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Novel dimers as inhibitors of alpha-synuclein aggregation
Get PDFMitacs GlobalinkNon-Peer ReviewedParkinson’s Disease is characterized by the death of dopaminergic neurons in the substantia nigra as a result of the aggregation of alpha synuclein (AS)
Nicotine from smoking and 1 aminoindan (a metabolite of Rasagiline) seem to be neuroprotective compounds and both have been associated with the reduction of the risk to develop Parkinson’s disease
These compounds bind to AS at both the N and C terminus, forcing the protein to adopt a loop conformation, which appear to contribute to the neuroprotective activity of the drugs
Dimer molecules linked with two neuroprotective compounds should increase the binding constants to AS and increase the efficacy to prevent AS aggregation
Phase 1 metabolic studies using hepatic microsomes in vitro are needed to determine the susceptibility of the compounds to biotransformatio
Unseating Broken Stories: A Decolonizing Case Study of Warrior Queenmother, Nana Yaa Asantewaa
Get PDFWestern scholarship and media continue to reproduce problematic, inaccurate representations of Africa. African women have borne the brunt of these misrepresentations, and despite all evidence to the contrary, have too often been presented as weak, submissive, voiceless, and dominated by African and other men. Pluralizing stories of African women’s agency, past and present, deserves more focused critical scholarly attention. This thesis aims to challenge stereotypical stories of African women’s defenselessness by modeling one approach to unseating such broken stories through a critical analysis of representations of the historical figure of Nana Yaa Asantewaa, an Asante warrior and one in a long line of anti-imperialist African women leaders seeking justice for their communities and nations. People who tell undermining stories about defenseless African women often do so from within the power systems they wish to uphold, or in which they are caught. Biases and stereotypes that benefit these systems inform circulating ideologies with a vested interest in producing and reproducing reductive stories about African women. The approach here is to start from strengths-based stories in a critical effort to model the construction of more complete stories about African women. Nana Yaa Asantewaa has left a profound legacy that still informs representations and understandings of contemporary Ghanaian women as critical subjects with agency. Her role in the war against the British from 1900-1901, and the ways that her story has been taken up since, illuminate the complex range of forces shaping Ghanaian histories, and framing local, regional, national, and transnational challenges perpetuated by, but also mounted against, hegemonic patriarchal power structures. This research examines the representations and vested interests of diversely positioned academic and non-academic storytellers in discussions surrounding Nana Yaa Asantewaa through narrative, discourse, and visual analyses, employing a critical decolonial theoretical lens that centers the perspectives, achievements, and promise of African women
Energy-Efficient and Fresh Data Collection in IoT Networks by Machine Learning
Get PDFThe Internet-of-Things (IoT) is rapidly changing our lives in almost every field, such as smart agriculture, environmental monitoring, intelligent manufacturing system, etc. How to improve the efficiency of data collection in IoT networks has attracted increasing attention. Clustering-based algorithms are the most common methods used to improve the efficiency of data collection. They group devices into distinct clusters, where each device belongs to one cluster only. All member devices sense their surrounding environment and transmit the results to the cluster heads (CHs). The CHs then send the received data to a control center via single-hop or multi-hops transmission. Using unmanned aerial vehicles (UAVs) to collect data in IoT networks is another effective method for improving the efficiency of
data collection. This is because UAVs can be flexibly deployed to communicate with ground
devices via reliable air-to-ground communication links. Given that energy-efficient data
collection and freshness of the collected data are two important factors in IoT networks, this thesis is concerned with designing algorithms to improve the energy efficiency of data
collection and guarantee the freshness of the collected data.
Our first contribution is an improved soft-k-means (IS-k-means) clustering algorithm
that balances the energy consumption of nodes in wireless sensor networks (WSNs). The
techniques of “clustering by fast search and find of density peaks” (CFSFDP) and kernel
density estimation (KDE) are used to improve the selection of the initial cluster centers of
the soft k-means clustering algorithm. Then, we utilize the flexibility of the soft-k-means
and reassign member nodes by considering their membership probabilities at the boundary
of clusters to balance the number of nodes per cluster. Furthermore, we use multi-CHs to
balance the energy consumption within clusters. Extensive simulation results show that, on
average, the proposed algorithm can postpone the first node death, the half of nodes death,
and the last node death when compared to various clustering algorithms from the literature.
