Unexpected Background Research Articles

Identifying incoherent mixing effects in the coherent two-dimensional photocurrent excitation spectra of semiconductors.

We have previously demonstrated that in the context of two-dimensional (2D) coherent electronic spectroscopy measured by phase modulation and phase-sensitive detection, an incoherent nonlinear response due to pairs of photoexcitations produced via linear excitation pathways contributes to the measured signal as an unexpected background [Grégoire et al., J. Chem. Phys. 147, 114201 (2017)]. Here, we simulate the effect of such incoherent population mixing in the photocurrent signal collected from a GaAs solar cell by acting externally on the transimpedance amplifier circuit used for phase-sensitive detection, and we identify an effective strategy to recognize the presence of incoherent population mixing in 2D data. While we find that incoherent mixing is reflected by the crosstalk between the linear amplitudes at the two time-delay variables in the four-pulse excitation sequence, we do not observe any strict phase correlations between the coherent and incoherent contributions, as expected from modeling of a simple system.

Plasmonic Color Printing via Bottom-Up Laser-Induced Photomodification Process.

Plasmonic color printing has received significant attention owing to its advantages such as nonfading and nontoxic color expression, without necessitating the use of chemical dyes. Recently, color generation from laser-induced plasmonic nanostructures has been extensively explored because of its simplicity, cost-effectiveness, and large-scale processability. However, these methods usually utilize a top-down method that causes unexpected background colors. Here, we proposed a novel method of plasmonic color printing via a bottom-up type laser-induced photomodification process. In the proposed method, selective silver nanoparticles (Ag NPs) structure could be fabricated on a transparent substrate through a unique organometallic solution-based laser patterning process. A set of color palettes was formed on the basis of different processing parameters such as laser fluence, scanning speed, and baking time. This color change was verified by finite-difference time-domain (FDTD) simulations via monitoring the spectral peak shift of the localized surface plasmon resonance (LSPR) at Ag NPs. It was also confirmed that the colors can be fabricated at a relatively high scanning speed (≥10 mm/s) on a large substrate (>300 mm2). Since semitransparent color images can be patterned on various transparent substrates, this process will broaden the application range of laser-induced plasmonic color generation.

Background Noise Removal Technique using Deep Learning Segmentation Network without Segmentation Map

Audio data acquired at industrial manufacturing sites often include unexpected background noise. Since the performance of data-driven models can be worse by background noise. Therefore, it is important to get rid of unwanted background noise. There are two main techniques for noise canceling in a traditional manner. One is Active Noise Canceling (ANC), which generates an inverted phase of the sound that we want to remove. The other is Passive Noise Canceling (PNC), which physically blocks the noise. However, these methods require large device size and expensive cost. Thus, we propose a deep learning-based noise canceling method. This technique was developed using audio imaging technique and deep learning segmentation network. However, the proposed model only needs the information on whether the audio contains noise or not. In other words, unlike the general segmentation technique, a pixel-wise ground truth segmentation map is not required for this method. We demonstrate to evaluate the separation using pump sound of MIMII dataset, which is open-source dataset.

Robust visual tracker integrating adaptively foreground segmentation into multi-feature fusion framework

Existing Discriminative Correlation Filter (DCF) based methods suffer from the limitations of rectangular shape assumptions. Aiming at this issue, in this paper, we propose an effective tracking approach which integrates a pixel-wise foreground segmentation mask into the correlation filter within a multi-feature fusion framework. Specifically, we first propose a novel segmentation algorithm which combines the color histogram with the spatial prior. On this basis, we implement a target-masked correlation filter (TMCF) tracker by introducing the foreground mask into a ridge regression, which successfully suppresses unexpected background information inside the bounding box. Secondly, we apply the alternating direction method of multipliers (ADMM) to solve our TMCF model efficiently to obtain the closed-form solution. Finally, a complementary fusion tracker by the combining of TMCF and color histogram scores (fTMCFCH) is formulated, which is robust to deformations and illumination changes simultaneously. The fusion factor is determined adaptively by the reliability derived from the target resolution of the trackers separately in each frame. We perform extensive experiments on three benchmarks: OTB-2013, OTB-2015 and Temple-Color-128. The concrete experimental results demonstrate that our tracker outperforms several state-of-the-art trackers.

