Cross-correlation Values Research Articles

Performance of orthogonal stochastic code signals in the presence of delayed interference

This article provides analytical expressions for performance evaluation of hybrid FH-DSSS system in delayed interference and fluctuation noise presence. Delayed interference is quite common in environment with multiple obstacles, occurring as consequence of signal reflection and multipath propagation (fig. 1). Introduction describes known methods of mitigating this interference many of whom include either use of direct sequence spreading or some variation on hybrid sequence spreading including pseudo random frequency hopping and periodical signal ensemble change. To improve on those methods considered dynamic program method for orthogonal stochastic spread spectrum code generation based on Viterby algorithm [6]. Section 1 of the paper describes FH-DSSS signal, it’s delayed interference, equation corresponding to their sum on the receiver input and noncoherent correlator response to it. By using Gaussian approximation, expressions derived for equivalent signal/noise level estimation and corresponding average probability of error at the output of the correlation receiver. By including actual signal statistic, like code length and cross-correlation value, final expressions (8)–(15) allow for accurate estimation of correlation receiver response to signal sequences with specific spread spectrum codes, as well as calculation for probability of error for M-ary spread spectrum communication system in delayed interference presence. Accuracy of the Gaussian approximation is examined in section 2 of the paper based on comparisons between analytical results and simulation modeling. Numerical results obtained, which showcase dependence of system performance on various signal characteristics, such as correlation properties, spreading code length, signal ensemble size and frequency hop delay time. Plotted graph on fig. 2 shows advantage from using M-ary orthogonal signals over binary in delayed interference presence for code sequences with length N = 32, 64, 128. Graph on fig. 3 shows gains from frequency hopping when interference delay equals to approximately half of signal information symbol. In the end performance gains from using hybrid FH-DSSS system under electronic suppression by delayed interference is also evaluated. As shown on fig. 4,a system performance significaly depend on value of delay between received signal and it’s delayed copy.

Study of high-frequency acoustic current tomography

<p indent="0mm">The sea-land interface is the most concentrated region of human marine development activities, and online monitoring of river current is very important for material flux and ecosystem evolution. In this study, the high-frequency acoustic current tomography of sea-land interface was studied. Based on the principle of acoustic reciprocity, the acoustic inversion algorithm of current was investigated. The experiment was carried out on the Jiulongjiang sea-land interface in Zhangzhou. The high-frequency transducer, with a center frequency of <sc>60 kHz</sc> and bandwidth of <sc>40–80 kHz,</sc> was used. According to the sound speed profile and underwater topographic survey, ray acoustic simulation was performed to reveal high-frequency sound propagation. The experimental results showed that the acoustic signal has high-signal amplitude and peak value of cross-correlation, which can be used to reconstruct the current of the river. Real-time monitoring of the river current during the typhoon “haibeisi” was achieved. The results showed that high-frequency acoustic tomography can be applied to the study of hydrodynamics of sea-land interface, hydrological measurement, and monitoring of extreme events, such as flood peak and heavy rainfall.

Principal component analysis in the modeling of HILDCAAs during the Solar Minimum of Cycle 23/24

In this article, we propose a new approach to model the high-intensity, long-duration, continuous AE (Auroral Electrojet) activity (HILDCAA) by relaxing one of the criteria originally designed, based on the interplanetary features during the unusual Solar Minimum of Cycle 23/24 (SMC23/24). This relaxation does not intend to suppress or modify the original HILDCAAs’ conception, but propose a new view of the same phenomena by enlarging the sample of events, which in turn may improve space weather monitoring and prediction programs. To assess and classify the Alfvénity associated with HILDCAAs, the values of 4h-Windowed Pearson Cross-Correlation (4WPCC) between the IMF components and the solar wind speed components observed in situ at the Lagrangian point L1 (1 AU) were evaluated. The principal component analysis (PCA) was performed on the dataset and, from the first three principal components, which represent ~65% of the accumulative percent variance, we applied principal component regression (PCR) in each of the following parameters: the AE index, the Interplanetary Magnetic Field (IMF) components, the plasma density, the solar wind speed, the temperature, the IMF magnitude, and the SYM-H geomagnetic index. Furthermore, we applied Multiple Linear Regression (MLR) to establish a linear model to express the AE index in terms of the PCR-based model parameters. The AE MLR-based model demonstrated to hold a prognosis potential for HILDCAAs. Despite that, this model is only suitable for the SMC23/24. In this sense, this model might be implemented a real-time analysis for short-term HILDCAA prognosis in the near future.

