Set Of Signals Research Articles

Research on comprehensive and effective acoustic signal processing methods for caculating downhole liquid level depth

When the acoustic method is used to measure oil well dynamic liquid level data, the collected signal will be affected by complex background noise, which makes the position of the tubing coupling echo and the liquid level echo easily submerged in the noise and difficult to identify. Therefore, this paper proposes an estimation method of downhole dynamic liquid level depth that integrates four kinds of signal processing methods. Firstly, Butterworth low-pass filter (BLPF) is used to filter the tubing coupling echo, so as to smooth the signal. Secondly, the average amplitude difference function (AMDF) is used to identify the average periodic sampling points of the tubing coupling echo, so as to calculate the propagation speed of acoustic wave in the oil well. On this basis, the liquid level echo is filtered by wavelet denoising (WD), and then the wavelet singular value detection (WSVD) is used to detect the position of the liquid level reflected wave, so as to calculate the propagation time of the acoustic wave in the oil well. Finally, the depth of oil well liquid level is calculated according to the speed and time of acoustic wave propagation theory. The stability and effectiveness of the proposed method under different sound velocities and different well depths are verified by testing multiple sets of acoustic signals obtained in the laboratory and field. Compared with other existing signal processing methods, the average relative error of the proposed method is about 0.18%. Therefore, the methods can meet the actual engineering needs.

Concurrent Optimization of Cycle Length, Green Splits, and Offsets for the Diverging Diamond Interchange

Diverging diamond interchange (DDI) has received increased attention from the traffic community for its efficiency in reducing delays for vehicles at on- and off-ramps. The conflicting through movements between a DDI’s two crossover intersections mean that its signal plan must concurrently consider the progression for all critical paths to ensure overall efficiency. In light of DDI’s unique geometric features, the design of its signal plans typically starts with the cycle length and green splits for its two crossover intersections, and then employs available progression models to produce the optimal offsets for those critical paths. Such a two-stage design methodology, however, often cannot yield system-wide optimal results because the optimal progression bandwidth and signal settings are interdependent. Moreover, inefficient coordination between its two crossover intersections may cause excessive queues on the DDI’s bridge segment. This paper therefore presents a mixed-integer linear programming (MILP) model that can concurrently optimize the cycle length, green splits, and offsets for a DDI’s two crossover intersections under the given traffic patterns and geometric constraints such as the link length. The results of extensive numerical analyses with a real-world DDI have confirmed the effectiveness of the proposed model and its robustness in response to demand fluctuation.

A coumarin-based fluorescent probe: Small but multi-signal

There remains a challenge for elegantly designing structurally simple but multi-signal fluorescence probes to visualize simultaneously various intracellular redox species and microenvironmental parameters. Herein we present such a design in the small probe COU-Mito featuring the graft of a strong electron-withdrawing 4-pyridiniumylacrylonitrile unit to an electron-donating diethylamino coumarin. The introduction of the cyano group destroys the coplanarity of the total push-pull π-conjugation system, thus the probe exhibits very weak background red fluorescence but a turn-on response to increased viscosity which restricts the rotation of the molecular rotor between the push and pull parts around a single bond. More importantly, the introduction of the cyano group together with the 4-pyridinium moiety improves significantly the electrophilicity of the carbon-carbon double bond in the probe that allows selective oxidative cleavage and nucleophilic addition on the double bond by peroxynitrite (ONOO-) and sulfur dioxide (SO2), respectively. Hence the probe, whilst superficially simple, is in fact a multifunctional probe capable of simultaneously discriminating viscosity, ONOO- and SO2 in a fashion of three sets of distinct signals: red for viscosity, green for ONOO-, and blue for SO2. The probe was successfully employed to visualize the change of mitochondrial viscosity and the fluctuation of mitochondrial ONOO- and SO2 levels in living cells and zebrafish, and to probe into their roles in the hepatotoxicity induced by acetaminophen, a widely used analgesic and antipyretic drug.

