University of Alberta
  • Edmonton, Canada
Recent publications
Exosomal non-coding RNAs (ncRNAs) have become essential contributors to advancing and treating lung cancers (LCs). The development of liquid biopsies that utilize exosomal ncRNAs (exo-ncRNAs) offers an encouraging method for diagnosing, predicting, and treating LC. This thorough overview examines the dual function of exo-ncRNAs as both indicators for early diagnosis and avenues for LC treatment. Exosomes are tiny vesicles secreted by various cells, including cancerous cells, enabling connection between cells by delivering ncRNAs. These ncRNAs, which encompass circular RNAs, long ncRNAs, and microRNAs, participate in the modulation of gene expression and cellular functions. In LC, certain exo-ncRNAs are linked to tumour advancement, spread, and treatment resistance, positioning them as promising non-invasive indicators in liquid biopsies. Additionally, targeting these ncRNAs offers potential for innovative treatment approaches, whether by suppressing harmful ncRNAs or reinstating the activity of tumour-suppressing ones. This review emphasizes recent developments in the extraction and analysis of exo-ncRNAs, their practical applications in LC treatment, and the challenges and prospects for translating these discoveries into clinical usage. Through this detailed examination of the current state of the art, we aim to highlight the significant potential of exo-ncRNAs for LC diagnostics and treatments.
Coaxial tilt-rotor (CTR) unmanned aerial vehicle (UAV) is a system with the specific configuration of two CTR modules and a rear-rotor module. The CTRUAV is a typical strongly coupled, nonlinear, and underactuated system whose control performance is always adversely affected by various disturbances. To realize robust, stable, and efficient flight control for the CTRUAV is a challenging task. A multivariable cascaded finite-time (FT) controller and an improved nonlinear control allocation law with variable parameters are proposed based on the particular configuration of the CTRUAV. Finally, the superiority and the relationship between the control performance of the proposed control scheme and the control parameters are demonstrated through simulations and real flight experiments. The results show that the proposed control system significantly improves the robustness, transient performance, stability, and efficiency of the CTRUAV. In the flight tests, the root mean square error of the velocity is reduced by 28% in the presence of external disturbance, and the settling time of the attitude is shortened up to 55.8% in tracking the step signal.
Three-level neutral point clamped (3L-NPC) converters are a favorable candidate for the grid interfacing converter stage in bipolar dc distribution systems. This article proposes the use of dual 3L-NPCs where, by virtue of connecting their ac ports in a differential fashion across a center-tapped transformer winding, two main benefits can be realized: i) full bipolar voltage balancing capability that can accommodate any degree of imbalance between two dc poles, and ii) improved dc-side power quality in terms of reduced ripples in the pole voltages and currents. The proposed converter system also avoids the reliance on more complex zigzag transformer arrangements used in prior art. Detailed theoretical analyses of the pole voltage balancing and the ripple reduction mechanisms are conducted, with the results guiding the development of a suitable control strategy. The advantages of the proposed scheme and the correctness of the theoretical analyses are validated through both simulation and experimental results.
The input-parallel output-series (IPOS) grid-connected inverter system is suitable for low input voltage and high output voltage occasions, such as solar energy based distributed power generation systems. This letter explores to select least number of control variables to realize multiple control objectives of IPOS grid-connected inverter system, including good system stability, high power factor, and power balance. Then, to avoid interconnection lines among modules to obtain better disturbance-rejection performance, a droop control strategy without interconnection lines is derived based on the duality of input-parallel output-parallel system. Even if the modules hardware parameters are unmatched, the power balance among the modules can also be ensured by increasing the droop coefficient. Finally, the experimental results based on a two-module IPOS grid-connected inverter prototype and simulation results based on three-modulate system are provided to verify the effectiveness of the proposed method.
The causality between different variables can reveal the flows of material, energy, and information in the process system. It is beneficial to reflect the relationship between quality variables and process variables. In this study, a concurrent quality and process monitoring method is proposed with intrinsic causality analytics. The proposed method explores the causality between different variables using transfer entropy. Then, the directly related variables and their corresponding time lags are combined to extract convolutional features, which are used to generate feature matrices for process and quality variables. In this way, the quality related information is extracted from the process variables which are directly related to the quality variables. After that, monitoring models are established for each pair of feature matrices, and the monitoring results are integrated to provide a final monitoring result. Since the process disturbances usually smear to directly related variables, the fault signature can be amplified to improve the detection sensitivity when the directly related variables are combined. Finally, the operation status of the process system is identified through the designed monitoring policy, which combines the decisions of different statistics. It is noted that the proposed strategy can be readily generalized to many other existing quality related monitoring methods. Experiments on a real industrial condenser show that the proposed method can distinguish the quality related faults from the process related faults in the condenser. Besides, it has better detection sensitivity than some commonly used quality related monitoring methods.
