Search for: All records

ABSTRACT Harmonizable processes are a class of nonstationary time series, that are characterized by their dependence between different frequencies of a time series. The covariance between two frequencies is the dual frequency spectral density, an object analogous to the spectral density function. Local stationarity is another popular form of nonstationarity, though thus far, little attention has been paid to the dual frequency spectral density of a locally stationary process. The focus of this paper is on the dual frequency spectral density of local stationary time series and locally periodic stationary time series, its natural extension. We show that there are some subtle but important differences between the dual frequency spectral density of an almost periodic stationary process and a locally periodic stationary time series. Estimation of the dual frequency spectral density is typically done by smoothing the dual frequency periodogram. We study the sampling properties of this estimator under the assumption of locally periodic stationarity. In particular, we obtain a Gaussian approximation for the smoothed dual frequency periodogram over a group of frequencies, allowing for the number of frequency lags to grow with sample size. These results are used to test for correlation between different frequency bands in the time series. The variance of the smooth dual frequency periodogram is quite complex. However, by identifying which covariances are the most pertinent we propose a nonparametric method for consistently estimating the variance. This is necessary for constructing confidence intervals or testing aspects of the dual frequency spectral density. Simulations are given to illustrate our results. 

Subgrade treatment has traditionally been achieved using calcium-based cement. However, it does not necessarily enhance sustainable design. Recently, low-carbon alternatives such as portland limestone cement (PLC) have gained attention as substitutes for traditional cement. In addition, recycled concrete aggregate fines (fRCA), a waste product, have shown potential for application in transportation infrastructure because of their enhancements in pavements. This study investigates the effectiveness of PLC and fRCA in improving soil properties under different environmental stressors. Clayey soil was treated with PLC (10% PLC or 10C) and PLC-fRCA mixtures at different ratios (8% PLC/15% fRCA or 8C_15fRCA and 8% PLC/30% fRCA or 8C_30fRCA). Improvements in strength, stiffness, and volumetric changes were evaluated through unconfined compressive strength and repeated load triaxial tests after exposure to various environmental conditioning cycles (0, 6, and 12 cycles of wet–dry or freeze–thaw) in the laboratory. Results indicated that untreated soil collapsed within two cycles of environmental conditioning. In contrast, treated soils exhibited significant improvements in strength and resilience to environmental stressors. Stiffness also improved with treatment, and despite some reduction after exposure to environmental conditioning, treated specimens maintained relatively higher stiffness values. These enhancements are attributed to the formation of strong binding gels from hydration and secondary reactions among PLC, fRCA, and soil, which exhibit strong resistance to moisture intrusion, helping to preserve their engineering properties. Overall, this study provides a comprehensive understanding of the potential of using fRCA as a co-additive to PLC, offering a more sustainable and durable alternative for the long-term performance of transportation infrastructures. 

The efficacy of metal‐organic chemical vapor deposition (MOCVD)‐based growth for the production of GaAs‐on‐Si virtual substrates following a recently reported process combining low‐temperature growth, thermal cyclic annealing (TCA), and an asymmetric step‐graded filter (ASG) structure is investigated. The impact of multiple process variables—substrate offcut, V/III molecular flux ratio, growth rate, and growth and annealing temperatures—with respect to resultant surface roughness (R_q) and threading dislocation density (TDD) is examined. Similar trends as those reported for the original molecular beam epitaxy‐based process are observed inR_qand TDD for growths on both 2° and 6° offcut substrates. MOCVD process conditions are established for a reduced‐thickness design yielding GaAs virtual substrates on 2° and 6° offcut Si with TDD (≤4.0 × 10⁶ cm⁻²) andR_q(2.4 and 5.3 nm, respectively), comparable to conventional graded buffers, but with a total III–V thickness of less than 2.0 µm. 

Abstract The delivery of nutrients from intermediate waters that form in the Southern Ocean is thought to be a key control on tropical ocean surface productivity. In this paper, we present geochemical evidence that an increase in low‐latitude productivity during the Last Interglacial (LIG) was driven by an increase in the preformed nutrient content of Subantarctic Mode Water (SAMW). We generated records of benthic foraminiferal δ¹³C, δ¹⁸O, Cd/Ca and Mg/Li which are used to reconstruct seawater cadmium, dissolved oxygen, and temperature from a core site in the Florida Straits. The Florida Straits is a location of mixing between SAMW and Northern Component Water, the ratio of which is dependent on the strength of the Atlantic Meridional Overturning Circulation. We find that Late LIG seawater cadmium—which in today's ocean is correlated to phosphate—was substantially higher than the Late Holocene (LH) average at this location, while apparent oxygen utilization was similar during these two periods. Thus, we invoke higher preformed phosphate in the Florida Straits during the Late LIG relative to the LH. Increased SAMW preformed phosphate could be the result of reduced Antarctic Zone winter mixed layer residence time and greater Southern Ocean surface nutrient supply during the Late LIG compared to the LH, as supported by published reconstructions of Southern Ocean biogeochemistry and dynamics. We therefore hypothesize that higher SAMW preformed phosphate would cause an increase in the transport of nutrients into the low latitudes, thereby increasing productivity there. 