The second contribution tackles the problem of minimizing the total energy consumption
of the UAV-IoT network. Specifically, we formulate and solve the optimization problem that
jointly finds the UAV’s trajectory and selects CHs in the IoT network. The formulated problem is a constrained combinatorial optimization and we develop a novel deep reinforcement
learning (DRL) with a sequential model strategy to solve it. The proposed method can effectively learn the policy represented by a sequence-to-sequence neural network for designing
the UAV’s trajectory in an unsupervised manner. Extensive simulation results show that the
proposed DRL method can find the UAV’s trajectory with much less energy consumption
when compared to other baseline algorithms and achieves close-to-optimal performance. In
addition, simulation results show that the model trained by our proposed DRL algorithm
has an excellent generalization ability, i.e., it can be used for larger-size problems without
the need to retrain the model.
The third contribution is also concerned with minimizing the total energy consumption
of the UAV-aided IoT networks. A novel DRL technique, namely the pointer network-A*
(Ptr-A*), is proposed, which can efficiently learn the UAV trajectory policy for minimizing
the energy consumption. The UAV’s start point and the ground network with a set of
pre-determined clusters are fed to the Ptr-A*, and the Ptr-A* outputs a group of CHs and
the visiting order of CHs, i.e., the UAV’s trajectory. The parameters of the Ptr-A* are
trained on problem instances having small-scale clusters by using the actor-critic algorithm
in an unsupervised manner. Simulation results show that the models trained based on 20- clusters and 40-clusters have a good generalization ability to solve the UAV’s trajectory
planning problem with different numbers of clusters, without the need to retrain the models.
Furthermore, the results show that our proposed DRL algorithm outperforms two baseline
techniques.
In the last contribution, the new concept, age-of-information (AoI), is used to quantify
the freshness of collected data in IoT networks. An optimization problem is formulated to
minimize the total AoI of the collected data by the UAV from the ground IoT network.
Since the total AoI of the IoT network depends on the flight time of the UAV and the data
collection time at hovering points, we jointly optimize the selection of the hovering points and the visiting order to these points. We exploit the state-of-the-art transformer and the
weighted A* to design a machine learning algorithm to solve the formulated problem. The
whole UAV-IoT system, including all ground clusters and potential hovering points of the
UAV, is fed to the encoder network of the proposed algorithm, and the algorithm’s decoder
network outputs the visiting order to ground clusters. Then, the weighted A* is used to find
the hovering point for each cluster in the ground IoT network. Simulation results show that
the model trained by the proposed algorithm has a good generalization ability to generate
solutions for IoT networks with different numbers of ground clusters, without the need to
retrain the model. Furthermore, results show that our proposed algorithm can find better
UAV trajectories with the minimum total AoI when compared to other algorithms
Equilibrium shapes of two and three dimensional two-phase rotating fluid drops with surface tension: effects of inner drop displacement
Get PDFNSERCPeer ReviewedThe shapes of rotating fluid drops held together by surface tension is an important field
of study in fluid mechanics. Recently, experiments with micron-scale droplets of liquid
helium have been undertaken and it has proven useful to compare the shapes of the resultant
superfluid droplets with classical analogs. If the helium is a mixture of He3 and He4, two
phases are present. In a recent paper, the shapes of rotating two phase fluid droplets were
calculated where the inner drop was constrained to stay at the drop center. The outer
shapes and dimensionless rotation rate-angular momentum relationships were shown to
be similar to single phase drops provided that the density and surface tension scales were
chosen appropriately. In the current paper, I investigate models in which the inner drop can
displace from the centre. In order to simplify the analyses, two dimensional drops are first
investigated. I show that the inner drop is unstable in the centre position if its density is
greater than the outer density and that the inner drop will move towards the outer boundary
of the drop in these cases. When the inner drop has a higher density than the outer drop,
the moment of inertia of displaced inner drops is increased relative to centered drops and
hence the kinetic energy is decreased. Shapes of two and three dimensional drops, rotation
rate-angular momentum and kinetic and surface energy relationships are investigated for
off-axis inner drops with parameters relevant to recent liquid He experiments
EVALUATING A DNA-BASED APPROACH TO DIET ASSESSMENT
Get PDFDNA-based approaches have become useful for ecologists to study the diets of wildlife, as molecular tools like qPCR allow researchers to analyze the DNA of prey in a predator’s feces. However, questions about whether these tools can accurately quantify dietary composition through fecal analyses remain largely unanswered. This thesis investigates the ability for qPCR to quantify arthropod prey in feces using a chicken model. Captive chickens (Gallus domesticus) were offered mealworms (MW; Tenebrio molitor) and black soldier fly larvae (BF; Hermetia illucens), and the chickens’ feces were collected for qPCR analyses. A multiplex assay was designed to analyze fecal DNA, which included species-specific assays targeting the cytochrome c oxidase subunit I gene of MWs and BFs. qPCR results were used to meet three objectives.
