Search Results (47)

The controlled formation of coherent interfaces in lattice-mismatched II–VI semiconductor heterostructures remains challenging. In this work, ZnSe/ZnS laminar nanomaterials were synthesized by an ultrasound-assisted reverse micelle method to determine how ultrasonic power (150 and 200 W) and water-to-surfactant molar ratio (16:1, 32:1, and 48:1) jointly regulate morphology, crystal structure, lattice accommodation, optical response, and photoelectrochemical behavior. Higher ultrasonic power favored more clearly defined laminar morphologies, whereas increasing the water-to-surfactant ratio produced more heterogeneous growth domains. XRD and Raman spectroscopy confirmed the presence of zinc-blende ZnSe and ZnS phases and provided indirect evidence consistent with partial pseudomorphic lattice accommodation, with calculated mismatch values of 1.59–3.07%, compared with the theoretical value of 4.43%. The apparent optical band gap decreased from 3.39 to 3.06 eV at 200 W and from 3.34 to 3.04 eV at 150 W as the water content increased. Photochronoamperometry showed predominantly cathodic responses, whereas P1R1 exhibited an anodic response. These results establish ultrasonic power and micellar composition as coupled synthesis parameters for tuning lamellar growth, interfacial strain, and optoelectronic response in ZnSe/ZnS heterostructures. Full article

Near-field beam shaping for phased-array antennas operating in the Fresnel region is a challenging non-convex electromagnetic synthesis problem, requiring coherent control of the radiated fields while accounting for the distinct positions, radiation patterns, and polarization states of individual array elements. This paper presents a physics-informed optimization framework for near-field beam shaping based on a unified vector formulation that enables the direct coherent summation of the electromagnetic fields radiated by array elements despite their distinct local spherical coordinate systems. Unlike conventional formulations that rely on repeated transformations between local spherical and global Cartesian coordinate systems, the proposed representation preserves the physical polarization properties of the electromagnetic field while providing a rigorous framework for near-field beam synthesis. To optimize the electromagnetic energy distribution over finite target surfaces rather than a single focal point, an analytical near-field point-focusing solution is integrated into the optimization process through a physically informed initialization strategy. The resulting non-convex optimization problem is solved using a genetic algorithm (GA) to determine the element phase distribution that maximizes electromagnetic energy within the prescribed target region while minimizing undesired field leakage. The proposed methodology is validated through full-wave electromagnetic simulations and extensive experimental measurements using a dedicated phased-array platform, including the design, fabrication, characterization, and calibration of the antenna array and phase-control network. The results demonstrate flexible near-field beam shaping and controlled energy focusing over finite target regions. The proposed framework is applicable to biomedical radar sensing, near-field synthetic aperture radar (SAR) illumination, wireless power transfer (WPT), high-power microwave (HPM) systems, and near-field millimeter-wave communications. Full article

Background: Vitamin D deficiency affects an estimated 40–60% of pregnant women worldwide and is associated with adverse obstetric and neonatal outcomes. Childhood asthma, the most prevalent chronic paediatric disease, has emerged as a plausible programming target, since vitamin D regulates foetal lung branching morphogenesis, calibrates the developing immune system, and modulates decidual and placental function in early gestation. Two landmark randomised trials, VDAART (intervention from weeks 10–18) and COPSAC2010 (from week 24), each reported a 20–25% reduction in offspring asthma or recurrent wheeze at age 3, yet neither reached significance in primary analysis, and the protective signal attenuated by school age. Post hoc stratification by baseline maternal 25-hydroxyvitamin D [25(OH)D] and 17q21 genotype recovered significant effects, raising the possibility that population-average nulls conceal a real but modifier-conditional benefit. Aim: This narrative review re-examines the evidence through a developmental-timing lens, arguing that the periconceptional and first-trimester window, rather than mid-gestation, is the biologically relevant interval for any protective effect. Methods: The review utilises a narrative synthesis of randomised trials, birth-cohort studies, mechanistic investigations, and recent meta-analyses (PubMed, Embase, Cochrane Library to April 2026) relevant to maternal vitamin D, placental biology, and offspring asthma. Findings: The periconceptional weeks coincide with implantation, decidualisation, the embryonic and pseudoglandular phases of airway morphogenesis, and the onset of epigenetic programming, while decidual CYP27B1 expression is prominent in the first trimester. Both trials initiated supplementation after branching morphogenesis was largely complete. Effect modifiers, including baseline 25(OH)D, vitamin D-binding protein, and maternal 17q21 genotype, indicate substantial inter-individual heterogeneity masked in unselected populations. Conclusions: Repositioning preventive supplementation toward the preconceptional and first-trimester window, stratified by baseline status, offers a biologically coherent strategy that existing mid-pregnancy trials have not tested. Adequately powered preconceptional trials with serial biomarker measurement and objective respiratory phenotyping are the priority. Full article