Tunable-illumination for laser Fourier ptychographic microscopy based on a background noise-reducing system

It is inherently difficult for a conventional microscopic imaging system to produce images with both wide field of view (FOV) and high-resolution because of its limited space bandwidth product. Fourier ptychographic microscopy (FPM) has been developed to overcome this limitation by using angle-varied illumination to enhance the performance of the system. In this paper, we propose a FPM imaging approach that employs a laser source with a newly developed illumination control optical system. The proposed system consists of a digital micromirror device and a zoom system with a condenser lens to provide sample illumination with angle-varied pattern directions and controllable pattern sizes. In addition, a total internal reflection prism is employed in the system to remove unexpected background noise and extend the FOV for reconstruction. The proposed system is validated against a USAF resolution target and a biological sample, and as a result reconstructs images with higher resolution and more details once the positional misalignment correction algorithm is employed. We envision that the proposed FPM system will be suitable for high-speed imaging applications.

Investigation of Physiological Swelling on Conductivity Distribution in Lower Leg Subcutaneous Tissue by Electrical Impedance Tomography.

There is a strong need for a non-invasive measurement technique that is capable of accurately identifying the physiological condition change or heterogeneity of subcutaneous adipose tissue (SAT) by localizing the abnormalities within the compartment. This paper aims to investigate the feasibility of Electrical Impedance Tomography (EIT) to assess the interstitial fluid in subcutaneous adipose tissue as an enhancement method of bioelectrical impedance spectroscopy (BIS). Here, we demonstrate the preliminary result of EIT with a wearable 16 electrodes sensor. The image-based reference EIT with fat weighted threshold method is proposed. In order to evaluate the performance of our novel method, a physiological swelling experiment is conducted, and Multi-Frequency Bioelectrical Impedance Analysis (MFBIA) is also applied as a comparison with EIT results. The experimental results showed that the proposed method was able to distinguish the physiological swelling condition and effectively to remove the unexpected background noise. Furthermore, the conductivity variation in the subcutaneous layer had a good correlation with extracellular water volume change from MFBIA data; the correlation coefficient R2 = 0.927. It is concluded that the proposed method provides a significant prospect for SAT assessment.

A Contextual Bidirectional Enhancement Method for Remote Sensing Image Object Detection

In remote sensing images, the backgrounds of objects include crucial contextual information that may contribute to distinguishing objects. However, there are at least two issues that should be addressed: not all the backgrounds are beneficial, and object information may be suppressed by backgrounds. To address these problems, in this article, we propose the contextual bidirectional enhancement (CBD-E) method to simultaneously remove unexpected background information and enhance objects’ features. CBD-E integrates the features of different background regions sequentially in two directions. On the one hand, a gate function is used to filter out unexpected information in the background and thus improve the recall of detection. On the other hand, a spatial-group-based visual attention mechanism is adopted to enhance the features of objects to reduce the false alarm. The gate function provides an approach to selecting meaningful information in the background, while the spatial-group- based visual attention mechanism enhances the information control ability of the gate function. In the experiments, we have validated the effectiveness of both the gate function and the visual attention mechanism and further demonstrated that the proposed contextual fusion strategy performs well on two published data sets.

Ultrasensitive Anti-Interference Voice Recognition by Bio-Inspired Skin-Attachable Self-Cleaning Acoustic Sensors.

