Abstracts & Biographies
Thursdays, 1:00 - 2:00 pm in S373
View the full seminar schedule.
A community-based approach to end land use planning at Highland Valley Copper
Jaimie Dickson, MSc, Teck Highland Valley Copper
The 2016 Highland Valley Copper (HVC) End Land Use Plan was developed as a collaboration between HVC and Nlaka’pamux communities. The two main goals of the plan were: 1) to incorporate input from Nlaka’pamux people about landscape reclamation goals, and 2) to identify potential land uses that the postclosure landscape is capable of providing and that are important to the Nlaka’pamux community. Nlaka’pamux communities were involved in the planning process through a number of collaborative workshops. The information shared was incorporated into a technical mapping process to identify possible post-closure ecosystems. This mapping involved first creating a map from aerial photographs from the 1950s to determine the biogeoclimatic ecosystems that existed prior to mining. Post-closure ecosystem maps were then created based on Nlaka’pamux input and constrained by the range of potential ecosystems that can exist on the mine site after closure. Projected post-closure ecosystems were estimated based on (i) necessary depths and available volumes of reclamation-cover materials, and (ii) altered topography and changes to the ability of surficial materials to store water due to mining activity. Potential land uses were then identified. A plain-language photobook was completed in addition to a technical report to communicate project results to participating communities.
Have you thought about studying Medicine or Vet Medicine in the Cayman Islands?
Dr. Samantha Shields, Doctor of Vet Medicine, St. Matthews University, Grand Cayman, British West Indies
Since 1997, more than two thousand students have obtained their MD and DVM degrees from SMU. Graduates have earned residencies and/or permanent licensure in nearly every state in the U.S., Canada, and numerous other countries. Our students achieve exceptional scholastic success, with U.S. licensing examination pass rates comparable to U.S. schools and well above the average of other non-U.S. schools.
No small feat: using quantum mechanics to see atoms, molecules and electrons at surfaces
Dr. Sarah Burke, Member of Physics & Astronomy and Chemistry Department, UBC
Quantum tunneling is one of the features of quantum mechanics that captures the imagination, with particles able to pass directly through barriers instead of over them. Scanning Tunneling Microscopy (STM) uses this phenomenon of quantum tunneling to give a unique view of materials, creating images of the atomic scale structure and quantum states of surfaces by scanning a tunneling tip over a surface a mere atom’s width away. The information that can be obtained about the real-space electron density, and energy dependence of the density of states provides us with insight into electronic transport, optoelectronic properties, magnetism and reactivity of materials. Together with a suite of related techniques collectively known as Scanning Probe Microscopy (SPM), these versatile methods have had impact in fields as diverse as biology and quantum computing. Using my group’s work, I will show examples of how SPM can be used to characterize the electronic landscapes that drive charge separation in organic solar cells, influence reactivity, and give rise to superconductivity and other electronic phases in quantum materials. These diverse topics have surprising commonalities in the underlying ways in which electrons in materials interact. I will describe the process of discovery in these vignettes to highlight the sometimes winding – and exciting! – path that research can take.
Aluminum Coordination Complexes in Polymerization Reactions
Mr. Hart Plommer: Ph.D candidate at Memorial University of Newfoundland in St. John’s. TRU Chemistry alumnus (2013) in computational chemistry.
Green chemistry principles are important for reducing hazards inherent with conventional chemistry practices. Our research group focuses on the synthesis of Al amino-phenolate complexes and their application as catalysts in polymerizations of polar monomers and copolymerization with CO2, an abundant and renewable feedstock. Previously in the Kerton group, an Al amino-phenolate complex incorporating two morpholinyl side-arm donors has shown promising reactivity in copolymerization of cyclohexene oxide (CHO) and CO2, furnishing copolymer with up to 54% carbonate linkages. Using this same complex, very high activities and molecular weights were obtained in the ring- opening polymerization of CHO. This led us to examine a simplified Al amino-(bis)phenolate system 1 containing a single morpholinyl donor in copolymerization of CHO/CO2. The resulting poly(cyclohexene carbonate)s showed exceptional carbonate content and narrow dispersities. Addition of different Lewis acids to 1 generated an Al cation (with associated weakly coordinating anion, WCA) by chloride abstraction. These cationic complexes showed excellent control in ε- caprolactone polymerizations using ethanol and glycerol carbonate as co-initiators.
Two-Phase Collaborative Group Exams: Increasing Student Enjoyment and Providing Them with Immediate Feedback
Joss Ives Senior Instructor, Dept. of Physics & Astronomy, Vantage College, UBC, Vancouver
In this talk, I will discuss our research on two-phase collaborative group exams, as well as discussing implementation details for this instructional strategy. Two-phase collaborative group exams promote individual accountability and collaborative learning in an exam environment. The most common implementation of this exam format has the students first take the exam individually, and then once all students have handed in their individual exams, they organize into small collaborative groups and take the same or similar exam again with only a single copy of the exam being given to each group. Our group’s research into this instructional strategy has looked at the impact on learning, how group composition impacts group performance, and various factors that influence students’ self-reported outcomes. Implementation details to be discussed include group formation considerations and common variations in implementation.
Predicting Homologous Proteins using an Ensemble of Subsets of Variables
Dr. Jabed Tomal: Assist. Prof. in Statistics, TRU; PhD (UBC); Research in statistical machine learning, data science, Bayesian statistical inference, statistical ecology.
Homologous proteins are considered to have a common evolutionary origin. To produce an evolutionary sequence of proteins, a scientist needs to predict their biological homogeneity. We have proposed a model to predict biological homogeneity of proteins using feature variables obtained from the similarity search and amino acid sequences between candidate and target proteins. The assumption is that the structural similarity and amino acid sequence identity of proteins relate to biological homogeneity. The proposed model is an ensemble of logistic regression models (LRM), where each constituent LRM is fitted to a subset of feature variables. An algorithm is developed to group the variables into subsets in a way that the variables in a subset appear to be good to put together in an LRM, and the variables in different subsets appear to be good in separate LRMs. The strength of the ensemble depends on the algorithm’s ability to identify strong and diverse subsets of feature variables. The methods are applied to rank rare homologous proteins ahead of non- homologous proteins in protein homology data obtained from the KDD cup website. The performances of our ensemble are found better than the winning procedures of the competition and state-of-the-art ensembles.