Faculty of Science

Permanent URI for this communityhttps://hdl.handle.net/10155/386

The Faculty of Science (FSCI) provides students with the tools needed to adapt to future developments in the scientific path of their choice. Areas of study include applied & industrial mathematics, chemistry, integrative neuroscience, forensic science, computer science and physics.

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Now showing 1 - 20 of 446

A few-shot learning method for single-object visual anomaly detection
(2024-04-01) Ejaz, Neha; Qureshi, Faisal
We propose a few-shot learning method for visually inspecting single objects in an industrial setting. The proposed method is able to identify whether or not an object is defective by comparing its visual appearance with a small set of images of the “working” object, i.e., the object that passes the visual inspection. The method does not require images of defective objects. Furthermore, the method does not need to be “trained” when used to inspect new, previously unseen, objects. This suggests that the method can be easily deployed in industrial settings. We have evaluated the method on three visual anomaly detection benchmarks—1) MVTec, 2) MPDD, and 3) VisA. On the first two datasets the proposed method achieves performance that is comparable to state-ofthe- art methods that require access to object-specific training data. Model performance on VisA is poor; however, it is to be noted that the model was never trained on VisA dataset. We also show that the proposed model boasts fast inference times, which is a plus for industry applications. This project is funded in part by Axiom Plastics Inc., and we have evaluated the proposed method on a proprietary dataset provided by Axiom. The results confirm that the proposed method is well-suited for single-object visual anomaly detection in industry settings.
A study of meta-learning methods on the problem of video matting
(2024-04-01) Tabaraki, Negin; Qureshi, Faisal; Pu, Ken
Applying image matting techniques directly to video matting presents challenges, primarily due to the complex temporal dynamics inherent in video data. In this work, we studied two Meta Learning approaches—Boosting with Adapters (BwA) and Boosting using Ensemble (BuE)—to tackle the task of video matting using pre-trained image matting models. BwA refines (image matting) alpha mattes by fine tuning pre-trained segmentation models, which we refer to as adapters, using video frames. BuE, additionally, combines multiple fine-tuned adapters using a convolutional neural network. We introduced a meta-learning architecture that incorporates both adapters and ensemble boosting through an iterative process of expert selection and fine tuning. Based on our evaluation on benchmarks based on a standard video matting dataset (VideoMatte240K), we confirm that the proposed scheme improves the performance of image matting models on the task of video matting. In addition, the proposed approach also improves the performance of VMFormer (c. 2022), a recent video matting method.
A targeted reverse mapping machine learning approach for non-dominated solutions in multi-objective optimization
(2024-08-01) Kermani Poor, Masoud; Ibrahimi, Mehran; Rahnamayan, Shahryar
Multi-objective optimization problems aim to identify solutions that maximize or minimize conflicting objectives. Population-based multi-objective algorithms, inspired by biological populations, are effective but often provide limited solutions within the decisionmakers’ region of interest (ROI) on the Pareto front. Recent advancements in machine learning have shown promise in generating solutions, yet they suffer from a lack of control and require knowledge of objective function attributes. This study proposes a framework using Gaussian process regression and artificial neural networks to generate innovative solutions in the ROI. By employing diverse sampling techniques and integrating long term memory, the framework can produce more than twice as many solutions in the ROI, as demonstrated in experiments with real-world problems and various benchmark functions.
Abbreviating Text Labels on Demand
(IEEE, 2017-10) Shimabukuro, Mariana; Collins, Christopher
Long text labels is a known challenge in information visualizations.There are some techniques used in order to solve this problem like setting a very small font size. On the other hand, sometimes the font size is so small that the text can be difficult to read. Wrapping sentences, dropping letters and text truncation are some techniques do deal with this problem. In order to investigate a solution for labeling long words we ran a study on how people create and interpret word abbreviations. Based on the study data we designed a new algorithm to automatically make words as short as they need to fit the text. Examples applications of this algorithm are presented in this paper.