Cooperation in the jaywalking dilemma of a road public good due to points guidance

Jaywalking is a dangerous illegal crossing behavior, which is common but difficult to govern. If road is a kind of public goods, jaywalking can be regarded as a completely uncooperative behavior in the game of the public goods. Jaywalking is a relatively broad concept, which includes both the behaviors of pedestrians running a red light at the crosswalks and the behaviors of pedestrians directly crossing the road regardless of the traffic rules outside the crosswalks. At the same time, the traffic signal settings in the road network include both the signal lights at the intersections and the signal lights in the mid-roadways. The jaywalking behavior outside the crosswalks in the mid-roadways may be more common and difficult to govern due to the lack of management. Therefore, this study aims at the governance of jaywalking behaviors outside the crosswalks in the mid-roadways. Clearly, time pressure has a huge impact on crossing decision-making processes of pedestrians, and even causes pedestrians to fall into a jaywalking dilemma. The points decision-making guidance mechanism (PDGM) established by us is proposed based on a crossing decision-making model and a points guidance system in this problem-oriented context, which takes time pressure as an important factor. The points rules that the points guidance system relies on mainly apply the Elo algorithm to realize the automatic update of the points. The decision-making processes of pedestrians crossing the road can be positively influenced by the PDGM, which adopts a multi-factor crossing decision-making model. Since our PDGM is an innovative soft strategy based on the development of future intelligent transportation systems, which has not yet been established, so the introduction of a simulation modeling method is very necessary. In particular, this paper establishes an agent-based model to describe the effects of various aspects of the PGDM, and further verifies its effectiveness and feasibility with quantitative methods. The PDGM is beneficial to reduce jaywalking behaviors of pedestrians and effectively promote cooperation between pedestrians and traffic rules. The establishment of the PDGM has been proved to be feasible and effective, which can significantly promote legal crossing and improve the level of crossing safety without affecting the operating efficiency of vehicles by a simulation modeling method. The PDGM, which achieves a good performance, can be pioneered and applied to induce pedestrians to cross the road cooperatively and legally. What's more, the PDGM has been proved to be effective and has great potential to be applied to more traffic scenarios. In summary, it is conducive to urban traffic road more efficient and safer through the study of the points guidance mechanism for pedestrians.

On–off switching of the correlated motion in a rotation‐inversion dual‐mode molecular system

AbstractWe report herein a new rotation‐inversion dual‐motion molecular switch (1), in which a 3,3‐dimethylazetidinyl (DMAZ) group is the rotator and a stiff‐stilbene is the helical stator. There are two sets of nuclear magnetic resonance (NMR) signals in the DMAZ group, the H‐shaped AZ protons and the planar C2‐symmetrical Me protons, for probing the kinetics of the DMAZ rotation and the stiff‐stilbene inversion. While the two motion modes are highly correlated in (E)‐1, they are decoupled in (Z)‐1. The rotation‐inversion correlated motion in (E)‐1 is governed by the faster inversion mode, whereas the inversion is much slower than the rotation in (Z)‐1. Consequently, photochemical isomerization between (E)‐1 and (Z)‐1 switches not only the relative rate of the rotation versus inversion motion but also the on–off behavior of the rotation‐inversion correlated motion. This work shows the cooperation of two sets of proton signals in elucidating the correlated motion in a dual‐motion molecular system.

A General Approach to Sampled-Data Modeling for Ripple-Based Control—Part II: Constant ON-Time and Constant OFF-Time Control

This part is the second part of this article and mainly presents the sampled-data modeling method for the dc–dc converters with the constant <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> -time (COT) and constant <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> -time (COFT) controls. Compared with the constant frequency control in the first part, the duty cycle perturbation signal in the COT/COFT control is found to have two sets of narrow pulse signals in each switching period. Then, by establishing the relationship between the two sets of signals and using Shannon's sampling theorem, the transfer functions of the modulator and the loop gain are derived. Based on the theoretical results, the phenomenon that a current-mode constant <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> / <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> time controlled buck converter is stable at any duty cycle, and the instability of a voltage-mode constant <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> / <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> -time controlled buck converter with the smaller time constant of the output capacitor could be predicted. Moreover, the sampled-data modeling method is further extended to the digital control by taking a digitally current-mode controlled buck converter as an example. Simulation results are provided to confirm the validity of the proposed modeling method.

