Fe is an impurity in most leach liquors. Its coexistence with copper in leaching solution of chalcopyrite (CuFeS2) which is the most important mineral of copper creates major extraction problems. Hydrochloric acid dissolves both copper and iron during chloride leaching of this mineral. Separation of Fe from Cu is thus necessary to obtain pure copper. This paper presents a novel metho...

The determination of glycohemoglobin [HbA1c, HbA1, or total glycohemoglobin (GHb)] has become an established procedure in the management of diabetes mellitus. Here, we describe the development of a simple, fluorescence, non-separation assay for the percentage of GHb (%GHb). The fluorescence of an eosin-boronic acid derivative when it was mixed with hemolysates of unwashed erythrocytes was quenc...

A pot experiment using root separation technique was conducted to further understand the effect of root interaction played in intercropping system under different nitrogen levels. The results showed that root interaction and increasing nitrogen application increased the green leaf area per plant and chlorophyll content of soybean, but their effects gradually decreased with increasing nitrogen f...

In sparse nonnegative component analysis (sparse NMF) a given dataset is decomposed into a mixing matrix and a feature data set, which are both nonnegative and fulfill certain sparsity constraints. In this paper, we extend the sparse NMF algorithm to allow for varying sparsity in each feature and discuss the uniqueness of an involved projection step. Furthermore, the eligibility of the extended...

We propose a novel acoustic beamforming method using blind source separation (BSS) techniques based on non-negative matrix factorization (NMF). In conventional mask-based approaches, hard or soft masks are estimated and beamforming is performed using speech and noise spatial covariance matrices calculated from masked noisy observations, but the phase information of the target speech is not adeq...

Blind source separation usually obtains limited performance on real and polyphonic music signals. To overcome these limitations, it is common to rely on prior knowledge under the form of side information as in Informed Source Separation or on machine learning paradigms applied on a training database. In the context of source separation based on factorization models such as the Non-negative Matr...