Achieving real-time video summarization on commodity hardware
(2018-04-01) Taylor, Wesley; Qureshi, Faisal
We present a system for automatic video summarization which is able to operate in real-time on commodity hardware. This is achieved by performing segmentation to divide a video into a series of small video clips, which are further reduced or eliminated with the assistance of highly efficient low-level features. A numerical score is then assigned to each segment by our model trained using a set of highperformance hand-crafted features. Finally, segments are selected based on their score to generate a final video summary. On our benchmark dataset, we achieve results competitive to other methods. In cases where our accuracy is lower than competitive methods, we achieve significantly higher performance. We additionally present methods for generating additional summaries almost instantly, and for learning user preferences over time—two processes which are often overlooked in work on video summarization, but essential for real-world use
An adaptive crowdsourced investigation of word abbreviation techniques for text visualizations
(2017-04-01) Shimabukuro, Mariana Akemi; Collins, Christopher
A known problem in information visualization labeling is when the text is too long to fit in the label space. There are some common known techniques used in order to solve this problem like setting a very small font size. On the other hand, sometimes the font size is so small that the text can be difficult to read. Wrapping sentences, dropping letters and text truncation can also be used. However, there is no research on how these techniques affect the legibility and readability of the visualization. In other words, we don’t know whether or not applying these techniques is the best way to tackle this issue. This thesis describes the design and implementation of a crowdsourced study that uses a recommendation system to narrow down abbreviations created by participants allowing us to efficiently collect and test the data in the same session. The study design also aims to investigate the effect of semantic context on the abbreviation that the participants create and the ability to decode them. Finally, based on the study data analysis we present a new technique to automatically make words as short as they need to be to maintain text legibility and readability.
Adaptive engagement of older adults’ fitness through gamification
(2017-07-01) Kappen, Dennis L.; Mirza-Babaei, Pejman; Nacke, Lennart
Older adults are often not physically active because they lack motivation, time, and/or physical ability. Not only does this impact the life of older adults, but it also affects society as a whole, because the cost of healthcare attached to maintaining the health of older adults is continually rising. This thesis addresses the problem by investigating the disenchantment of older adults with physical activity (PA), reasons for their lack of participation in PA, and contributes motivational affordances for PA. This thesis makes three important contributions to human-computer interaction: a) the development of adaptive engagement guidelines for PA technology for older adults. b) the Exercise Motivation Technology Framework (EMFT) - a framework to aid in the design and development of PA technology for older adults, and c) the Kaleidoscope of Effective Gamification (KEG) - a design and analysis tool for helping designers design and develop gamified apps. These contributions were achieved through a phased investigative approach. The analysis of preliminary studies (Phase 1) resulted in the development of the EMTF for older adults PA technology. A survey study (Phase 2) on the preferences of motivational affordances for PA across different age groups suggested that ‘health pressures’ and ‘ill-health avoidance’ were significant exercise motives for PA in different age groups. Age-differentiated guidelines from Phase 2 were used to develop and evaluate Spirit50 (Phase 3), a gamified technology artifact, specifically developed under my supervision for adults over 50 years of age. Phase 4 was a synchronous, three-condition (gamified, non-gamified, and control groups) experimental study over an eight-week period with a total of 30 participants. Expert evaluation (Phase 5) to review technology facilitation of PA using the Spirit50 app also pointed to the usefulness and the applicability of gamification as a behaviour change technology for delivering PA solutions for older adults. The findings of this thesis contribute to understanding PA motivation among older adults on a granular level from a technology facilitation standpoint using gamification strategies. The EMTF model helped to design PA technology by combining desirability, customization, and motivational affordances for older adults. Finally, this thesis contributes to tailoring and personalizing of adaptive engagement strategies using specific gamification elements like goals supported by challenges, selection of quests based on ability, progressive feedback, and rewards validating performance and efforts as potential ways to deliver age-centric PA technology for older adults
Adaptive learning game to personalize occupational health and safety training
(2017-11-01) Chodan, Cameron; Mirza-Babaei, Pejman; Sankaranarayanan, Karthik
In 2012, the Association of Workers’ Compensation Boards of Canada recorded approximately a quarter-million workplace injuries, a staggering figure keeping in mind that some incidents go undocumented. It is important that organizations continue make Occupational Health and Safety (OHS) one of their top priorities. In this thesis, we discuss an implementation of an adaptive personalized learning support system within a game that is centered on health and safety training to promote the understanding of health and safety material. The design of the game incorporates a feedback loop that constantly evaluates the player’s performance while they complete learning challenges. As the players proceed within the game's environment their profile is constantly updated thus providing an insight into their strengths and weaknesses. The game is designed to adjust the challenges given to the player to focus on improving the player’s underperforming skills. The goal of this game is to promote health and safety in small and medium enterprises. Through this game we created a motivational designed application that helps to teach targeted health and safety information to the workers. The game was made in collaboration with the Public Services Health and Safety Association based in Toronto. The game aims to better the player’s health and safety performance in the Organizational Performance Metric and hone their underlying health and safety skills.