Nickel ferrite (NiFe₂O₄) is one of the most studied inverse-spinel ferrites because it combines moderate saturation magnetization, comparatively high electrical resistivity, chemical stability, and broad synthesis flexibility. Yet the literature shows that the measured structure and magnetism of NiFe₂O₄ are not intrinsic constants; they evolve strongly with dimensionality, size, thickness, strain state, cation distribution, surface spin disorder, and synthesis pathway. This review develops a unified theoretical and literature-based interpretation of how dimensionality reshapes the structural and magnetic behavior of NiFe₂O₄ across bulk ceramics, nanoparticles, one-dimensional nanostructures, polycrystalline thin films, and ultrathin epitaxial films. The review is anchored in the two uploaded nickel ferrite attachments and expanded using internet-sourced journal literature on spinel inversion, surface effects, mechanochemical synthesis, sputtered and pulsed laser deposited thin films, and epitaxial ultrathin-film anomalies. The central novelty of this article is the formulation of a dimensionality-dependent framework in which the observed magnetic response is governed by a competition among three coupled factors: (i) the cation-distribution function, which controls the A–B superexchange balance and therefore the net ferrimagnetic moment; (ii) the microstructural coherence function, which measures how crystallinity, strain, defects, and anti-phase boundaries preserve or degrade exchange continuity; and (iii) the surface/interface spin-order parameter, which quantifies the loss or reconfiguration of magnetic order at free surfaces and buried interfaces. Within this framework, bulk NiFe₂O₄ behaves as a near-equilibrium inverse spinel with relatively stable magnetization, whereas nanoscale NiFe₂O₄ experiences strong spin canting and finite-size suppression due to the growing fraction of disordered surface spins. Thin films introduce a distinct regime in which strain, texture, anti-phase boundaries, substrate mismatch, and growth kinetics determine both anisotropy and magnetization. In ultrathin epitaxial films, off-equilibrium cation redistribution and interface-controlled electronic reconstruction may even generate magnetization values far above bulk expectations. The review also compares major synthesis routes—solid-state reaction, sol–gel, co-precipitation, hydrothermal growth, reactive milling, combustion, pulsed laser deposition, and radio-frequency sputtering—and explains why each route biases the final dimensionality-dependent properties differently. A set of word-style equations is provided to formalize spinel inversion, finite-size suppression, anisotropy scaling, coercivity trends, and superparamagnetic crossover. Beyond summarizing the field, the review proposes a regime map linking dimensionality to characteristic structural defects and magnetic signatures, and it identifies unresolved questions concerning the true origin of enhanced magnetization in ultrathin NiFe₂O₄, the interplay between anti-phase boundaries and strain, and the distinction between intrinsic inversion changes and extrinsic substrate artifacts. The resulting article offers a submission-ready, originality-focused review that positions dimensionality as the master variable governing structure–magnetism correlations in nickel ferrite. Full article

