14,278 research outputs found

    Optimizations of Autoencoders for Analysis and Classification of Microscopic In Situ Hybridization Images

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    Currently, analysis of microscopic In Situ Hybridization images is done manually by experts. Precise evaluation and classification of such microscopic images can ease experts' work and reveal further insights about the data. In this work, we propose a deep-learning framework to detect and classify areas of microscopic images with similar levels of gene expression. The data we analyze requires an unsupervised learning model for which we employ a type of Artificial Neural Network - Deep Learning Autoencoders. The model's performance is optimized by balancing the latent layers' length and complexity and fine-tuning hyperparameters. The results are validated by adapting the mean-squared error (MSE) metric, and comparison to expert's evaluation.Comment: 9 pages; 9 figure

    The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

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    The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, and culture. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution

    Ausubel's meaningful learning re-visited

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    This review provides a critique of David Ausubelā€™s theory of meaningful learning and the use of advance organizers in teaching. It takes into account the developments in cognition and neuroscience which have taken place in the 50 or so years since he advanced his ideas, developments which challenge our understanding of cognitive structure and the recall of prior learning. These include (i) how effective questioning to ascertain previous knowledge necessitates in-depth Socratic dialogue; (ii) how many findings in cognition and neuroscience indicate that memory may be non-representational, thereby affecting our interpretation of student recollections; (iii) the now recognised dynamism of memory; (iv) usefully regarding concepts as abilities or simulators and skills; (v) acknowledging conscious and unconscious memory and imagery; (vi) how conceptual change involves conceptual coexistence and revision; (vii) noting linguistic and neural pathways as a result of experience and neural selection; and (viii) recommending that wider concepts of scaffolding should be adopted, particularly given the increasing focus on collaborative learning in a technological world

    Pretrained Embeddings for E-commerce Machine Learning: When it Fails and Why?

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    The use of pretrained embeddings has become widespread in modern e-commerce machine learning (ML) systems. In practice, however, we have encountered several key issues when using pretrained embedding in a real-world production system, many of which cannot be fully explained by current knowledge. Unfortunately, we find that there is a lack of a thorough understanding of how pre-trained embeddings work, especially their intrinsic properties and interactions with downstream tasks. Consequently, it becomes challenging to make interactive and scalable decisions regarding the use of pre-trained embeddings in practice. Our investigation leads to two significant discoveries about using pretrained embeddings in e-commerce applications. Firstly, we find that the design of the pretraining and downstream models, particularly how they encode and decode information via embedding vectors, can have a profound impact. Secondly, we establish a principled perspective of pre-trained embeddings via the lens of kernel analysis, which can be used to evaluate their predictability, interactively and scalably. These findings help to address the practical challenges we faced and offer valuable guidance for successful adoption of pretrained embeddings in real-world production. Our conclusions are backed by solid theoretical reasoning, benchmark experiments, as well as online testings

    Integrative multi-omics analysis for the effect of genetic alterations in cancer xenograft and organoid models