Adaptive serious games for computer science education
(2020-10-01) Miljanovic, Michael A.; Bradbury, Jeremy
Serious games have the potential to effectively engage students to learn, however, these games tend to struggle accommodating learners with diverse abilities and needs. Furthermore, customizing a serious game to the individual learner has historically required a great deal of effort on the part of subject matter experts, and is not always feasible for increasingly complex games. This thesis proposes the use of automatic methods to adapt serious programming games to learners' abilities. To understand the context of the problem, a survey was conducted of the serious programming game literature, which found that while many games exist, there has been very little consideration for the use of adaptation. Given the breadth of the existing serious programming game literature, a methodology was developed to support adaptation of existing games. To demonstrate the efficacy of this adaptive methodology in serious programming games, two case studies were conducted: 1) a study comparing adaptive and non-adaptive gameplay in the Gidget game, and 2) a study assessing non-adaptive gameplay, adaptive gameplay, and adaptive hints in the RoboBug game. The results from both case studies provide evidence to the need for adaptation in serious programming games, and illustrate how the adaptive methodology can be utilized to positively affect the engagement of learners and their ability to achieve learning outcomes.
Advancing and expanding siRNA and saRNA therapeutics applications through chemical modifications
(2024-04-01) Giorgees, Ifrodet; Desaulniers, Jean-Paul
Oligonucleotides are short strands of DNA or RNA that are used to treat complex diseases like cancer and rare genetic diseases. They rely on biological pathways in our body to work. Two pathways that are important to this study are gene silencing and activation. Short interfering RNAs (siRNAs) silence genes, while short activating RNAs (saRNAs) activate them. Both types of strands can be used to create new cancer treatments. However, RNA-based therapies face challenges like instability, off-target effects, and low cell membrane permeability. To overcome these challenges, this study focuses on incorporating new chemical modifications into the RNA and assessing their impact on RNA activity. Our aim is to enhance RNA therapeutic efficacy for potential cancer therapy applications. The first goal focused on creating a combination therapy for cancer treatment by directly conjugating free base corrole molecules to siRNA. This novel construct created a combination therapy effect of gene silencing and simultaneous photodynamic therapy (PDT). This combination therapy is expected to be more targeted and non-invasive compared to traditional cancer treatments like surgery or chemotherapy. The second goal of this research involved exploring the potential of metal corrole molecules within siRNA for personalized cancer treatment. In this study, Ga-corrole was directly conjugated to siRNA, resulting in an advanced treatment consisting of live imaging and gene silencing. This novel construct created a new tool for siRNA real-time imaging applications that could potentially allow for real-time drug monitoring during cancer treatment. The third goal focused on discovering nuclease-resistant and active saRNAs targeting STING, which is a potential target for the treatment of solid tumors. In this study, a library of chemically modified saRNA was screened for their nuclease resistance ability and investigated for any potential correlations between chemical modifications, nuclease resistance and high gene upregulation activity. The results of nuclease stability assays revealed that the position of the chemical modifications within the RNA can significantly influence nuclease resistance. Furthermore, novel chemical modification designs were established for the synthesis of stable and highly active STING saRNA duplexes. In conclusion, this dissertation highlights novel approaches to enhance RNA therapeutics and employ RNA molecules for cancer drug monitoring or treatment applications.
