Search Results (2,539)

This paper presents an all-digital fractional-N phase-locked loop (ADPLL) operating in the 2.86–3.2 GHz range, optimized for IoT and high-frequency RF transceiver applications demanding stringent phase noise performance, fast settling time, and high integration capability. The key innovation lies in the introduction of a bandpass delta-sigma time-to-digital converter (BPDSTDC) that achieves high-resolution phase detection, an extended detection range of ±2$\pi$, and superior noise-shaping characteristics, completely eliminating the complex calibration procedures typically required in conventional TDC designs. The proposed architecture synergistically combines the BPDSTDC with digital down-conversion blocks to extract phase error at baseband, a divider chain integrated with phase interpolators achieving 1/4 fractional resolution to suppress in-band quantization noise, and a wide-bandwidth digital loop filter (>1 MHz) ensuring fast dynamic response and robust stability. The bandpass delta-sigma modulator is implemented with compact resonator structures and a flash quantizer, achieving an optimal balance among resolution, power consumption, and silicon area. The incorporation of highly linear phase interpolators extends fractional frequency synthesis capability without requiring complex digital-to-time converters (DTCs), significantly reducing design complexity and calibration overhead. Fabricated in a 180-nm CMOS technology, the proposed chip demonstrates robust measured performance. The band-pass delta-sigma TDC achieves a low integrated rms timing noise of 183 fs within a 1-MHz bandwidth. Leveraging this low TDC noise, the complete ADPLL exhibits a measured in-band phase noise of −120 dBc/Hz at a 1-MHz offset for a 3.2-GHz output frequency while operating with a loop bandwidth exceeding 1 MHz. This corresponds to a normalized phase noise of −216 dBc/Hz. The system operates from a 1.8-V supply and consumes 10 mW, achieving competitive performance compared with prior noise-shaping TDC-based all-digital PLLs. Full article

Greenhouse gases (GHG), accumulated in the atmosphere, are the main cause of climate change. In 2017, the increase in average temperature was about 1 °C (between 0.8 °C–1.2 °C) above pre-industrial levels. Global warming refers to the increase in air surface, sea surface, and soil surface temperature and according to IPCC (Intergovernmental Panel Climate Change), since the industrial revolution, C emissions are due to land use changes like deforestation, biomass burning, conversion of natural lands, drainage of wetlands, soil cultivation, and tillage. As the world population has increased, world food production has risen too with a subsequent increase in GHG emissions and agricultural production, which is worsened by climate change. Negative consequences are well known such as the loss in water availability and in soil fertility, and pest infestations which are climate change’s effects on agriculture activity. Climate change’s main aftermath is the frequency of extreme weather events influencing crop yields. As climate change exacerbates degradation processes, land management can mitigate its impact and aid adaptation strategies for climate change. About 21–37% of GHGs have been caused by the agriculture activity, so the application of Nature-based Solutions (NbS) like sustainable agriculture could be a way to reduce GHGs worldwide. The aim of this article is to review how NbS may mitigate GHG emissions from soil, with solutions defined as an integrated approach to tackle climate change and to sustainably restore and manage ecosystems, delivering multiple benefits. NbS is a low-cost tool working within and with nature, which holds many benefits for people and the environment. Full article

This paper presents an efficient optimization framework for high-frequency control of active downhole Flow Control Valves (FCVs) under geological uncertainty. Traditional proactive optimization methods for FCVs, while capable of maximizing life-of-field objectives such as Net Present Value (NPV), are computationally prohibitive when frequent updates are required. Conversely, reactive approaches are efficient but often neglect long-term recovery objectives. To address these challenges, we integrate two complementary strategies within a reservoir simulator: a reactive nonlinear programming method to maximize instantaneous cash flow, and a proactive streamline-based Time-of-Flight (TOF) equalization approach to improve sweep efficiency by balancing flood front arrival times. The framework is demonstrated on synthetic and realistic reservoir models, including the Olympus and Almakman references. Results show that, compared to conventional annual control strategies, the proposed approach increases NPV by 15–25% while reducing water handling costs and deferring breakthrough by up to four years. Furthermore, hybrid optimization effectively neutralizes fracture uncertainty, improving both mean recovery and the certainty of outcomes. Three field-scale case studies highlight the practical benefits of FCVs in improving lift performance, maximizing recovery from bypassed hydrocarbons, and reducing the number of wells required to meet production targets. By combining reactive and proactive control within a computationally tractable workflow, this study advances the practical deployment of intelligent completions for closed-loop reservoir management. Full article