Abstract A major open question in the theory of Gorenstein liaison is whether or not every arithmetically Cohen–Macaulay subscheme of can be G‐linked to a complete intersection. Migliore and Nagel showed that if such a scheme is generically Gorenstein (e.g., reduced), then, after re‐embedding so that it is viewed as a subscheme of , indeed it can be G‐linked to a complete intersection. Motivated by this result, we consider techniques for constructing G‐links on a scheme from G‐links on a closely related reduced scheme. Polarization is a tool for producing a squarefree monomial ideal from an arbitrary monomial ideal. Basic double G‐links on squarefree monomial ideals can be induced from vertex decompositions of their Stanley–Reisner complexes. Given a monomial ideal and a vertex decomposition of the Stanley–Reisner complex of its polarization , we give conditions that allow for the lifting of an associated basic double G‐link of to a basic double G‐link of itself. We use the relationship we develop in the process to show that the Stanley–Reisner complexes of polarizations of stable Cohen– Macaulay monomial ideals are vertex decomposable. We then introduce and study polarization of a Gröbner basis of an arbitrary homogeneous ideal and give a relationship between geometric vertex decomposition of a polarization and elementary G‐biliaison that is analogous to our result on vertex decomposition and basic double G‐linkage. 

In the complex traffic environments, understanding how a focal vehicle interacts (e.g., maneuvers) with various traffic elements (e.g., other vehicles, pedestrians, and road infrastructures), i.e., vehicle-to-X interactions (VXIs), is essential for developing the advanced driving support and intelligent vehicles. To derive the VXI scene understanding, reasoning, and decision support (e.g., suggesting cautious move in response of a pedestrian crossing the street), this work takes into account the recent advances of multi-modality large language models (MLLMs). We develop VXI-SUR, a novel VXI Scene Understanding and Reasoning system based on vision-language modeling. VXI-SUR takes in the visual VXI scene, and generates the structured textual responses that interpret the VXI scene and suggests an appropriate decision (e.g., braking, slowing down). We have designed within VXI-SUR a VXI memory mechanism with both scene and knowledge augmentation mechanisms, and enabled scene-knowledge co-learning to capture complex correspondences across scenes and decisions. We have performed extensive and comprehensive evaluations of VXI-SUR based on an open-source dataset with ∼17k VXI scenes. We have conducted extensive experimentation studies upon VXI-SUR, and corroborated VXI awareness, description preciseness, semantic matching, and quality in understanding and reasoning the complex VXI scenes. 

As data‐intensive applications increasingly strain conventional computing systems, processing‐in‐memory (PIM) has emerged as a promising paradigm to alleviate the memory wall by minimizing data transfer between memory and processing units. This review presents the recent advances in both stateful and non‐stateful logic techniques for PIM, focusing on emerging nonvolatile memory technologies such as resistive random‐access memory (RRAM), phase‐change memory (PCM), and magnetoresistive random‐access memory (MRAM). Both experimentally demonstrated and simulated logic designs are critically examined, highlighting key challenges in reliability and the role of device‐level optimization in enabling scalable and commercial viable PIM systems. The review begins with an overview of relevant logic families, memristive device types, and associated reliability metrics. Each logic family is then explored in terms of how it capitalizes on distinct device properties to implement logic techniques. A comparative table of representative device stacks and performance parameters illustrates trade‐offs and quality indicators. Through this comprehensive analysis, the development of optimized, robust memristive devices for next‐generation PIM applications is supported. 

ABSTRACT Two‐photon polymerization (TPP) is a powerful technique to create microscale structures with high precision, offering significant potential in tissue engineering and drug delivery. While conventional TPP‐fabricated drug carriers rely on passive encapsulation, these systems often suffer from low payload capacity and diffusion‐controlled release kinetics. To address these challenges, we present the first demonstration of TPP‐printed polyprodrug microstructures, where the therapeutic agent is covalently integrated into the polymer network as the repeating unit itself. Estrogen‐based diacrylate monomers derived from 17β‐estradiol were synthesized via one‐step esterification/transesterification to create a photocurable resin. Curing under flood UV irradiation yielded a rigid thermoset (E′ ∼2.5 GPa at 25°C) with a glass transition temperature of about 50°C. Using TPP, we fabricated various microscale needles (100 × 100 × 400 µm, 2 µm resolution) from this resin, enabling direct printing of intrinsically therapeutic microstructures without post‐processing drug loading. The cured polymer acts as both a structural matrix and a hydrolytically degradable polyprodrug, releasing estradiol through cleavage of ester bonds. By combining covalent drug‐polymer integration with high‐resolution 3D printing, this work establishes a platform for personalized transdermal drug delivery devices with spatially controlled release profiles determined by microstructure design and polymer degradation kinetics. 

ABSTRACT MicroRNAs (miRNAs) play critical regulatory roles in diverse biological processes and are key biomarkers in a wide range of physiological and pathological conditions, including cancer. However, their inherently low concentrations in biological samples pose a major challenge for reliable detection and quantification. To overcome this limitation, we developed a fluorescence‐based biosensing platform that integrates rolling circle amplification (RCA) and multi‐primed chain amplification (MCA) to enhance signal and detection sensitivity. The system is engineered to allow flexible reconfiguration for different miRNA targets by altering probe and primer sequences. In this modular system, miR‐i, a miRNA commonly expressed in healthy and cancerous samples, serves as a universal initiator for RCA. Signal amplification was subsequently driven by hybridization with two randomly selected miRNAs (miR‐A and miR‐D), enabling evaluation of system performance under varied input conditions. Fluorescence emission was measured following the addition of a molecular beacon and subsequent spectrofluorometric analysis. The biosensor exhibited a strong linear correlation between miRNA concentration and fluorescence intensity, achieving a limit of detection (LOD), and limit of quantification (LOQ) below 10 pM in both buffer and human serum. These findings demonstrate the platform's high sensitivity and robustness. Importantly, modular architecture allows for easy reconfiguration to detect a wide array of miRNAs or other non‐coding RNAs, positioning this platform as a broadly applicable tool for molecular diagnostics beyond any specific disease context.