6,597 research outputs found
A Pairwise Dataset for GUI Conversion and Retrieval between Android Phones and Tablets
With the popularity of smartphones and tablets, users have become accustomed
to using different devices for different tasks, such as using their phones to
play games and tablets to watch movies. To conquer the market, one app is often
available on both smartphones and tablets. However, although one app has
similar graphic user interfaces (GUIs) and functionalities on phone and tablet,
current app developers typically start from scratch when developing a
tablet-compatible version of their app, which drives up development costs and
wastes existing design resources. Researchers are attempting to employ deep
learning in automated GUIs development to enhance developers' productivity.
Deep learning models rely heavily on high-quality datasets. There are currently
several publicly accessible GUI page datasets for phones, but none for pairwise
GUIs between phones and tablets. This poses a significant barrier to the
employment of deep learning in automated GUI development. In this paper, we
collect and make public the Papt dataset, which is a pairwise dataset for GUI
conversion and retrieval between Android phones and tablets. The dataset
contains 10,035 phone-tablet GUI page pairs from 5,593 phone-tablet app pairs.
We illustrate the approaches of collecting pairwise data and statistical
analysis of this dataset. We also illustrate the advantages of our dataset
compared to other current datasets. Through preliminary experiments on this
dataset, we analyse the present challenges of utilising deep learning in
automated GUI development and find that our dataset can assist the application
of some deep learning models to tasks involving automatic GUI development.Comment: 10 pages, 9 figure
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Studies on genetic and epigenetic regulation of gene expression dynamics
The information required to build an organism is contained in its genome and the first
biochemical process that activates the genetic information stored in DNA is transcription.
Cell type specific gene expression shapes cellular functional diversity and dysregulation
of transcription is a central tenet of human disease. Therefore, understanding
transcriptional regulation is central to understanding biology in health and disease.
Transcription is a dynamic process, occurring in discrete bursts of activity that can be
characterized by two kinetic parameters; burst frequency describing how often genes
burst and burst size describing how many transcripts are generated in each burst. Genes
are under strict regulatory control by distinct sequences in the genome as well as
epigenetic modifications. To properly study how genetic and epigenetic factors affect
transcription, it needs to be treated as the dynamic cellular process it is. In this thesis, I
present the development of methods that allow identification of newly induced gene
expression over short timescales, as well as inference of kinetic parameters describing
how frequently genes burst and how many transcripts each burst give rise to. The work is
presented through four papers:
In paper I, I describe the development of a novel method for profiling newly transcribed
RNA molecules. We use this method to show that therapeutic compounds affecting
different epigenetic enzymes elicit distinct, compound specific responses mediated by
different sets of transcription factors already after one hour of treatment that can only
be detected when measuring newly transcribed RNA.
The goal of paper II is to determine how genetic variation shapes transcriptional bursting.
To this end, we infer transcriptome-wide burst kinetics parameters from genetically
distinct donors and find variation that selectively affects burst sizes and frequencies.
Paper III describes a method for inferring transcriptional kinetics transcriptome-wide
using single-cell RNA-sequencing. We use this method to describe how the regulation of
transcriptional bursting is encoded in the genome. Our findings show that gene specific
burst sizes are dependent on core promoter architecture and that enhancers affect burst
frequencies. Furthermore, cell type specific differential gene expression is regulated by
cell type specific burst frequencies.
Lastly, Paper IV shows how transcription shapes cell types. We collect data on cellular
morphologies, electrophysiological characteristics, and measure gene expression in the
same neurons collected from the mouse motor cortex. Our findings show that cells
belonging to the same, distinct transcriptomic families have distinct and non-overlapping
morpho-electric characteristics. Within families, there is continuous and correlated
variation in all modalities, challenging the notion of cell types as discrete entities
Fairness Testing: A Comprehensive Survey and Analysis of Trends
Unfair behaviors of Machine Learning (ML) software have garnered increasing
attention and concern among software engineers. To tackle this issue, extensive
research has been dedicated to conducting fairness testing of ML software, and
this paper offers a comprehensive survey of existing studies in this field. We
collect 100 papers and organize them based on the testing workflow (i.e., how
to test) and testing components (i.e., what to test). Furthermore, we analyze
the research focus, trends, and promising directions in the realm of fairness
testing. We also identify widely-adopted datasets and open-source tools for
fairness testing
Endogenous measures for contextualising large-scale social phenomena: a corpus-based method for mediated public discourse
This work presents an interdisciplinary methodology for developing endogenous measures of group membership through analysis of pervasive linguistic patterns in public discourse. Focusing on political discourse, this work critiques the conventional approach to the study of political participation, which is premised on decontextualised, exogenous measures to characterise groups. Considering the theoretical and empirical weaknesses of decontextualised approaches to large-scale social phenomena, this work suggests that contextualisation using endogenous measures might provide a complementary perspective to mitigate such weaknesses.
This work develops a sociomaterial perspective on political participation in mediated discourse as affiliatory action performed through language. While the affiliatory function of language is often performed consciously (such as statements of identity), this work is concerned with unconscious features (such as patterns in lexis and grammar). This work argues that pervasive patterns in such features that emerge through socialisation are resistant to change and manipulation, and thus might serve as endogenous measures of sociopolitical contexts, and thus of groups.
