Search Results (202)

The anatase and rutile phases of titanium dioxide (TiO₂) have been widely studied for their photocatalytic and electronic properties, while the brookite phase is rarely explored. The investigations of intrinsic magnetotransport in mixed-phase systems are limited. Magnetic susceptibility and magnetotransport measurements were performed between 2 K and 300 K in magnetic fields up to 12 T. Both samples with different anatase–rutile–brookite ratios exhibit Curie–Weiss susceptibility. Transport measurements reveal an insulating behavior at low temperatures with activation energies 1–20 meV and signatures of variable-range hopping (VRH) conduction. Strong positive magnetoresistance at low temperatures obeys the Efros–Shklovskii VRH model. Full article

With the continuous expansion and increasing topological complexity of modern power grids, achieving high-precision fault localization under sparse measurement conditions has become a core challenge in the operation and maintenance of smart grids. Existing methods based on deep graph networks generally face complex spatiotemporal coupling between fault types and fault localization. To address this, this paper proposes a recognition method for fault localization based on sparse measurements and spatial configuration. A reinforcement learning algorithm with a Checking-Action mechanism, termed DQN-CA, is adopted to identify optimal PMU installation buses. In parallel, a dual-path spatio-temporal multi-task graph convolutional network, termed ST-MTGCN, is developed to decouple fault-type-related features from topology-sensitive fault-Localization features through a global feature dimensionality-reduction path and a K-hop spatial graph convolution path, thereby accomplishing the fault localization task. Experimental results on the IEEE 39-bus system show that ST-MTGCN achieves 99.68% fault type accuracy, 89.94% fault localization accuracy, and 88.62% accuracy for 185 joint fault type-Localization classes under the OPT13 configuration. Comparative experiments, PMU configuration sensitivity analysis, and ablation studies further demonstrate the effectiveness of the proposed framework under sparse measurement conditions. Full article

In modern radar and electronic countermeasure systems, frequency-agile (FA) signal generators with low phase noise are of vital importance. The optoelectronic oscillator (OEO) is restricted by the periodic boundary condition (PBC), despite its superior performance in phase noise and frequency tunability. This paper proposes a new FA optoelectronic hybrid oscillator scheme, which employs a reconfigurable aperiodic FA filter and a dynamic frequency compensation module to collaboratively break the PBC limitation. It achieves fast switching and fine-grained frequency hopping at the 100 kHz level while maintaining low phase noise. Theoretical and experimental verification show that the system can generate arbitrary FA radio frequency (RF) signals from 1.95 GHz to 2.05 GHz with a tuning range of 10³ times the free spectral range (FSR), and the phase noise reaches −120 dBc/Hz at 10 kHz offset. This study provides a novel technical route for generating narrow-step frequency-agile signals and effectively improves target detection accuracy and anti-jamming performance in electronic warfare applications. Full article

Biosensing performance in graphene-derived field-effect transistors (BioFETs) is widely attributed to surface chemistry, yet the role of the underlying charge transport mechanism remains poorly understood. This work establishes a direct correlation between disorder-driven transport and biosensing transduction in vertical graphene (VG) and nanocrystalline graphite (NCG) FET devices. Temperature-dependent electrical characterization (15–500 K) reveals a hybrid transport regime: three-dimensional Mott variable-range hopping below 240 K, transitioning to thermally activated Arrhenius-type conduction above 240 K. The extracted VRH parameters characteristic temperature T₀, localization length ξ, and density of states N(E_F) quantify fundamentally distinct disorder landscapes: VG operates in a strongly localized, edge-dominated regime, while NCG forms a continuous percolative network with greater transport stability. Surface functionalization via PASE and amine-terminated ssDNA probes, followed by DNA hybridization across four nucleobase systems, demonstrates that the sequence-dependent electrical response is mechanistically interpretable within the VRH–transconductance framework. NCG transduces biomolecular binding through direct charge transfer and hopping pathway perturbation, whereas VG responds through interfacial electrostatic reorganization. These results introduce a unified VRH–transconductance–sensing framework, providing a rational physical basis for next-generation graphene BioFET design. Full article