By analyzing the influence of the titanium–sapphire (Ti:S) crystal thermal effect on the laser resonator during the generation of a 689 nm laser, the thermal characteristics of the Ti:S crystal operating near the gain edge were investigated in this letter. On this basis, a Ti:S laser with high conversion efficiency suitable for operation at the wavelength of 689 nm was designed. Benefiting from the quantification of thermal effects, the beam waist size at the center of the Ti:S crystal was precisely controlled. Finally, a single-frequency continuous-wave 689 nm laser with an output power of 3.65 W was achieved, and the corresponding optical-to-optical conversion efficiency was up to 23.1%. Then, after locking the transmission peak of the inserted etalon to the resonance frequency of the resonator, the continuous-frequency tuning range of 17 GHz around 689 nm was realized by scanning the voltage applied to the piezoelectric transducer (PZT) mounted on the cavity mirror. Furthermore, based on the realized single-frequency continuous-wave tunable 689 nm laser source, the absorption spectra of strontium atoms near 689 nm were obtained, which established a promising method for preparing 689 nm laser sources designed for strontium atomic ensembles. Full article

A hybrid AI and LLM-enabled architecture is presented for real-time decision support in industrial batch processes, where supervision still relies heavily on human operators and ad hoc SCADA logic. Unlike algorithmic contributions proposing novel AI methods, this work addresses the practical integration and deployment challenges arising when applying existing AI techniques to safety-critical industrial environments with legacy PLC/SCADA infrastructure and real-time constraints. The framework combines deterministic rule-based agents, fuzzy and statistical enrichment, and large language models (LLMs) to support monitoring, diagnostic interpretation, preventive maintenance planning, and operator interaction with minimal manual intervention. High-frequency sensor streams are collected into rolling buffers per active process instance; deterministic agents compute enriched variables, discrete supervisory states, and rule-based alarms, while an LLM-driven analytics agent answers free-form operator queries over the same enriched datasets through a conversational interface. The architecture is instantiated and deployed in the Clean-in-Place (CIP) system of an industrial beverage plant and evaluated following a case study design aimed at demonstrating architectural feasibility and diagnostic behavior under realistic operating regimes rather than statistical generalization. Three representative multi-stage CIP executions—purposively selected from 24 runs monitored during a six-month deployment—span nominal baseline, preventive-warning, and diagnostic-alert conditions. The study quantifies stage-specification compliance, state-to-specification consistency, and temporal stability of supervisory states, and performs spot-check audits of numerical consistency between language-based summaries and enriched logs. Results in the evaluated CIP deployment show high time within specification in sanitizing stages (100% compliance across the evaluated runs), coherent and mostly stable supervisory states in variable alkaline conditions (state-specification consistency ${\Gamma }_s\ge 0.98$), and data-grounded conversational diagnostics in real time (median numerical error below 3% in audited samples), without altering the existing CIP control logic. These findings suggest that the architecture can be transferred to other industrial cleaning and batch operations by reconfiguring process-specific rules and ontologies, though empirical validation in other process types remains future work. The contribution lies in demonstrating how to bridge the gap between AI theory and industrial practice through careful system architecture, data transformation pipelines, and integration patterns that enable reliable AI-enhanced decision support in production environments, offering a practical path toward AI-assisted process supervision with explainable conversational interfaces that support preventive maintenance decision-making and equipment health monitoring. Full article

