Kaolinite-NMF intercalates

Bulk and size-fractionated kaolinites from seven localities in Australia as well as the Clay Minerals Society Source Clays Georgia KGa-1 and KGa-2 have been studied by X-ray diffraction (XRD), laser scattering, and electron microscopy in order to understand the variation of particle characteristics across a range of environments and to correlate specific particle characteristics with intercalation behavior. All kaolinites have been intercalated with N-methyl (NMF) after pretreatment with hydrazine hydrate, and the relative efficiency of intercalation has been determined using XRD. Intercalate yields of kaolinite: NMF are consistently low for bulk samples that have a high proportion of small-sized particles (i.e., <0.5 µm) and for biphased kaolinites with a high percentage (>60%) of low-defect phase. In general, particle size appears to be a more significant controlling factor than defect distribution in determining the relative yield of kaolinite: NMF intercalate.

Kaolinite - NMF intercalates

Bulk and size-fractionated kaolinites from seven localities in Australia as well as the Clay Minerals Society Source Clays Georgia KGa-1 and KGa-2 have been studied by X-ray diffraction (XRD), laser scattering, and electron microscopy in order to understand the variation of particle characteristics across a range of environments and to correlate specific particle characteristics with intercalation behavior. All kaolinites have been intercalated with N-methyl formamide (NMF) after pretreatment with hydrazine hydrate, and the relative efficiency of intercalation has been determined using XRD. Intercalate yields of kaolinite: NMF are consistently low for bulk samples that have a high proportion of small-sized particles (i.e., <0.5 µm) and for biphased kaolinites with a high percentage (>60%) of low-defect phase. In general, particle size appears to be a more significant controlling factor than defect distribution in determining the relative yield of kaolinite: NMF intercalate.

Parts based representation for pedestrian using NMF with robustness to partial occlusion

Computer Vision has seen a resurgence in the parts-based representation for objects over the past few years. The parts are usually annotated beforehand for training. We present an annotation free parts-based representation for the pedestrian using Non-Negative Matrix Factorization (NMF). We show that NMF is able to capture the wide range of pose and clothing of the pedestrians. We use a modified form of NMF i.e. NMF with sparsity constraints on the factored matrices. We also make use of Riemannian distance metric for similarity measurements in NMF space as the basis vectors generated by NMF aren't orthogonal. We show that for 1% drop in accuracy as compared to the Histogram of Oriented Gradients (HOG) representation we can achieve robustness to partial occlusion.

Discovering subgroups of patients from DNA copy number data using NMF on compacted matrices

In the study of complex genetic diseases, the identification of subgroups of patients sharing similar genetic characteristics represents a challenging task, for example, to improve treatment decision. One type of genetic lesion, frequently investigated in such disorders, is the change of the DNA copy number (CN) at specific genomic traits. Non-negative Matrix Factorization (NMF) is a standard technique to reduce the dimensionality of a data set and to cluster data samples, while keeping its most relevant information in meaningful components. Thus, it can be used to discover subgroups of patients from CN profiles. It is however computationally impractical for very high dimensional data, such as CN microarray data. Deciding the most suitable number of subgroups is also a challenging problem. The aim of this work is to derive a procedure to compact high dimensional data, in order to improve NMF applicability without compromising the quality of the clustering. This is particularly important for analyzing high-resolution microarray data. Many commonly used quality measures, as well as our own measures, are employed to decide the number of subgroups and to assess the quality of the results. Our measures are based on the idea of identifying robust subgroups, inspired by biologically/clinically relevance instead of simply aiming at well-separated clusters. We evaluate our procedure using four real independent data sets. In these data sets, our method was able to find accurate subgroups with individual molecular and clinical features and outperformed the standard NMF in terms of accuracy in the factorization fitness function. Hence, it can be useful for the discovery of subgroups of patients with similar CN profiles in the study of heterogeneous diseases.

Estudo de N-metilformamida em meio não aquoso. O caso NMF-acetona

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Inducing shades of meaning by matrix methods : a first step towards thematic analysis of opinion

This article explores two matrix methods to induce the ``shades of meaning" (SoM) of a word. A matrix representation of a word is computed from a corpus of traces based on the given word. Non-negative Matrix Factorisation (NMF) and Singular Value Decomposition (SVD) compute a set of vectors corresponding to a potential shade of meaning. The two methods were evaluated based on loss of conditional entropy with respect to two sets of manually tagged data. One set reflects concepts generally appearing in text, and the second set comprises words used for investigations into word sense disambiguation. Results show that for NMF consistently outperforms SVD for inducing both SoM of general concepts as well as word senses. The problem of inducing the shades of meaning of a word is more subtle than that of word sense induction and hence relevant to thematic analysis of opinion where nuances of opinion can arise.