Multi-hop question answering (MQA) requires models to perform multi-step reasoning and integrate multiple knowledge sources. However, existing methods combining pre-trained language models (PLMs) and graph neural networks (GNNs) often suffer from low computational efficiency, insufficient deep semantic fusion, and imbalanced modeling of heterogeneous relations. To solve these problems, we propose a Dynamic Hierarchical Adaptive Graph Convolution Network (DHACNet). First, to deal with the issues of insufficient computational efficiency and feature interpretability, we introduce Dynamic Sparse Activation (DSA). A trainable gate unit is used to generate importance masks for the encoder outputs, keeping only the task-relevant neurons. This greatly decreases the computational burden and enhances the interpretability of the model’s decisions. Second, to alleviate insufficient deep semantic fusion, we design a Hierarchical Feature Fusion (HFF) mechanism. It adaptively weights and fuses hidden states from different layers, enhancing the extraction and representation of deep textual semantics. Furthermore, for graph structure modeling, we present Adaptive Graph Convolution (AGC), which assigns learnable weights to different edge types in the graph, thereby improving heterogeneous relation modeling. Finally, hierarchical graph pooling is introduced, which integrates attention mechanism and Top-$K$ selection to achieve efficient and robust graph-level representation. The experimental results show that our proposed model maintains the symmetry between the text representation and graph representation through adaptive layered fusion and relational perceptual graph propagation. This symmetry-aware reasoning process encourages semantic consistency during multi-hop inference and makes knowledge integration more robust. Full article

Conventional recommender systems often rely on shallow collaborative signals, which limits their performance under sparse and popularity-skewed conditions. To address this, we propose a knowledge-aware framework that combines an item hypergraph induced by user interaction histories, a top-k user similarity graph, and one-hop, relation-aware knowledge-graph aggregation. The hypergraph branch learns high-order item co-occurrence representations, which are aggregated into initial user vectors and then refined through user similarity propagation. On the item side, user-conditioned relation attention aggregates one-hop KG neighbors to produce semantic item representations. User and item representations are fused by an MLP scorer, and a lightweight popularity-aware post-scoring adjustment can optionally be applied to moderate head-item dominance. Experiments on MovieLens-1M, Last.FM and Book-Crossing show strong performance among the compared baselines in AUC, ACC, and Recall@K. Full article

The number of patients who require endoprosthetic treatment related to osteoporosis has increased in recent years. Vitamin D3 supplementation has long been standard practice in osteoporosis treatment, while vitamin K2 has gained importance. Using our in vitro model, we compared the osteogenic behaviour of primary healthy human osteoblasts (hOBs) and primary osteoporotic human osteoblasts (hopOBs) under unchanged conditions, with vitamin K2, vitamin D3 and the combined addition. Fluorescence microscopy examinations on a plastic surface and a rough titanium surface structure revealed morphological differences. A quantitative analysis of mineralisation and differentiation was performed using an alizarin red S assay and analysis of alkaline phosphatase activity. It was shown that the hopOBs behave differently morphologically on the titanium surface, while hopOBs are particularly noticeable due to the higher number of cell–cell interactions with vitamin K2. The rough surface led to more pronounced mineralisation of the hopOBs. This effect was pronounced under vitamin K2. Vitamin D3 had an effect in the initial phase of hopOB differentiation. Overall, vitamin K2 had a greater influence on the mineralisation of hopOBs than expected. It must be assumed that vitamin K2 plays a significantly greater role in the metabolism of hopOBs than previously assumed. Full article