Time-varying or temporal metamaterials and metasurfaces, in which electromagnetic parameters are deliberately modulated in time, have emerged as a powerful route to engineer wave–matter interaction beyond what is possible in static media. By enabling the controlled exchange of energy and momentum with the fields, they underpin magnet-free nonreciprocity, low-loss frequency conversion, temporal impedance matching beyond Bode-Fano limit, and unconventional parametric gain and noise control. This survey provides a coherent framework that unifies the main theoretical and experimental developments in the area, from early analyses of velocity-modulated dielectrics to recent demonstrations of temporal photonic crystals, non-Foster temporal boundaries, and spatiotemporally driven metasurfaces relevant to nanophotonic platforms. We systematically compare time-varying permittivity, joint $\epsilon$-$\mu$ modulation, time-varying conductivity, plasmas, and circuit-equivalent implementations, including stochastic and rapidly sign-switching regimes, and relate them to acoustic and quantum analogs using common figures of merit, such as conversion efficiency, isolation versus insertion loss, modulation depth and speed, dynamic range, and stability. Our work concludes by outlining key challenges, loss and pump efficiency, high-speed modulation at the nanoscale, dispersion engineering for broadband operation, and fair benchmarking, which must be addressed for robust, integrable temporal metasurfaces. Full article

Harmful algal blooms pose significant risks to water resource management and aquatic ecosystem health, rendering early detection of algal bloom proliferation essential. In this study, we present an electrochemical strategy for the real-time detection of individual Chlorella cells using the single-particle collision method at an ultramicroelectrode (UME). The detection principle relies on monitoring changes in the redox probe flux at the UME induced by attachment of the target. Both diffusional and migrational transport were considered to promote particle collision at the UME. Detection sensitivity for negatively charged microalgae was enhanced by exploiting migration effects. To control migration strength, neutral and charged redox probes were selected, and the ionic strength was adjusted to tune electrostatic attraction, yielding microalgae capture on the UME with a collision frequency that depended on the solution composition. Conversely, migration was suppressed by increasing the ionic strength, and inverse migration was implemented, and resulting collision responses were compared. Furthermore, COMSOL Multiphysics simulations were used to estimate the size of detected Chlorella cells. The collision frequencies expected from diffusion and migration were compared with the experimental values, and a calibration curve relating collision frequency to Chlorella concentration was established. Consequently, this methodology provides a promising platform for the early monitoring of algal blooms by simultaneously determining microalgal size and concentration. Full article

Molecular genotyping is a key factor for plant breeding programming and plant variety protection (PVP). However, its potential still remains to be elucidated when considering ornamental plants like Petunia × hybrida. In this study, a petunia breeding clone collection, including sister line groups, was genotyped through double digest Restriction-site Associated DNA sequencing (ddRADseq), and its genetic diversity and structure were studied. In addition to estimating the high genetic similarity observed among sister lines, this approach allowed the unique discrimination of each clone too. Molecular results agreed with genealogy data, supporting the assessment of genotyping effectiveness. In addition, the minimal number of variants able to uniquely discriminate and/or correctly cluster the experimental lines was investigated. The loci number could be reduced to eight to achieve line discrimination, and a method to identify the specific variant sets is presented. Conversely, to preserve the original clustering with minor adjustments, one hundred loci were required and were obtained through minor allele frequency (MAF) filtering. Moreover, analysis of the chromosomal distribution of variants revealed a predominant accumulation in distal regions. Genetic analyses were repeated considering only variants located in coding sequences and results were in agreement with what previously observed, disclosing the potential of the expressed regions for genotyping purposes. Eventually, the applied approach enabled the investigation of SNPs within genes putatively involved in traits of interest. Our findings encourage the adoption of high-throughput and cost-effective sequencing techniques for petunia genotyping aimed at achieving PVP, supporting new variety registration, and developing marker-assisted breeding (MAB) and marker-assisted selection (MAS) strategies. Full article