Empirical analysis of the effect of dimension reduction and word order on semantic vectors

The aim of this paper is to provide a comparison of various algorithms and parameters to build reduced semantic spaces. The effect of dimension reduction, the stability of the representation and the effect of word order are examined in the context of the five algorithms bearing on semantic vectors: Random projection (RP), singular value decom- position (SVD), non-negative matrix factorization (NMF), permutations and holographic reduced representations (HRR). The quality of semantic representation was tested by means of synonym finding task using the TOEFL test on the TASA corpus. Dimension reduction was found to improve the quality of semantic representation but it is hard to find the optimal parameter settings. Even though dimension reduction by RP was found to be more generally applicable than SVD, the semantic vectors produced by RP are somewhat unstable. The effect of encoding word order into the semantic vector representation via HRR did not lead to any increase in scores over vectors constructed from word co-occurrence in context information. In this regard, very small context windows resulted in better semantic vectors for the TOEFL test.

Induction of epithelial to mesenchymal transition in PMC42-LA human breast carcinoma cells by carcinoma-associated fibroblast secreted factors

Background Breast carcinoma is accompanied by changes in the acellular and cellular components of the microenvironment, the latter typified by a switch from fibroblasts to myofibroblasts. Methods: We utilised conditioned media cultures, Western blot analysis and immunocytochemistry to investigate the differential effects of normal mammary fibroblasts (NMFs) and mammary cancer-associated fibroblasts (CAFs) on the phenotype and behaviour of PMC42-LA breast cancer cells. NMFs were obtained from a mammary gland at reduction mammoplasty, and CAFs from a mammary carcinoma after resection. Results We found greater expression of myofibroblastic markers in CAFs than in NMFs. Medium from both CAFs and NMFs induced novel expression of α-smooth muscle actin and cytokeratin-14 in PMC42-LA organoids. However, although conditioned media from NMFs resulted in distribution of vimentin-positive cells to the periphery of PMC42-LA organoids, this was not seen with CAF-conditioned medium. Upregulation of vimentin was accompanied by a mis-localization of E-cadherin, suggesting a loss of adhesive function. This was confirmed by visualizing the change in active β-catenin, localized to the cell junctions in control cells/ cells in NMF-conditioned medium, to inactive β-catenin, localized to nuclei and cytoplasm in cells in CAF-conditioned medium. Conclusion We found no significant difference between the influences of NMFs and CAFs on PMC42-LA cell proliferation, viability, or apoptosis; significantly, we demonstrated a role for CAFs, but not for NMFs, in increasing the migratory ability of PMC42-LA cells. By concentrating NMF-conditioned media, we demonstrated the presence of factor(s) that induce epithelial-mesenchymal transition in NMF-conditioned media that are present at higher levels in CAF-conditioned media. Our in vitro results are consistent with observations in vivo showing that alterations in stroma influence the phenotype and behaviour of surrounding cells and provide evidence for a role for CAFs in stimulating cancer progression via an epithelial-mesenchymal transition. These findings have implications for our understanding of the roles of signalling between epithelial and stromal cells in the development and progression of mammary carcinoma.

New insights into the molecular structure of kaolinite–methanol intercalation complexes

A series of kaolinite–methanol complexes with different basal spacings were synthesized using guest displacement reactions of the intercalation precursors kaolinite–N-methyformamide (Kaol–NMF), kaolinite–urea (Kaol–U), or kaolinite–dimethylsulfoxide (Kaol–DMSO), with methanol (Me). The interaction of methanol with kaolinite was examined using X-ray diffraction (XRD), infrared spectroscopy (IR), and nuclear magnetic resonance (NMR). Kaolinite (Kaol) initially intercalated with N-methyformamide (NMF), urea (U), or dimethylsulfoxide (DMSO) before subsequent reaction with Me formed final kaolinite–methanol (Kaol–Me) complexes characterized by basal spacing ranging between 8.6 Å and 9.6 Å, depending on the pre-intercalated reagent. Based on a comparative analysis of the three Kaol–Me displacement intercalation complexes, three types of Me intercalation products were suggested to have been present in the interlayer space of Kaol: (1) molecules grafted onto a kaolinite octahedral sheet in the form of a methoxy group (Al-O-C bond); (2) mobile Me and/or water molecules kept in the interlayer space via hydrogen bonds that could be partially removed during drying; and (3) a mixture of types 1 and 2, with the methoxy group (Al-O-C bond) grafted onto the Kaol sheet and mobile Me and/or water molecules coexisted in the system after the displacement reaction by Me. Various structural models that reflected four possible complexes of Kaol–Me were constructed for use in a complimentary computational study. Results from the calculation of the methanol kaolinite interaction indicate that the hydroxyl oxygen atom of methanol plays the dominant role in the stabilization and localization of the molecule intercalated in the interlayer space, and that water existing in the intercalated Kaol layer is inevitable.

Simulation of the infrared spectra of N-methylformamide and N-methylacetamide by the extended molecular mechanics method

The infrared spectra of the matrix isolated species of N-methylformamide (NMF) and N-methylacetamide (NMA) and their N-deuterated molecules have been simulated by the extended molecular mechanics method using an empirical force field which includes charges and charge fluxes as coulombic potential parameters. The structural parameters and dipole. moments of NMF and NMA have. also been computed in satisfactory agreement with the experiment. Good agreement between experimental and calculated vibrational frequencies and infrared absorption band intensities for NMF and NMA and their deuterated molecules has been obtained. The vibrational assignments of NMF and NMA are-discussed taking also into account the infrared absorption intensities.