This study investigates the dielectric relaxation and conduction mechanisms in $S{e}_{90}S{n}_{6}P{b}_4$ chalcogenide glassy material, which is of interest for applications in phase-change memory devices, optical memory, and thermoelectric sensors. Despite previous studies on chalcogenide glasses, the conduction mechanisms at varying temperatures and the role of correlated barrier hopping (CBH) remain unclear. Using impedance spectroscopy in the frequency range 1 Hz–1 MHz at temperatures from 288 K to 318 K, the real ($Z\prime$) and imaginary ($Z″$) parts of the complex impedance were recorded. The sample was also characterized by X-ray diffraction (XRD) to confirm its glassy nature, and X-ray photoelectron spectroscopy (XPS) to determine the surface chemical composition and oxidation states of the elements. Peaks in $Z″$ at each temperature were used to evaluate the relaxation time τ, revealing thermally activated processes with an activation energy of 0.62 eV. Nyquist plots showed semicircular behavior with decreasing radii at higher temperatures, indicating enhanced d.c. conductivity with an activation energy of 0.63 eV. A.C. conductivity analysis demonstrated frequency-dependent behavior consistent with the CBH model, with hopping energy calculated as 0.32 eV. The dielectric loss increased with temperature and decreased with frequency, stabilizing above 250 Hz at 318 K. These findings provide new insights into the dielectric and conduction properties of $S{e}_{90}S{n}_{6}P{b}_4$ glasses, supporting their optimization for practical electronic applications. Full article

The present study aimed to characterize the vegetative growth and phenology of hop cultivars grown in successive seasons with artificial supplementation in a subtropical region. The experiment was conducted in Palotina, Paraná, Brazil (24° S) during the summer 2023–2024, winter 2024, and fall 2024–2025 growing seasons. LED lamps were used to extend the daily photoperiod to 17 h during the vegetative phase. The following hop cultivars were assessed: (a) Alpharoma; (b) Cascade; (c) Chinook; (d) Comet; (e) Dr. Rudi; (f) Hallertau Magnum; (g) Hallertau Mittelfruher; (h) Nugget; (i) Saaz; (j) Smooth; (k) Sorachi Ace; (l) Southern Cross; (m) Triple Pearl; (n) Yakima Gold; (o) Zeus. The assessed variables included plant height (Ht), hop growth rate (HGR), classification of four growth stages, number of lateral shoots, plant fresh mass, and phenology. Ht and HGR were analyzed by means of Gompertz and Gaussian regression models, respectively. The number of lateral shoots per plant and fresh mass were subjected to analysis of variance (ANOVA), and means were grouped using the Scott-Knott test (p < 0.01). Seasonal temperature fluctuations, associated with advancing age and plant establishment throughout successive cycles, acted as important modulating factors in vegetative growth and phenology. In the summer season (2023–2024), Cascade and Hallertau Magnum were characterized as early cultivars. In the winter season (2024), Chinook, Nugget, Saaz, and Zeus were classified as early cultivars, while in the fall season (2024–2025), Dr. Rudi, Sorachi Ace, and Zeus were also considered early hops. The vegetative growth Stage I was found to be critical for earliness classification. The phenological cycle variability was amplified during seasons with higher temperatures. The ‘Sorachi Ace’, ‘Triple Pearl’, and ‘Zeus’ hops were the only ones capable of completing the phenological cycle in all three harvest seasons, with ‘Sorachi Ace’ standing out due to its uniform, stable growth pattern regardless of the season. It is concluded that successive hop cultivation is technically viable for specific hop cultivars grown under subtropical conditions with supplemental lighting. Full article

Frequency-hopping (FH) signals appear as small rectangular pulses in time-frequency spectrograms. At low signal-to-noise ratios (SNRs), noise along the frequency axis, caused by short-time Fourier transform (STFT) spectral leakage, blurs pulse boundaries, while the varying scales of hop rectangles exceed the capacity of a single receptive field. This paper presents YOLO11-FH, a modified YOLO11 detector that introduces two signal-processing-motivated modules. A FreqSmoothBlock (FSB) uses a $(3,1)$ depthwise convolution to smooth exclusively along the frequency axis, while adding only $5C$ parameters. A TFMultiResBlock (TFMRB) fuses three parallel dilated convolution branches (dilation rates of 1, 2, and 3) to cover different hop scales, replacing a heavier C3k2 module. The detection head is further simplified by halving the Bottleneck repeat count and disabling the deep submodule at the P5 scale. On a simulated FH dataset (SNRs ranging from $-15$ dB to $-10$ dB, five jamming types), YOLO11-FH achieves 96.04% mean average precision (mAP)@0.5 and 76.18% mAP@0.5:0.95, outperforming the YOLO11n baseline by 0.95 and 2.91 percentage points (pp) with 2.9% fewer parameters. Full article