Electric Arc Furnaces Reactive Power Optimized Calculation Used in SVC

This study deals with a new approach to tackle the challenges encountered in the filters-based reactive power calculation techniques utilized in the control system of static VAr compensators. In this approach, step and time-varying responses are improved by a combination of differential and filter-based methods. Then, optimum values of the main parameters of the low-pass and band-stop filters are determined considering three criteria: accuracy, speed, and capability for following the time-varying loads. To assess the performance of the proposed method, a new objective function is introduced, calculated for two sets of signals, captured from a real field in Mobarakeh Steel Company in Isfahan/Iran. Then, the proposed and the other reactive power calculation methods are assessed in practice and simulation. Also, the algorithm is implemented using a TMDSCNCD28335 as the processor to assess the real-time feasibility of the method. To do so, the reactive power variation of an electrical arc furnace is emulated in a prototype test bench and the algorithm is run in real-time by the processor during the system operation.

A Novel Method for Automated Estimation of Effective Parameters of Complex Auditory Brainstem Response: Adaptive Processing Based on the Correntropy Concept

Objectives: Automated Auditory Brainstem Responses (ABR) peak detection is a novel technique to facilitate the measurement of neural synchrony along the auditory pathway through the brainstem. Analyzing the location of the peaks in these signals and the time interval between them may be utilized either for analyzing the hearing process or detecting peripheral and central lesions in the human hearing system. Methods: In this paper, model-based signal processing is proposed to estimate the effective parameters of ABR signals. In this process, the biological parameters of the signal are assessed by utilizing a Finite Impulse Response (FIR) adaptive filter in which its adaptation procedure is performed based on the correntropy concept. The proposed method is applied on a set of ABR signals recorded in response to three stimuli of /da/, /ba/, and /ga/, and then its performances are compared with an existing state-of-the-art technique. Results: The results show that the proposed method can significantly increase the accuracy of estimating the parameters in stable stimulations (/da/, /ba/) for major positive and negative peaks. This improvement is more significant (up to 2-3 times) for /ba/ stimulus and especially in major positive peaks. However, in other peaks, the improvements also occurred in smaller amounts. However, for unstable stimuli (/ga/), no significant improvement was achieved. Discussion: Increasing the accuracy performance of the proposed method for detecting the stable stimuli (while its performance remains unchanged) for detecting unstable stimuli indicates its effectiveness in automated clinical analysis of ABR signals.

Statistical analysis of quantitative electrocardiographic signals with standard limb leads: Influences of gel use, subject positions, and electrodes configurations

An electrocardiogram records the heart’s electrical activity that provides helpful information on the cardio electrophysiological process. One cycle of cardiac contraction and relaxation produces the basic waves that consist of a P wave (atrial depolarization), a QRS complex (ventricular depolarization), and a T wave (ventricular repolarization). In this study, the quantitative electrocardiographic signals from six adult females aged 19 to 22 years in a relaxed state were measured using Cobra4 Electrophysiology with standard limb leads. Six conditions of the experiments were carried out for each subject to investigate the influence of gel use, subject positions, and electrodes configurations on electrocardiographic signals parameters: amplitude, duration, RRinterval, and correlation coefficient between two signals. It was obtained that the gel did not significantly influence the results for subjects when sitting but marginally influenced some electrocardiographic parameters for some individual subjects in lying positions. The subject positions influenced marginally for RRinterval. Electrode configurations are found to be related to the positive or negative deflection of the resulting electrocardiographic signals. All the measurements showed that two data sets of the ECG signals have a strong correlation for each subject in each condition.