Human voice recognition systems (VRSs) are a prerequisite for voice-controlled human-machine interfaces (HMIs). In order to avoid interference from unexpected background noises, skin-attachable VRSs are proposed to directly detect physiological mechanoacoustic signals based on the vibrations of vocal cords. However, the sensitivity and response time of existing VRSs are bottlenecks for efficient HMIs. In addition, water-based contaminants in our daily lives, such as skin moisture and raindrops, normally result in performance degradation or even functional failure of VRSs. Herein, we present a skin-attachable self-cleaning ultrasensitive and ultrafast acoustic sensor based on a reduced graphene oxide/polydimethylsiloxane composite film with bioinspired microcracks and hierarchical surface textures. Benefitting from the synergetic effect of the spider-slit-organ-like multiscale jagged microcracks and the lotus-leaf-like hierarchical structures, our superhydrophobic VRS exhibits an ultrahigh sensitivity (gauge factor, GF = 8699), an ultralow detection limit (ε = 0.000 064%), an ultrafast response/recovery behavior, an excellent device durability (>10 000 cycles), and reliable detection of acoustic vibrations over the audible frequency range (20-20 000 Hz) with high signal-to-noise ratios. These superb performances endow our skin-attachable VRS with anti-interference perception of human voices with high precision even in noisy environments, which will expedite the voice-controlled HMIs.

Spatial–temporal adaptive feature weighted correlation filter for visual tracking

In recent years, the discriminative correlation filter (DCF) tracking method has attracted considerable attention for its promising results and high efficiency. However, it introduces unexpected background information and is susceptible to distractors, owing to the larger training patches it uses. This paper proposes a correlation filter-based visual tracking approach that integrates spatial–temporal adaptive feature weights into the DCF method to derive an efficient solution. The feature weights, which are adaptively adjusted according to the target likelihood and prior knowledge, effectively enhance the target and suppress the background. The correlation filter in our formulation is learned based on weighted features. By assigning small weights to the background and large weights to the target, the tracker is less likely to drift. To preserve the circulant property in the DCF formulation, a new variable called the pseudo correlation filter is introduced to reformulate and solve the cost function efficiently by employing the iterative Gauss–Seidel method. The proposed method is tested on both handcrafted and deep features. Extensive experiments on three benchmark datasets demonstrate that the proposed tracker achieves favorable performance compared with recent state-of-the-art methods.

TLR2 signal influences the iNOS/NO responses and worm development in C57BL/6J mice infected with Clonorchis sinensis

BackgroundAlthough the responses of inducible nitric oxide synthase (iNOS) and associated cytokine after Clonorchis sinensis infection have been studied recently, their mechanisms remain incompletely understood. In this study, we investigated the effects of toll-like receptor 2 (TLR2) signals on iNOS/nitric oxide (NO) responses after C. sinensis infection. We also evaluated the correlations between iNOS responses and worm development, which are possibly regulated by TLR2 signal.MethodsTLR2 wild-type and mutant C57BL/6 J mice were infected with 60 C. sinensis metacercariae, and the samples were collected at 30, 60, 90 and 120 days post-infection (dpi). The total serum NO levels were detected using Griess reagent after nitrate was reduced to nitrite. Hepatic tissue samples from the infected mice were sliced and stained with hematoxylin and eosin (HE) to observe worm development in the intrahepatic bile ducts. The iNOS mRNA transcripts in the splenocytes were examined by real time reverse transcriptase polymerase chain reaction (qRT-PCR), and iNOS expression was detected by immunohistochemistry.ResultsDeveloping C. sinensis juvenile worms were more abundant in the intrahepatic bile ducts of TLR2 mutant mice than those of TLR2 wild-type mice. However, no eggs were found in the faeces of both mice samples. The serum levels of total NO significantly increased in TLR2 mutant mice infected with C. sinensis at 30 (t(5) = 2.595, P = 0.049), 60 (t(5) = 7.838, P = 0.001) and 90 dpi (t(5) = 3.032, P = 0.029). Meanwhile, no changes occurred in TLR2 wild-type mice compared with uninfected controls during the experiment. The iNOS expression in splenocytes showed unexpected higher background levels in TLR2 mutant mice than those in TLR2 wild-type mice. Furthermore, the iNOS mRNA transcripts in splenocytes were significantly increased in the TLR2 wild-type mice infected with C. sinensis at 30 (t(5) = 5.139, P = 0.004), 60 (t(5) = 6.138, P = 0.002) and 90 dpi (t(5) = 6.332, P = 0.001). However, the rising of iNOS transcripts dropped under the uninfected control level in the TLR2 mutant mice at 120 dpi (t(5) = -9.082, P < 0.0001). Both total NO and iNOS transcripts were significantly higher in the TLR2 mutant mice than those in the TLR2 wild-type mice at 30 (t(5) = 3.091/2.933, P = 0.027/0.033) and 60 dpi (t(5) = 2.667/6.331, P = 0.044/0.001), respectively. In addition, the remarkable increase of iNOS expressions was immunohistochemically detected in the splenic serial sections of TLR2 wild-type mice at 30 and 60 dpi. However, the expressions of iNOS were remarkably decreased in the splenocytes of both TLR2 wild-type and mutant mice at 120 dpi.ConclusionsThese results demonstrate that TLR2 signal plays an important role in the regulation of iNOS expression after C. sinensis infection. TLR2 signal is also beneficial to limiting worm growth and development and contributing to the susceptibility to C. sinensis in which the iNOS/NO reactions possibly participate.