A portable device with low-power consumption for monitoring mouse vital signs during in vivo photoacoustic imaging and photothermal therapy

Objective: The aim of this study was to monitor the physiological changes and cytotoxic effects of exogenous contrast agents during photoacoustic imaging (PAI) and photothermal therapy (PTT). In this paper, a low-power telemetric device for mouse vital signs monitoring was designed and demonstrated. Approach: The power consumption was optimized through hardware and software co-design with a 17% increased operating time compared with typical operation. To demonstrate the feasibility of the monitoring device, PAI and PTT experiments with chitosan-polypyrrole nanocomposites (CS-PPy NCs) as exogenous contrast agents were conducted. Herein, the physiological variation in groups of mice with different CS-PPy NC concentrations was observed and analyzed. Main results: The experimental results indicated the influence of CS-PPy NCs and anesthesia on mouse vital signs in PAI and PTT. Additionally, the association between core temperature, heart rate, and saturation of peripheral oxygen (SpO2) during PAI and PTT was shown. The strong near-infrared absorbance of exogenous contrast agents could account for the increase in mouse core temperature and tumor temperature in this study. Furthermore, high cross-correlation values between core temperature, heart rate, and SpO2 were demonstrated to explain the fluctuation of mouse vital signs during PAI and PTT. Significance: A design of a vital signs monitoring device, with low power consumption, was introduced in this study. A high cross correlation coefficient of mouse vital signs and the effects of CS-PPy NCs were observed, which explained the mouse physiological variation during the PAI and PTT experiments.

Seismo-Acoustic Characterization of Mount Cleveland Volcano Explosions

Volcanic explosions can produce large, ash-rich plumes that pose great hazard to aviation, yet may often have few precursory geophysical signals. Mount Cleveland is one of the most active volcanoes in the Aleutian Arc, Alaska (United States) with at least 65 explosions between December 2011 and June 2020. We characterize the seismo-acoustic signals from explosions at Mount Cleveland over a period of 4 years starting in 2014 when the permanent local instrumentation was installed. While the seismic explosion signals are similar, the acoustic signals vary between explosions. Some explosion acoustic waveforms exhibit a single main compressional phase while other waveforms have multiple compressions. The time lag between seismic and acoustic arrivals varies considerably (up to 2.20 s) at a single station ∼3 km from the vent, suggesting a change in propagation path for the signals between explosions. We apply a variety of methods to explore the potential contributions to this variable time lag from atmospheric conditions, nonlinear propagation, and source depth within the conduit. This variable time lag has been observed elsewhere, but explanations are often unresolved. Our results indicate that while changes in atmospheric conditions can explain some of the variation in acoustic arrival time relative to the seismic signal arrivals, substantial residual time lag variations often still exist. Additionally, nonlinear propagation modeling results do not yield a change in the onset time of the acoustic arrival with source amplitudes comparable to (and larger) than Cleveland explosions. We find that a spectrum of seismic cross-correlation values between events and particle motion dip angles suggests that a varying explosion source depth within the conduit likely plays a dominant role in the observed variations in time lag. Explosion source depths appear to range from very shallow depths down to ∼1.5–2 km. Understanding the seismo-acoustic time lag and the subsequent indication of a variable explosion source depth may help inform explosion source modeling for Mount Cleveland, which remains poorly understood. We show that even with a single co-located seismic and acoustic sensor that does not always remain on scale, it is possible to provide meaningful interpretations of the explosion source depth which may help monitoring agencies understand the volcanic system.