This paper presents the results of the preparation and electrical characterization of Ru–Si–O thin-film nanocomposites deposited by magnetron sputtering (pDC) with varying oxygen content ranging from 0% to 50%. Measurements were conducted over a wide frequency range of 50 Hz–5 MHz and temperatures of 20–373 K. Conductivity analysis revealed that DC conduction occurs at low frequencies (≤10³ Hz), while an increase in conductivity associated with electron tunneling mechanisms is observed at higher frequencies. The determined charge transport activation energies range from 3 × 10⁻⁴ eV for the oxygen-free sample to 6 × 10⁻² eV for the high-oxygen samples, indicating a significant effect of composition on the conduction mechanisms. In samples containing 30% and 50% oxygen, two characteristic frequency ranges for the activation of transport processes were observed (e.g., ~10²–10³ Hz and 10⁴–10⁶ Hz), suggesting the coexistence of multiple tunneling mechanisms. Phase angle analysis revealed a transition from values near –90° at 151 K to values near 0° at 333 K, characteristic of parallel RC systems. The minimum dielectric loss tangent occurs in the range of 10³–10⁵ Hz, corresponding to Maxwell–Wagner relaxation. The dispersion coefficient α reaches maximums in two frequency ranges, decreasing with increasing oxygen content. EDS analysis showed a decrease in Ru content from ~24.9 at.% (0% O₂) to ~0.7 at.% (50% O₂) and an increase in oxygen content to ~78 at.% at 10% O₂. The results confirm the transition from metallic conduction to tunneling and hopping mechanisms with increasing oxidation state of the structure. Full article

For the challenging scenario in which only normal node labels are available in semi-supervised graph anomaly detection, existing generative methods usually synthesize abnormal nodes through random perturbation or feature interpolation. However, these methods fail to consider node abnormality comprehensively from both structural and attribute perspectives, resulting in generated pseudo-anomalies of limited quality and insufficient reliability. In order to address this problem, we propose DGAM (dual-guided anomaly mining), a framework for selecting pseudo-anomaly nodes based on the dual-index measurement of topological anomaly and feature consistency. The core of the framework is the joint anomaly evaluation module, which quantifies node anomaly through two computable metrics. The topological boundary score (TBS) measures the boundary of a node’s topological position based on the proportion of connections between a node and labeled normal nodes in its K-hop neighborhood. The feature deviation score (FDS) evaluates the consistency of a node’s local features by calculating the average cosine similarity between its features and those of its K-hop neighbors. The module selects a fixed set of nodes with higher comprehensive anomaly scores from the labeled normal nodes as pseudo-anomalies, so as to construct a training set containing explicit supervision signals. The model adopts a shared encoder architecture and jointly optimizes the classification loss based on pseudo-labels and the embedding regularization loss of the graph nodes to learn a more discriminative node representation. Experimental results on multiple real-world graph datasets show that DGAM can stably improve anomaly detection performance, effectively verifying the effectiveness of the proposed screening mechanism and joint training strategy. Full article

Physical-layer key generation (PLKG) is a technique that produces symmetric encryption keys by exploiting the inherent characteristics of wireless channels. It offers advantages including high physical-layer security, elimination of pre-shared keys, dynamic upgradability, and resistance to quantum attacks, making PLKG a promising security solution for next-generation (6G) networks. However, satellite communication channels exhibit high dynamics and long propagation delays. Characteristics such as large Doppler shifts, short coherence times, and orbital predictability pose severe challenges to PLKG, including reciprocity degradation, low key generation rate (KGR), and susceptibility to channel-prediction attacks. This work proposes a delay-Doppler domain time-hopping key generation scheme (KE-DD-TH) based on Orthogonal Time Frequency Space (OTFS) modulation for high-speed links between Low-Earth-Orbit (LEO)/Medium-Earth-Orbit (MEO) satellites and ground terminals in Ka/Ku bands. The scheme performs non-uniform sampling on the DD domain grid of OTFS symbols using an ephemeris-driven pseudo-random time-hopping sequence generated by cascaded linear feedback shift registers (LFSRs) and a nonlinear matrix transformation. Both legitimate parties estimate the channel only at time-hopping instants and multiply two adjacent estimates to construct an “equivalent channel” matrix, yielding a random source with high entropy, high reciprocity, and low predictability. The eavesdropper’s key disagreement rate (KDR) remains close to 0.5 under all signal-to-noise ratio (SNR) conditions, corresponding to the ideal random-guessing baseline. This indicates that Eve obtains negligible mutual information, i.e., $I(K_A;K_E)\approx 0$. By contrast, the conventional KE-DD scheme allows Eve’s KDR to degrade to 0.014 at 30 dB SNR, indicating near-complete key recovery. The generated keys pass all 12 randomness tests of the NIST SP 800-22 statistical test suite. Full article

