University of Nottingham

About: University of Nottingham is a education organization based out in Nottingham, Nottingham, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 54772 authors who have published 119600 publications receiving 4227408 citations. The organization is also known as: The University of Nottingham & University College, Nottingham.

Ambiguity as a resource for design

Abstract: Ambiguity is usually considered anathema in Human Computer Interaction. We argue, in contrast, that it is a resource for design that can be used to encourage close personal engagement with systems. We illustrate this with examples from contemporary arts and design practice, and distinguish three broad classes of ambiguity according to where uncertainty is located in the interpretative relationship linking person and artefact. Ambiguity of information finds its source in the artefact itself, ambiguity of context in the sociocultural discourses that are used to interpret it, and ambiguity of relationship in the interpretative and evaluative stance of the individual. For each of these categories, we describe tactics for emphasising ambiguity that may help designers and other practitioners understand and craft its use.

Tumor-Infiltrating CD8+ Lymphocytes Predict Clinical Outcome in Breast Cancer

Abstract: Breast carcinomas are often infiltrated by inflammatory cells, particularly macrophages and T lymphocytes, but the significance of these cells remains unclear. One possible role of these inflammatory cells is that they represent a cell-mediated immune response against the carcinoma. CD8+ lymphocytes are a known crucial component of cell-mediated immunity. The purpose of this study was to explore the prognostic value of tumor-infiltrating CD8+ cytotoxic lymphocytes in breast cancer. Tumor-infiltrating CD8+ lymphocytes were assessed by immunohistochemical staining of tissue microarray cores from 1,334 unselected breast tumors from patients with long-term follow-up. The number of CD8+ T cells was counted in tumor nests (intratumoral), in stroma adjacent to tumor cells, and in stroma distant to tumor cells, and their relationship with clinical outcome was determined. The total number of CD8+ cells was positively correlated with tumor grade (rs = 0.20; P < .001) and inversely correlated with patient's age at d...

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Abstract: Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumoris a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses thestate-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross tota lresection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset.

Molecular imprinting science and technology: a survey of the literature for the years up to and including 2003

Abstract: Molecular imprinting science and technology: a survey of the literature for the years up to and including 2003

Energy storage applications of activated carbons: supercapacitors and hydrogen storage

Abstract: Porous carbons have several advantageous properties with respect to their use in energy applications that require constrained space such as in electrode materials for supercapacitors and as solid state hydrogen stores. The attractive properties of porous carbons include, ready abundance, chemical and thermal stability, ease of processability and low framework density. Activated carbons, which are perhaps the most explored class of porous carbons, have been traditionally employed as catalyst supports or adsorbents, but lately they are increasingly being used or find potential applications in the fabrication of supercapacitors and as hydrogen storage materials. This manuscript presents the state-of-the-art with respect to the preparation of activated carbons, with emphasis on the more interesting recent developments that allow better control or maximization of porosity, the use of cheap and readily available precursors and tailoring of morphology. This review will show that the renewed interest in the synthesis of activated carbons is matched by intensive investigations into their use in supercapacitors, where they remain the electrode materials of choice. We will also show that activated carbons have been extensively studied as hydrogen storage materials and remain a strong candidate in the search for porous materials that may enable the so-called Hydrogen Economy, wherein hydrogen is used as an energy carrier. The use of activated carbons as energy materials has in the recent past and is currently experiencing rapid growth, and this review aims to present the more significant advances.