Investigation of surface pressures on CAARC tall building concerning effects of turbulence

This paper presents an experimental investigation on the surface pressures on the CAARC standard tall building model concerning the effects of freestream turbulence. Two groups of incidence turbulence are generated in the wind tunnel experiment. The first group has an approximately constant turbulence intensity of 10.3% but different turbulence integral scale varying from 0.141 m to 0.599 m or from 0.93 to 5.88 in terms of scale ratio (turbulence integral scale to building dimension). The second group presents similar turbulence integral scale but different turbulence intensity ranging from 7.2% to 13.5%. The experimental results show that the mean pressure coefficients on about half of the axial length of the side faces near the leading edge slightly decrease as the turbulence integral scale ratio that is larger than 4.25 increases, but respond markedly to the changes in turbulence intensity. The root-mean-square (RMS) and peak pressure coefficients depend on both turbulence integral scale and intensity. The RMS pressure coefficients increase with turbulence integral scale and intensity. As the turbulence integral scale increases from 0.141 m to 0.599 m, the mean peak pressure coefficient increases by 7%, 20% and 32% at most on the windward, side faces and leeward of the building model, respectively. As the turbulence intensity increases from 7.2% to 13.5%, the mean value of peak pressure coefficient increases by 47%, 69% and 23% at most on windward, side faces and leeward, respectively. The values of cross-correlations of fluctuating pressures increase as the turbulence integral scale increases, but decrease as turbulence intensity increases in most cases.

A Spatial Near-Field Clutter Reduction Filter Preserving Tissue Speckle in Echocardiography.

Near-field (NF) clutter in echocardiography is depicted as a diffuse haze hindering the visualization of the myocardium and the blood-pool, thereby degrading its diagnostic value. Several clutter filters have been developed, which are limited in patients with contraction motion and rhythm anomalies, and in 3-D ultrasound (US). This study introduces a new NF clutter reduction method, which preserves US speckles required for strain imaging. The filter developed detects the NF clutter region in the spatial frequency domain. The filter employs an oriented, multiscale approach, and assumes the NF clutter to be predominantly present in the highest and lowest bandpass images. These bandpass images were filtered, whilst sparing features in the myocardium and NF clutter-free regions. The performance of the filter was assessed in a volunteer study, in ten 3-D apical and parasternal view acquisitions, and in a retrospective clinical study composed of 20 cardiac patients with different indications for echocardiography. The filter reduced NF clutter in all data sets, whilst preserving all or most of the myocardium. Additionally, it demonstrated a consistent enhancement of image quality, with an increase in contrast of 4.3 dB on average, and generated a clearer myocardial boundary distinction. Furthermore, the speckles were preserved according to the quality index based on local variance, the structural similarity index method, and normalized cross correlation values, being 0.82, 0.92, and 0.95 on average, respectively. Global longitudinal strain measurements on NF clutter reduced images were improved or equivalent compared to the original acquisitions, with an average increase in strain signal-to-noise ratio of 34%.

Scatterometer and Intensity Distribution Meter With Screen Image Synthesis

A screen image synthesis (SIS) system is superior than the conventional methods in terms of high-speed measurement and low screen-cross-talk noise when used as a whole-field light-distribution meter. However, reflection signals cannot be measured using the conventional SIS system when it is used as a scattering meter. Furthermore, the conventional SIS system cannot be used to measure a large sample when it is used as an intensity distribution meter. In this study, we devised a rail-based SIS system as long as an image reconstruction algorithm. This would allow whole-field scattering light and intensity distribution measurements for various sample sizes. For this purpose, a versatile instrument was assembled by combining a whole-field intensity distribution meter and a whole-field scattering meter. The results of the experiments confirmed that the measuring time was drastically improved when the proposed instrument was used as a whole-field intensity distribution meter and a whole-field scattering meter. The high normalized cross correlation values of both measurements demonstrated the accuracy and feasibility of the proposed algorithm.

Flow and Frequency Characterization of the Synchronized Stacked Sweeping Jets

This work characterizes a pair of feedback-type fluidic oscillators in a stacked arrangement. Quasi-rectangular synchronization channels were used to connect both feedback channels of each oscillator; thus communication between fluidic oscillators was established. Synchronization through these channels provided strong cross-correlation values () obtained with hot-wire probes for a total flow rate range of 10–30 standard liters per minute. The oscillation frequencies were varied from 263 to 672 Hz for a Reynolds number range from 5660 to 17,000, respectively. The resultant sweeping jets were also observed through water flow visualizations. Details of the internal flowfield leading to synchronized behavior were extracted employing numerical simulations that were validated with the frequency measurements. It was determined that the feedback flow in feedback channels occurs simultaneously in a periodic manner, and thus jet switching inside each oscillator is synchronized. It was also observed that a pair of strong recirculation zone forms for every period inside both synchronization channels, and this zone plays a major role in balancing the momentum in the feedback channels, thus creating simultaneous feedback flow. The overall switching mechanism of the fluidic oscillators seems to be intact, whereas the pair found to act as a single dynamic system.