California sage scrub is an endangered, shrub-dominated, southern California ecosystem threatened by increasing fire frequencies and type-conversion to non-native grasslands. Once non-native grasses become established, their presence promotes more frequent fires, perpetuating grass dominance. To better understand how fire influences soil seed bank assemblages, we examined soil seed banks in burned and adjacent unburned sage scrub at the Robert J. Bernard Field Station (BFS) in two areas that burned in September 2013 and May 2017. In contrast to a previous soil seed bank study in California sage scrub, we found that unburned soil seed banks in sage scrub at the BFS were primarily composed of native seeds (88% of sprouts in unburned areas were native), highlighting that soil seed bank dynamics differ among California sage scrub sites. Despite burned areas supporting elevated densities of non-native seeds (the majority of which included Festuca myuros, a non-native grass), soil seed banks in our burned areas retained native seeds (21% of sprouts in burned areas were native), including native shrub species, suggesting that not all sage scrub habitats are primed to transition to non-native grasslands following disturbances. However, elevated densities on non-native seedlings in burned areas highlight the vulnerability of sage scrub to fire disturbances and the subsequent establishment of non-native grasses. Full article

Endoscopes are widely used in medicine, making objective evaluation of imaging performance essential for device development and quality assurance. Image resolution is commonly characterized by the modulation transfer function (MTF); however, its interpretation depends critically on how spatial frequency is defined and reported. Because spatial frequency is directly tied to sampling, it can be expressed in different units across the imaging chain, including the object plane, image sensor plane, and digital image domain. Inconsistent conversion between these spaces and domains can mislead comparisons and even alter the apparent ranking of regions of interest (ROIs) or imaging systems. This work presents a systematic analysis of spatial-frequency relationships along the endoscopic imaging chain and provides a practical conversion and interpretation workflow for MTF analysis. The framework accounts for sensor sampling, in-camera processing, resampling or scaling, and geometric distortion. Because geometric distortion introduces position-dependent sampling across the field of view, ROI-specific local-magnification measurements are incorporated to convert measured MTFs to a consistent object space spatial-frequency axis. Two case studies illustrate the implications. First, an off-axis ROI may appear to outperform the image center when MTF is expressed in digital image domain cycles per pixel, but this conclusion reverses after conversion to object space cycles per millimeter using local magnification. Second, resampled image outputs can yield inflated MTF curves unless scaling differences between formats are explicitly incorporated into the spatial-frequency axis. Overall, the proposed conversion and reporting workflow enables consistent and physically meaningful MTF comparison across devices, ROIs, and acquisition configurations when geometric distortion, sampling, or resampling differs, clarifying how optics, sensor characteristics, and image processing jointly determine reported MTF results. Full article

Millimeter-wave (mmWave)/terahertz (THz) devices relying on conventional semiconductor technologies face significant performance bottlenecks, constraining their use in next-generation electronic systems. To address these challenges, this work demonstrates high-performance THz Schottky barrier diodes (SBDs) based on aligned carbon nanotube (ACNT) arrays, and the realization of a D-band second-harmonic frequency multiplier. The ACNT-SBDs exhibit superior electrical and radio-frequency (RF) characteristics, achieving a forward current density of 0.14 mA·μm⁻¹ at −1.3 V and an intrinsic cutoff frequency (f_C) of 506 GHz. The developed small-signal model of diodes shows close agreement with measurements, with S-parameter relative errors below 0.7% from 100 MHz to 67 GHz. The implemented 154 GHz D-band multiplier achieved a maximum output power of −18.97 dBm and a minimum conversion loss of 27.92 dB, outperforming previously reported frequency multipliers based on carbon nanotubes or two-dimensional (2D) materials. This study not only establishes the outstanding high-frequency response, nonlinear efficiency, and integration potential of ACNT-based devices but also provides a promising technical pathway for future THz communication and sensing applications. Full article

