conjugated polymers was tested using human-adipose derived stem cells (hADSCs) revealing that the sub products from the degradation of the polymers over 7 days did not negatively affect the cellular metabolic activity. This work highlights the significance of initial characterization of fluorescent modified polymers for future biomedical application
An EIS approach to quantify the effects of inlet air relative humidity on the performance of proton exchange membrane fuel cells: A pathway to developing a novel fault diagnostic method
No full textIn this work, the effect of low air relative humidity on the operation of a polymer electrolyte membrane fuel cell is investigated. An innovative method through performing in situ electrochemical impedance spectroscopy is utilised to quantify the effect of inlet air relative humidity at the cathode side on internal ionic resistances and output voltage of the fuel cell. In addition, algorithms are developed to analyse the electrochemical characteristics of the fuel cell. For the specific fuel cell stack used in this study, the membrane resistance drops by over 39 % and the cathode side charge transfer resistance decreases by 23 % after increasing the humidity from 30 % to 85 %, while the results of static operation also show an increase of ∼2.2 % in the voltage output after increasing the relative humidity from 30 % to 85 %. In dynamic operation, visible drying effects occur at < 50 % relative humidity, whereby the increase of the air side stoichiometry increases the drying effects. Furthermore, other parameters, such as hydrogen humidification, internal stack structure, and operating parameters like stoichiometry, pressure, and temperature affect the overall water balance. Therefore, the optimal humidification range must be determined by considering all these parameters to maximise the fuel cell performance and durability. The results of this study are used to develop a health management system to ensure sufficient humidification by continuously monitoring the fuel cell polarisation data and electrochemical impedance spectroscopy indicators
Hybrid CNN-transformer network for interactive learning of challenging musculoskeletal images
No full textBackground and objectives: Segmentation of regions of interest (ROIs) such as tumors and bones plays an essential role in the analysis of musculoskeletal (MSK) images. Segmentation results can help with orthopaedic surgeons in surgical outcomes assessment and patient's gait cycle simulation. Deep learning-based automatic segmentation methods, particularly those using fully convolutional networks (FCNs), are considered as the state-of-the-art. However, in scenarios where the training data is insufficient to account for all the variations in ROIs, these methods struggle to segment the challenging ROIs that with less common image characteristics. Such characteristics might include low contrast to the background, inhomogeneous textures, and fuzzy boundaries. Methods: we propose a hybrid convolutional neural network – transformer network (HCTN) for semi-automatic segmentation to overcome the limitations of segmenting challenging MSK images. Specifically, we propose to fuse user-inputs (manual, e.g., mouse clicks) with high-level semantic image features derived from the neural network (automatic) where the user-inputs are used in an interactive training for uncommon image characteristics. In addition, we propose to leverage the transformer network (TN) – a deep learning model designed for handling sequence data, in together with features derived from FCNs for segmentation; this addresses the limitation of FCNs that can only operate on small kernels, which tends to dismiss global context and only focus on local patterns. Results: We purposely selected three MSK imaging datasets covering a variety of structures to evaluate the generalizability of the proposed method. Our semi-automatic HCTN method achieved a dice coefficient score (DSC) of 88.46 ± 9.41 for segmenting the soft-tissue sarcoma tumors from magnetic resonance (MR) images, 73.32 ± 11.97 for segmenting the osteosarcoma tumors from MR images and 93.93 ± 1.84 for segmenting the clavicle bones from chest radiographs. When compared to the current state-of-the-art automatic segmentation method, our HCTN method is 11.7%, 19.11% and 7.36% higher in DSC on the three datasets, respectively. Conclusion: Our experimental results demonstrate that HCTN achieved more generalizable results than the current methods, especially with challenging MSK studies
Why and when do emotionally intelligent employees perform safely? The roles of thriving at work and career adaptability
No full textBased on the socially embedded model of thriving, the present study examined a moderated mediation framework, which involves the mediating role of employee thriving and the moderating role of career adaptability in the relationship between emotional intelligence (EI) and safety performance. A two-wave survey was administered among full-time commercial pilots working for airlines (N = 131). Our results showed that EI had a positive influence on employee thriving, which in turn positively affected safety performance. In addition, the results further revealed that the positive effect of EI on safety performance was stronger among pilots with a higher level of career adaptability. These findings have important implications for theoretical developments on EI, thriving, and performance in a safety context, and they also provide practical insights on how to enhance workplace safety
BIM enabler for facilities management: a review of 33 cases
No full textThe purpose of this paper is to investigate the application of building information modelling (BIM) for asset management. It will discuss what tools and processors are used for applying BIM for asset management in construction projects. The method comprises a literature review of 33 projects that have applied BIM or planned to apply BIM for asset management functions. The findings show that a combination of software, hardware, processors, and standards can enable the BIM models to be integrated with the asset management systems. It facilitates easy extraction of information, avoid errors and duplication of work. The most popular way of developing a BIM-based asset management system is incorporating BIM asset data with CMMS or CAFM systems used for asset lifecycle and maintenance management. Engagement of stakeholders related to the operation phase is required as early as possible. Consideration should be given for protecting the information generated within the cyber environment. The research shows how BIM related tools and processors could be integrated to successfully implement BIM enabled asset management. The knowledge can be potentially useful for planning or implementing BIM enabled asset management systems. The research provides insight on the application of BIM for asset management in construction projects globally