The Effects of Assumed Source Depth and Shear-Wave Velocity on Moment Tensors Estimated for Small, Contained Chemical Explosions in Granite

ABSTRACTThe Source Phenomenology Experiment (SPE-Arizona) included of a series of chemical explosions detonated within a copper mine in Arizona. This study focuses on ground motions from detonations in the copper mine, which are analyzed to assess the uniqueness of the resulting source representation when the source region propagation characteristics have a range of possible models. P-wave velocities are well constrained by refraction data with less constraint of the S-wave velocities. The effects of explosion source depth and VS are assessed with Green’s functions for a range of models in which VP is held constant. Propagation models with a Poisson’s value of 0.25 and a source depth 30–60 m most accurately replicate the data. The explosion was detonated at a centroid depth of 30 m, so trade-offs in depth are demonstrated. The compensated linear vector dipole and explosion components of the Green’s functions convolved with a Mueller–Murphy source function are compared. Both produce significant energy in the 2–12 Hz band, due to surface-wave contributions with no clear depth dependencies above 20 Hz. The range of propagation models is used with the observational data to invert for the frequency-domain moment tensor. Fits to the data from these inversions have cross-correlation values of 0.64, demonstrating effectiveness in replicating the observations with the assumed propagation path effects and resulting source function. Inversions produce horizontal dipoles (Mxx and Myy), roughly half the maximum amplitude of Mzz, consistent with a compensated linear vector dipole source, which is frequency dependent. Denny and Johnson, Mueller–Murphy, Walter and Ford, and the revised Mueller–Murphy source models, parameterized for granite, are compared to the moment tensors. Despite a nonisotropic moment tensor source, the revised Mueller–Murphy isotropic source model best replicates the long-period moments, overshoot, and corner frequency.

Directed correlation network of concepts determined by the dynamics of publications

A technique for forming, clustering and visualizing so-called directed correlation networks is herein proposed. The links between nodes of such networks correspond to the values of cross-correlations between vectors - sets of parameters corresponding to these nodes modified in a certain way. To build network structures for each node (topic), vectors are formed - arrays of numbers corresponding to a certain time series. As an example, the article considers a time series generated by the Google Books Ngram Viewer service. This approach, unlike the existing one, has advantages such as intuitive and realistic rules, the definition of the weight of nodes and links, a reliable mathematical basis for correlation analysis, an accounting of previously unused parameters of time series of publications corresponding to entities, allowing one to the group said entities according to their trends in time, and objectivity and relative simplicity. This technique can be based on data obtained, for example, from content monitoring systems, and can be used in analytical systems for various purposes in order to generalize a set of variables without explicit links between them.

Repeating Earthquakes Along the Colombian Subduction Zone

Colombia is tectonically active, and several large earthquakes have ruptured the Colombia-Ecuador subduction zone (CESZ) during the last century. Among them, the Colombia-Ecuador earthquake in 1906 (Mw8.4) and the Tumaco earthquake in 1979 (Mw8.3) generated destructive tsunamis. Therefore, it is important to characterize the seismic rupture processes and their relation with interplate coupling along the CESZ. We searched for repeating earthquakes by performing waveform similarity analysis. Cross correlation (CC) values were computed between earthquake pairs with hypocenter differences of less than 50 km that were located in the northern CESZ (1°–4°N) and that occurred from June 1993 to February 2018. We used broadband and short-period seismic waveform data from the Servicio Geológico Colombiano (SGC) seismic network. A CC threshold value of 0.90 was used to identify the waveform similarity and select repeating earthquakes. We found repeating earthquakes distributed near the trench and the coast. Our estimated repeating earthquakes near the trench suggest that the interplate coupling in this region is low. This is in clear constrast to the occurrence of a large slip in the 1906 Colombia-Ecuador earthquake along the trench in the southern part of the CESZ, and suggests that rupture modes are different between the northern and southern parts of CESZ near the trench.

