Feature Selection for Anomaly Detection Using Optical Emission Spectroscopy

To maintain the pace of development set by Moore's law, production processes in semiconductor manufacturing are becoming more and more complex. The development of efficient and interpretable anomaly detection systems is fundamental to keeping production costs low. As the dimension of process monitoring data can become extremely high anomaly detection systems are impacted by the curse of dimensionality, hence dimensionality reduction plays an important role. Classical dimensionality reduction approaches, such as Principal Component Analysis, generally involve transformations that seek to maximize the explained variance. In datasets with several clusters of correlated variables the contributions of isolated variables to explained variance may be insignificant, with the result that they may not be included in the reduced data representation. It is then not possible to detect an anomaly if it is only reflected in such isolated variables. In this paper we present a new dimensionality reduction technique that takes account of such isolated variables and demonstrate how it can be used to build an interpretable and robust anomaly detection system for Optical Emission Spectroscopy data.

Immunoassays, optical and electrochemical immunosensorsfor tetrodotoxin determination in puffer fish samples

Tetrodotoxin (TTX) is a low molecular weight and potent marine neurotoxin which is usually present in some species of puffer fish. TTX selectively binds to voltage-sensitive sodium channels (VSGCs), blocking the influx of sodium into the cell and affecting neural transmission. The bioaccumulation of this toxin in seafood can poses a risk to human safety. With the purpose of achieving cheap, specific and reliable tools to determine TTX in puffer fish samples, a self-assembled dithiol-based immunoassay, an electrochemical immunosensor and an optical Surface Plasmon Resonance (SPR) immunosensor are proposed. The immunoassay for TTX based on the use of dithiols self-assembled on maleimide-plates (mELISA) has been able to detect as low as 2.28 μg/L of TTX. The effect of different puffer fish matrixes on this mELISA has been quantified and the corresponding correction factors have been established. This
mELISA has enabled to establish the cross-reactivity factors for four TTX analogues: 5,6,11-trideoxy-TTX, 5,6,11-trideoxy-4-anhydro-TTX, 11-nor-TTX-6-ol and 5,11-deoxy-TTX. The crossreactivity factors have also been established by the optical SPR immunosensor previously reported, which had a limit of detection (LOD) of 4.27 μg/L. The mELISA and the SPR immunosensor have then been tested with spiked-puffer fish matrixes, providing an effective
LOD of 0.23 and 0.43 mg/kg respectively, well below the limit set in Japan (2 mg/kg). The mELISA and the SPR immunosensor have also been applied to the analysis of naturally contaminated puffer fish samples, providing similar TTXs contents between techniques and also compared to LC-MS/MS. The suitability of these immunochemical techniques has been demonstrated not only for screening purposes, but also for research activities. Currently, given that dithiols could improve the electron transfer and the sensitivity of an electrochemical assay, the mELISA strategy is being transferred to gold electrodes for the electrochemical detection of TTX and the subsequent development of the multiplexed electrochemical immunosensor.

Semantic feature-based visual attention model for pedestrian detection

Objective
Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism.
Method
The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model.
Result
Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video.
Conclusion
This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians.

Detection of H2O and Evidence for TiO/VO in an Ultra-hot Exoplanet Atmosphere

We present a primary transit observation for the ultra-hot (T eq ~ 2400 K) gas giant expolanet WASP-121b, made using the Hubble Space Telescope Wide Field Camera 3 in spectroscopic mode across the 1.12–1.64 μm wavelength range. The 1.4 μm water absorption band is detected at high confidence (5.4σ) in the planetary atmosphere. We also reanalyze ground-based photometric light curves taken in the B, r', and z' filters. Significantly deeper transits are measured in these optical bandpasses relative to the near-infrared wavelengths. We conclude that scattering by high-altitude haze alone is unlikely to account for this difference and instead interpret it as evidence for titanium oxide and vanadium oxide absorption. Enhanced opacity is also inferred across the 1.12–1.3 μm wavelength range, possibly due to iron hydride absorption. If confirmed, WASP-121b will be the first exoplanet with titanium oxide, vanadium oxide, and iron hydride detected in transmission. The latter are important species in M/L dwarfs and their presence is likely to have a significant effect on the overall physics and chemistry of the atmosphere, including the production of a strong thermal inversion.

Enzyme-induced Aggregation of Plasmonic Nanoparticles for the Development of Label-free and Ultrasensitive Detection of Bacterial DNA

Sensitive detection of pathogens is critical to ensure the safety of food supplies and to prevent bacterial disease infection and outbreak at the first onset. While conventional techniques such as cell culture, ELISA, PCR, etc. have been used as the predominant detection workhorses, they are however limited by either time-consuming procedure, complicated sample pre-treatment, expensive analysis and operation, or inability to be implemented at point-of-care testing. Here, we present our recently developed assay exploiting enzyme-induced aggregation of plasmonic gold nanoparticles (AuNPs) for label-free and ultrasensitive detection of bacterial DNA. In the experiments, AuNPs are first functionalized with specific, single-stranded RNA probes so that they exhibit high stability in solution even under high electrolytic condition thus exhibiting red color. When bacterial DNA is present in a sample, a DNA-RNA heteroduplex will be formed and subsequently prone to the RNase H cleavage on the RNA probe, allowing the DNA to liberate and hybridize with another RNA strand. This continuously happens until all of the RNA strands are cleaved, leaving the nanoparticles ‘unprotected’. The addition of NaCl will cause the ‘unprotected’ nanoparticles to aggregate, initiating a colour change from red to blue. The reaction is performed in a multi-well plate format, and the distinct colour signal can be discriminated by naked eye or simple optical spectroscopy. As a result, bacterial DNA as low as pM could be unambiguously detected, suggesting that the enzyme-induced aggregation of AuNPs assay is very easy to perform and sensitive, it will significantly benefit to development of fast and ultrasensitive methods that can be used for disease detection and diagnosis.

VLT FORS2 comparative transmission spectroscopy: Detection of Na in the atmosphere of WASP-39b from the ground

We present transmission spectroscopy of the warm Saturn-mass exoplanet WASP-39b made with the Very Large Telescope (VLT) FOcal Reducer and Spectrograph (FORS2) across the wavelength range 411-810nm. The transit depth is measured with a typical precision of 240 parts per million (ppm) in wavelength bins of 10nm on a V = 12.1 magnitude star. We detect the sodium absorption feature (3.2-sigma) and find evidence for potassium. The ground-based transmission spectrum is consistent with Hubble Space Telescope (HST) optical spectroscopy, strengthening the interpretation of WASP-39b having a largely clear atmosphere. Our results demonstrate the great potential of the recently upgraded FORS2 spectrograph for optical transmission spectroscopy, obtaining HST-quality light curves from the ground.