Regulatory conflict and a latent public safety risk? The case of gas infrastructure
No full textWhile the literature on regulatory compliance is extensive, little scholarly attention has focused on how companies respond to conflicting regulatory requirements. As a case in point, gas pipelines and networks—deemed monopolies—are subject to economic regulation to emulate the price pressures of competition and encourage “efficient” expenditure. Technical (safety) regulation of the same infrastructure also addresses an expenditure trade-off with safety, potentially drawing different conclusions as to the most appropriate balance. This article reports on a study—drawing on 49 interviews, document review and case studies—analyzing if these two regulatory regimes, as enacted in Australia, are in conflict. We find a significant tension between the two regimes, exhibited through the impact that economic regulation has on a company's planned safety-related expenditure and thus, long-term public safety outcomes may be at risk. Australian safety regulation is performance-based, requiring “reasonably practicable” measures are in place to minimize risk to the public. The San Bruno California disaster, in which eight people died as a result of failed gas infrastructure in the US, shows that such regulatory conflicts also exist in jurisdictions that have adopted prescriptive forms of safety regulation
In-situ elimination of β-flecks in additively manufactured Ti-3.5 wt% Fe alloy
No full textMeta-stable β titanium alloys that feature excellent mechanical properties are of great interest for a range of engineering applications. In particular, Fe containing titanium alloy is one of the most promising alloy systems because Fe is the most economic β stabilizer. However, Fe solute is highly prone to segregation during casting, which leads to the formation of “β flecks” in the subsequent thermo-mechanical treatment and deteriorates the fatigue properties. This paper aims to eliminate β flecks in Ti-3.5 wt� alloy fabricated by Laser Directed Energy Deposition (L-DED), that utilises the high cooling rate during solidification and multiple thermal cycles after solidification. SEM and EDS analysis established that a large β-fleck free zone can be achieved in as-fabricated Ti-3.5 wt� thin-walled samples. Combining the finite element temperature field simulation results and the one-dimensional dynamic diffusion model, the elimination of β flecks is well rationalized. The current work provides a paradigm to evaluate the segregation elimination in the additively manufactured alloy components
Regulating the structural polymorphism and protein corona composition of phytantriol-based lipid nanoparticles using choline ionic liquids
No full textLipid-based lyotropic liquid crystalline nanoparticles (LCNPs) face stability challenges in biological fluids during clinical translation. Ionic Liquids (ILs) have emerged as effective solvent additives for tuning the structure of LCNP’s and enhancing their stability. We investigated the effect of a library of 21 choline-based biocompatible ILs with 9 amino acid anions as well as 10 other organic/inorganic anions during the preparation of phytantriol (PHY)-based LCNPs, followed by incubation in human serum and serum proteins. Small angle X-ray scattering (SAXS) results show that the phase behaviour of the LCNPs depends on the IL concentration and anion structure. Incubation with human serum led to a phase transition from the inverse bicontinuous cubic (Q2) to the inverse hexagonal (H2) mesophase, influenced by the specific IL present. Liquid chromatography-mass spectrometry (LC-MS) and proteomics analysis of selected samples, including PHY control and those with choline glutamate, choline hexanoate, and choline geranate, identified abundant proteins in the protein corona, including albumin, apolipoproteins, and serotransferrin. The composition of the protein corona varied among samples, shedding light on the intricate interplay between ILs, internal structure and surface chemistry of LCNPs, and biological fluids
Household income supplements in early childhood to reduce inequities in children's development
No full textBackground: Early childhood interventions have the potential to reduce children's developmental inequities. We aimed to estimate the extent to which household income supplements for lower-income families in early childhood could close the gap in children's developmental outcomes and parental mental health. Methods: Data were drawn from a nationally representative birth cohort, the Longitudinal Study of Australian Children (N = 5107), which commenced in 2004 and conducted follow-ups every two years. Exposure was annual household income (0–1 year). Outcomes were children's developmental outcomes, specifically social-emotional, physical functioning, and learning (bottom 15% versus top 85%) at 4–5 years, and an intermediate outcome, parental mental health (poor versus good) at 2–3 years. We modelled hypothetical interventions that provided a fixed-income supplement to lower-income families with a child aged 0–1 year. Considering varying eligibility scenarios and amounts motivated by actual policies in the Australian context, we estimated the risk of poor outcomes for eligible families under no intervention and the hypothetical intervention using marginal structural models. The reduction in risk under intervention relative to no intervention was estimated. Results: A single hypothetical supplement of AU17,350) provided to lower-income families (below AU37,915) per annum) in a child's first year of life demonstrated an absolute reduction of 2.7%, 1.9% and 2.6% in the risk of poor social-emotional, physical functioning and learning outcomes in children, respectively (equivalent to relative reductions of 12%, 10% and 11%, respectively). The absolute reduction in risk of poor mental health in eligible parents was 1.0%, equivalent to a relative reduction of 7%. Benefits were similar across other income thresholds used to assess eligibility (range, AU99,864). Conclusions: Household income supplements provided to lower-income