Feature selection for unsupervised learning

In this paper, we present a methodology for identifying best features from a large feature space. In high dimensional feature space nearest neighbor search is meaningless. In this feature space we see quality and performance issue with nearest neighbor search. Many data mining algorithms use nearest neighbor search. So instead of doing nearest neighbor search using all the features we need to select relevant features. We propose feature selection using Non-negative Matrix Factorization(NMF) and its application to nearest neighbor search. Recent clustering algorithm based on Locally Consistent Concept Factorization(LCCF) shows better quality of document clustering by using local geometrical and discriminating structure of the data. By using our feature selection method we have shown further improvement of performance in the clustering.

Hybrid online non-negative matrix factorization for clustering of documents

When document corpus is very large, we often need to reduce the number of features. But it is not possible to apply conventional Non-negative Matrix Factorization(NMF) on billion by million matrix as the matrix may not fit in memory. Here we present novel Online NMF algorithm. Using Online NMF, we reduced original high-dimensional space to low-dimensional space. Then we cluster all the documents in reduced dimension using k-means algorithm. We experimentally show that by processing small subsets of documents we will be able to achieve good performance. The method proposed outperforms existing algorithms.

On the relation between K-means and PLSA

Non-negative matrix factorization [5](NMF) is a well known tool for unsupervised machine learning. It can be viewed as a generalization of the K-means clustering, Expectation Maximization based clustering and aspect modeling by Probabilistic Latent Semantic Analysis (PLSA). Specifically PLSA is related to NMF with KL-divergence objective function. Further it is shown that K-means clustering is a special case of NMF with matrix L2 norm based error function. In this paper our objective is to analyze the relation between K-means clustering and PLSA by examining the KL-divergence function and matrix L2 norm based error function.

棕色固氮菌突变种(UW45、DJ54和DJ35)的缺失FeMoco钼铁蛋白的纯化、特性鉴定及结晶研究

一．棕色固氮菌突变种UW45、缺失nifH（DJ54）和缺失nifE(DJ35)突变种的钼铁蛋白的纯化、特性鉴定及结晶研究 棕色固氮菌突变种UW45的菌体破碎后，所得粗提物经两次DEAE 52柱层析后得到部分纯的nifB- MoFe蛋白和Fe蛋白。再经Sephacryl S-300和 DEAE柱的进一步纯化，便使nifB- MoFe蛋白基本达到SDS凝胶电泳纯。SDS-PAGE结果表明，nifB- MoFe蛋白具有与野生型棕色固氮菌（OP）MoFe蛋白相同的亚基种类和组成。此粗提物可为用NMF抽提的 OP MoFe蛋白的FeMoco激活，所得Fe蛋白具有与OP Fe蛋白相似的互补活性，可使OP MoFe的比活性达到2192 nmol C2H2/min/mg蛋白。FeMoco可使无互补活性的 nifB- MoFe蛋白与nifB- Fe蛋白组成具有可观放氢活性的固氮酶，使FeMoco显出的比活性接近文献报道的还原乙炔的最高值。对nifB- MoFe蛋白的结晶及晶体生长进行了的研究，初步探讨了结晶溶液各组分的种类和浓度、结晶方法和实验操作等与能否出现晶体及晶体的数目、大小、质量、形状和出晶时间等的相互关系。在结晶实验时，一次就得到了国内外尚未报道的该蛋白的短斜四棱柱的棕色晶体。目前所得的最大的晶体的二维边长都为0.1mm。初步结果表明，这种晶体可能就是nifB- MoFe蛋白的晶体。 从棕色固氮菌突变种DJ54中得到了ΔnifH MoFe蛋白;并参与了棕色固氮菌突变种DJ35的ΔnifE MoFe蛋白的分离纯化，所用方法与nifB- MoFe蛋白的分离纯化相似。对这两种突变种蛋白的特性和结晶进行了初步研究。在结晶实验时，也是一次就得到了国内外尚未报道的ΔnifH MoFe蛋白和ΔnifEMoFe蛋白的晶体。 二．新型固氮酶MnFe蛋白和CrFe蛋白的特性与结晶研究 在已有的工作基础上，分离纯化了几批MnFe蛋白和CrFe蛋白，并用部分纯的nifB- Fe蛋白进行活性互补，分别测定了MnFe蛋白和CrFe蛋白的底物还原活性。不断优化MnFe蛋白和CrFe蛋白晶体生长条件，获得了晶质良好的MnFe蛋白和CrFe蛋白的较大晶体。 在2001年的“神舟2号”飞船搭载实验中，MnFe蛋白的出晶率达到100%，所获得的晶体也比地面对照略厚些。继续进行MnFe蛋白和CrFe蛋白的空间计划的地面匹配实验，以满足对蛋白质样品的要求，以保证宇宙飞船“神舟3号”的蛋白质搭载实验获得更好的结果。