Polymeric fibers represent a vital class of functional materials due to their versatile properties, such as wide availability, low cost, recyclability, biodegradability, and excellent mechanical and chemical stability. Polymer fibers can be fabricated at both micro- and nanoscale dimensions using a variety of processing techniques. This review provides a comprehensive overview of the principal methods employed for polymer fiber preparation, including electrospinning, melt and solution blowing, dry and wet spinning, template synthesis, phase separation, and self-assembly. The technical principles, as well as the advantages and limitations, of each technique are systematically discussed. The review also explores polymeric fibers as smart materials for actuation applications. Particular focus is given to stimulus-responsive fiber systems such as shape memory fibers, hydrogel fibers, liquid crystal fibers, and electroactive polymers. Overall, this review establishes a coherent framework linking polymer fiber fabrication strategies with structure–property–function relationships, offering practical guidance for material selection and accelerating the development of next-generation smart polymer fibers for advanced actuation and multifunctional applications. Full article

Real-time binaural beat synthesis in dynamic acoustic environments is challenged by carrier non-stationarity, interaural phase discontinuities, and processing delay in conventional digital signal processing pipelines. This study proposes a predictive dual-stage neural framework for phase-coherent auditory synthesis under non-stationary acoustic conditions. The framework decouples real-time carrier estimation from phase-coherent signal generation through two specialized modules. An intelligent acoustic sensing module (AI-1) estimates time-varying carrier information across harmonic, fluctuating, and broadband acoustic profiles using a causal neural front-end with an adaptive confidence-driven strategy. A predictive phase-coherent generator (AI-2) then forecasts short-horizon carrier trajectories and drives a discrete-time phase accumulator to maintain continuous phase evolution during binaural beat embedding. Objective evaluation under multiple acoustic profiles and noise conditions shows that the proposed framework maintains strong phase continuity, with a Phase Coherence Factor greater than 0.91, and low artifact levels, with a Signal-to-Artifact Ratio greater than 39.8 dB, under the evaluated conditions. Additional comparisons with conventional DSP baselines, stronger classical F0 estimators, a lightweight neural F0 tracker, and component-wise ablation variants further demonstrate that the performance improvement arises from the combination of adaptive carrier estimation and predictive phase-coherent actuation, rather than from carrier estimation alone. Hardware profiling shows a combined INT8 inference time of 2.4 ms per frame on a resource-constrained Raspberry Pi Zero 2W-class edge device. Importantly, this inference time and the sub-millisecond phase-accumulator resolution should not be interpreted as sub-millisecond end-to-end physical audio latency. The complete system still includes buffering, framing, neural inference, and output processing delay; the proposed method instead reduces effective phase-boundary misalignment through short-horizon predictive compensation. These results support the proposed framework as a lightweight engineering solution for real-time phase-continuous auditory synthesis in dynamic listening environments. The reported PCF and SAR values should be interpreted as signal-level indicators of phase continuity and artifact suppression, rather than as evidence of listener comfort, perceptual preference, or neurophysiological efficacy. Full article

Ground-based scatterometers are widely used for quantitative microwave backscattering measurements in soil moisture retrieval, vegetation monitoring, and satellite scatterometer validation. However, low-cost software-defined radio (SDR) transceivers provide limited instantaneous bandwidth, making it difficult to transmit and process signals with bandwidths on the order of hundreds of MHz for fine range resolution, especially for systems requiring real-time onboard processing. To address this problem, this paper presents a vehicular, fully polarimetric, SDR-based scatterometer that achieves an equivalent wideband response by sequentially transmitting adjacent narrow subbands and coherently synthesizing them onboard. To enable real-time operation on a resource-limited field-programmable gate array/system-on-chip (FPGA/SoC) platform, we adopt a frequency-domain synthesis-pulse-compression pipeline that avoids interpolation and eliminates repeated matched filtering across subbands. A slot-based online phase calibration is performed within the settling window after each fast lock to estimate and compensate random local oscillator (LO) phase offsets, preserving coherent stitching. In addition, pulse repetition within each subband and coherent accumulation are integrated to improve the signal-to-noise ratio (SNR) under real-time throughput constraints. A Zynq-based implementation demonstrates deterministic onboard range-profile output, with a minimum processing latency of about 1.57 ms per frame. Loopback and outdoor experiments validate the equivalent 200 MHz bandwidth (five 40 MHz subbands), achieving approximately 0.75 m resolution and yielding sidelobe metrics consistent with the designed windowing, including a peak sidelobe ratio (PSLR) of −27.43 dB and an integrated sidelobe ratio (ISLR) of −12.38 dB. Field scans over farmland further show consistent ${\mathsf{\sigma }}_0$ trends across incidence angle and azimuth, indicating reliable onboard quantitative backscattering measurement. These results demonstrate that the proposed method provides a feasible solution for deterministic real-time equivalent wideband scatterometry on a low-cost SDR platform. Full article

