Stevens Institute of Technology

About: Stevens Institute of Technology is a education organization based out in Hoboken, New Jersey, United States. It is known for research contribution in the topics: Computer science & Cognitive radio. The organization has 5440 authors who have published 12684 publications receiving 296875 citations. The organization is also known as: Stevens & Stevens Tech.

Mechanisms of photocatalytical degradation of monomethylarsonic and dimethylarsinic acids using nanocrystalline titanium dioxide.

Abstract: Photodegradation mechanisms of monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) with nanocrystalline titanium dioxide under UV irradiation were investigated. In the presence of UV irradiation and 0.02 g/L TiO2, 93% MMA (initial concentration is 10 mg-As/L) was transformed into inorganic arsenate, [As(V)], after 72 h of a batch reaction. The mineralization of DMA to As(V) occurred in two steps with MMA as an intermediate product. The photodegradation rate of MMA and DMA could be described using first-order kinetics, where the apparent rate constant is 0.033/h and 0.013/h for MMA and DMA, respectively. Radical scavengers, including superoxide dimutase (SOD), sodium bicarbonate, tert-butanol, and sodium azide, were used to study the photodegradation mechanisms of MMA and DMA. The results showed that hydroxyl radicals (HO•) was the primary reactive oxygen species for the photodegradation of MMA and DMA. The methyl groups in MMA and DMA were transformed into organic carbon, including formic acid and...

An experimental study on ferromagnetic nickel nanowires functionalized with antibodies for cell separation.

Abstract: In this paper, a cell separation technique has been explored using antibody-functionalized Ni nanowires. An antibody (anti-CD31) against mouse endothelial cells (MS1) was conjugated to the Ni nanowire surface through self-assembled monolayers (SAMs) and chemical covalent reactions. The measured cytotoxicity was negligible on the CD-31 antibody-functionalized nanowires by the tetrazolium salt (MTT) assay. The use of functionalized nanowires for magnetically separating MS1 cells revealed that the cell separation yield was closely related to cell concentration and the nanowire/cell ratio. Cell separation yield using functionalized Ni nanowires was compared with that using commercial magnetic beads. Considering the volume difference of the material used between the beads and nanowires, antibody-functionalized nanowires showed an obvious advantage in cell separation. Further study on the effect of Ni nanowires on MS1 cells for extended culture confirmed that cell morphology remained comparable to control cells with a lower proliferation rate. This work demonstrates that antibody-functionalized Ni nanowires provide an effective means to separate target cells.

A neural network approach to infrared spectrum interpretation

Abstract: The simple linear neural network model was investigated as a method for automated interpretation of infrared spectra. The model was trained using a database of infrared spectra of organic compounds of known structure. The model was able to learn, without any prior input of spectrum-structure correlations, to recognize and identify 76 functional groupings with accuracies ranging from fair to excellent. The effect of network input parameters and of training set composition were studied, and several sources of spurious correlations were identified and corrected.

Joint Delay and Doppler Estimation for Passive Sensing With Direct-Path Interference

Abstract: We consider the problem of joint delay-Doppler estimation of a moving target in a passive radar that employs a non-cooperative illuminator of opportunity (IO) for target illumination, a reference channel (RC) steered to the IO to obtain a reference signal, and a surveillance channel (SC) for target monitoring. We consider a practically motivated scenario, where the RC receives a noise-contaminated copy of the IO signal and the SC observation is polluted by a direct-path interference that is usually neglected by prior studies. We develop a data model without discretizing the parameter space, which may lead to a straddle loss, by treating both the delay and Doppler as continuous parameters. We propose an expectation-maximization based estimator, as well as a modified cross-correlation (MCC) estimator that is a computationally simpler solution resulting from an approximation of the former. In addition, we derive the Cramer-Rao lower bound for the estimation problem. Simulation results are presented to illustrate the performance of the proposed estimators and the widely used CC estimator.