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    Department of Biomedical EngineeringDNA damage is a well-recognized factor in the development and progression of cancer. Numerous studies on genetic changes associated with cancer or the DNA repair pathway have been conducted, however, there is still a need for additional research on their function. The establishment of patient-derived xenografts or organoids for the purpose of testing functional genomic approaches is the subject of ongoing research. According to model-specific characteristics, it is not fully understood how these attempts to simulate patient cancer differ from original cancer. To comprehend the distinction between genuine patient cancer and these patient-derived disease models in more depth, multi-omics analysis is required to comprehend the overall genotypes, phenotypes, and environmental variables. Depending on the characteristics of each disease model, distinct omics analysis approaches and factors must be considered. In addition, care must be taken to avoid technical errors when integrating omics data generated by different sequencing equipment. There is currently no golden rule for data integration, but several approaches are being developed. It is crucial to determine the function of genes linked with the DNA repair pathway because these genes contribute to the induction or prevention of cancer. In chapter 1, I identified the interaction between MRE11 and TRIP13 through proximity labeling combined with the SILAC method which is quantitative proteomics using metabolic labeling. TRIP13 depletion doesn???t affect the nuclease activity and conformation of the MRN complex but directly inhibits the interaction of MDC1 with MRN complex and MDC1 recruitment on the DNA damage site. TRIP13 degradation with mirin treatment shows additive effects on ATM signaling activation. In conclusion, TRIP13 regulates immediate-early DNA damage sensing through MRE11 and ATM signaling independently of mirin. When assessing the functional genomic approach using patient-derived disease models, it is essential to determine which aspects of the models' correlation to actual cancer should be properly considered. In chapter 2, I found there are a few overlapped deleterious somatic mutations of the PDX model and their original tumor. I suspected novel mutagen exposure during PDX establishment or sample contamination. However, germline mutations of PDX models are well conserved from original tumors, and their mutational signatures of PDX also mimic that of their tumor. Though the number of overlapped mutations between the PDX model and their tumor was few, brain tumor-specific mutations are found in PDX samples. Especially, histone methylation- and cilia-related gene mutations are enriched in PDX samples. While it suggested these mutated genes are needed for maintaining the stemness of brain tumor PDX model or PDX model would be more appropriate for the samples with high heterogeneity, I have presented precautions and considerations in PDX model genome analysis. Multi-omics analysis that takes into consideration genetic, expressive, and clinical aspects can provide important information for the study of diseases with complicated etiologies, such as cancer, and can contribute to the development of diagnosis and treatment. To utilize colorectal cancer organoids for Companion Diagnostics (CDx), in chapter 3, I characterized patient-derived colorectal cancer (CRC) organoids through well-known genomic markers such as Tumor mutation burden (TMB), Microsatellite instability (MSI) and propose a novel grouping method using sharing same mutation site. The classification of CRC patients was more detailed combined with consensus molecular subtype (CMS) classifications. Additionally, I extract the expression features of the patients who experience recurrence or metastasis after first-line chemotherapy treatment with reference to clinical data. Drug response of CRC organoids by patient group and knockdown of the extracted features in the selected organoids would be validated in further study. In summary, with this dissertation, I conducted functional research on the DNA repair pathway of cancer-related genes, as well as the genetic analysis between patient-derived xenograft and original tumors, and introduced a novel perspective on the diagnosis and treatment of colorectal cancer patients using patient-derived organoids through multi-omics analysis.ope

    Platform workers and digital agency: Making out on three types of labor platforms

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    Much of the research on platform workers has focused on individuals involved in low-skilled and highly standardized tasks. However, platform workers are not a homogeneous group. Utilizing a classification system that makes a distinction between different layers of platform control and grouping platforms according to how they divide decision rights between platforms and workers, we examine how and for what purposes platform workers operating in three types of control contexts have practiced and developed their digital agency for making out. The study, based on an analysis of platform webpages and 32 semi-structured interviews of food couriers, freelancers, and interim managers, shows that workers can exercise their digital agency on all three types of platforms, but different platforms create different conditions for this depending on their special forms of control. In addition, the forms of control also affect to what extent workers are motivated to direct their agency for making out. Instead of regarding platform work as just another layer of a periphery segment in the labor market, our analysis suggests that platforms exercising algorithmic control are new types of arenas for work, which seem to reproduce, or even amplify, the inequalities found in the offline world of work in the digital world

    Model Diagnostics meets Forecast Evaluation: Goodness-of-Fit, Calibration, and Related Topics

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    Principled forecast evaluation and model diagnostics are vital in fitting probabilistic models and forecasting outcomes of interest. A common principle is that fitted or predicted distributions ought to be calibrated, ideally in the sense that the outcome is indistinguishable from a random draw from the posited distribution. Much of this thesis is centered on calibration properties of various types of forecasts. In the first part of the thesis, a simple algorithm for exact multinomial goodness-of-fit tests is proposed. The algorithm computes exact pp-values based on various test statistics, such as the log-likelihood ratio and Pearson\u27s chi-square. A thorough analysis shows improvement on extant methods. However, the runtime of the algorithm grows exponentially in the number of categories and hence its use is limited. In the second part, a framework rooted in probability theory is developed, which gives rise to hierarchies of calibration, and applies to both predictive distributions and stand-alone point forecasts. Based on a general notion of conditional T-calibration, the thesis introduces population versions of T-reliability diagrams and revisits a score decomposition into measures of miscalibration, discrimination, and uncertainty. Stable and efficient estimators of T-reliability diagrams and score components arise via nonparametric isotonic regression and the pool-adjacent-violators algorithm. For in-sample model diagnostics, a universal coefficient of determination is introduced that nests and reinterprets the classical R2R^2 in least squares regression. In the third part, probabilistic top lists are proposed as a novel type of prediction in classification, which bridges the gap between single-class predictions and predictive distributions. The probabilistic top list functional is elicited by strictly consistent evaluation metrics, based on symmetric proper scoring rules, which admit comparison of various types of predictions