Automatic arterial input function selection in CT and MR perfusion datasets using deep convolutional neural networks.

The computation of perfusion parameter images requires knowledge of the arterial blood flow in the form of an arterial input function (AIF). This work proposes a novel method to automatically identify AIFs in computed tomography perfusion (CTP) and dynamic susceptibility contrast perfusion-weighted MRI (PWI) datasets using a deep convolutional neural network (CNN). One-hundred CTP and 100 PWI datasets of acute ischemic stroke patients were available for model development and evaluation. For each modality, 50 datasets were used for CNN training and 20 for validation using manually selected AIFs and non-arterial tissue concentration time curves. Model evaluation was performed using the remaining 30 independent validation datasets from each modality with manual AIF selections provided by two experts as ground truth. Additionally, AIFs were also extracted using an established automatic shape-based algorithm for comparison purposes. The extracted AIFs were compared using normalized cross-correlation and shape features as well as using the Dice similarity metric and volume of the corresponding hypoperfusion (Tmax>6s) lesions. The cross-correlation values comparing the manual AIFs and those extracted by the proposed CNN method were significantly greater than those comparing the manual AIFs to the shape-based comparison method. Likewise, hypoperfusion lesions generated using the manually selected AIFs and CNN-based AIFs showed higher Dice values compared to hypoperfusion lesions generated using the comparison AIF extraction method. Shape features for AIFs generated by the proposed method did not differ significantly from the manual AIFs, with the exception that the CNN-derived AIFs for the PWI datasets showed marginally greater peak heights. Deep convolutional neural network models are viable for the automatic extraction of the AIF from CTP and PWI datasets.

Image Watermarking Using All Phase Discrete Cosine Biorthogonal Transform in Selected Pixel Blocks

In the past decade, a transform called all phase discrete cosine biorthogonal transform (APDCBT) appeared in the field of digital image processing. It is mainly used to solve the negativity found in discrete cosine transform (DCT), especially in a low bit rate. In this paper, the APDCBT is employed for watermark insertion based on selected regions of an image. The insertion is depending on the homogeneity of each part of the image. To determine the extent of homogeneity, there are two criteria: Mean and standard deviation are applied for the intensity of the image. Medium frequency bands of APDCBT in image pixel blocks are used to hold the embedded watermark. Then, the transform is inversed to obtain the resultant watermarked image. The robustness of APDCBT against watermark removal attacks is tested and the experimental results showed the superiority of the APDCBT over traditional DCT in the watermark embedding system. More specifically, when the LSB reset attack applied. For instance, when the contrast adjustment attack applied, the average of normalized cross-correlation (NCC) values of extracted watermark images with the original watermark, it was 0.992 for the proposed method. This is a promised result, if it is compared with the NCC of the DCT method, which was 0.423. The proposed method can be used for copyright protection purpose.

Learning to localize sounds in a highly reverberant environment: Machine-learning tracking of dolphin whistle-like sounds in a pool.

Tracking the origin of propagating wave signals in an environment with complex reflective surfaces is, in its full generality, a nearly intractable problem which has engendered multiple domain-specific literatures. We posit that, if the environment and sensor geometries are fixed, machine learning algorithms can "learn" the acoustical geometry of the environment and accurately track signal origin. In this paper, we propose the first machine-learning-based approach to identifying the source locations of semi-stationary, tonal, dolphin-whistle-like sounds in a highly reverberant space, specifically a half-cylindrical dolphin pool. Our algorithm works by supplying a learning network with an overabundance of location "clues", which are then selected under supervised training for their ability to discriminate source location in this particular environment. More specifically, we deliver estimated time-difference-of-arrivals (TDOA's) and normalized cross-correlation values computed from pairs of hydrophone signals to a random forest model for high-feature-volume classification and feature selection, and subsequently deliver the selected features into linear discriminant analysis, linear and quadratic Support Vector Machine (SVM), and Gaussian process models. Based on data from 14 sound source locations and 16 hydrophones, our classification models yielded perfect accuracy at predicting novel sound source locations. Our regression models yielded better accuracy than the established Steered-Response Power (SRP) method when all training data were used, and comparable accuracy along the pool surface when deprived of training data at testing sites; our methods additionally boast improved computation time and the potential for superior localization accuracy in all dimensions with more training data. Because of the generality of our method we argue it may be useful in a much wider variety of contexts.

