Optimal Rates for the Random Fourier Feature Method

Kernel methods represent one of the most powerful tools in machine learning to tackle problems expressed in terms of function values and derivatives. While these methods show good versatility, they are computationally intensive and have poor scalability to large data as they require operations on Gram matrices. In order to mitigate this serious computational limitation, recently randomized methods have been proposed in the literature, which allow the application of fast linear algorithms. Random Fourier features (RFF) are among the most popular and widely applied constructions: they provide an easily computable, low-dimensional feature representation for shift-invariant kernels. Despite the popularity of RFFs, very little is understood theoretically about their approximation quality. In this talk, I am going to present the main ideas and results of a detailed finite-sample theoretical analysis about the approximation quality of RFFs by (i) establishing optimal (in terms of the RFF dimension, and growing set size) performance guarantees in uniform norm, and (ii) providing guarantees in Lr (1 <= r < \infty) norms. I will also propose an RFF approximation to derivatives of kernel with a theoretical study on its approximation quality

Postnatal Survival of Mice with Maternal Duplication of Distal Chromosome 7 Induced by a Igf2/H19 Imprinting Control Region Lacking Insulator Function

The misexpressed imprinted genes causing developmental failure of mouse parthenogenones are poorly defined. To obtain further insight, we investigated misexpressions that could cause the pronounced growth deficiency and death of fetuses with maternal duplication of distal chromosome (Chr) 7 (MatDup.dist7). Their small size could involve inactivity of Igf2, encoding a growth factor, with some contribution by over-expression of Cdkn1c, encoding a negative growth regulator. Mice lacking Igf2 expression are usually viable, and MatDup.dist7 death has been attributed to the misexpression of Cdkn1c or other imprinted genes. To examine the role of misexpressions determined by two maternal copies of the Igf2/H19 imprinting control region (ICR)—a chromatin insulator, we introduced a mutant ICR (ICRΔ) into MatDup.dist7 fetuses. This activated Igf2, with correction of H19 expression and other imprinted transcripts expected. Substantial growth enhancement and full postnatal viability was obtained, demonstrating that the aberrant MatDup.dist7 phenotype is highly dependent on the presence of two unmethylated maternal Igf2/H19 ICRs. Activation of Igf2 is likely the predominant correction that rescued growth and viability. Further experiments involved the introduction of a null allele of Cdkn1c to alleviate its over-expression. Results were not consistent with the possibility that this misexpression alone, or in combination with Igf2 inactivity, mediates MatDup.dist7 death. Rather, a network of misexpressions derived from dist7 is probably involved. Our results are consistent with the idea that reduced expression of IGF2 plays a role in the aetiology of the human imprinting-related growth-deficit disorder, Silver-Russell syndrome

Tensor based multichannel reconstruction for breast tumours identification from DCE-MRIs

A new methodology based on tensor algebra that uses a higher order singular value decomposition to perform three-dimensional voxel reconstruction from a series of temporal images obtained using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is proposed. Principal component analysis (PCA) is used to robustly extract the spatial and temporal image features and simultaneously de-noise the datasets. Tumour segmentation on enhanced scaled (ES) images performed using a fuzzy C-means (FCM) cluster algorithm is compared with that achieved using the proposed tensorial framework. The proposed algorithm explores the correlations between spatial and temporal features in the tumours. The multi-channel reconstruction enables improved breast tumour identification through enhanced de-noising and improved intensity consistency. The reconstructed tumours have clear and continuous boundaries; furthermore the reconstruction shows better voxel clustering in tumour regions of interest. A more homogenous intensity distribution is also observed, enabling improved image contrast between tumours and background, especially in places where fatty tissue is imaged. The fidelity of reconstruction is further evaluated on the basis of five new qualitative metrics. Results confirm the superiority of the tensorial approach. The proposed reconstruction metrics should also find future applications in the assessment of other reconstruction algorithms

A new biphasic osteoinductive calcium composite material with a negative Zeta potential for bone augmentation

The aim of the present study was to analyze the osteogenic potential of a biphasic calcium composite material (BCC) with a negative surface charge for maxillary sinus floor augmentation. In a 61 year old patient, the BCC material was used in a bilateral sinus floor augmentation procedure. Six months postoperative, a bone sample was taken from the augmented regions before two titanium implants were inserted at each side. We analyzed bone neoformation by histology, bone density by computed tomography, and measured the activity of voltage-activated calcium currents of osteoblasts and surface charge effects. Control orthopantomograms were carried out five months after implant insertion. The BCC was biocompatible and replaced by new mineralized bone after being resorbed completely. The material demonstrated a negative surface charge (negative Zeta potential) which was found to be favorable for bone regeneration and osseointegration of dental implants

Selection of diagnostic features on breast MRI to differentiate between malignant and benign lesions using computer-aided diagnosis: differences in lesions presenting as mass and non-mass-like enhancement