    Consent and the Construction of the Volunteer: Institutional Settings of Experimental Research on Human Beings in Britain during the Cold War

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    This study challenges the primacy of consent in the history of human experimentation and argues that privileging the cultural frameworks adds nuance to our understanding of the construction of the volunteer in the period 1945 to 1970. Historians and bio-ethicists have argued that medical ethics codes have marked out the parameters of using people as subjects in medical scientific research and that the consent of the subjects was fundamental to their status as volunteers. However, the temporality of the creation of medical ethics codes means that they need to be understood within their historical context. That medical ethics codes arose from a specific historical context rather than a concerted and conscious determination to safeguard the well-being of subjects needs to be acknowledged. The British context of human experimentation is under-researched and there has been even less focus on the cultural frameworks within which experiments took place. This study demonstrates, through a close analysis of the Medical Research Council's Common Cold Research Unit (CCRU) and the government's military research facility, the Chemical Defence Experimental Establishment, Porton Down (Porton), that the `volunteer' in human experiments was a subjective entity whose identity was specific to the institution which recruited and made use of the subject. By examining representations of volunteers in the British press, the rhetoric of the government's collectivist agenda becomes evident and this fed into the institutional construction of the volunteer at the CCRU. In contrast, discussions between Porton scientists, staff members, and government officials demonstrate that the use of military personnel in secret chemical warfare experiments was far more complex. Conflicting interests of the military, the government and the scientific imperative affected how the military volunteer was perceived

    On the Mechanism of Building Core Competencies: a Study of Chinese Multinational Port Enterprises

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    This study aims to explore how Chinese multinational port enterprises (MNPEs) build their core competencies. Core competencies are firmsā€™special capabilities and sources to gain sustainable competitive advantage (SCA) in marketplace, and the concept led to extensive research and debates. However, few studies include inquiries about the mechanisms of building core competencies in the context of Chinese MNPEs. Accordingly, answers were sought to three research questions: 1. What are the core competencies of the Chinese MNPEs? 2. What are the mechanisms that the Chinese MNPEs use to build their core competencies? 3. What are the paths that the Chinese MNPEs pursue to build their resources bases? The study adopted a multiple-case study design, focusing on building mechanism of core competencies with RBV. It selected purposively five Chinese leading MNPEs and three industry associations as Case Companies. The study revealed three main findings. First, it identified three generic core competencies possessed by Case Companies, i.e., innovation in business models and operations, utilisation of technologies, and acquisition of strategic resources. Second, it developed the conceptual framework of the Mechanism of Building Core Competencies (MBCC), which is a process of change of collective learning in effective and efficient utilization of resources of a firm in response to critical events. Third, it proposed three paths to build core competencies, i.e., enhancing collective learning, selecting sustainable processes, and building resource base. The study contributes to the knowledge of core competencies and RBV in three ways: (1) presenting three generic core competencies of the Chinese MNPEs, (2) proposing a new conceptual framework to explain how Chinese MNPEs build their core competencies, (3) suggesting a solid anchor point (MBCC) to explain the links among resources, core competencies, and SCA. The findings set benchmarks for Chinese logistics industry and provide guidelines to build core competencies

    Building body identities - exploring the world of female bodybuilders

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    This thesis explores how female bodybuilders seek to develop and maintain a viable sense of self despite being stigmatized by the gendered foundations of what Erving Goffman (1983) refers to as the 'interaction order'; the unavoidable presentational context in which identities are forged during the course of social life. Placed in the context of an overview of the historical treatment of women's bodies, and a concern with the development of bodybuilding as a specific form of body modification, the research draws upon a unique two year ethnographic study based in the South of England, complemented by interviews with twenty-six female bodybuilders, all of whom live in the U.K. By mapping these extraordinary women's lives, the research illuminates the pivotal spaces and essential lived experiences that make up the female bodybuilder. Whilst the women appear to be embarking on an 'empowering' radical body project for themselves, the consequences of their activity remains culturally ambivalent. This research exposes the 'Janus-faced' nature of female bodybuilding, exploring the ways in which the women negotiate, accommodate and resist pressures to engage in more orthodox and feminine activities and appearances
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