Aerodynamic and thermal analysis of a heat source at the underside of a passenger vehicle
(2014-12-01) Khasow, Rocky; Agelin-Chaab, Martin
The first part of this thesis involves full experimental and numerical studies to understand the effects of cross-winds on the automotive underbody aero-thermal phenomena using a 2005 Chevrolet Aveo5 with a heat source affixed to it to create a baseline. The results show that irrespective of the yaw angle used, only temperatures in the vicinity of the heat source increased. The rear suspension also deflected the airflow preventing heat transfer. The second part of this thesis investigated using a diffuser to improve hybrid electric battery pack cooling. It was found that the diffuser led to more consistent temperatures on the diffuser surface, suggesting the same for the battery.
Agent-based modeling framework for adaptive cyber defence of the Internet of Things
(2022-12-01) Rafferty, Laura; Hung, Patrick
The adoption of the Internet of Things (IoT) continues to increase significantly, introducing unique challenges and threats to cybersecurity. In parallel, adaptive and autonomous cyber defence has become an emerging research topic leveraging Artificial Intelligence for cybersecurity solutions that can learn to recognize, mitigate, and respond to cyber attacks, and evolve over time as the threat surface continues to increase in complexity. This paradigm presents an environment strongly conducive to agent-based systems, which offer a model for autonomous, cooperative, goal-oriented behaviours which can be applied to perform adaptive cyber defence activities. This thesis aims to bridge the gap between theoretical multi-agent systems research and cybersecurity domain knowledge by presenting a novel applied framework for adaptive cyber defence that can address a wide range of challenges and provide a foundation for significant future research in systems modeling for cybersecurity. Belief-Desire-Intention (BDI) agent architecture is extended within this work through a novel application of knowledge graphs to provide a scalable data model for agents to understand their environment, infer the context of threats, create goals associated with security requirements, and select plans based on possible actions and expected results. The framework has been implemented to demonstrate the feasibility of the architecture and evaluate the design properties through applied security use cases. While the experimental results have demonstrated the value of the framework applied to IoT systems, the concept can be easily expanded to other domains. This thesis provides the foundation to inspire further research works in this area for continued development, application, and optimization to support the advancement of the industry and bring autonomous, adaptive cyber defence to realization.
Aiding the experts: how artificial intelligence can augment expert evaluation with PathOS+
(2022-07-01) Nova, Atiya Nowshin; Mirza-Babaei, Pejman
Within games user research (GUR) predictive methods like expert evaluation are good for getting easy insights on a game in development but may not accurately reflect the player experience. On the other hand, experimental methods like playtesting can accurately capture the player experience but are time consuming and resource intensive. AI agents have been able to mitigate the issues of playtesting, and the data generated from these agents can supplement expert evaluation. To that end we introduce PathOS+. This tool allows the simulations of agents and has features that allows users to conduct their evaluations in the same place as the game, and then export their findings. We ran a study to evaluate how PathOS+ fares as an expert evaluation tool with participants of varying levels of UR experience. The results show that it is viable to use AI to identify design problems and offer more validity to expert evaluation.