The H-bridge (HB) converters are essential components in various power typologies, offering dual energy flow, increasing power density, and enhancing extensibility. For the HB converters, the dead zone plays a crucial role in avoiding power semiconductors against shoot-through phenomenon in the phase leg of an HB converter. However, it also negatively affects the quality of the output ac currents, impacting system performance. This letter introduces a simplified digital logic-based scheme that effectively compensates for the dead zone in HB converters. Initially, the scheme examines the repercussions of dead zones in HB converter. Subsequently, it adjusts pulsewidth modulation signal waveforms by either delaying the leading edge or the lagging edge for the dead-zone compensation, irrespective of the control and modulation methods employed. Furthermore, extensibility of the proposed scheme to other power converters, such as a neutral-point-clamped converter is discussed. The effectiveness of the proposed scheme is validated by experimental results.
Feature selection plays a significant role in data mining and machine learning. It is challenging to determine how many features are necessary to form an optimal feature subset. To address this challenge, an innovative visual 2D feature selection framework is introduced, in which the feature discernibility and independence are defined to evaluate its capability for classification and its relevance to other features, respectively. All features are represented in 2D space with discernibility as xx -axis and independence as yy -axis. The features located in the upper right corner represent high discernibility and high independence, so comprise the optimal feature subset. This leads to the formation of a family of feature selection algorithms. Three such algorithms are proposed in this paper referred to as FSDIE, FSDIR, and FSDIS (Feature Selection based on the Discernibility and the Independence, respectively, of Exponent, Reciprocal, and anti-Similarity). To speed-up these three algorithms, a clustering based feature preselection first eliminates some unrelated and redundant features. Extensive experiments on UCI datasets, face datasets and gene expression datasets demonstrate that these three 2D feature selection algorithms are superior to the state-of-the-art methods indicating the power of our 2D feature selection framework.
This study is devoted to the design of gradient boosted fuzzy rule-based models for regression problems. Fuzzy rule-based models are built on the basis of information granules formed in the input and output spaces whose structure involves a family of conditional ‘if-then’ statements. The architecture of fuzzy rule-based models contributes to the realization of a sound tradeoff between modeling accuracy and interpretability and computing overhead. Gradient boosting paradigm has emerged as a powerful learning method realized through sequentially fitting additive base learners to current residuals in the steepest descent way. However, surprisingly, studies on the design and analysis of gradient boosted fuzzy rule-based models are still lacking. In this study, fuzzy rule-based model is regarded as a base learner. Different loss functions and their influence on the performance of the final models are explored. We also thoroughly investigate an impact of the initial quality of the rule-based model (implied by the number of rules) on the process of gradient boosting. The performance of the proposed approach is illustrated by a series of experimental studies concerning synthetic and publicly available datasets.
Networked systems, in practice, suffer from several network-induced imperfections. In this paper, we consider the problem of distributed control of nonlinear multi-agent systems (MASs) where the information broadcasts over a network are susceptible to one such imperfection, namely, transmission delays. The design methodology employed is such that the sampling instants (at which agents broadcast information) could be both aperiodic and asynchronous in nature. The broadcasts, upon arrival, are propagated by the agents through dynamical models and these propagates are used in their control protocols. The overall MAS is formulated as a hybrid dynamical system whose stability governs the upper bounds on: a) the sampling interval, namely, the duration between two consecutive broadcasts, and b) the transmission delays that the broadcasts might be prone to. Finally, through a case study on the consensus of Lipschitz nonlinear agents, we demonstrate the effectiveness of the proposed methodology.
