Symmetric Window Research Articles

A Transformer and LSTM-Based Approach for Blind Well Lithology Prediction

Petrographic prediction is crucial in identifying target areas and understanding reservoir lithology in oil and gas exploration. Traditional logging methods often rely on manual interpretation and experiential judgment, which can introduce subjectivity and constraints due to data quality and geological variability. To enhance the precision and efficacy of lithology prediction, this study employed a Savitzky–Golay filter with a symmetric window for anomaly data processing, coupled with a residual temporal convolutional network (ResTCN) model tasked with completing missing logging data segments. A comparative analysis against the support vector regression and random forest regression model revealed that the ResTCN achieves the smallest MAE, at 0.030, and the highest coefficient of determination, at 0.716, which are indicative of its proximity to the ground truth. These methodologies significantly enhance the quality of the training data. Subsequently, a Transformer–long short-term memory (T-LS) model was applied to identify and classify the lithology of unexplored wells. The input layer of the Transformer model follows an embedding-like principle for data preprocessing, while the encoding block encompasses multi-head attention, Add & Norm, and feedforward components, integrating the multi-head attention mechanism. The output layer interfaces with the LSTM layer through dropout. A performance evaluation of the T-LS model against established rocky prediction techniques such as logistic regression, k-nearest neighbor, and random forest demonstrated its superior identification and classification capabilities. Specifically, the T-LS model achieved a precision of 0.88 and a recall of 0.89 across nine distinct lithology features. A Shapley analysis of the T-LS model underscored the utility of amalgamating multiple logging data sources for lithology classification predictions. This advancement partially addresses the challenges associated with imprecise predictions and limited generalization abilities inherent in traditional machine learning and deep learning models applied to lithology identification, and it also helps to optimize oil and gas exploration and development strategies and improve the efficiency of resource extraction.

Abstract P462: A Novel Framework for the Extraction and Modeling of Meal-Related Glucose Excursions Detected via Continuous Glucose Monitoring (CGM)

Introduction: Understanding factors that influence glycemic response to meals can inform strategies for diabetes management. Continuous glucose monitoring (CGM) facilitates analyzing glycemic regulation, but concurrent meal timing, required to study meal-induced excursions, is rarely collected. Objective: We develop a framework for extracting meal-related glucose excursions from CGM time series, modeling the excursions using interpretable features, and estimating feature variability explained by patient characteristics and instance-specific patterns. Methods: We used CGM data (Abbott Freestyle Pro) from N = 175 clinical trial participants with type 2 diabetes not using insulin (HYPNOS Trial: mean age 60; 49% female; 36% Black adults). To find excursions, we marked local maxima points in the CGM time series. We discarded points with glucose increases <50 mg/dL in a symmetric window around the point. Remaining point-windows became excursions ( Fig. 1A) . We summarized excursions using relevant features: baseline, height, and shape quantified by splines ( Fig. 1B ).We then assumed each feature could be modelled as the sum of patient-specific effects, both measured as covariates and unmeasured, and instance-specific effects ( Fig. 1C ). Covariates included demographic, biometric, and lifestyle characteristics. Using linear mixed-effects models, we estimated the effects and corresponding variance explained for each feature. Results: For baseline glucose, measured covariate effects notably explain 61.2% of variability. For both height and shape, the summed patient-specific effects explain negligible variation, 17.8% and 10% respectively ( Fig. 1D ). Conclusion: Using our novel framework, we found that instance-specific information explains most variability in glucose excursions. As diet and adjacent physical activity are the instance-specific features primarily impacting glucose metabolism, it follows that healthy lifestyle choices impact postprandial glucose patterns more than inherent traits.