Alloy catalysts for fuel cell-based alcohol sensors
(2016-05-01) Zamanzad Ghavidel, Mohammadreza; Easton, Brad
Direct ethanol fuel cells (DEFCs) are attractive from both economic and environmental standpoints for generating renewable energy and powering vehicles and portable electronic devices. The cost and performance of the DEFCs are mainly controlled by the Pt-base catalysts used at each electrode. In addition to energy conversion, DEFC technology is commonly employed in the fuel-cell based breath alcohol sensors (BrAS). BrAS is a device commonly used to measure blood alcohol concentration (BAC) and enforce drinking and driving laws. The BrAS is non-invasive and has a fast respond time. However, one of the most important drawback of the commercially available BrAS is the very high loading of Pt employed. One well-known and cost effective method to reduce the Pt loading is developing Pt-alloy catalysts. Recent studies have shown that Pt-transition metal alloy catalysts enhanced the electroactivity while decreasing the required loadings of the Pt catalysts. In this thesis, carbon supported Pt-Mn and Pt-Cu electrocatalysts were synthesized by different methods and the effects of heat treatment and structural modification on the ethanol oxidation reaction (EOR) activity, oxygen reduction reaction (ORR) activity and durability of these samples were thoroughly studied. Finally, the selected Pt-Mn and Pt-Cu samples with the highest EOR activity were examined in a prototype BrAS system and compared to the Pt/C and Pt3Sn/C commercial electrocatalysts. Studies on the Pt-Mn catalysts produced with and without additives indicate that adding trisodium citrate (SC) to the impregnation solution improved the particle dispersion, decreased particle sizes and reduced the time required for heat treatment. Further studies show that the optimum weight ratio of SC to the metal loading in the impregnation solution was 2:1 and optimum results achieved at pH lower than 4. In addition, powder X-ray diffraction (XRD) analyses indicate that the optimum heat treatment temperature was 700°C where a uniform ordered PtMn intermetallic phase was formed. Although the electrochemical active surface area (ECSA) decreased due to the heat treatment, the EOR activity of Pt-Mn samples was improved. Moreover, it was shown that the heat-treated samples prepared in the presence of SC showed superior the EOR activity compared to the samples made without SC. The Pt-Cu/C alloys were produced by three different methods: impregnation, impregnation in the presence of sodium citrate and microwave assisted polyol methods. These studies showed that the polyol method was the optimum method to produce the Pt-Cu alloy. The XRD analysis indicates that the heat treatment at 700 °C developed catalysts rich in the PtCu and PtCu3 ordered phases. The highest EOR activity was measured for the Pt-Cu/C-POL (sample made by the polyol method) and heat treated at 700°C for 1h. Comparing the EOR activity of the Pt-Cu and Pt-Mn samples also demonstrates that the heat treated Pt-Cu/C-POL sample showed higher EOR activity compared to the Pt-Mn samples. These results indicate that the benefits of thermally treating alloy nanoparticles could outweigh any activity losses that may occur due to the particle size growth and the ECSA loss. Besides, accelerated stress tests (ASTs) illustrate that the heat treatment improved the durability of the Pt-Mn and Pt-Cu samples. The durability and EOR activity of the heat treated Pt-Mn and Pt-Cu samples was similar or better than commercial samples. On the other hand, the ORR activity of Pt-Mn and Pt-Cu after the heat treatment was slightly lower than the commercial samples but the ORR activity loss can be compensated by the economic benefits from using the lower Pt loading. Finally, studying the alcohol sensing characteristic of different samples shows that the heat treated Pt-Mn and Pt-Cu catalysts could be used for the ethanol sensing. Additionally, among the different commercial samples tested for ethanol sensing, Pt-Sn/C showed the highest sensitivity but with slightly higher standard deviation. Further studies on the Pt- Cu/C and Pt-Mn/C samples indicate that the heat treatment improved the sensitivity of these samples and the highest normalized sensitivity among all the samples belonged to the Pt-Cu/C-POL (sample produced by polyol method) and heat treated at 700°C. It can be concluded that the heat treated Pt-Mn and Pt-Cu samples could be used as an alternative to replace Pt black in commercial sensors which would dramatically decrease the Pt loading. This could reduce the price and increase the sensitivity of commercial alcohol sensors.
An investigation of the environmental factors that affect water quality and the occurrence of harmful cyanobacteria in stormwater management ponds
(2024-04-01) Horton, Kaitlyn; Kirkwood, Andrea
Stormwater management ponds (SWMP) have an important role in flood mitigation and basic water quality treatment via sedimentation. As aquatic ecosystems, less is known about their role as habitats for aquatic organisms and their potential to transform pollutants. This study focused on twelve SWMP in Oshawa, Ontario, Canada to assess the impacts of flow conditions and pond characteristics on SWMP water quality treatment and algal growth, including toxic cyanobacteria. Net release of total phosphorus (TP) and net retention of total nitrogen (TN) by SWMP were observed. Flow conditions had little affect on the overall functioning of the study SWMP. Large pond designs and recent dredging were observed to positively influence the reduction of total suspended solids (TSS), TN, and TP net release from SWMP. Algae and cyanobacteria were observed to be generally N-limited. The presence of the cyanobacterial toxin gene mcyE was positively associated with chloride and heterocyst-forming cyanobacteria.