Background: Chronic diabetic wounds, particularly diabetic foot ulcers (DFUs), are prone to recurrent infection and delayed healing, resulting in substantial morbidity, mortality, and economic burden. Multifunctional wound dressings that combine antibacterial, antioxidant, conductive, and self-healing properties may help to address the complex microenvironment of chronic diabetic wounds. Methods: In this study, ε-poly-L-lysine and amino-terminated polyethylene glycol were grafted onto carboxylated single-walled carbon nanotubes (SWCNTs) via amide coupling to obtain ε-PL-CNT-PEG. Aminated chondroitin sulfate (CS-ADH) and a catechol–metal coordination complex of protocatechualdehyde and Fe³⁺ (PA@Fe) were then used to construct a dynamic covalently cross-linked hydrogel network through Schiff-base chemistry. The obtained hydrogels (Gel0–3, Gel4) were characterized for photothermal performance, rheological behavior, microstructure, swelling/degradation, adhesiveness, antioxidant capacity, electrical conductivity, cytocompatibility, hemocompatibility, and antibacterial activity in the presence and absence of near-infrared (NIR, 808 nm) irradiation. Results: ε-PL-CNT-PEG showed good aqueous dispersibility, NIR-induced photothermal conversion, and improved cytocompatibility after surface modification. Incorporation of ε-PL-CNT-PEG into the PA@Fe/CS-ADH network yielded conductive hydrogels with porous microstructures and storage modulus (G′) higher than loss modulus (G′′) over the tested frequency range, indicating stable gel-like behavior. The hydrogels exhibited self-healing under alternating strain and macroscopic rejoining after cutting. Swelling and degradation studies demonstrated pH-dependent degradation, with faster degradation in mildly acidic conditions (pH 5.0), mimicking infected chronic diabetic wounds. The hydrogels adhered to diverse substrates and tolerated joint movements. Gel4 showed notable DPPH• and H₂O₂ scavenging (≈65% and ≈60%, respectively, within several hours). The electrical conductivity was 0.19 ± 0.0X mS/cm for Gel0–3 and 0.21 ± 0.0Y mS/cm for Gel4 (mean ± SD, n = 3), falling within the range reported for human skin. In vitro, NIH3T3 cells maintained >90% viability in the presence of hydrogel extracts, and hemolysis ratios remained below 5%. Hydrogels containing ε-PL-CNT-PEG displayed enhanced antibacterial effects against Escherichia coli and Staphylococcus aureus, and NIR irradiation further reduced bacterial survival, with some formulations achieving near-complete inhibition under low-power (0.2–0.3 W/cm²) 808 nm irradiation. Conclusions: A dynamic, conductive hydrogel based on PA@Fe, CS-ADH, and ε-PL-CNT-PEG was successfully developed. The hydrogel combines photothermal antibacterial activity, antioxidant capacity, electrical conductivity, self-healing behavior, adhesiveness, cytocompatibility, and hemocompatibility. These properties suggest potential for application as a wound dressing for chronic diabetic wounds, including diabetic foot ulcers, although further in vivo studies are required to validate therapeutic efficacy. Full article

Baroclinic wave resonance, particularly Rossby waves, has attracted great interest in ocean and atmospheric physics since the 1970s. Research on Rossby wave resonance covers a wide variety of phenomena that can be unified when focusing on quasi-stationary Rossby waves traveling at the interface of two stratified fluids. This assumes a clear differentiation of the pycnocline, where the density varies strongly vertically. In the atmosphere, such stationary Rossby waves are observable at the tropopause, at the interface between the polar jet and the ascending air column at the meeting of the polar and Ferrel cell circulation, or between the subtropical jet and the descending air column at the meeting of the Ferrel and Hadley cell circulation. The movement of these air columns varies according to the declination of the sun. In oceans, quasi-stationary Rossby waves are observable in the tropics, at mid-latitudes, and around the subtropical gyres (i.e., the gyral Rossby waves GRWs) due to the buoyant properties of warm waters originating from tropical oceans, transported to high latitudes by western boundary currents. The thermocline oscillation results from solar irradiance variations induced by the sun’s declination, as well as solar and orbital cycles. It is governed by the forced, linear, inviscid shallow water equations on the β-plane (or β-cone for GRWs), namely the momentum, continuity, and potential vorticity equations. The coupling of multi-frequency wave systems occurs in exchange zones. The quasi-stationary Rossby waves and the associated zonal/polar and meridional/radial geostrophic currents modify the geostrophy of the basin. Here, it is shown that the ubiquity of resonant forcing in (sub)harmonic modes of Rossby waves in stratified media results from two properties: (1) the natural period of Rossby wave systems tunes to the forcing period, (2) the restoring forces between the different multi-frequency Rossby waves assimilated to inertial Caldirola–Kanai (CK) oscillators are all the stronger when the imbalance between the Coriolis force and the horizontal pressure gradients in the exchange zones is significant. According to the CK equations, this resonance mode ensures the sustainability of the wave systems despite the variability of the forcing periods. The resonant forcing of quasi-stationary Rossby waves is at the origin of climate variations, as well-known as El Niño, glacial–interglacial cycles or extreme events generated by cold drops or, conversely, heat waves. This approach attempts to provide some new avenues for addressing climate and weather issues. Full article