Synchronous odd symmetric transform for rolling bearing fault diagnosis

Time-frequency analysis (TFA) is an important tool to process non-stationary signals and detect bearing faults. For considering energy concentration, computational efficiency, and computational accuracy, a novel TFA technique, termed synchronous odd symmetric transform (SOST) is proposed in this paper. In the SOST, the odd symmetry extraction operator (OSEO) is defined according to the odd symmetric window based short-time Fourier transform (OSTFT). The main idea of OSEO is to obtain accurate instantaneous frequency (IF) ridges in a satisfactory computation time. Meanwhile, the STFT result is retained at the IF ridges, and the time–frequency representation (TFR) with high energy concentration is calculated. The performance of the developed technique is verified by a multi-component signal with strong frequency-modulated and amplitude-modulated (FM-AM) laws. Experimental analysis results show that the proposed SOST can display bearing fault-related time–frequency trajectories with high time–frequency resolution.

Functional Enhancement and Characterization of an Electrophysiological Mapping Electrode Probe with Carbonic, Directional Macrocontacts.

Electrophysiological mapping (EM) using acute electrode probes is a common procedure performed during functional neurosurgery. Due to their constructive specificities, the EM probes are lagging in innovative enhancements. This work addressed complementing a clinically employed EM probe with carbonic and circumferentially segmented macrocontacts that are operable both for neurophysiological sensing ("recording") of local field potentials (LFP) and for test stimulation. This paper illustrates in-depth the development that is based on the direct writing of functional materials. The unconventional fabrication processes were optimized on planar geometry and then transferred to the cylindrically thin probe body. We report and discuss the constructive concept and architecture of the probe, characteristics of the electrochemical interface deduced from voltammetry and chronopotentiometry, and the results of in vitro and in vivo recording and pulse stimulation tests. Two- and three-directional macrocontacts were added on probes having shanks of 550 and 770 μm diameters and 10-23 cm lengths. The graphitic material presents a ~2.7 V wide, almost symmetric water electrolysis window, and an ultra-capacitive charge transfer. When tested with clinically relevant 150 μs biphasic current pulses, the interfacial polarization stayed safely away from the water window for pulse amplitudes up to 9 mA (135 μC/cm2). The in vivo experiments on adult rat models confirmed the high-quality sensing of LFPs. Additionally, the in vivo-prevailing increase in the electrode impedance and overpotential are discussed and modeled by an ionic mobility-reducing spongiform structure; this restricted diffusion model gives new applicative insight into the in vivo-uprisen stimulation overpotential.

Dependence of the AUC of NTCP models on the observational dose-range highlights cautions in comparison of discriminative performance

BackgroundNormal tissue complication probability (NTCP) models are probabilistic models that describe the risk of radio-induced toxicity in tissues or organs. In the field of radiotherapy, the area under the ROC curve (AUC) is widely used to estimate the performance in risk prediction of NTCP models. MethodsIn this work, we derived an analytical expression of the AUC for the logistic NTCP model in the case of both symmetrical and asymmetrical dose (to the normal tissue) windows around D50. Using numerical simulations, we studied the behavior of the AUC in general clinical settings, enforcing non-logistic NTCP models (Lyman-Kutcher-Burman and LogEUD) and including risk factors beyond the dose. We validated our findings using real-world radiotherapy data sets of prostate cancer patients. ResultsOur analytical expression of the AUC made explicit the dependence on both the steepness of the logistic curve (β) and the dose window width (w), showing that an increase of w pushes AUC towards higher values. Increasing values of the AUC with increasing values of w were consistently observed across simulated data sets with diverse clinical settings from published studies and real clinical data sets. ConclusionOur results reveal that the AUC of NTCP models inherits intrinsic characteristics from the clinical setting of the data set on which the models are developed, and warn against the use of the AUC to compare the performance of models constructed upon data from trials in which substantially different dose ranges were administered or accounting for different risk factors beyond the dose.

