926 research outputs found
Evaluating probability forecasts
Probability forecasts of events are routinely used in climate predictions, in
forecasting default probabilities on bank loans or in estimating the
probability of a patient's positive response to treatment. Scoring rules have
long been used to assess the efficacy of the forecast probabilities after
observing the occurrence, or nonoccurrence, of the predicted events. We develop
herein a statistical theory for scoring rules and propose an alternative
approach to the evaluation of probability forecasts. This approach uses loss
functions relating the predicted to the actual probabilities of the events and
applies martingale theory to exploit the temporal structure between the
forecast and the subsequent occurrence or nonoccurrence of the event.Comment: Published in at http://dx.doi.org/10.1214/11-AOS902 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Learning Fine-grained Image Similarity with Deep Ranking
Learning fine-grained image similarity is a challenging task. It needs to
capture between-class and within-class image differences. This paper proposes a
deep ranking model that employs deep learning techniques to learn similarity
metric directly from images.It has higher learning capability than models based
on hand-crafted features. A novel multiscale network structure has been
developed to describe the images effectively. An efficient triplet sampling
algorithm is proposed to learn the model with distributed asynchronized
stochastic gradient. Extensive experiments show that the proposed algorithm
outperforms models based on hand-crafted visual features and deep
classification models.Comment: CVPR 201
Health literacy issues in the care of Chinese American immigrants with diabetes: a qualitative study
Objectives. To investigate why first-generation Chinese immigrants with diabetes have difficulty obtaining, processing and understanding diabetes related information despite the existence of translated materials and translators. Design This qualitative study employed purposive sampling. Six focus groups and two individual interviews were conducted. Each group discussion lasted approximately 90 min and was guided by semistructured and open-ended questions. Setting. Data were collected in two community health centres and one elderly retirement village in Los Angeles, California. Participants 29 Chinese immigrants aged ≥45 years and diagnosed with type 2 diabetes for at least 1 year. Results. Eight key themes were found to potentially affect Chinese immigrants' capacity to obtain, communicate, process and understand diabetes related health information and consequently alter their decision making in self-care. Among the themes, three major categories emerged: cultural factors, structural barriers, and personal barriers. Conclusions. Findings highlight the importance of cultural sensitivity when working with first-generation Chinese immigrants with diabetes. Implications for health professionals, local community centres and other potential service providers are discussed.published_or_final_versio
Advanced microscopic characterisation of multi-scale high-resolution mechanical behaviour of a nacre-inspired composite
Fabrication and characterisation of alumina/aluminium composite materials with a nacre-like micro-layered architecture
Cost-effective fabrication of bio-inspired nacre-like composite materials with high strength and toughness
A cost-effective one-step densification process based on bi-directional freeze casting was investigated to produce nacre-like alumina/poly (methyl methacrylate) (PMMA) composites with a unique micro-layered (μL) architecture. This method has the advantage of shorter processing time, as it requires only sintering once instead of twice as in the fabrication of conventional brick-and-mortar (BM) composites via freeze casting. By tuning the processing parameters, composites with different ceramic content and layer thickness were obtained. The resultant mechanical properties of μL composites showed that ceramic content and wall thickness affected mechanical properties significantly. The μL composite with fine ceramic walls (8 μm) and relatively high ceramic fraction (72 vol%) exhibited an exceptional combination of high flexural strength (178 MPa) and fracture toughness (12.5 MPa m1/2). The μL composites were also compared with the conventional BM composites. Although the fracture behaviour of both composites exhibited similar extrinsic toughening mechanisms, the μL composites with longer ceramic walls displayed superior mechanical properties in terms of strength and fracture toughness in comparison with the BM composites comprising short ceramic walls (i.e. bricks), due to the effectiveness of stress transfer of load-bearing ceramic phase within the composites
On correspondences between toric singularities and (p,q) webs
We study four-dimensional N=1 gauge theories which arise from D3-brane probes of toric Calabi-Yau threefolds. There are some standing paradoxes in the literature regarding relations among (p,q)-webs, toric diagrams and various phases of the gauge theories, we resolve them by proposing and carefully distinguishing between two kinds of (p,q)-webs: toric and quiver (p,q)-webs. The former has a one to one correspondence with the toric diagram while the latter can correspond to multiple gauge theories. The key reason for this ambiguity is that a given quiver (p,q)-web can not capture non-chiral matter fields in the gauge theory. To support our claim we analyse families of theories emerging from partial resolution of Abelian orbifolds using the Inverse Algorithm of hep-th/0003085 as well as (p,q)-web techniques. We present complex inter-relations among these theories by Higgsing, blowups and brane splittings. We also point out subtleties involved in the ordering of legs in the (p,q) diagram
Introductory Notes to Algebraic Statistics
These are the notes of a short course on algebraic
statistics, a new discipline across the fields of statistical modeling
and computational commutativa algebra. The basics of the
theory are provided together with brief reference to applications to
design of experiments, to exponential and graphical models, and
to computational biology
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Differential requirements of androgen receptor in luminal progenitors during prostate regeneration and tumor initiation
Master regulatory genes of tissue specification play key roles in stem/progenitor cells and are often important in cancer. In the prostate, androgen receptor (AR) is a master regulator essential for development and tumorigenesis, but its specific functions in prostate stem/progenitor cells have not been elucidated. We have investigated AR function in CARNs (CAstration-Resistant Nkx3.1-expressing cells), a luminal stem/progenitor cell that functions in prostate regeneration. Using genetically--engineered mouse models and novel prostate epithelial cell lines, we find that progenitor properties of CARNs are largely unaffected by AR deletion, apart from decreased proliferation in vivo. Furthermore, AR loss suppresses tumor formation after deletion of the Pten tumor suppressor in CARNs; however, combined Pten deletion and activation of oncogenic Kras in AR-deleted CARNs result in tumors with focal neuroendocrine differentiation. Our findings show that AR modulates specific progenitor properties of CARNs, including their ability to serve as a cell of origin for prostate cancer
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