Power system coherency assessment by the affinity propagation algorithm and distance correlation

This paper assesses the coherency in power systems employing the affinity propagation (AP) algorithm with different distance metrics and quality measurements. This assessment allows determining the appropriate metric to cluster a frequency dataset that possesses coherent patterns. Thanks to the AP method does not require initialization for the number of clusters, its convergence characteristics guaranteed by the optimization process, and its capacity for using different distance metrics as input, the AP is adopted to identify and distinguish such coherent patterns that embody the collective motion of an operative area in a power system. The AP method is a data-driven method that uses an affinity matrix as input, i.e., the square matrix computed with pairwise distances. Since the distance function significantly impacts the quality of the resulting clustering, this contribution evaluates three different distance metrics, distance correlation, and the results are compared using four cluster indexes. The data collection is constituted by a set of frequency signals and the representative objects are the nodes identified as the center of each operative area. This contribution presents experimental results using simulated signals with added noise and real event signals captured by 94 PMUs. We found that our proposed strategy achieves highly competitive results for identifying coherent generator and non-generator buses in large-scale power systems.

Genomic profiling and outcomes of BRAF V600E mutated papillary thyroid cancer.

e18086 Background: BRAF (BRAF mut) is the most common mutation in PTC (45% prevalence). It is associated with a higher clinical stage, tumor recurrence, absence of tumor avidity, and treatment failure. Methods: BRAF WT or BRAF mut (n = 538) PTC tumors tested with NextGen Sequencing on DNA (592 genes or WES) and RNA (WTS) by Caris Life Sciences (Phoenix, AZ) were analyzed. PD-L1 expression was tested by IHC (22c3 antibody, ≥1 combined positive score (CPS) being positive). Real world overall survival (rwOS) was obtained from insurance claims data, calculated from treatment start to last contact. Time-on-treatment (TOT) is calculated from start to end of treatment. Kaplan-Meier estimates were used for comparison. Statistical significance was determined using Fisher’s-Exact/Mann Whitney/X2 test with Benjamini-Hochberg correction. Differential gene expression was analyzed using the Limma R package (q &lt; 0.001, logFC &gt; 1.5, -log10 FDR &gt; 20). Gene Set Enrichment Analysis (GSEA) was used with a p &lt; 0.01 cutoff. Results: BRAF mut were found in PTC (69%, 369/538) but not in the follicular subtype (0/117). No gender difference was seen in BRAF mut PTC (F: 53%, 297/538). BRAF mut were more prevalent in metastases compared to primary/local tumors (42% vs. 30%) and BRAF mut was highest in metastatic lymph nodes (55%, 130/235). TERT promoter was the most common mutation in both BRAF mut and WT groups but higher in BRAF mut (64% vs 40%, q &lt; 0.0001), while NRAS (0.2% vs 23%, q &lt; 0001), HRAS (0% vs 8.8%, q &lt; 0001), KRAS (0.4% vs 5.4%, q &lt; 0001), and EIF1AX (0% vs 6.6%, q = 0.0005) mutations were more prevalent in BRAF WT PTC. PD-L1 expression was higher in the BRAF mut patients compared to WT (37% vs 22%, q &lt; 0.01). BRAF mut PTCs were associated with higher immune cell infiltrate including M1 macrophages, and Treg cells, but lower M2 macrophages, NK cells, CD4+ T cells, and myeloid dendritic cells (all q &lt; 0.01). GSEA analysis revealed enrichment in IL6, JAK, and STAT3 signaling, inflammatory response, apoptosis, and interferon gamma response (all NES = 1.5 - 1.8, p &lt; 0.01) gene sets. DCSTAMP was the most differentially expressed gene in BRAF mut tumors relative to WT (logFC = 4.4). When comparing BRAF mut with WT, no significant difference in rwOS was seen (NR vs 50 mo, HR 0.73, P&gt; 0.2). In BRAF mut patients, treatment with multikinase inhibitors (n = 32) was associated with longer rwOS compared to BRAF inhibitor treatment (n = 37) (61 mo vs 27 mo, HR 0.364, P&lt; 0.05). Despite small patient number, data suggests BRAF mut patients may benefit from immunotherapy (n = 4) when compared to BRAF inhibitors (n = 31) (TOT, HR = 0.35, p = 0.07). Conclusions: Our data highlights new genomic signatures that indicate potential new, while also validating current targets for BRAF mut PTC: higher PD-L1 expression, immune infiltrate, and inflammatory gene signature. Clinical trials are needed to assess the best sequencing of therapies used in this group, particularly TKIs vs BRAF inhibitors and the role of immunotherapy.