In the low-voltage islanded multi-bus microgrid (LVIMB-MG), the virtual synchronous generators’ (VSGs’) inertia constant and damping coefficient play an important role in low-frequency oscillations (LFOs). However, existing LFO analyses lack the consideration of microgrids’ required rate of change of frequency (RoCoF) and steady-state active power – frequency (P-f) characteristics when designing the VSG’s inertia and damping. With these practical considerations, this paper reveals that the interactions between VSGs can cause significant LFOs, posing a threat to the microgrid’s stability. In contrast, the LFOs related to the interactions between SGs are less pronounced. To this end, a distributed LFO damping (DLFOD) control is proposed to suppress the LFOs between VSGs from two aspects: the adjustment of the VSG’s phase angle mitigates the uneven instantaneous active power sharing, while the adjustment of the VSG’s active power setpoint enhances the mutual damping. Compared with existing methods, the proposed DLFOD control 1) pertains to multi-bus microgrids, 2) guarantees the RoCoF and steady-state P-f characteristics, and 3) possesses a linear structure. Furthermore, a dynamic switching variable is devised to handle the disconnection and reconnection of communication links or VSGs, which enables the DLFOD control to remain partially functional during these interruptions. Finally, the proposed method is evaluated through theoretical analysis, real-time simulations, and experiments.
Knowledge discovery of heterogeneous data is an active topic in knowledge engineering. Feature selection for heterogeneous data is an important part of effective data analysis. Although there have been many attempts to study the feature selection for heterogeneous data, there are still some challenges, such as the unbalanced problem between the stability and validity of the designed model. Hence, this paper focuses on how to design an effective and robust heterogeneous feature selection method, namely a zentropy-based uncertainty measure for heterogeneous feature selection(Ze-HFS). Different from other entropy-based uncertainty measures, the proposed method does not consider single-level information measures but systematically analyzes and integrates the information between different granular levels, which has an obvious advantage in the study of heterogeneous data knowledge discovery. Specifically, a heterogeneous distance metric is first introduced to construct heterogeneous neighborhood granules and heterogeneous neighborhood rough sets(HNRS). Then, the zentropy-based uncertainty measure is developed by analyzing the granular level structure in the HNRS model. Finally, two significant measures based on the above research are designed for heterogeneous feature selection. Compared with other state-of-the-art methods, the experimental results on 18 public datasets demonstrate the robustness and effectiveness of the proposed method.
Fuzzy information granularity is an effective granular computation approach for feature evaluation and selection. However, most existing methods rely on a single granulation channel, neglecting different granularity representations. In this paper, a novel dual-channel fuzzy interaction information fused feature selection with fuzzy sparse and shared granularities is proposed. It mainly comprises three parts. First, a dual-channel framework is introduced to construct the fuzzy information granularity from two different strategies. One channel employs sparse mutual strategy to form the sparse representation-based fuzzy information granularity, while the other constructs the fuzzy shared information granularity with a novel fuzzy semi-ball. Second, in each channel, the criteria of maximum relevancy, minimum redundancy and maximum interaction is adopted to access feature correlation and perform feature ranking. Third, the two feature sequences derived from the dual-channel are fused to form a final feature sequence based on the within-class and between-class mechanism. To validate the efficacy of the proposed method, experimental validations on 15 datasets and schizophrenia data are conducted. The results show that the proposed method outperforms other algorithms in classification accuracy and statistical analysis. Moreover, its superiority regarding accuracy can be demonstrated in the experiments of schizophrenia detection, where it performs well in recognizing schizophrenia through visual interpretation.
To address responsiveness, time-dependence, and limited emergency supply issues, we introduce a new flexible districting policy, aiming to improve satisfaction in multiperiod emergency resource allocation (MPERA), and set demand priorities to guarantee allocation balance in resource-limited scenarios. The modeling and solution process involves the following: 1) formulating a mixed-integer programming (MILP) model for MPERA with demand priority (MPERA-DP), aiming to maximize utility considering the transportation cost, districting change, and penalty for unsatisfied demand and 2) incorporating the justifiable granularity principle (JGP) and particle swarm optimization (PSO) into the brand-and-price (B&P) algorithm for initial districting and allocating decisions to improve the solution quality and calculation speed. The results of the experiments show that 1) the JGP-PSO-B&P algorithm achieves superior efficiency in terms of optimality and convergence for large-scale cases. This algorithm could improve the optimality by 13.42% compared with that of the JGP-PSO algorithm, 13.15% compared with that of the B&P algorithm, and 28.18% compared with that of the PSO algorithm, on average; 2) the MPERA-DP model with flexible districting policy outperforms flexible MPERA without demand priority, emergency resource allocation with rescheduling (ERAR) and fixed emergency resource allocation with demand priority (FERA-DP), improving the utility by 20.56%, 5.14% and 41.84%, respectively; and 3) the scheme efficiency is influenced by the desirable satisfaction deviation, and when set to 0.6, it allows for the optimization of both demand satisfaction and utility.