Noise and spike-time-dependent plasticity drive self-organized criticality in spiking neural network: Toward neuromorphic computing

Self-organized criticality (SoC) may optimize information transmission, encoding, and storage in the brain. Therefore, the underlying mechanism of the SoC provides significant insight for large-scale neuromorphic computing. We hypothesized that noise and stochastic spiking plays an essential role in SoC development in spiking neural networks (SNNs). We demonstrated that under appropriate noise levels and spike-time-dependent plasticity (STDP) parameters, an SNN evolves a SoC-like state characterized by a power-law distribution of neuronal avalanche size in a self-organized manner. Consistent with the physiological findings, the development of SNN was characterized by a transition from a subcritical state to a supercritical state and then to a critical state. Excitatory STDP with an asymmetric time window dominated the early phase of development; however, it destabilized the network and transitioned to the supercritical state. Synchronized bursts in the supercritical state enable inhibitory STDP with a symmetric time window, induce the development of inhibitory synapses, and stabilize the network toward the critical state. This sequence of transitions was observed when the appropriate noise level and STDP parameters were set to the initial conditions. Our results suggest that noise or stochastic spiking plays an essential role in SoC development and self-optimizes SNN for computation. Such neural mechanisms of noise harnessing would offer insight into the development of energy-efficient neuromorphic computing.

Improving the short‐range forecast of storm surges in the southwestern Atlantic continental shelf using 4DEnSRF data assimilation

In this study, the assimilation of tide gauge and altimetry data into a two‐dimensional barotropic numerical model for the southwestern Atlantic continental shelf (SWACS) was developed. To do this, the preoperative 4‐day storm surges ensemble prediction system developed by Dinápoli et al. (2021, Journal of the Royal Meteorological Society 147: 557–572) was implemented for the SWACS. This new configuration, called “Model for Storm Surge Simulations” (M3S), considers a curvilinear grid that covers the SWACS with higher resolution along the shoreline (from 2 to 10 km). M3S was forced with an ensemble of 60 members conformed by the combination of perturbations of the eight principal tidal constituents and of the atmospheric products derived from the Global Ensemble Forecast System. Tidal gauge and altimetry data were assimilated in an asynchronous mode using the four‐dimensional‐ensemble square‐root filter (4DEnSRF). The system was developed and validated forecasting two strong positive storm surges. Results show that 4DEnSRF's innovations produce a positive impact upon the forecast skill up to 2 days. Hence, the 4‐day forecast can be divided into two parts: the first 2 days with a stronger dependence on the initial conditions and the other 2 days purely driven by external forcing. It was found that a symmetric assimilation window of 12 hr length produces the best initial condition. Under this configuration, 4DEnSRF removes biases and improves the timing of the M3S forecasted solutions. The largest improvements were observed at the northern SWACS, where more chaotic processes, such as the atmospheric circulation, explain a large part of the sea‐surface height variability. No significant improvements were found at the southern SWACS, which can be attributed to the strong tidal dynamics that characterise the zone. Our results show that the incorporation of 4DEnSRF into M3S can significantly improve the forecast in the SWACS and also the accuracy of the short‐range detection of storm surges.

Heterogeneous Integration of Atomically-Thin Indium Tungsten Oxide Transistors for Low-Power 3D Monolithic Complementary Inverter.

In this work, the authors demonstrate a novel vertically-stacked thin film transistor (TFT) architecture for heterogeneously complementary inverter applications, composed of p-channel polycrystalline silicon (poly-Si) and n-channel amorphous indium tungsten oxide (a-IWO), with a low footprint than planar structure. The a-IWO TFT with channel thickness of approximately 3-4 atomic layers exhibits high mobility of 24 cm2 V-1 s-1 , near ideally subthreshold swing of 63mV dec-1 , low leakage current below 10-13 A, high on/off current ratio of larger than 109 , extremely small hysteresis of 0mV, low contact resistance of 0.44 kΩ-µm, and high stability after encapsulating a passivation layer. The electrical characteristics of n-channel a-IWO TFT are well-matched with p-channel poly-Si TFT for superior complementary metal-oxide-semiconductor technology applications. The inverter can exhibit a high voltage gain of 152V V-1 at low supply voltage of 1.5V. The noise margin can be up to 80% of supply voltage and perform the symmetrical window. The pico-watt static power consumption inverter is achieved by the wide energy bandgap of a-IWO channel and atomically-thin channel. The vertically-stacked complementary field-effect transistors (CFET) with high energy-efficiency can increase the circuit density in a chip to conform the development of next-generation semiconductor technology.