KERNEL MACHINE AND DISTRIBUTED LAG MODELS FOR ASSESSING WINDOWS OF SUSCEPTIBILITY TO ENVIRONMENTAL MIXTURES IN CHILDREN'S HEALTH STUDIES.

Exposures to environmental chemicals during gestation can alter health status later in life. Most studies of maternal exposure to chemicals during pregnancy have focused on a single chemical exposure observed at high temporal resolution. Recent research has turned to focus on exposure to mixtures of multiple chemicals, generally observed at a single time point. We consider statistical methods for analyzing data on chemical mixtures that are observed at a high temporal resolution. As motivation, we analyze the association between exposure to four ambient air pollutants observed weekly throughout gestation and birth weight in a Boston-area prospective birth cohort. To explore patterns in the data, we first apply methods for analyzing data on (1) a single chemical observed at high temporal resolution, and (2) a mixture measured at a single point in time. We highlight the shortcomings of these approaches for temporally-resolved data on exposure to chemical mixtures. Second, we propose a novel method, a Bayesian kernel machine regression distributed lag model (BKMR-DLM), that simultaneously accounts for nonlinear associations and interactions among time-varying measures of exposure to mixtures. BKMR-DLM uses a functional weight for each exposure that parameterizes the window of susceptibility corresponding to that exposure within a kernel machine framework that captures non-linear and interaction effects of the multivariate exposure on the outcome. In a simulation study, we show that the proposed method can better estimate the exposure-response function and, in high signal settings, can identify critical windows in time during which exposure has an increased association with the outcome. Applying the proposed method to the Boston birth cohort data, we find evidence of a negative association between organic carbon and birth weight and that nitrate modifies the organic carbon, elemental carbon, and sulfate exposure-response functions.

Canonical Wnt signaling and the regulation of divergent mesenchymal Fgf8 expression in axolotl limb development and regeneration.

The expression of fibroblast growth factors (Fgf) ligands in a specialized epithelial compartment, the Apical Ectodermal Ridge (AER), is a conserved feature of limb development across vertebrate species. In vertebrates, Fgf 4, 8, 9, and 17 are all expressed in the AER. An exception to this paradigm is the salamander (axolotl) developing and regenerating limb, where key Fgf ligands are expressed in the mesenchyme. The mesenchymal expression of Amex.Fgf8 in axolotl has been suggested to be critical for regeneration. To date, there is little knowledge regarding what controls Amex.Fgf8 expression in the axolotl limb mesenchyme. A large body of mouse and chick studies have defined a set of transcription factors and canonical Wnt signaling as the main regulators of epidermal Fgf8 expression in these organisms. In this study, we address the hypothesis that alterations to one or more of these components during evolution has resulted in mesenchymal Amex.Fgf8 expression in the axolotl. To sensitively quantify gene expression with spatial precision, we combined optical clearing of whole-mount axolotl limb tissue with single molecule fluorescent in situ hybridization and a semiautomated quantification pipeline. Several candidate upstream components were found expressed in the axolotl ectoderm, indicating that they are not direct regulators of Amex.Fgf8 expression. We found that Amex.Wnt3a is expressed in axolotl limb epidermis, similar to chicken and mouse. However, unlike in amniotes, Wnt target genes are activated preferentially in limb mesenchyme rather than in epidermis. Inhibition and activation of Wnt signaling results in downregulation and upregulation of mesenchymal Amex.Fgf8 expression, respectively. These results implicate a shift in tissue responsiveness to canonical Wnt signaling from epidermis to mesenchyme as one step contributing to the unique mesenchymal Amex.Fgf8 expression seen in the axolotl.