A compact and low-profile antenna for global navigation satellite systems (GNSS), with particular optimization for tri-band Global Positioning System (GPS) coverage, is presented. A dual-band antenna is developed with the use of metamaterial-based electromagnetic bandgap structures (MTM-EBGs) that covers GPS L1, L2, and L5 bands and a majority of the GNSS spectrum. The patch antenna is fabricated on two sides of a single substrate sheet above a ground plane, with a 3D printed polylactic acid (PLA) substrate spacer for simple fabrication. The antenna is fed by a wideband and planar feed network below the ground plane, and simulation and measurement results show good performance in terms of matching, gain, pattern shape, and axial ratio, demonstrating that this antenna is an excellent candidate for use with modern high-accuracy multi-band and multi-system GPS/GNSS receivers.
Iron‐sulfur clusters are ancient cofactors that could have played a role in the prebiotic chemistry leading to the emergence of protometabolism. Previous research has shown that certain iron‐sulfur clusters can form from prebiotically plausible components, such as cysteine‐containing oligopeptides. However, it is unclear if these iron‐sulfur clusters could have survived in prebiotically plausible environments. To begin exploring this possibility, we tested the stability of iron‐sulfur clusters coordinated to a tripeptide and to N‐acetyl‐L‐cysteine methyl ester in a variety of solutions meant to mimic prebiotically plausible environments. We also assessed the impact of individual chemical components on stability. We find that iron‐sulfur clusters form over a wide variety of conditions but that the type of iron‐sulfur cluster formed is strongly impacted by the chemical environment and the coordinating scaffold. These findings support the general hypothesis that iron‐sulfur clusters were present on the prebiotic Earth and that different types of iron‐sulfur cluster predominated in different environments.
Immunologic self-tolerance involves signals from co-inhibitory receptors. Several T cell co-inhibitors, including PD-1, are expressed upon activation, whereas CD5 and BTLA are expressed constitutively. The relationship between constitutively expressed co-inhibitors and when they are needed is unknown. Deletion of Btla demonstrated BTLA regulates CD5 expression. Loss of BTLA signals, but not signalling by its ligand, HVEM, leads to increased CD5 expression. Higher CD5 expression set during thymic selection is associated with increased self-recognition, suggesting that BTLA might be needed early to establish self-tolerance. We found that BTLA and PD-1 were needed post-thymic selection in recent thymic emigrants (RTE). RTE lacking BTLA caused a CD4 T cell and MHC class II dependent multi-organ autoimmune disease. Together, our findings identify a negative regulatory pathway between two constitutively expressed co-inhibitors, calibrating their expression. Expression of constitutive and induced co-inhibitory receptors is needed early to establish tolerance in the periphery for RTE.
Background Acute liver failure (ALF) is a rare condition leading to morbidity and mortality. Liver transplantation (LT) is often required, but patients are not always listed for LT. There is a lack of data regarding outcomes in these patients. Our aim is to describe outcomes of patients with ALF not listed for LT and to compare this with those listed for LT. Methods Retrospective analysis of all nonlisted patients with ALF enrolled in the Acute Liver Failure Study Group (ALFSG) registry between 1998 and 2018. The primary outcome was 21-day mortality. Multivariable logistic regression was done to identify factors associated with 21-day mortality. The comparison was then made with patients with ALF listed for LT. Results A total of 1672 patients with ALF were not listed for LT. The median age was 41 (IQR: 30–54). Three hundred seventy-one (28.9%) patients were too sick to list. The most common etiology was acetaminophen toxicity (54.8%). Five hundred fifty-eight (35.7%) patients died at 21 days. After adjusting for relevant covariates, King’s College Criteria (adjusted odds ratio: 3.17, CI 2.23–4.51), mechanical ventilation (adjusted odds ratio: 1.53, CI: 1.01–2.33), and vasopressors (adjusted odds ratio: 2.10, CI: 1.43–3.08) ( p < 0.05 for all) were independently associated with 21-day mortality. Compared to listed patients, nonlisted patients had higher mortality (35.7% vs. 24.3%). Patients deemed not sick enough had greater than 95% survival, while those deemed too sick still had >30% survival. Conclusions Despite no LT, the majority of patients were alive at 21 days. Survival was lower in nonlisted patients. Clinicians are more accurate in deeming patients not sick enough to require LT as opposed to deeming patients too sick to survive.