Constraining the QCD phase diagram

Lattice QCD and functional methods are making significant progress in constraining the QCD phase diagram. As an important milestone, the chiral phase transition with massless u, d-quarks at zero density is now understood to be of second order for all strange quark masses, and a smooth crossover as soon as mu,d, ≠ 0. Together with information on fluctuations and refined reweighted simulations, this bounds a possible critical point to be at µB/T ≲3. On the other hand, an approximately chiral-spin symmetric temperature window has been discovered above the chiral crossover, Tch<T ≳3Tch, with distinct correlator multiplet patterns and a pion spectral function suggesting resonance-like degrees of freedom, which dissolve graduallly with temperature.

Nonlinear Optomechanically Induced Transparency in a Spinning Kerr Resonator

We theoretically study optomechanically induced transparency in a spinning Kerr-nonlinear resonator. The interplay between the optical Kerr effect and the Sagnac effect provides a flexible tool for modifying the optomechanically induced transparency windows of the signal comparing to the system of a single spinning resonator. It is found that the system will exhibit distinct transparency phenomenon and fast-to-slow light effects. More importantly, a symmetric transparency window appears by adjusting the rotation-induced Sagnac frequency shift to compensate for the Kerr-induced frequency shift. These results open up a new way to explore novel light propagation of optomechanically induced transparency devices in spinning resonators with Kerr nonlinearity.

Tunable quantum interference effects in Floquet two- and three-level systems

Quantum interference effects in the unmodulated quantum systems with light-matter interaction have been widely studied, such as electromagnetically induced transparency (EIT) and Autler-Townes splitting (ATS). However, the similar quantum interference effects in the Floquet systems (i.e., periodically modulated systems), which might cover rich new physics, were rarely studied. In this article, we investigate the quantum interference effects in the Floquet two- and three-level systems analytically and numerically. We show a coherent destruction tunneling effect in a lotuslike multipeak spectrum with a Floquet two-level system, where the intensity of the probe field is periodically modulated with a square-wave sequence. We demonstrate that the multipeak split into multiple transparency windows with tunable quantum interference if the Floquet system is asynchronously controlled via a third level. Based on phenomenological analysis with Akaike information criterion, we show that the symmetric central transparency window has a similar mechanism to the traditional ATS or EIT depending on the choice of parameters, additional with an extra degree of freedom to control the quantum interference provided by the modulation period. The other transparent windows are shown to be asymmetric, different from the traditional ATS and EIT windows. These nontrivial quantum interference effects open up a scope to explore the applications of the Floquet systems.

Improved Wound Healing by Naringin Associated with MMP and the VEGF Pathway.

This study aims to investigate the wound-healing effectiveness of the phenolic compound, naringin, both in vitro and in vivo. Male mice were shaved on their dorsal skin under isoflurane, a biopsy punch was made in four symmetrical circular resection windows (6 mm) to induce a wound. These excision wounds were used to study the topical effects of naringin in terms of various biochemical, molecular, and histological parameters. We observed a significant recovery in the wound area. Increased levels of MMP-2, 9, 14, TIMP-2, VEGF-A, and VEGF-R1 were induced by naringin in the HaCaT cells. The time course experiments further revealed that levels of VEGF-A and B increased within 36 h; whereas levels of VEGF-C decreased. In line with this, VEGF-R3 levels, but not VEGF-R1 and 2 levels, increased soon after stimulation; although the increase subsided after 36 h. Additionally, naringin cream upregulated wound healing in vitro. The blockage of VEGF by Bevacizumab abolished the function of naringin cream on cell migration. Histological alterations in the wounded skin were restored by naringin cream, which accelerated wound healing via upregulated expression of growth factors (VEGF-A, B, and C and VEGF-R3), and thus increased MMP-2, 9, 14 expressions.