Microalgae are among the most efficient photosynthetic organisms on Earth, and their capacity for CO₂ fixation directly links the global carbon cycle with green energy conversion, positioning them as strategic biological platforms for achieving carbon neutrality. This review provides a comprehensive and multiscale synthesis of the engineering and biological mechanisms underlying microalgal CO₂ fixation, integrating perspectives from gas–liquid mass transfer, CO₂ assimilation pathways, key enzymatic systems, metabolic regulation, and environmental control. From an engineering standpoint, we analyze the limitations governing CO₂ transfer from the gas phase to the aqueous phase and critically evaluate intensification strategies aimed at enhancing inorganic carbon availability in cultivation systems. At the biological and biochemical levels, we dissect carbon concentrating mechanisms (CCMs), including C₄-like pathways, and elucidate the structural organization, regulatory properties, and functional coordination of Rubisco and carbonic anhydrase systems. Particular emphasis is placed on the coupling between enzyme-level regulation and metabolic flux redistribution, supported by insights from metabolic flux analysis and systems-level modeling, to establish theoretical and engineering foundations for improving carboxylation efficiency. Finally, we propose an integrated roadmap for the future development of microalgal CO₂ fixation technologies, highlighting the convergence of synthetic biology, artificial intelligence, and systems engineering to achieve end-to-end optimization from molecular mechanisms to reactor-scale performance, while enabling the valorization of waste gas streams and circular carbon utilization. This review aims to provide a coherent theoretical framework and forward looking perspective for the development of efficient, intelligent, and sustainable microalgal CO₂ fixation systems. Full article

Based on the thermodynamic design of metallurgical reduction, this paper investigates the thermodynamic principles and reaction regulation mechanism of aluminothermic self-propagating reduction for the in situ synthesis of a Ti₄₅Al₈Nb (at%) titanium–aluminum–niobium alloy. The influence of the aluminum distribution coefficient (ADC) on the self-propagating reaction process was verified via high-temperature thermal state experiments. The results show that the thermodynamically predicted trends of phase composition and alloy composition are consistent with the experimental results, with only a ~20% lateral offset in the ADC. When the ADC is set to 0.8, the mass fractions of Ti, Al, Nb, O, and N in the alloy are 51.8%, 29.5%, 17.4%, 1.2%, and 0.0016%, respectively, with a homogeneous microstructure and inclusion size no larger than 8 µm. The alloy presents a typical coarse-grained structure, where 83.1% of the total grain boundary length is low-angle grain boundaries, and the <111> orientation is dominant. A low-energy coherent interface is formed between the Ti-enriched and Nb-enriched regions by TiAl, TiAl₃ and Al₃Nb phases, which enhances the structural stability of the alloy. Full article