A Nonproprietary Movement Analysis System (MoJoXlab) Based on Wearable Inertial Measurement Units Applicable to Healthy Participants and Those With Anterior Cruciate Ligament Reconstruction Across a Range of Complex Tasks: Validation Study.

BackgroundMovement analysis in a clinical setting is frequently restricted to observational methods to inform clinical decision making, which has limited accuracy. Fixed-site, optical, expensive movement analysis laboratories provide gold standard kinematic measurements; however, they are rarely accessed for routine clinical use. Wearable inertial measurement units (IMUs) have been demonstrated as comparable, inexpensive, and portable movement analysis toolkits. MoJoXlab has therefore been developed to work with generic wearable IMUs. However, before using MoJoXlab in clinical practice, there is a need to establish its validity in participants with and without knee conditions across a range of tasks with varying complexity.ObjectiveThis paper aimed to present the validation of MoJoXlab software for using generic wearable IMUs for calculating hip, knee, and ankle joint angle measurements in the sagittal, frontal, and transverse planes for walking, squatting, and jumping in healthy participants and those with anterior cruciate ligament (ACL) reconstruction.MethodsMovement data were collected from 27 healthy participants and 20 participants with ACL reconstruction. In each case, the participants wore seven MTw2 IMUs (Xsens Technologies) to monitor their movement in walking, jumping, and squatting tasks. The hip, knee, and ankle joint angles were calculated in the sagittal, frontal, and transverse planes using two different software packages: Xsens’ validated proprietary MVN Analyze and MoJoXlab. The results were validated by comparing the generated waveforms, cross-correlation (CC), and normalized root mean square error (NRMSE) values.ResultsAcross all joints and activities, for data of both healthy and ACL reconstruction participants, the CC and NRMSE values for the sagittal plane are 0.99 (SD 0.01) and 0.042 (SD 0.025); 0.88 (SD 0.048) and 0.18 (SD 0.078) for the frontal plane; and 0.85 (SD 0.027) and 0.23 (SD 0.065) for the transverse plane (hip and knee joints only). On comparing the results from the two different software systems, the sagittal plane was very highly correlated, with frontal and transverse planes showing strong correlation.ConclusionsThis study demonstrates that nonproprietary software such as MoJoXlab can accurately calculate joint angles for movement analysis applications comparable with proprietary software for walking, squatting, and jumping in healthy individuals and those following ACL reconstruction. MoJoXlab can be used with generic wearable IMUs that can provide clinicians accurate objective data when assessing patients’ movement, even when changes are too small to be observed visually. The availability of easy-to-setup, nonproprietary software for calibration, data collection, and joint angle calculation has the potential to increase the adoption of wearable IMU sensors in clinical practice, as well as in free living conditions, and may provide wider access to accurate, objective assessment of patients’ progress over time.

An inertial measurement unit tracking system for body movement in comparison with optical tracking.

The recent advancement of motion tracking technology offers better treatment tools for conditions, such as movement disorders, as the outcome of the rehabilitation could be quantitatively defined. The accurate and fast angular information output of the inertial measurement unit tracking systems enables the collection of accurate kinematic data for clinical assessment. This article presents a study of a low-cost microelectromechanical system inertial measurement unit-based tracking system in comparison with the conventional optical tracking system. The system consists of seven microelectromechanical system inertial measurement units, which could be mounted on the lower limbs of the subjects. For the feasibility test, 10 human participants were instructed to perform three different motions: walking, running, and fencing lunges when wearing specially designed sleeves. The subjects' lower body movements were tracked using our inertial measurement unit-based system and compared with the gold standard-the NDI Polaris Vega optical tracking system. The results of the angular comparison between the inertial measurement unit and the NDI Polaris Vega optical tracking system were as follows: the average cross-correlation value was 0.85, the mean difference of joint angles was 2.00°, and the standard deviation of joint angles was ± 2.65°. The developed microelectromechanical system-based tracking system provides an alternative low-cost solution to track joint movement. Moreover, it is able to operate on an Android platform and could potentially be used to assist outdoor or home-based rehabilitation.