In terms of method, the work takes a corpus-based approach to the analysis of data from the Twitter messaging service whereby patterns in usersā speech are examined statistically in order to trace potential community membership. The method is applied in the US state of Michigan during the second half of 2018ā6 November having been the date of midterm (i.e. non-Presidential) elections in the United States. The corpus is assembled from the original posts of 5,889 users, who are nominally geolocalised to 417 municipalities. These users are clustered according to pervasive language features. Comparing the linguistic clusters according to the municipalities they represent finds that there are regular sociodemographic differentials across clusters. This is understood as an indication of social structure, suggesting that endogenous measures derived from pervasive patterns in language may indeed offer a complementary, contextualised perspective on large-scale social phenomena
OxPhos Defects Cause Hypermetabolism and Reduce Lifespan in Cells and in Patients With Mitochondrial Diseases
Patients with primary mitochondrial oxidative phosphorylation (OxPhos) defects present with fatigue and multi-system disorders, are often lean, and die prematurely, but the mechanistic basis for this clinical picture remains unclear. By integrating data from 17 cohorts of patients with mitochondrial diseases (n = 690) we find evidence that these disorders increase resting energy expenditure, a state termed hypermetabolism. We examine this phenomenon longitudinally in patient-derived fibroblasts from multiple donors. Genetically or pharmacologically disrupting OxPhos approximately doubles cellular energy expenditure. This cell-autonomous state of hypermetabolism occurs despite near-normal OxPhos coupling efficiency, excluding uncoupling as a general mechanism. Instead, hypermetabolism is associated with mitochondrial DNA instability, activation of the integrated stress response (ISR), and increased extracellular secretion of age-related cytokines and metabokines including GDF15. In parallel, OxPhos defects accelerate telomere erosion and epigenetic aging per cell division, consistent with evidence that excess energy expenditure accelerates biological aging. To explore potential mechanisms for these effects, we generate a longitudinal RNASeq and DNA methylation resource dataset, which reveals conserved, energetically demanding, genome-wide recalibrations. Taken together, these findings highlight the need to understand how OxPhos defects influence the energetic cost of living, and the link between hypermetabolism and aging in cells and patients with mitochondrial diseases
Molecular Mechanisms and Therapies of Colorectal Cancer
Colorectal cancer (CRC) is currently the third leading cause of cancer-related mortality, with 1.9 million incidence cases and 0.9 million deaths worldwide. The global number of new CRC cases is predicted to reach 3.2 million in 2040, based on the projection of aging, population growth, and human development.In clinics, despite advances of diagnosis and surgical procedures, 20% of the patients with CRC present with metastasis at the time of diagnosis, caused by residual tumor cells that have spread to distant organs prior to surgery, affecting the patient survival rate. Standard systemic chemotherapy, alternative therapies that target mechanisms involved in cancer progression and metastasis, immunotherapy, and combination therapies are the major CRC-treatment strategies. In the advanced stage of CRC the transforming growth factor-beta (TGF-Ī²) plays an oncogenic role by promoting cancer cell proliferation, cancer cell self-renewal, epithelial-to-mesenchymal transition, invasion, tumor progression, metastatic spread, and immune escape. Furthermore, high levels of TGF-Ī²1 confers poor prognosis and is associated with early recurrence after surgery, resistance to chemo- or immunotherapy, and shorter survival. Based on the body of experimental evidence indicating that TGF-Ī² signaling has the potential to be a good therapeutic target in CRC, several anti-TGF-Ī² drugs have been investigated in cancer clinical trials. Here, we presented a comprehensive collection of manuscripts regarding studies on targeting the TGF-Ī² signaling in CRC to improve patientās prognosis and personalized treatments
Pathophysiology of Spinal Cord Injury (SCI)
Spinal cord injury (SCI) leads to paralysis, sensory, and autonomic nervous system dysfunctions. However, the pathophysiology of SCI is complex, and not limited to the nervous system. Indeed, several other organs and tissue are also affected by the injury, directly or not, acutely or chronically, which induces numerous health complications. Although a lot of research has been performed to repair motor and sensory functions, SCI-induced health issues are less studied, although they represent a major concern among patients. There is a gap of knowledge in pre-clinical models studying these SCI-induced health complications that limits translational applications in humans. This reprint describes several aspects of the pathophysiology of spinal cord injuries. This includes, but is not limited to, the impact of SCI on cardiovascular and respiratory functions, bladder and bowel function, autonomic dysreflexia, liver pathology, metabolic syndrome, bones and muscles loss, and cognitive functions
Glioblastoma and the search for non-hypothesis driven combination therapeutics in academia
Glioblastoma (GBM) remains a cancer of high unmet clinical need. Current standard of care for GBM, consisting of maximal surgical resection, followed by ionisation radiation (IR) plus concomitant and adjuvant temozolomide (TMZ), provides less than 15-month survival benefit. Efforts by conventional drug discovery to improve overall survival have failed to overcome challenges presented by inherent tumor heterogeneity, therapeutic resistance attributed to GBM stem cells, and tumor niches supporting self-renewal. In this review we describe the steps academic researchers are taking to address these limitations in high throughput screening programs to identify novel GBM combinatorial targets. We detail how they are implementing more physiologically relevant phenotypic assays which better recapitulate key areas of disease biology coupled with more focussed libraries of small compounds, such as drug repurposing, target discovery, pharmacologically active and novel, more comprehensive anti-cancer target-annotated compound libraries. Herein, we discuss the rationale for current GBM combination trials and the need for more systematic and transparent strategies for identification, validation and prioritisation of combinations that lead to clinical trials. Finally, we make specific recommendations to the preclinical, small compound screening paradigm that could increase the likelihood of identifying tractable, combinatorial, small molecule inhibitors and better drug targets specific to GBM
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