Analysing atomic structure in nano-scale imagery
(2017-01-01) Nemirovsky, David M.; Qureshi, Faisal Z.; Tamblyn, Isaac
This thesis presents methods for both detecting atoms and reconstructing single layer molecular geometry depicted within high resolution nanoscale imagery. Nanoscale imaging is a common method of analysing molecular structures produced through self-assembly. The second derivatives of the nanoscale images are then computed and used to aid in analysis of the depicted molecules. Peaks from the derivative images are used as the locations of the atoms and using those locations we derive the molecular geometry. In order to efficiently determine the performance of our proposed methods, a system to synthesize HRTEM imagery and ground truth data was developed. We demonstrate and compare the effectiveness of our system to other proposed systems using both experimentally produced nanoscale images and the synthetic data that has been produced.
Analysis of peptide production by Lactobacillus species and evaluation of their antihypertensive and immunomodulatory activities
(2015-08-01) Adams, Christina; Strap, Janice L.
Cardiovascular disease (CVD) is the leading cause of death among Canadian adults. Research has demonstrated an inverse relationship between the consumption of fermented dairy products and a decreased risk of CVD due to lactic acid bacteria used in the fermentation process which liberate small bioactive peptides from larger milk proteins (eg. casein). We observed that supplementation with 0.1% casein significantly increased the growth rate of L. helveticus R0389 and L. rhamnosus R0011 and increased the ACE-inhibitory activity of their secreted peptide fractions. Peptide-containing supernatants of L. rhamnosus R0011 show comparable ACE inhibition to known antihypertensive peptides, VPP and IPP. Supernatants of milk ferments induced the production of the regulatory cytokine, IL-10, by THP-1 monocytes. Novel antihypertensive and immunomodulatory activities of individually synthesized peptides were also reported. By investigating the relationship between these bioactive properties, we can improve upon the use of probiotic organisms to confer maximal health benefits to Canadians.
Analysis of resistance nodulation division efflux pumps in Acinetobacter baumannii
(2015-01-01) Fernando, Dinesh Malinda; Kumar, Ayush; Green-Johnson, Julia
Strains from Canadian hospitals were classified as A. baumannii, A. pitti, or A. osocomialis and the most commonly expressed resistance nodulation division (RND) efflux pump was adeFGH. A collection of A. baumannii isolates from the environment showed decreased susceptibility to at least three antibiotics and expression of three RND efflux pumps (adeFGH, adeABC, adeIJK). From the clinical collection two blood isolates, AB030 and AB031, were chosen to evaluate the outcomes of three virulence models. Using Caenorhabditis elegans and Galleria mellonella a statistically significant difference was shown in AB030 the extremely drug resistant strain. Investigation of the physiological role of adeFGH pump revealed its expression may be more important to cell metabolism and independent of factors controlling expression of the other pumps. This was further demonstrated through examination of local regulator knockout (adeL) in ATCC17978 showing expression levels of adeFGH pump increased only 2-fold. Expression in sub-lethal concentrations of chloramphenicol or florfenicol showed >5-fold induction of adeFGH expression as well as adeABC, independently of AdeL. These data show that the AdeFGH pump is likely regulated by AdeL, but more so by another unknown regulatory mechanism that responds to aberrant peptide formation and not DNA synthesis error or nitrosative stress. In addition strain specific differences likely also account for differences in phenotypic observations since nitrosative stress has improved tolerance and induced adeFGH expression in ATCC19606 and AB031. Finally analysis of efflux pumps in two triclosan resistant mutants, AB042 and AB043, revealed overexpression of AdeIJK and mutation in the adeIJK regulator, AdeN. Complementation repressed adeIJK expression levels and increased susceptibility to moxifloxacin and ciprofloxacin. The AB043 strain did not have any mutations in adeN, promoter region or RND operon. Osmotic stress tolerance revealed more C16 fatty acids and less C18 compared to the parent strain. The more triclosan resistant strain AB043, showed biofilm formation exclusively at 30°C. Twitching was observed and caused by mutation in the histone-like nucleoid structuring (HNS) protein but did not affect biofilm formation. Using RNA-seq and proteomic analysis putative targets of AdeIJK regulation were identified.