Interplane bulk motion analysis and removal based on normalized cross-correlation in optical coherence tomography angiography.

Bulk motion seriously degrades the image quality of optical coherence tomography angiography (OCTA). Conventional correction methods focus on in-plane displacement, while the bulk motion component perpendicular to B-scans also introduces noise. This work first presents an evaluation of this component using a specific scan protocol and an approximate expression derived from peak-normalized cross-correlation values, and then quantitatively assesses how interplane bulk motion noise reduce the sensitivity of cross-sectional angiograms. Finally, we developed a repetitive bulk motion correction method based on the estimated displacements and redundant volume scans. The correction does not require registration and angiogram reconstruction of low flow sensitivity frames, and the results of in vivo mice skin OCTA imaging experiments show that the proposed method can effectively reduce bulk motion noise caused by cardiac and respiratory motion and occasional shaking, and improve OCTA image quality, which has practical significance for clinical OCTA diagnosis and analysis.

Modeling and prediction of dengue occurrences in Kolkata, India, based on climate factors.

Dengue is one of the most serious vector-borne infectious diseases in India, particularly in Kolkata and its neighbouring districts. Dengue viruses have infected several citizens of Kolkata since 2012 and it is amplifying every year. It has been derived from earlier studies that certain meteorological variables and climate change play a significant role in the spread and amplification of dengue infections in different parts of the globe. In this study, our primary objective is to identify the relative contribution of the putative drivers responsible for dengue occurrences in Kolkata and project dengue incidences with respect to the future climate change. The regression model was developed using maximum temperature, minimum temperature, relative humidity and rainfall as key meteorological factors on the basis of statistically significant cross-correlation coefficient values to predict dengue cases. Finally, climate variables from the Coordinated Regional Climate Downscaling Experiment (CORDEX) for South Asia region were input into the statistical model to project the occurrences of dengue infections under different climate scenarios such as Representative Concentration Pathways (RCP4.5 and RCP8.5). It has been estimated that from 2020 to 2100, dengue cases will be higher from September to November with more cases in RCP8.5 (872 cases per year) than RCP4.5 (531 cases per year). The present research further concludes that from December to February, RCP8.5 leads to suitable warmer weather conditions essential for the survival and multiplication of dengue pathogens resulting more than two times dengue cases in RCP8.5 than in RCP4.5. Furthermore, the results obtained will be useful in developing early warning systems and provide important evidence for dengue control policy-making and public health intervention.

Current cross-correlations and waiting time distributions in Andreev transport through Cooper pair splitters based on a triple quantum dot system

We study the spin-resolved subgap transport in a triple quantum-dot system coupled to one superconducting and two ferromagnetic leads. We examine the Andreev processes in the parallel and antiparallel alignments of ferromagnets magnetic moments in both the linear and nonlinear response regimes. The emphasis is put on the analysis of the current cross-correlations between the currents flowing through the left and right arms of the device and relevant electron waiting time distributions. We show that both quantities can give an important insight into the subgap transport processes and their analysis can help optimizing the system parameters for achieving the considerable Andreev current and efficient Cooper pair splitting. Strong positive values of cross-correlations are associated with the presence of tunneling processes enhancing the Cooper pair splitting efficiency, while short waiting times for electrons tunneling through distinct ferromagnetic contacts indicate fast splitting of emitted Cooper pairs. In particular, we study two detuning schemes and show that antisymmetric shift of side quantum dots energy levels is favorable for efficient Cooper pair splitting. The analysis of spin-resolved waiting time distributions supports the performance enhancement due to the presence of ferromagnetic contacts, which is in particular revealed for short times. Finally, we consider the effect of changing the inter-dot hopping amplitude and predict that strong inter-dot correlations lead to a reduction of Andreev transport properties in low-bias limit.