Purpose: To investigate methods developed for the characterisation of the morphology and enhancement kinetic features of both mass and non-mass lesions, and to determine their diagnostic performance to differentiate between malignant and benign lesions that present as mass versus non-mass types. Methods: Quantitative analysis of morphological features and enhancement kinetic parameters of breast lesions were used to differentiate among four groups of lesions: 88 malignant (43 mass, 45 non-mass) and 28 benign (19 mass, 9 non-mass). The enhancement kinetics was measured and analysed to obtain transfer constant (Ktrans) and rate constant (kep). For each mass eight shape/margin parameters and 10 enhancement texture features were obtained. For the lesions presenting as nonmass-like enhancement, only the texture parameters were obtained. An artificial neural network (ANN) was used to build the diagnostic model. Results: For lesions presenting as mass, the four selected morphological features could reach an area under the ROC curve (AUC) of 0.87 in differentiating between malignant and benign lesions. The kinetic parameter (kep) analysed from the hot spot of the tumour reached a comparable AUC of 0.88. The combined morphological and kinetic features improved the AUC to 0.93, with a sensitivity of 0.97 and a specificity of 0.80. For lesions presenting as non-mass-like enhancement, four texture features were selected by the ANN and achieved an AUC of 0.76. The kinetic parameter kepfrom the hot spot only achieved an AUC of 0.59, with a low added diagnostic value. Conclusion: The results suggest that the quantitative diagnostic features can be used for developing automated breast CAD (computer-aided diagnosis) for mass lesions to achieve a high diagnostic performance, but more advanced algorithms are needed for diagnosis of lesions presenting as non-mass-like enhancement. © The Author(s) 2009

Multi-parametric assessment of the anti-angiogenic effects of liposomal glucocorticoids

Inflammation plays a prominent role in tumor growth. Anti-inflammatory drugs have therefore been proposed as anti-cancer therapeutics. In this study, we determined the anti-angiogenic activity of a single dose of liposomal prednisolone phosphate (PLP-L), by monitoring tumor vascular function and viability over a period of one week. C57BL/6 mice were inoculated subcutaneously with B16F10 melanoma cells. Six animals were PLP-L-treated and six served as control. Tumor tissue and vascular function were probed using MRI before and at three timepoints after treatment. DCE-MRI was used to determine Ktrans, ve, time-to-peak, initial slope and the fraction of non-enhancing pixels, complemented with immunohistochemistry. The apparent diffusion coefficient (ADC), T2 and tumor size were assessed with MRI as well. PLP-L treatment resulted in smaller tumors and caused a significant drop in Ktrans 48 h post-treatment, which was maintained until one week after drug administration. However, this effect was not sufficient to significantly distinguish treated from non-treated animals. The therapy did not affect tumor tissue viability but did prevent the ADC decrease observed in the control group. No evidence for PLP-L-induced tumor vessel normalization was found on histology. Treatment with PLP-L altered tumor vascular function. This effect did not fully explain the tumor growth inhibition, suggesting a broader spectrum of PLP-L activities

A brief report on the associations amongst social media use, gender, and body esteem in a UK student sample

Research into the effects of social media on personal wellbeing have been controversial in recent years, with recent research highlighting links between social media use and body esteem. This conceptual replication study aimed to explore relationships amongst social media use, body esteem and gender amongst UK university students (n=100). Participants completed measures of social media use and body image esteem. It was hypothesised that social media intensity and usage would negatively predict body esteem, with high social media intensity relating to lower body esteem. We find that gender was the only significant predictor of body esteem, with women having lower body esteem compared to men. We were unable to replicate previous findings, as our findings show no relationships amongst social media intensity, use, and body esteem

Renewable, ethical? Assessing the energy justice potential of renewable electricity

Energy justice is increasingly being used as a framework to conceptualize the impacts of energy decision making in more holistic ways and to consider the social implications in terms of existing ethical values. Similarly, renewable energy technologies are increasingly being promoted for their environmental and social benefits. However, little work has been done to systematically examine the extent to which, in what ways and in what contexts, renewable energy technologies can contribute to achieving energy justice. This paper assesses the potential of renewable electricity technologies to address energy justice in various global contexts via a systematic review of existing studies analyzed in terms of the principles and dimensions of energy justice. Based on publications including peer reviewed academic literature, books, and in some cases reports by government or international organizations, we assess renewable electricity technologies in both grid integrated and off-grid use contexts. We conduct our investigation through the rubric of the affirmative and prohibitive principles of energy justice and in terms of its temporal, geographic, socio-political, economic, and technological dimensions. Renewable electricity technology development has and continue to have different impacts in different social contexts, and by considering the different impacts explicitly across global contexts, including differences between rural and urban contexts, this paper contributes to identifying and understanding how, in what ways, and in what particular conditions and circumstances renewable electricity technologies may correspond with or work to promote energy justice