C–H⋯S Hydrogen Bond Assisted Supramolecular Encapsulation of Fullerenes with Nanobelts

C–H⋯S Hydrogen Bond Assisted Supramolecular Encapsulation of Fullerenes with Nanobelts

Some features of Hilbert transform and their use in energy informatics

Information-measuring technologies (IMT) are an important instrument for solving problems of energy informatics. They allow to form primary information based on the interaction of energy facilities with IMT sensors that form information signals. In many practical applications, the constructive model of information signals is the model of narrowband signals. The article summarizes the features of the discrete Hilbert transform and its application to obtain the primary characteristics of information signals – bypass and phase as functions of time. The main advantages of using the discrete Hilbert transform in signal processing for energy informatics are considered, including the consistency of obtaining frequency and time characteristics, high information content, the ability to analyze the dynamics of changes in signal characteristics, the possibility of obtaining samples of characteristics of information signals of significant volumes, etc. It is proposed to use a phase characteristic to select the time interval that limits the signal sample and sets it to a multiple of the signal period, and the sampling rate of information signals to reduce the errors in estimating their spectrum. The possibility of obtaining on their basis secondary deterministic (voltage level, voltage deviations from the nominal level, attenuation coefficient, signal period, signal phase shift, oscillation frequency, etc.) and statistical (sample characteristic, sample variance, sample median, sample circular variance, sample circular median, sample circular kurtosis, etc.) of signal information characteristics, which allows more complete to use their information resource. These characteristics can be used both for assessing power quality characteristics and for monitoring and diagnosing of energy facilities. Keywords: energy informatics, information signals, signal processing, discrete Hilbert transform, amplitude signal characteristics, phase signal characteristics

The impact of SMARTpass algorithm status on inappropriate shock rates in the UNTOUCHED Study

Abstract Funding Acknowledgements Type of funding sources: Private company. Main funding source(s): Boston Scientific Corporation Background The current Subcutaneous ICD (S-ICD) model incorporates SMART Pass (SP) to improve sensing and discrimination capabilities to reduce inappropriate shocks (IAS). SP status is programmable but may also be disabled automatically in the setting of low amplitude signals or low heart rate in order to avoid under-sensing of VT/VF. Objective To evaluate SP impact on IAS, appropriate shocks (AS), complications and mortality in the UNTOUCHED S-ICD trial. Methods Primary prevention patients (pts, n=1111) with ejection fraction ≤35% and no pacing requirement were followed for up to 18 months. SP status during a study visit was programmed ON or OFF and status between visits was either consistently OFF, ON, or automatically disabled (DIS). The impact of SP status on pt outcomes was evaluated using Kaplan-Meier (K-M) analysis. Multivariable proportional hazard analysis identified predictors of IAS and SP disable events. Results Percent of pts with SP always ON, always OFF, ON with DIS, and OFF then ON with no DIS were 56, 16, 15, and 13%, respectively. At least one SP DIS occurred in 177 pts, but only 13% had 2 or more, mostly due to PVCs and low EGM amplitudes. Significant multivariable predictors of SP disable events are history of atrial fibrillation (hazard ratio (HR) 2.49, odds ratio (OR) (1.49-4.16); p=.0005), only one passing vector at S-ICD screening, (HR 1.85, OR (1.10-3.10; p=.0202) and lower left ventricular ejection fraction (HR 1.05, OR (1.01-1.08); p=.0074). K-M IAS rates were highest for pts experiencing DIS (fig 1) and lowest for SP ON. While neither AS (p=0.58) nor complication (p=0.58) rates varied significantly according to SP status, mortality was lower for pts with SP ON during any duration of time (p=0.044) by univariate analysis. Further analysis is planned to better understand the relationship between SP status and mortality. Conclusion Patients in the UNTOUCHED trial with SMART Pass (SP) consistently ON had significantly fewer inappropriate shocks, with no impact on appropriate therapy for VT/VF. Patients with history of atrial fibrillation, lower left ventricular ejection fraction, and only one passing vector at S-ICD screening are at higher risk of SP disable events; therefore, care should be taken for these patients to assess SP status and their higher risk for inappropriate shocks.