Exercise adaptation depends on overload that is resolved by recovery, yet the same biology becomes maladaptive when immune, endocrine, metabolic, and muscle-centered stress signals fail to normalize. Exercise-induced maladaptation represents a systems-level failure of biological resolution, with direct relevance to disease-like dysregulation. Functional overreaching, non-functional overreaching, and overtraining syndrome remain difficult to diagnose because no single biomarker provides adequate specificity, temporal stability, or clinical portability. This narrative review synthesizes human and mechanistic evidence across proteomics, transcriptomics, metabolomics, endocrine profiling, extracellular vesicles, and mitochondrial quality-control biology to define the molecular architecture most relevant to athlete monitoring. Across these layers, the most coherent signatures cluster in immune-acute-phase activation, redox-buffering strain, endocrine drift, altered substrate availability, excitation–contraction dysfunction, integrated stress-response signaling, and defects in autophagy–mitophagy and lysosomal remodeling. Three translational elements emerge from this synthesis: a systems-convergence model of recovery failure, a staged biomarker deployment hierarchy, and a provisional recovery failure index. The practical priority is therefore not a solitary marker, but serial phenotype-anchored multimarker panels that connect circulating signals with muscle-centered biology and support decision-making before prolonged recovery failure becomes entrenched. Full article

Surface Acoustic Wave (SAW) technology, long central to analog signal processing and RF filtering, is undergoing a major renewal. Driven by advances that decouple SAWs from traditional piezoelectric materials and fixed-function devices, the field is gaining unprecedented control over acoustic, optical, and electronic interactions at the micro and nanoscale. This review synthesizes these developments across four fronts: new physical mechanisms for SAW manipulation, emerging material platforms, ranging from thin films to 2D systems, along with reconfigurable device architectures and circuits, and the expanding landscape of applications they enable. Optical methods are reshaping how SAWs are generated and controlled, bypassing the limits of conventional electromechanical coupling. Coherent optical excitation of high-Q SAW cavities via Brillouin-like optomechanical interactions now grants access to modes in non-piezoelectric substrates such as diamond and silicon, while on-chip SAW excitation in photonic waveguides through backward stimulated Brillouin scattering opens new integrated sensing routes. In parallel, magneto-acoustic experiments have revealed nonreciprocal SAW diffraction from resonant scattering in magnetoelastic gratings. On the device side, ZnO thin-film transistors integrated on LiNbO₃ exploit acoustoelectric coupling to realize voltage-tunable phase shifters; UHF Z-shaped delay lines achieve high sensitivity in a compact footprint; and parametric synthesis of wideband, multi-stage lattice filters targets 5G-class performance. Atomistic simulations show that SAW propagation in 2D MXene films can be engineered via surface terminations, while aerosol jet printing and SAW-assisted particle patterning provide agile, cleanroom-light fabrication of microfluidic and magnetic components. These advances enable applications ranging from hybrid quantum systems and quantum links to lab-on-a-chip particle control, SBS-based and UHF sensing, reconfigurable RF front-ends, and soft robotic actuators based on patterned magnetic composites. At the same time, optical techniques offer non-contact probes of dissipation, and MXenes and other emerging materials open new regimes of acoustic control. Conclusively, they are transforming SAW technology into a versatile, programmable platform for mediating complex interactions in next-generation electronic, photonic, and quantum systems. Full article

This study presents a bibliometric analysis of 461 studies on refugee and (im)migrant education governance, covering the period from 2015 to 2025. All studies were articles indexed in the Web of Science category. The analysis reveals publication trends, conceptual and intellectual structures, and the evolution of themes. Data were analyzed using the Bibliometrix R package. Document coupling and thematic analyses indicate a modular research ecosystem structured around policy governance, inclusion and diversity, refugee education, and access to higher education, with governance-focused scholarship playing a prominent connective role. A systematic review, guided by the PRISMA technique, was conducted to enhance these structural insights, focusing on the 25 most cited and conceptually significant studies identified during the bibliometric phase. The systematic review examined research features, participant demographics, educational settings, and analytical frameworks, with particular attention to the theoretical and operational aspects of governance, bordering, and surveillance themes. The findings reveal a pronounced geographic concentration in affluent Western contexts, especially the United States, alongside a smaller but conceptually significant body of work situated in refugee-hosting regions of the Global South. Education systems are consistently described as mechanisms of migratory governance, in which policies, accountability frameworks, and routine institutional activities establish borders and surveillance. This study combines extensive bibliometric mapping with comprehensive systematic synthesis to present a coherent overview of the conceptualization of refugee and (im)migrant education over the past decade, highlighting ongoing theoretical fragmentation and the need for more cross-scalar, integrative strategies in education governance within migration contexts. Full article