Salient motion detection using proximal robust principal component analysis method

The recently proposed robust principal component analysis (RPCA) theory and its derived methods have attracted much attention in many computer vision and machine intelligence applications. From a wide view of these methods, independent motion objects are modeled as pixel-wised sparse or structurally sparse outliers from a highly correlated background signal, and all these methods are implemented under an l1 -penalized optimization. Real data experiments reveal that even if l1-penalty is convex, the optimization sometimes cannot be satisfactorily solved, especially when the signal-to-noise ratio is relatively high. In addition, the unexpected background motion (e.g., periodic or stochastic motion) may also be included. We propose a moving object detection method based on a proximal RPCA along with saliency detection. Convex penalties including low-rank and sparse regularizations are substituted with proximal norms to achieve robust regression. After the foreground candidates have been extracted, a motion saliency map using spatiotemporal filtering is constructed. The foreground objects are then filtered out by dynamically adjusting the penalty parameter according to the corresponding saliency values. Evaluations on challenging video clips and qualitative and quantitative comparisons with several state-of-the-art methods demonstrate that the proposed approach works efficiently and robustly.

In-beam test of the Boron-10 Multi-Grid neutron detector at the IN6 time-of-flight spectrometer at the ILL

A neutron detector concept based on solid layers of boron carbide enriched in 10B has been in development for the last few years as an alternative for 3He by collaboration between the ILL, ESS and Linköping University. This Multi-Grid detector uses layers of aluminum substrates coated with 10B4C on both sides that are traversed by the incoming neutrons. Detection is achieved using a gas counter readout principle. By segmenting the substrate and using multiple anode wires, the detector is made inherently position sensitive. This development is aimed primarily at neutron scattering instruments with large detector areas, such as time-of-flight chopper spectrometers. The most recent prototype has been built to be interchangeable with the 3He detectors of IN6 at ILL. The 10B detector has an active area of 32 x 48cm2. It was installed at the IN6 instrument and operated for several weeks, collecting data in parallel with the regularly scheduled experiments, thus providing the first side-by-side comparison with the conventional 3He detectors. Results include an efficiency comparison, assessment of the in-detector scattering contribution, sensitivity to gamma-rays and the signal-to-noise ratio in time-of-flight spectra. The good expected performance has been confirmed with the exception of an unexpected background count rate. This has been identified as natural alpha activity in aluminum. New convertor substrates are under study to eliminate this source of background.