Introduction In the last decade, hybrid linear accelerator magnetic resonance imaging (Linac‐MR) devices have evolved into FDA‐cleared clinical tools, facilitating magnetic resonance guided radiotherapy (MRgRT). The addition of a magnetic field to radiation therapy has previously demonstrated dosimetric and electron effects regardless of magnetic field orientation. Purpose This study uses Monte Carlo simulations to investigate the importance and efficacy of the magnetic field design in mitigating surface dose enhancement in the Aurora‐RT, focusing specifically on contaminant electrons, their origin, and energy spectrum. Methods The Aurora‐RT 0.5 T Biplanar Linac‐MR device was modeled using the BEAMnrc package using the updated EM macros, a magnetic field map generated from Opera 3D. Simulation generated phasespace data at the distal side of the first magnetic pole plate (89 cm) and at machine isocenter (120 cm) were analyzed with respect to electron energy spectra and electron creation origins, both with and without the static magnetic field. Results The presence of the main magnetic field was verified to affect the origin and distribution of contaminant electrons, removing them from the air column up to 60 cm from the target, and focusing them along the CAX within the region below. Analysis of the remaining electron energy fluence reveals the net removal of electrons with energies > 2 MeV and generation of electrons with energies < 2 MeV in the presence of the static magnetic field as compared to no magnetic field. Moreover, in the presence of the magnetic field the integral energy contained in the contaminant electrons increases from 89 cm to isocenter but is still 15% less overall than the integral energy contained in contaminant electrons without the magnetic field. Conclusion This study provides an analysis of contaminant electrons in the Aurora‐RT 0.5 T Linac‐MR, emphasizing the role of magnetic field design in successfully minimizing electron contaminants.
We ask whether artificially induced testosterone pulses (T-pulses), administered to males in the wild at the territory boundary, adjust location preferences within the territory. Multiple transient T-pulses occurring after social interactions in males can alter behaviour and spatial preferences. We previously found that T-pulses administered at the nest induce male California mice, a biparental and territorial species, to spend more time at the nest likely through conditioned place preferences. We hypothesized that T’s reinforcing effects would increase future time by the T-injected males at the boundary and promote territorial defence. Contrary to predictions, T-pulses induced a decrease in male time at the boundary, and instead appeared to promote male territorial/home range expansion, accompanied by shorter sustained vocalizations (SVs) and decreased proportion of three SV bouts. Shorter SVs are associated with aggression in the laboratory. Furthermore, in response to T-male behavioural changes, uninjected female partners decreased boundary time. Our results suggest new functions for socially induced T-pulses, such as extending territorial boundaries/home ranges. Location preferences induced through reinforcing/rewarding mechanisms may be more plastic and dependent on physical and social contexts than previously thought. Moreover, the results suggest that location preferences produced through rewarding/reinforcing mechanisms can be viewed from adaptive perspectives to influence future behaviour.
Introduction The aim of this study was to pilot test a question prompt list (QPL) about cardiovascular disease (CVD) risk reduction after hypertensive pregnancy (HDP). Methods In a prospective cohort study of adult women who had HDP given the QPL before and surveyed after a physician visit, we assessed perceived person‐centred care, self‐efficacy for self‐management, perceived self‐management and QPL feasibility. Results Twenty‐three women participated: 57% of diverse ethno‐cultural groups, 65% < 40 years of age and 48% immigrants. Most scored high for person‐centred care (mean 4.1 ± 0.2/5); and moderately for self‐efficacy (mean 7.4 ± 0.6/10) and self‐management (mean 3.1 ± 0.3/5). Most appreciated QPL design and reported QPL benefits: helped them to prepare for the visit and know what to ask; increased confidence to ask questions, knowledge of the link between HDP and CVD and lifestyle behaviours to reduce CVD risk. Most reported that physicians were receptive to discussing QPL questions. Conclusion Women appreciated the QPL and knowledge about self‐management was high but self‐efficacy for or perceived self‐management was moderate. It appears feasible to share a QPL with ethno‐culturally diverse women who can share it with physicians to facilitate discussions about post‐pregnancy HDP‐related CVD risk. Patient or Public Contribution This study involved women who experienced HDP and engaged ethno‐culturally diverse women with lived experience of HDP as study advisors in all stages of the research.
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Nelson Lee
  • Division of Infectious Diseases
Zaher Hashisho
  • Department of Civil and Environmental Engineering and the School of Mining and Petroleum Engineering
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