First, I evaluated whether detection and quantification of prey DNA differed between species. Analyzing DNA from hard-bodied arthropods (MWs) may be affected by their more substantial exoskeleton relative to soft-bodied arthropods (BFs). Results showed that in feces, BF DNA was detected more often with a higher but more variable quantity compared to MW DNA. In whole arthropods, a higher and less variable quantity of BF DNA was measured than MW DNA, but the difference between species was smaller in whole arthropods than in feces. Second, I investigated how the time between ingestion of prey and defecation affects detection and quantification of prey DNA. Detection first occurred 30 minutes after feeding and peaked after 4 hours, and trace amounts of DNA were detected on days following consumption. Models showed that time had a negative linear effect on detection and a negative quadratic effect on quantity. Third, I evaluated whether qPCR results could be used to estimate dietary composition. With the results, I was able to accurately characterize the relative composition of mixed diets, and models indicated that estimated and true consumption were significantly related for both species.
I have shown that molecular analyses of feces can be used to infer the relative composition of an arthropod-based diet. Results also provide insight on how sampling time may affect conclusions about diet. However, soft-bodied BFs were overrepresented, suggesting a potential bias based on the prey’s body type. To confirm this bias, more research is needed with additional species of each body type, fed to predators with more complex proportions. By addressing questions about the quantitative potential of this molecular technique, my work has contributed to improving inference from DNA-based diet studies
PREPARATION AND CHARACTERIZATION OF POLYANILINE-BASED MATERIALS FOR ELECTROCHEMICAL DETECTION OF NITROPHENOLS
Get PDFThe development of modified polyaniline (PANI)-based composites is an emerging field of advanced materials with fascinating applications such as the adsorption of metals and dyes, sensors, and biocatalysts. The electrical conductivity of PANI and its structural properties are influenced by the method used for its synthesis. Thus, if an appropriate synthetic method is employed, modified PANI-based composites can be utilized for sensor-based applications. Unfortunately, pristine PANI presents numerous challenges. It is difficult to process and has poor film-forming ability, which limits its application for practical environmental applications. The mentioned disadvantages can be addressed through formation of composites, where the use of additives or supporting materials are combined with PANI.
Chitosan (CHI) is a biopolymer that includes hydroxyl and amine functional groups that can be modified by forming a composite with PANI (CHI-PANI). Doping PANI with organic acids such as citric acid can improve its hydrophilicity and conductivity. To study the electrocatalytic properties of modified PANI-based composites, silver nanoparticles (Ag NPs) were deposited onto the composites to monitor the oxidation of 2-nitrophenol (2-NP) and 4-nitrophenol (4-NP) in aqueous media. Cyclic voltammetry (CV) was chosen as the electrochemical method for the analytical detection of 2-NP and 4-NP.
The short-term objectives of the thesis are summarized below:
(i) To synthesize ternary composites of Ag NPs-Chitosan-PANI (Ag@CP(x), where x = 25, 50, or 75, referring to the weight fraction (%) of aniline relative to CHI) and Ag NPs-PANI-citric acid (Ag@P-CA).
(ii) To carry out structural and physicochemical characterization of modified PANI-based composites with thermogravimetric analysis (TGA), atomic absorption analysis (AAS), 13C solid-state NMR spectroscopy, FTIR spectroscopy, X-ray diffraction (XRD), UV-Vis spectroscopy, X-ray photoelectron spectroscopy (XPS) and dye adsorption techniques.
(iii) A CV study that employs modified PANI-based electrode materials (Ag@CHI-PANI and Ag@P-CA) for electrochemical characterization of properties and nitrophenol detection.