The growing demand for electric vehicles, renewable energy systems, and portable electronics has led to the widespread adoption of power conversion systems. Although advanced structures like the superjunction MOSFET have prolonged the viability of silicon in power applications, maintaining its dominance through cost efficiency, Si-based technology is ultimately constrained by its intrinsic limitations in critical electric fields. To address these constraints, research into wide bandgap semiconductors aims to minimize system footprint while maximizing efficiency. This study reviews the semiconductor landscape, demonstrating why Gallium Nitride (GaN) has emerged as the most promising technology for next-generation power applications. With a critical electric field of $3.75\mathrm{MV}/\mathrm{cm}$ ($12.5\times$ higher than Si), GaN facilitates power devices with lower conduction loss and higher frequency capability when compared to their Si counterpart. Furthermore, this paper surveys the GaN ecosystem, ranging from device modeling and packaging to monolithic ICs and switching converter implementations based on discrete transistors. While existing literature primarily focuses on discrete devices, this work addresses the critical gap regarding GaN monolithic integration. It synthesizes key challenges and achievements in the design of GaN integrated circuits, providing a comprehensive review that spans semiconductor technology, monolithic circuit architectures, and system-level applications. Reported data demonstrate monolithic stages reaching $30\mathrm{m}\Omega$ and $25\mathrm{MHz}$, exceeding Si performance limits. Additionally, the study reports on high-density hybrid implementations, such as a space-grade POL converter achieving $123.3\mathrm{kW}/\mathrm{L}$ with $90.9\%$ efficiency. Full article

Background/Objectives: Research across multiple disciplines has explored how nutrition is shaped by social isolation and feelings of loneliness, especially in the elderly population. Evidence from neuroscience highlights that loneliness may alter eating patterns, encouraging emotional eating or other compensatory food behaviors. Conversely, isolation from social contexts is often linked to a reduced variety of nutrient intake. This study set out to examine how psychosocial aspects, particularly social connectedness and feeling alone, relate to adherence to the Mediterranean diet among older adults residing in Sicily, southern Italy. Methods: Dietary habits of 883 adults were collected through food frequency questionnaires and assessed for adherence to the Mediterranean diet. Loneliness was measured through a targeted question from a standardized tool designed to capture depressive symptoms. Direct questions asked whether participants were engaged in social networks, such as family, friends and neighborhoods, or religious communities, in order to assess objective aloneness. Logistic regression analyses were performed to assess associations between variables of interest. Results: After accounting for potential confounders, both loneliness and aloneness showed an association with stronger adherence to the Mediterranean diet. Specifically, individuals experiencing loneliness and aloneness were less likely to have high adherence to the Mediterranean diet (OR = 0.28, 95% CI: 0.15, 0.51, and OR = 0.26, 95% CI: 0.12, 0.54, respectively). Conclusions: These findings underscore the importance of fostering social engagement among older populations, who may particularly benefit from maintaining active social ties to support healthier eating behaviors. Full article