Three-photon electromagnetically induced absorption in a dressed atomic system

We present a theoretical treatment for the complete dynamics process of three-photon electromagnetically induced absorption (TPEIA). The nested-cascade doubly dressed TPEIA is considered when two counterpropagating coupling fields are tuned to the upper line in a closed-cycle ladder-type three-level atomic system. The enhancement or suppression of the TPEIA signal relies on the constructive interference between the excitation pathways of doubly dressed states, which can be controlled by changing the intensity of the coupling field. Meanwhile, two symmetrical transparency frequency windows are observed and discussed. The theoretical results and dressed-state analysis are demonstrated experimentally in the 5 S 1 / 2 ( F = 2 ) − 5 P 3 / 2 ( F ′ = 3 ) − 5 D 5 / 2 ( F ′ ′ = 4 ) transition of the 87 R b atoms.

Short-time Fourier Transform Using Odd Symmetric Window Function

In this paper, a novel time–frequency (TF) analysis method, called the short-time Fourier transform using odd symmetric window function (OSTFT), is proposed using odd symmetric window function to replace the conventional even window function of STFT. Different from conventional STFT acquiring the amplitude maximum at time and frequency centers, OSTFT acquires the minimum amplitude of 0. Hence, OSTFT can obtain a TF representation (TFR) with high TF resolution by utilizing the leaked energy rather than restraining it. It is worth to mention that the proposed OSTFT can vitiate the effect of window size we choose on the TFR obtained. Furthermore, it also has a good performance on signals with complex instantaneous frequencies (IFs), even crossing IFs. Because we just replace the conventional window function of STFT, the time-consuming of the proposed OSTFT is at the same level as the conventional STFT. The effectiveness of proposed OSTFT has been validated on two complex multi-component simulated numerical signals and a signal collected from the brown bat.

Demonstration of a p-Type Ferroelectric FET With Immediate Read-After-Write Capability

In this letter, p-type ferroelectric field-effect-transistors (FeFETs) based on HfO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> and embedded in GlobalFoundries 28 nm bulk high- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> metal gate (HKMG) technology (28SLPe) are systematically investigated and compared to their n-type counterparts. We show that the two device types, based on Si channel, exhibit a symmetric memory window (MW) and very similar switching behavior, yet profoundly different trapping kinetics. In contrast to n-FeFETs, p-FeFETs display a full MW immediately after the write operation and apparently no parasitic electron trapping. Based on this, we demonstrate an immediate read-after-write operation. Finally, we illustrate how slight structural changes of the gate stack, such as the introduction of the SiGe channel material, can enhance charge trapping and nullify the above-mentioned advantages.

Edge feature enhancement approach using hilbert transform of Cauchy distribution and its applications

Building on past work showing that the Hilbert transform can be used for edge feature enhancement, a new edge feature enhancement method is developed using a two-dimensional (2D) isotropic Hilbert transform of the Cauchy distribution. First, both the shape of the Hilbert kernel and the Hilbert transform of edge feature models (step and delta) and various simulated signals result in edge feature enhancement, the properties of which are derived and confirmed. Second, Cauchy distribution as low-pass filter is introduced in Hilbert transform to get new edge feature enhancement operator, and its efficiency under various criteria is comprehensively discussed. Third, a 2D isotropic extension is presented using a circularly symmetric window function. Finally, two experiments, including edge detection and image segmentation, are performed to validate the proposed edge feature enhancement method. The experimental results of the method applied to the Berkeley Segmentation Dataset and remote sensing images demonstrate that the new method is effective for edge detection and image segmentation.