The analysis of the entomological and chemical decomposition of human remains to ultimately assess the viability of the domestic pig as a substitute in forensic applications
(2022-09-01) Skopyk, Angela D.; LeBlanc, Helene
Death investigations often rely on the minimum post mortem interval (minPMI) estimations provided by forensic entomologists. The models accepted by courts in Canada are not based on research involving humans but rather on a human substitute, the domestic pig. However, now that facilities for human decomposition research are opening, we are faced with the prospect that pigs may not be so similar to humans as originally thought. The purpose of this research is to analyze the entomological and chemical decomposition of human and pig remains to determine if the domestic pig is an appropriate substitute for humans in research applied to minPMI estimations. Two human (n=4, n=2) and one pig (n=2) study were performed in Sydney, Australia, while three pig (n=3, n=2, n=3) studies were performed in Oshawa, Ontario. The environmental conditions were monitored as well as the accumulated degree days (ADD), rates of decomposition, primary dipteran colonizers, and volatile organic compound (VOC) production. Domestic pigs in Oshawa, Ontario, had rates of decomposition that were highly alike. Rates of insect colonization were rapid, with little to no delay. The production of 5 known apneumones showed no significant difference (p < 0.05) between pigs. Human decomposition in Sydney yielded results with varied rates of decomposition and colonization – some with long pre-colonization intervals (Pre-CIs), which affected the rate of decomposition. It was noted that the donors with long Pre-CIs were likely to have been taking strong peri-mortem antibiotics due to their antemortem health conditions. These antibiotics could have affected the donor’s microbiome, killing the beneficial bacteria that produce apneumones. The domestic pigs observed in Sydney showed decompositions, colonizations and VOC productions more similar to the pigs in Ontario than to the humans in Sydney. Humans live differently than domestic pigs with varying diets, habits, body types, and medications that can influence their decomposition and colonization after death. Since this cannot be said for the domestic pig, it is recommended that the researching community aim to shift future research to human donors so that the data collected can be applied to human death investigations while considering comorbidities and how it affects insect colonization.
Analysis of the volatile organic compounds produced by the decomposition of pig carcasses and human remains
(2013-03-01) Stadler, Sonja; Forbes, Shari; Desaulniers, Jean-Paul
Complex processes of decomposition produce a variety of chemicals as soft tissues and their component parts are degraded. Among others, these decomposition by-products include volatile organic compounds (VOCs) responsible for the odour of decomposition. Human remains detection (HRD) canines utilize this odour signature to locate human remains during police investigations and recovery missions in the event of a mass disaster. Currently, it is unknown which compounds or combinations of compounds are recognized by the HRD canines. In this study decomposition VOCs were collected from the decomposition headspace of pig carcasses and were analyzed using thermal desorption gas chromatography mass spectrometry (TD-GC-MS). The difficulties associated with the non-target analysis of complex samples led to the further analysis of decomposition odour using a novel application of thermal desorption coupled to comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (TD-GCxGC-TOFMS). The additional peak capacity and spectral deconvolution of the GCxGC-TOFMS system generated a characteristic profile of decomposition VOCs across the various stages of soft tissue decomposition. The profile was comprised of numerous chemical families, particularly alcohols, carboxylic acids, aromatics and sulfides. Characteristic compounds identified in this study included 1-butanol, 1-octen-3-ol, 2-and 3-methyl butanoic acid, hexanoic acid, octanal, indole, phenol, benzaldehyde, dimethyl disulfide and trisulfide, which represent potential target compounds of decomposition odour. Currently there is a demand for improved canine training aids and pig carcasses have been proposed as an alternative due to their acceptance as human body analogues. This work investigated the similarities in the decomposition odour profile of pig carcasses and human remains through surface decomposition trials and comparisons to the published literature. It was determined that pig carcasses cannot be eliminated as potential human decomposition odour mimics. Additionally, following the examination of commercially available synthetic training aids, pig carcasses demonstrated a more suitable profile for the training of cadaver dogs. Further investigation into the chemical composition of decomposition odour utilizing TD-GCxGC-TOFMS will aid in determining the signature of human decomposition odour and facilitate the comparisons of these profiles between environments, individuals and species.

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