Programming VDD leadless pacemakers: relation of algorithm settings of A3 and A4 signals with atrioventricular synchrony

Abstract Funding Acknowledgements Type of funding sources: None. Background The development of VDD mode in leadless pacemakers (Micra AV) has allowed the use of leadless pacing in patients with an atrioventricular (AV) block. Keeping AV synchrony (AVS) on pacing improves cardiac output and quality of life and reduces the risk of atrial fibrillation (AF) and PM syndrome. The AVS of the pivotal study with Micra AV (MARVEL2), in a post-implant situation of low activity was 89%. Methods Prospective single-center study of consecutive patients who received a VDD leadless pacemaker (Micra AV), and who remained in VDD mode throughout the follow-up. The initial programming changes were conducted following the standard recommendation for problems resolution, and further changes were made based on experience. Univariate association was tested for different programming parameters with the percentage of AVS. Our goal was to find the best possible programming for the Micra AV pacemaker with the scope of achieving high percentages of AVS in real life. Results We included 26 patients who received a VDD leadless pacemaker (Micra AV) between Jun/20 and Nov/21 and were kept in VDD mode at least during the first month of follow-up. We made an intermediate analysis from the first 18 patients who reached the first month after implant, and a significant association was found between the adjustment of the end of the window of A3 (VE) with the percentage of AVS: in the group in which automatic VE adjustment was maintained after implantation (4 patients), the mean AVS was 76.9 ± 6.0% (VE 702± 60 ms), while in the group in which the automatic adjustment was deactivated and the VE was set at 600-650 ms (14 patients), AVS was 84.9 ± 7.2% (VE 614 ± 23 ms), p = 0.04 (Figure 1). When discriminating by AVS ≥ 85%, the deactivation of the automatic adjustment of VE had an OR of 5.6 compared to maintaining automatic adjustment (p = 0.018), with a χ2 of 4.1 (p = 0.043). Moreover, when we analyzed the data until the sixth month of follow-up for those patients in VDD mode, we found that the shorter the interval of VE window we programmed, the larger the AVS percentage was (1st month, 26 patients: VE 631±46 ms, AVS 83.8±6.9%; 3rd month, 24 patients: VE 621±35 ms, AVS 86.2±6.6%; 6th month, 19 patients: VE 614±25 ms, AVS 88.3±6.5%, p&amp;lt;0.001; Figure 2). On the other side, there was no significant association between the modification of the A4 threshold (p = 0.104), adjustment of the rate smoothing (p = 0.331), or signal vector change (p = 0.276) with the percentage of AVS. Conclusions In real life, AVS percentages can vary considerably from the data obtained in resting situations and short follow-up time. Even though our series is not extensive, the preliminary data suggest the importance of adding modifications in the standard programming, especially in the algorithm for adjusting the A3 window, altogether with the standard recommendations for problem-solving to achieve high AVS percentages.