The long-term objective of this thesis is to develop novel modified PANI-based electrode materials for the electrochemical detection of 2-NP in water and environmental groundwater samples. Based on the 2-NP adsorption isotherms, Ag@CP75 was effective as an electrode material with 40% and 330% higher 2-NP adsorption capacity than PANI and CHI, respectively. Based on the CV of modified PANI-based composites in nitrophenol solutions, the relative standard deviation (RSD) of 5.70% was assigned to Ag@CP75's selectivity in the presence of nitrophenol isomers and inorganic salts. The RSD’s of 2.68% and 2.64% were accredited to Ag@CP75's stability (nine cycles) and reproducibility (ten cycles) for the electrochemical detection of 2-NP, respectively. CV studies on Ag@P-CA supported the increase in electron transfer rate after the deposition of Ag NPs onto P-CA. Lastly, an illustration of the pathway for the detection of nitrophenols with PANI-modified electrode materials was proposed based on the electrochemical results obtained in this thesis and the theory of electrochemistry (cf. Figure 5-11). This illustrated pathway divides 2-NP detection mechanism into various steps (chemical reaction, adsorption, desorption, electrochemical reaction). By optimizing each of these steps, the detection mechanism can be improved for future studies
First-principles Studies on the Structures and Properties of Glasses and Melts under Extreme Conditions
Get PDFThe objective of this thesis is to study the bonding, electronic properties and chemical reactions of glasses and melts under high pressure. The work is mainly based on first- principles molecular dynamics (FPMD) simulations. State-of-the-art first-principles computational methods are employed in the further analyses of the MD trajectories to obtain the electronic properties. This thesis is composed of four projects and it is divided as follows.
The first project investigates the reaction of CaCO3 melts and H2 at pressure-temperature conditions similar to the Earth’s lower mantle and the core-mantle boundary via first-principles molecular dynamics (FPMD) simulations. Two models with different H2/CO3 2– ratios are studied under different pressure-temperature conditions. A variety of chemical reactions are observed. It is found that H dissociates readily and reacts with free CO3 2–, forming various transient chemical species and water molecules. Further reactions of these reactive species serve as intermediates to form C-C and C-O connections. The unreacted bulk carbonates are linked via polymeric-cornered shared CO4 tetrahedra. At 110 GPa and 4087 K, “diamondoids” with tetrahedral C4 moieties are found. This may be the precursor for diamond formation. The theoretical results support recent reports on the observation of tetrahedral CO4 in high-pressure carbonate glasses and suggest a plausible explanation of ice-VII inclusion in the deep-Earth diamonds.
The second project explores the bonding of B2O3 glass up to 350 GPa. The main concern is whether a higher order of B-O bonds can be formed at high pressure. Experiments on the B2O3 glass performed up to 125 GPa have suggested that the coordination numbers of B higher than 4 were presented. This proposal is puzzling since there are no low-lying d orbitals in the second-row elements, i.e., B and O. In this thesis, B K-edge X-ray absorption spectra (XAS) are calculated via the core-hole methods and the Bethe-Salpeter equation (BSE) method. Chemical shifts from nuclear magnetic resonance (NMR), Bader’s quantum theory of atoms in molecules (QTAIM), and electron localization function (ELF) are calculated to investigate whether extra B-O bonds can be formed in the B2O3 glass at high pressure. It is found that 5- and 6-coordinated B is formed under high pressure, but not all the close interactions of B and O are actual covalent bonds. Instead, the BO5 or BO6 clusters consist of 4 short B-O covalent bonds forming weaker B-O interactions with the other O atoms. In a parallel study, structure prediction of crystalline B2O3 is performed at similar pressures to the glass. No 6-coordinated B is found in the predicted structures.
The third project explores the bonding of amorphous SiO2 up to 198 GPa to investigate whether OSi4 quadclusters can be formed in SiO2 glass, as was claimed in a recent experiment. O K-edge X-ray Raman scattering (XRS) spectra are calculated. Various electronic structures and QTAIM analyses are performed. It is found that the OSi4 quadclusters do exist, but the four O-Si are not 4 equivalent covalent O-Si bonds. Instead, OSi4 quadclusters consist of 3 short O-Si bonds and 1 long O-Si with weaker interaction.