The relationship between announcements of complete mergers and acquisitions and acquirers' abnormal CDS spread changes

Employing a sample of 492 merger and acquisition (M&A) announcements from 284 acquirers across North America and Europe between 2005 and 2018, this study analyzes the impact of M&A announcements on an acquirers abnormal CDS spread changes. We nd that spreads from CDS which are written on acquirers increase by 310 bps during a symmetric ve-day event window suggesting that investors expect an increase in the acquirers credit risk exposure due to M&As. Next to this baseline nding, we conduct a large variety of sensitivity analyses to gain more insight into the driving factors of the rising risk perception of CDS investors due to M&A announcements.

Share price reactions to tariff imposition announcements in the Trump era – An event study of the trade conflict

Employing a unique sample of 2,849 tariff imposition announcements by and against the United States (U.S.) over the period from 2018 to 2019, this study analyzes the impact of recent tariff announcements on share prices from 859 U.S. companies. We provide evidence for negative (cumulative) average abnormal stock returns due to tariff announcements during a symmetric three-day event window. We suggest that stock market investors expect adverse impacts of tariff impositions, e.g. a decrease in the companies' future cash flows and a threat of retaliation. The negative wealth effects are observed irrespective of whether the Trump administration announces safeguard tariffs to protect domestic firms or a retaliation is declared by foreign countries. Moreover, building several subsamples, we find that the adverse impact is mostly driven by announcements involving China and is associated with a variety of sector, tariff, trade and firm characteristics.

Investigation on Symmetric and Asymmetric Broadband Low-Loss W-Band Pillbox Windows

In order to develop wide-band low-loss windows for W-band vacuum electronic devices and easily fabricate them, symmetric and asymmetric pillbox windows are investigated and reported in this paper. A symmetric pillbox window and an asymmetric pillow-box window were designed, simulation optimized, fabricated, and tested. The initial parameters for the two pillbox windows were designed by equivalent circuit theory. Computer simulation technology (CST) three-dimensional (3D) electromagnetic simulation software was used to verify and optimize the design. Because of the uncontrollability of welding during the experiment, this article provides two solutions. One is to measure and reprocess the symmetrical pillbox window with the dielectric sheet welded to reduce the influence of welding on the measurement results; the other is an asymmetrical box window which is designed to avoid the error caused by the welding of the box window. The best experimental results for the symmetric pillbox window were |S21| close to 1 dB and reflection parameter |S11| close to 10 dB in the frequency range of 77–110 GHz. The experimental results for the asymmetric pillbox window were |S21| &lt; 1 dB nearly in the frequency range of 76–109.5 GHz. The experimental results show that both solutions efficiently complete the design of broadband pillbox windows and would potentially be operated in the gigahertz millimeter-wave region.

An Iterative Weighted-Mean Filter for Removal of High-Density Salt-and-Pepper Noise

Salt-and-pepper noise, which is often introduced by sharp and sudden disturbances in the image signal, greatly reduces the quality of images. Great progress has been made for the salt-and-pepper noise removal; however, the problem of image blur and distortion still exists, and the efficiency of denoising requires improvement. This paper proposes an iterative weighted-mean filter (IWMF) algorithm in detecting and removing high-density salt-and-pepper noise. Three steps are required to implement this algorithm: First, the noise value and distribution characteristics were used to identify the noise pixels, effectively improving the accuracy of noise detection. Second, a weighted-mean filter was applied to the noisy pixels. We adopted an un-fixed shape symmetrical window with better detail preservation ability. Third, this method was performed iteratively, avoiding the streak effect and artifacts in high noise density. The experimental results showed that IWMF outperformed other state-of-the-art filters at various noise densities, both in subjective visualization and objective digital measures. The extremely fast execution speed of this method is quite suitable for real-time processing.