Deep Learning Methods for Automated Classification of Fish Behavior

Masteroppgåve i informatikkINF399MAMN-INFMAMN-PRO

Advanced methods in reproductive medicine: Application of optical nanoscopy, artificial intelligence-assisted quantitative phase microscopy and mitochondrial DNA copy numbers to assess human sperm cells

Declined fertility rate and population is a matter of serious concern, especially in the developed nations. Assisted Reproductive Technologies (ART), including in vitro fertilization (IVF), have provided great hope for infertility treatment and maintaining population growth and social structure. With the help of ART, more than 8 million babies have already been born so far. Despite the worldwide expansion of ART, there is a number of open questions on the IVF success rates. Male factors for infertility contribute equally as female factors, however, male infertility is primarily focused on the “semen quality”. Therefore, the search of new semen parameters for male fertility evaluation and the exploration of the optimal method of sperm selection in IVF have been included among the top 10 research priorities for male infertility and medically assisted reproduction. The development of imaging systems coupled with image processing by Artificial Intelligence (AI) could be the revolutionary step for semen quality analysis and sperm cell selection in IVF procedures. For this work, we applied optical nanoscopy technology for the analysis of human spermatozoa, i.e., label-based Structured Illumination Microscopy (SIM) and non-invasive Quantitative Phase Microscopy (QPM). The SIM results demonstrated a prominent contrast and resolution enhancement for subcellular structures of living sperm cells, especially for mitochondria-containing midpiece, where features around 100 nm length-scale were resolved. Further, non-labeled QPM combined with machine learning technique revealed the association between gradual progressive motility loss and the morphology changes of the sperm head after external exposure to various concentrations of hydrogen peroxide. Moreover, to recognize healthy and stress-affected sperm cells, we applied Deep Neural Networks (DNNs) to QPM images achieving an accuracy of 85.6% on a dataset of 10,163 interferometric images of sperm cells. Additionally, we summarized the evidence from published literature regarding the association between mitochondrial DNA copy numbers (mtDNAcn) and semen quality. To conclude, we set up the high-resolution imaging of living human sperm cells with a remarkable level of subcellular structural details provided by SIM. Next, the morphological changes of sperm heads resulting from peroxidation have been revealed by QPM, which may not be explored by microscopy currently used in IVF settings. Besides, the implementation of DNNs for QPM image processing appears to be a promising tool in the automated classification and selection of sperm cells during IVF procedures. Moreover, the results of our meta-analysis showed an association of mtDNAcn in human sperm cells and semen quality, which seems to be a relevant sperm parameter for routine clinical practice in male fertility assessment

Understanding Nanoparticle Toxicity to Direct a Safe-by-Design Approach in Cancer Nanomedicine

Nanomedicine is a rapidly growing field that uses nanomaterials for the diagnosis, treatment and prevention of various diseases, including cancer. Various biocompatible nanoplatforms with diversified capabilities for tumor targeting, imaging, and therapy have materialized to yield individualized therapy. However, due to their unique properties brought about by their small size, safety concerns have emerged as their physicochemical properties can lead to altered pharmacokinetics, with the potential to cross biological barriers. In addition, the intrinsic toxicity of some of the inorganic materials (i.e., heavy metals) and their ability to accumulate and persist in the human body has been a challenge to their translation. Successful clinical translation of these nanoparticles is heavily dependent on their stability, circulation time, access and bioavailability to disease sites, and their safety profile. This review covers preclinical and clinical inorganic-nanoparticle based nanomaterial utilized for cancer imaging and therapeutics. A special emphasis is put on the rational design to develop non-toxic/safe inorganic nanoparticle constructs to increase their viability as translatable nanomedicine for cancer therapies

The doctoral research abstracts. Vol:10 2016 / Institute of Graduate Studies, UiTM