The final project starts with investigating the equation of states (EOS) of MgSiO3 glasses at high pressure via FPMD simulations. It is found that at low pressures (0 and 5 GPa), the calculated density of MgSiO3 glass well-reproduced the experimental density values. However, at higher pressures, the density from calculation is underestimated compared with the experiment, partly due to using the generalized gradient approximation (GGA). Despite the deviation in density, the structures of the MgSiO3 glass from calculation are in good agreement with experiments and other calculations. Inspired by the sudden perovskite to post-perovskite transform in the MgSiO3 crystal above 125 GPa and 2000 K, this thesis also studies whether there is a similar sudden change in the local structure of MgSiO3 melts. Analysis of the electronic structure of MgSiO3 melts reveals a semi-metallic/metallic property at high temperature, even at 0 pressure
THE EPIDEMIOLOGY OF CHRONIC WASTING DISEASE ON SASKATCHEWAN CERVID FARMS (2002 – 2017)
Get PDFChronic wasting disease (CWD) is a naturally occurring fatal transmissible spongiform encephalopathy of cervids. In 1996, CWD was recognized in a herd of farmed elk in Saskatchewan (SK) and by the year 2000 the disease was detected in wild mule deer (Bollinger et al., 2004). Records of CWD in farmed elk and white-tailed deer (WTD) in SK from 2002 – 2017 were reviewed to: 1) summarize the epidemiology of the disease in farmed elk and WTD within the province, and 2) develop a quantitative risk assessment to determine the probability of there being at least one infected WTD or elk in a movement event dependent on the location of the farm within the province. Data collected and compiled by the Canadian Food Inspection Agency and the SK Ministry of Agriculture were used to describe the epidemiology of CWD in SK farm cervids from 2002 – 2017. During this time period a total of 56 farms were found to be infected with CWD and underwent an eradication process. Animal movements within the period were numerous, with immigration events occurring more frequently than emigration events. Infected farms averaged nine movement events over the 16-year time period (range 0 – 74 movement events), and movement events onto and off farms involving at least one known CWD-positive animal occurred in 13 and 10 of the 16 years, respectively. Sources of CWD transmission for case farms were determined for 84% (47/56) of farms, and were primarily linked to within-farm (68%, 15/47) and off-farm sources (32%, 15/47), while for the remaining 16% (9/56) of farms, the source was unproven. The 132MM and 96GG genotypes were most prominent for CWD detected in elk and WTD, respectively. Higher immunohistochemistry grading was observed for clinically infected animals (70% of WTD were Grade 3, and 58% elk were Grade 4). Since the initial evaluation period (1996 – 2002) of CWD on farmed elk, the median period prevalence of CWD on farms slightly decreased from 4.4% to 3.9%, and the median prevalence at the time of depopulation (point prevalence) for this review period was 2.6%.
A quantitative risk assessment determined that the risk of an infected animal being involved in a movement event was dependent on the geographic location, sex and age of the animal. The quadrant sections Q1 (central west) and Q2 (central east) had the greatest probability of an infected animal being involved in a movement event for WTD and elk, respectively, while Q4 (southeast) had the lowest probability for both species. Captive WTD within SK had a greater mean probability of at least one infected animal (4.80%) being involved in a movement event compared to elk (3.22%) for the province as a whole. For elk, males less than the median age of CWD detection (70 mo) posed the greatest risk of contributing at least one infected animal in a shipment within the province, while for WTD the disease prevalence on WTD farms posed the greatest risk.
We conclude that during this time period within-farm transmission was an increasingly important source of infection; however, the movement of infected animals among farms continued to play a role in the spread of disease within the province. Further investigation and identification of farm management factors associated with within-farm CWD transmission could help mitigate disease spread and decrease prevalence on SK cervid farms. The risk assessment study concluded that the geographic location, species, sex and age influence the potential risk of having at least one CWD infected animal involved in a movement event. Although additional risks (provincial surveillance program compliance, history of CWD detection on farm, duration and distance of shipment and quarantine protocol) were not investigated, further analysis involving added risks would be needed to further understand and lessen disease spread
Are honey bees a suitable model for fetal alcohol spectrum disorders?
Get PDFFetal alcohol spectrum disorders (FASDs) are a continuum of disorders caused
by prenatal exposure to ethanol. They affect an estimated 4% of Canadians. FASDs are associated with a host of complications including, but not limited to, cognitive difficulties, developmental delay, increased mortality, smaller birth weight, smaller brain size, as well as gross and fine motor issues.
It has been previously established that fruit flies (Drosophila melanogaster) are a suitable invertebrate model for FASDs. Honey bees (Apis mellifera) share many similarities to Drosophila as a research model, but with the distinct advantage of highly social behaviour, similar to that of humans.
In this project we exposed honey bees to incremental, sublethal concentrations of ethanol during larval development and monitored their survival, developmental rate, and weight at adult emergence. We found that larval honey bees exposed to ≥6% ethanol experienced significantly higher mortality, developmental delay, and lower body weight at emergence. Accordingly, these results, in combination with ongoing neurobehavioural analyses of adult bees exposed to ethanol as larvae, suggest that honey bees may be an ideal model for human FASDs
ABS and Biodiversity Conservation: Does the Design of the ABS system allow for the realization of the Post-2020 Framework?
Get PDF©DivSeek International Network Inc. Sept 2022Peer Reviewe