Music to Your Brain: Background Music Changes Are Processed First, Reducing Ad Message Recall

ABSTRACTBackground music captures attention, evokes images, and creates ambience, but may interfere with processing of advertised messages, reducing recall. Brains are hardwired to process unexpected background sound changes first, automatically preempting processing of brand message elements and reducing recall. The degree of this recall reduction depends on the structural characteristics of the music, as well as the advertised brand. Backgrounds with more frequent harmonic and textural changes create more frequent distraction, reducing message recall. Faster tempos increase the frequency of those distractions. However, faster tempos also enable streaming of like distractions, improving message recall. In Experiment 1, backgrounds, varying in harmonic, textural, and temporal characteristics, were compared across ads for six brands. Message recall was higher for ads with backgrounds with less‐frequent change. Message recall from ads for new, unfamiliar brands suffered more from background music interference than from ads for established brands. In Experiment 2, background change frequency was reduced in two ads, holding all else constant, which improved message recall.

Proposed experiment to measure γ-rays in high resolution experiment [formula omitted] and [formula omitted], and the γ-ray production in ν–16O interaction

The γ-ray production in neutral-current neutrino-oxygen interaction is very important to neutrino experiment using water target, since those γ-rays can produce extra signals or unexpected background in the energy region from 5 to 30 MeV. We propose to measure γ-rays in O16(p,p′) and O16(He3,t) reactions at Reseach Center for Nuclear Physics.

Acute Coronary Syndrome With Unexpected Background: Rupture of Left Valsalva Sinus Aneurysm

Acute Coronary Syndrome With Unexpected Background: Rupture of Left Valsalva Sinus Aneurysm

Spontaneous light emission from fibers in MINOS

We report on the observation and measurements of unexpected background rates in the MINOS Far Detector. The noise level at the Far Detector is significantly greater than that expected from natural radioactivity and intrinsic photomultiplier dark current. We have conducted a series of additional tests which demonstrate that the excess rate is caused by spontaneous light emission in the wavelength-shifting fibers, which are used to read out signals from scintillator strips. This noise due to fibers exhibits an exponential fall off with time with a decay time constant of the order of 100 days.

Anti-biotin Antibodies Offer Superior Organelle-specific Labeling of Mitochondria over Avidin or Streptavidin

The mitochondrial matrix contains endogenously biotinylated proteins. These proteins can cause unexpected background signal when biotin-avidin- or biotin-streptavidin-based detection systems are used in immunocytochemistry. Here we show that this reactivity can be deliberately exploited, using a simple anti-biotin reagent, to obtain strong and highly specific labeling of mitochondria by both light and electron microscopy. The signal is substantially stronger than when either avidin or streptavidin is used to detect the endogenous biotin. These results confirm the accessibility of protein-bound endogenous biotin to exogenous probes, and localize the biotinylated enzymes to the mitochondrial matrix.

Physical consequences of mass singularities

We argue that the perturbation expansion of massless field theories are uniquely and unambiguously defined for properly formed observables. In so doing, we generalize the Kinoshita-Lee-Nauenberg theorem to show that there are no observable “mass-shell anomalies”. Paradoxically, in realistic circumstances, massive electrons give rise to non-intuitive, enhanced effects, for example, an unexpected background to the search for right-handed charged currents at HERA.

Q→ qZ decays at Tevatron and SSC energies

The possible existence of a new heavy quark Q that decays predominantly viathe flavor changing neutral current transition Q→ qZ is discussed. Candidates include a fourth generation charge — 1 3 quark, or a more exotic vector-like quark. Such particles are interesting both as extensions of the standard model and due to their unique decay modes. The primary experimental indication of the pair production and subsequent decay of such quarks is ZZ pair production at an essentially strong interaction rate. This mode can then constitute an unexpected background to the searches for other particles. In particular the channel Q Q→ZZ+X can generate a serious background to the search for the Higgs boson via the H 0→ ZZ mode at the SSC. Thus it is essential to search for such new heavy quarks at the Tevatron. Possible detection signatures for this purpose are discussed.

Suppression of unexpected recombinant background in λEMBL3 cloning

Suppression of unexpected recombinant background in λEMBL3 cloning