Signal-in-space range error and positioning accuracy of BDS-3

Being the first mixed-constellation global navigation system, the global BeiDou navigation system (BDS-3) designs new signals, the service performance of which has attracted extensive attention. In the present study, the Signal-in-space range error (SISRE) computation method for different types of navigation satellites was presented. The differential code bias (DCB) correction method for BDS-3 new signals was deduced. Based on these, analysis and evaluation were done by adopting the actual measured data after the official launching of BDS-3. The results showed that BDS-3 performed better than the regional navigation satellite system (BDS-2) in terms of SISRE. Specifically, the SISRE of the BDS-3 medium earth orbit (MEO) satellites reached 0.52 m, slightly inferior compared to 0.4 m from Galileo, marginally better than 0.59 m from GPS, and significantly better than 2.33 m from GLONASS. The BDS-3 inclined geostationary orbit (IGSO) satellites achieved the SISRE of 0.90 m, on par with that (0.92 m) of the QZSS IGSO satellites. However, the average SISRE of BDS-3 geostationary earth orbit (GEO) satellites was 1.15 m, which was marginally inferior to that of the QZSS GEO satellite (0.91 m). In terms of positioning accuracy, the new signals B1C and B2a are considered together with the transition signals B1I and B3I. The overall three-dimensional single-frequency standard point positioning (SPP) accuracy of BDS-3 B1C, B2a, B1I, and B3I gained an accuracy level better than 5 m. Moreover, the B1I signal exhibited the best positioning accuracy in the Asian-Pacific region, while the B1C signal set forth the best positioning accuracy in the other regions. Owing to the advantage in signal frequency, the dual-frequency SPP accuracy of B1C + B2a surpassed that of the transitional signal of B1I + B3I. Since there are more visible satellites in Asia–Pacific, the positioning accuracy of BDS-3 was moderately superior to that of GPS. The precise point positioning (PPP) accuracy of BDS-3 B1C + B2a or B1I + B3I converged to the order of centimeters, marginally inferior to that of the GPS L1 + L2. However, these three combinations had a similar convergence time of approximately 30 min.

End-to-End Convolutional Neural Network Framework for Breast Ultrasound Analysis Using Multiple Parametric Images Generated from Radiofrequency Signals

Breast ultrasound (BUS) is an effective clinical modality for diagnosing breast abnormalities in women. Deep-learning techniques based on convolutional neural networks (CNN) have been widely used to analyze BUS images. However, the low quality of B-mode images owing to speckle noise and a lack of training datasets makes BUS analysis challenging in clinical applications. In this study, we proposed an end-to-end CNN framework for BUS analysis using multiple parametric images generated from radiofrequency (RF) signals. The entropy and phase images, which represent the microstructural and anatomical information, respectively, and the traditional B-mode images were used as parametric images in the time domain. In addition, the attenuation image, estimated from the frequency domain using RF signals, was used for the spectral features. Because one set of RF signals from one patient produced multiple images as CNN inputs, the proposed framework overcame the limitation of datasets in a broad sense of data augmentation while providing complementary information to compensate for the low quality of the B-mode images. The experimental results showed that the proposed architecture improved the classification accuracy and recall by 5.5% and 11.6%, respectively, compared with the traditional approach using only B-mode images. The proposed framework can be extended to various other parametric images in both the time and frequency domains using deep neural networks to improve its performance.

One-bit LFM signal recovery: A consistency algorithm with one-sided weighted quadratic penalty

The non-ideal sparse representation (SR) and harmonics are universal problems in linear frequency modulated (LFM) signal recovery from one-bit data contaminated by noise. Given these issues, we develop a consistency algorithm with the one-sided weighted quadratic penalty (OWQP) to reconstruct LFM signals quantized to one bit. In our recovery model, a stochastic quantization approach is first employed to address the harmonic problem in one-bit sampling. Then, depending on the block-shaped fractional Fourier spectrum of LFM signals and the symmetry of the sinc function, we extend the sparse support set of signals to decrease the SR error caused by the non-ideal SR of LFM signals in the fractional Fourier transform basis. After identifying this set, the original under-determined optimization is readily reformulated as an overdetermined one estimating a proxy of the desired signal. An OWQP function is further proposed to penalize the noise-induced inconsistencies of the proxy with measurements. Numerical results show that the performance of our algorithm is superior to state-of-the-art methods in terms of the reconstructed signal-to-noise ratios and mean square errors.