University admissions services must answer large volumes of applicant questions that differ substantially in complexity, ranging from repetitive FAQ-type requests to multi-step questions involving programs, entrance exams, admission rules, passing scores, and temporal comparisons. Ungrounded large language model responses are risky in this domain because answers must be factually correct, source-based, and consistent with official institutional data. This paper presents a three-tier hybrid architecture for an admissions dialogue assistant that combines deterministic FAQ matching, hybrid retrieval-augmented generation, and graph-grounded retrieval for complex queries. The first tier, Hash-FAQ, returns verified answers for frequent intents using normalized keys, hash-based lookup, near-duplicate fingerprinting, and semantic similarity checks. The second tier applies hybrid RAG based on BM25 retrieval, vector search, rank fusion, and optional cross-encoder reranking. The third tier uses GraphRAG to extract a constrained k-hop subgraph from a Neo4j knowledge graph built from relational admissions data and document-derived facts. All tiers are synchronized through a versioned indexing pipeline with shadow collections and atomic switching across lexical, vector, FAQ, relational, and graph stores. The system was evaluated using real admissions-campaign traffic and a labeled subset of applicant queries. Tier 1 resolved 68.7% of requests with low latency, while the GraphRAG branch improved factual accuracy with attribution on multi-step queries from 0.55 to 0.91 compared with the non-graph baseline. The main contribution of the study is a production-oriented, cost-aware retrieval-and-generation architecture that links tiered routing, synchronized knowledge publication, source attribution, and operational evaluation for applicant-facing institutional dialogue systems. Full article

Pre-elite female field hockey players have a high incidence of lower extremity injury, highlighting the need for practical and reliable screening approaches. A dual assessment combining Functional Performance Tests (FPTs) with movement quality scoring (QASLS) may provide a more comprehensive evaluation; however, its reliability in this population is unclear. Fifteen pre-elite female field hockey players (16.7 ± 0.7 years) completed an FPT battery (anterior reach (AR), single leg drop vertical jump–land (DVJL), single hop for distance (SHFD), side hop (SH)) on two occasions, 28 days apart. Movement quality was assessed by three raters using QASLS. Reliability was evaluated using ICC with 95% confidence intervals (CI), alongside standard error of measurement (SEM), smallest detectable difference (SDD), and percentage exact agreement (PEA). Test–retest reliability varied across tasks (ICC_2,1 0.33–0.90), with wide confidence intervals indicating uncertainty in several estimates. AR demonstrated the most consistent reliability, supporting its use for monitoring over time. In contrast, the DVJL and SH showed the greatest variability, likely reflecting higher task complexity, while the SHFD required relatively large performance changes to exceed measurement error. Intra-rater reliability for QASLS was consistent across the FPT battery (ICC_2,k 0.79–0.90), whereas inter-rater reliability was more variable (0.38–0.82), indicating rater-dependent differences. PEA demonstrated generally high agreement (60–100%), although lower agreement was observed for pelvic alignment components. These findings support the use of a dual assessment approach as a practicable profiling approach in pre-elite female field hockey, enabling practitioners to identify movement deficits not captured by performance metrics alone. However, variability in complex tasks and between raters highlights the need to consider measurement error and implement standardised rater training when profiling or monitoring performance. Full article