Power system control rooms are undergoing a profound transformation as renewable integration, distributed energy resources, sector coupling, and increasing operational uncertainty reshape the technical, organisational, and cognitive demands of grid operation. At the same time, Digital Twins and Agentic Artificial Intelligence offer new possibilities for monitoring, forecasting, reasoning, and decision support. However, existing control room architectures remain fragmented and insufficiently structured to support the coherent integration of digital models, intelligent reasoning systems, human operators, and regulatory accountability mechanisms in safety-critical power system environments. This article addresses that gap through a PRISMA ScR-informed scoping review combined with a structured architectural synthesis process. The study develops Infostructure as a reference architectural framework for situation awareness in future power system control rooms. The framework is derived from a synthesis of operational challenges, regulatory constraints, and human AI collaboration requirements identified across the scientific and regulatory literature. Infostructure formalises four interrelated architectural layers, Physical, Semantic, Orchestration, and Cognitive, constrained by cross cutting governance and compliance principles. The architectural coverage and internal coherence of the framework are illustrated through representative transmission and distribution system use cases, including wide area disturbance anticipation, distribution level congestion management, and cross organisational coordination during extreme events. A structured research and validation agenda is further outlined to support empirical evaluation and phased implementation. By transforming review-based synthesis into a coherent architectural formalisation, Infostructure contributes a rigorous foundation for the evolution of transparent, accountable, and resilient power system control rooms. Full article

Regarding the problem of the accurate estimation of coherent parameters for the distributed coherent jamming system (DCJS) in active radar applications, this paper first establishes a transmit–receive signal model of the DCJS in the presence of coherent parameter estimation errors. Then, it analyzes and verifies that the generalized cross-correlation function weighting method causes a decrease in the estimation accuracy of coherent parameters due to whitening processing, which in turn impairs the synthesis efficiency of the DCJS. Finally, a coherent parameter estimation method based on frequency-domain feature matching is proposed. The weighting method based on frequency-domain feature matching can effectively preserve the intra-pulse features of signals, thereby improving the estimation accuracy of coherent parameters. The simulation results show that, compared with the existing algorithms, the proposed method improves the time delay estimation accuracy by 27.0% and the phase difference estimation accuracy by 8.3%. Full article

A major challenge in research on cognitive decline and dementia is the identification of at-risk populations in the preclinical phase. In this context, there is growing interest in language markers as early indicators of cognitive impairment. Objectives: This study aims to identify early linguistic markers that may facilitate the detection of individuals at risk of cognitive decline and dementia during the preclinical stage. Additionally, it seeks to evaluate the effectiveness of various assessment techniques and instruments for detecting such language impairments. Methods: A systematic review was conducted in accordance with the PRISMA guidelines, encompassing studies published between 2014 and 2025. A total of 109 articles were included in the qualitative synthesis. Results: The findings indicate that syntactic–structural features—particularly complexity, discourse coherence, and global organization—together with acoustic parameters such as pause duration, exhibit a higher accuracy and predictive value for the early diagnosis of cognitive decline and its progression to dementia. Furthermore, narrative-based tasks analyzed through automated methods demonstrate significant advantages for the assessment of language impairments. Conclusions: The analysis of language markers—particularly through the examination of syntactic complexity, acoustic features, and automated narrative assessments—represents a promising and effective approach for the early identification of cognitive impairment and the prediction of subsequent dementia onset. Full article