Foreword: Congratulations to Institute of Graduate Studies on the continuous efforts to publish the 10th issue of the Doctoral Research Abstracts which showcases the research carried out in the various disciplines range from science and technology, business and administration to social science and humanities. This issue captures the novelty of research contributed by seventy (70) PhD graduands receiving their scrolls in the UiTM’s 85th Convocation. As of October 2016, this year UiTM has produced 138 PhD graduates soaring from125 in the previous year (2015). It shows that UiTM is in the positive direction to achive the total of 1200 PhD graduates in 2020. To the 70 doctorates, I would like it to be known that you have most certainly done UiTM proud by journeying through the scholarly world with its endless challenges and obstacles, and by persevering right till the very end. This convocation should not be regarded as the end of your highest scholarly achievement and contribution to the body of knowledge but rather as the beginning of embarking into more innovative research from knowledge gained during this academic journey, for the community and country. This year marks UiTM’s 60th Anniversary and we have been producing many good quality graduates that have a major impact on the socio-economic development of the country and the bumiputeras. As alumni of UiTM, we hold you dear to our hearts. We sincerely wish you all the best and may the Almighty guide you to a path of excellence and success. As you leave the university as alumni we hope a new relationship will be fostered between you and the faculty in soaring UiTM to greater heights. “UiTM Sentiasa di Hati Ku” / Prof Emeritus Dato’ Dr Hassan Said Vice Chancellor Universiti Teknologi MAR

2023 IMSAloquium

Welcome to IMSAloquium 2023. This is IMSA’s 36 th year of leading in educationalinnovation, and the 35th year of the IMSA Student Inquiry and Research (SIR) Program.https://digitalcommons.imsa.edu/archives_sir/1033/thumbnail.jp

Applied Deep Learning: Case Studies in Computer Vision and Natural Language Processing

Deep learning has proved to be successful for many computer vision and natural language processing applications. In this dissertation, three studies have been conducted to show the efficacy of deep learning models for computer vision and natural language processing. In the first study, an efficient deep learning model was proposed for seagrass scar detection in multispectral images which produced robust, accurate scars mappings. In the second study, an arithmetic deep learning model was developed to fuse multi-spectral images collected at different times with different resolutions to generate high-resolution images for downstream tasks including change detection, object detection, and land cover classification. In addition, a super-resolution deep model was implemented to further enhance remote sensing images. In the third study, a deep learning-based framework was proposed for fact-checking on social media to spot fake scientific news. The framework leveraged deep learning, information retrieval, and natural language processing techniques to retrieve pertinent scholarly papers for given scientific news and evaluate the credibility of the news

Orchestration : the movement and vocal behavior of free-ranging Norwegian killer whales (Orcinus orca)

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2008Studying the social and cultural transmission of behavior among animals helps to identify patterns of interaction and information content flowing between individuals. Killer whales are likely to acquire traits culturally based on their population-specific feeding behaviors and group-distinctive vocal repertoires. I used digital tags to explore the contributions of individual Norwegian killer whales to group carousel feeding and the relationships between vocal and non-vocal activity. Periods of tail slapping to incapacitate herring during feeding were characterized by elevated movement variability, heightened vocal activity and call types containing additional orientation cues. Tail slaps produced by tagged animals were identified using a rapid pitch change and occurred primarily within 20m of the surface. Two simultaneously tagged animals maneuvered similarly when tail slapping within 60s of one another, indicating that the position and composition of the herring ball influenced their behavior. Two types of behavioral sequence preceding the tight circling of carousel feeding were apparent. First, the animals engaged in periods of directional swimming. They were silent in 2 of 3 instances, suggesting they may have located other foraging groups by eavesdropping. Second, tagged animals made broad horizontal loops as they dove in a manner consistent with corralling. All 4 of these occasions were accompanied by vocal activity, indicating that this and tail slapping may benefit from social communication. No significant relationship between the call types and the actual movement measurements was found. Killer whale vocalizations traditionally have been classified into discrete call types. Using human speech processing techniques, I considered that calls are alternatively comprised of shared segments that can be recombined to form the stereotyped and variable repertoire. In a classification experiment, the characterization of calls using the whole call, a set of unshared segments, or a set of shared segments yielded equivalent performance. The shared segments required less information to parse the same vocalizations, suggesting a more parsimonious system of representation. This closer examination of the movements and vocalizations of Norwegian killer whales, combined with future work on ontogeny and transmission, will inform our understanding of whether and how culture plays a role in achieving population-specific behaviors in this species.Funding sources: The Ocean Life Institute at WHOI and the National Geographic Society, the National Defense Science and Engineering Graduate Fellowship, a National Science Foundation Graduate Fellowship, the Academic Programs Office at WHOI and Dennis McLaughlin at MIT