Search Results (440)

Background: Temporomandibular disorders (TMDs) are multifactorial conditions frequently encountered in orthodontic practice, and the independent associations of occlusal and structural variables remain unclear. This case–control study constructed a multivariable model integrating clinical, cephalometric, panoramic, and functional variables to examine their associations with TMD, diagnosed according to the DC/TMD Axis I protocol. Fifty patients with TMD and 50 non-TMD controls were consecutively recruited between October 2024 and December 2025. Occlusal characteristics, lateral cephalometric measurements, and Kjellberg panoramic symmetry indices (SI1/SI2) were assessed using standardized protocols. Candidate variables were initially explored using univariable analyses with false discovery rate adjustment, followed by multivariable Firth penalized logistic regression to reduce small-sample bias and separation. Mandibular deflection (OR = 3.57, 95% CI 1.54–9.09) and deviation (OR = 4.35, 95% CI 1.69–12.50) demonstrated the strongest independent associations with TMD, while SI1 asymmetry (<90%) became significant after multivariable adjustment (OR = 3.57, 95% CI 1.08–14.29). The final model showed apparent discrimination within the study sample (AUC = 0.822; 95% CI: 0.742–0.902). However, this value was calculated using the same dataset and should not be interpreted as validated model performance or compared to other studies. The observed SI1 effect should be interpreted cautiously, as it may reflect model instability due to the relatively small sample size. Within the limitations of this case–control design, functional disturbances showed stronger associations with TMD than static structural variables; however, external validation is required before clinical application. Full article

The self-directed channel (SDC) class of memristors employs a multilayer architecture that is designed to enable robust Ag ion conduction, long cycling lifetime, and thermal stability. While several layers contribute to mechanical and chemical reliability, two layers primarily govern the electrical behavior: the amorphous Ge–chalcogenide active layer that is adjacent to the bottom electrode and the overlying metal–chalcogenide source layer. In this work, we investigate how the variation in the chalcogen species in these two layers influences switching characteristics in the pre-write regime, both in the pristine state and after a write/erase cycle, as well as the conduction behavior at room temperature. The devices were fabricated using Ge-rich chalcogenides containing O, S, Se, or Te, combined with SnS, SnSe, or Ag₂Se metal–chalcogenide layers. The DC current-voltage measurements were analyzed using the standard linearization approaches to examine whether the transport behavior in the pre-write regime exhibits characteristics that are associated with Ohmic, Schottky, Poole–Frenkel, or space charge limited conduction. These measurements specifically probe the pre-write region of the I-V curve, where early ionic redistribution and structural rearrangement precede the abrupt formation of the conductive channels responsible for the resistive switching. The results show that the chalcogen composition strongly affects the threshold voltage, the resistance window, and the onset of field-enhanced transport, reflecting the differences in ionic distribution and channel formation dynamics. The results indicate that transport evolves with a bias and a compliance current, transitioning between regimes that are influenced by the interface injection and bulk-limited conduction, depending on the material stack. These findings clarify the role of chalcogen chemistry in governing the SDC switching behavior and provide guidance for the material selection in application-specific device design. Full article

Background/Objectives: Odontogenic cysts and ameloblastomas (AB) are mostly asymptomatic, often discovered later due to severe symptoms, and only histopathological examination provides definitive diagnosis. AI-assisted diagnostics offer a fast, noninvasive, painless diagnostic tool. To our knowledge, this is the first meta-analysis aiming to evaluate the classification, detection, and segmentation performance of artificial intelligence (AI) for odontogenic cysts and ABs as distinct entities and to determine if it can achieve clinically acceptable accuracy. Methods: Our systematic search was conducted on 11 January 2026, in Medline, EMBASE, and Cochrane Central Register of Controlled Trials without restrictions or filters. Studies comparing AI diagnostics with histopathological diagnostics for odontogenic cysts and ABs were included. Diagnostic parameters, including sensitivity, specificity, and accuracy, were extracted and analyzed; additionally, diagnostic odds ratios were calculated. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Recommendations of the GRADE workgroup were followed to determine the certainty of evidence. Results: Thirteen articles were found eligible, of which seven were included in our meta-analysis. The group with the highest sensitivity (Se) was the “no lesion” (N) group (0.9726, 95% CI 0.9284–1; I2 = 46%), followed by the radicular cyst (RC) (mean 0.9054, 95% CI 0.8051–1; I2 = 89%), dentigerous cyst (DC) (mean 0.8788, 95% CI 0.7828–0.9749; I2 = 93%), odontogenic keratocyst (OKC) (0.763, 95% CI 0.6999–0.8262; I2 = 14%) and AB (mean 0.4369, 95% CI 0.231–0.6429; I2 = 79%) groups. Results for AB, RC, and DC were statistically significant. The AB achieved the highest specificity (Sp) (mean 0.9889, 95% CI 0.9736–1; I2 = 0%), followed by RC (mean 0.9724, 95% CI 0.9431–1; I2 = 79%), DC (mean 0.9516, 95% CI 0.9116 0.9917; I2 = 90%), N (mean 0.9226, 95% CI 0.8385–1; I2 = 95%) and OKC (mean 0.8991, 95% CI 0.8683–0.9298; I2 = 8%) groups. DC, N, and RC had statistically significant results. Diagnostic odds ratios (DOR) showed that classification was better than chance for all lesion types. Conclusions: AI demonstrated high specificity, and is therefore effective in identifying healthy individuals. However, its sensitivity in detecting diseased patients remains suboptimal and requires further improvement. Full article

To improve the process controllability and fabrication uniformity of porous silicon (PS)-based electron emission devices (EEDs), we employed an epitaxial (epi) silicon film as the functional layer, leveraging its advantages of high crystalline quality and flexibility of resistivity modulation regardless of the substrate. Precise modulation of the epi film resistivity was achieved via ion implantation. We investigated the effects of resistivity modulation on the fabrication process and device performance. This scheme enabled the formation of PS through electrochemical etching without illumination, and therefore etch self-termination. As a direct result, the etching uniformity in both the vertical and horizontal directions is enhanced. It then facilitated the optimization of the oxidation of the PS surface, which is essential for EED performance. The devices exhibited a maximum electron emission current density (J_e) of 80 μA/cm² with high stability. Driven under DC mode at a bias voltage (V_ps) of 23 V, J_e decreased temporarily to 28 μA/cm² after 4 h of continuous operation. This study provides a new feasible approach for research on PS EEDs. Full article

Molded inductors play a critical role in a wide range of power electronic devices, where soft magnetic composite materials serve as the key functional component. This study proposes a synergistic optimization strategy, which integrates warm compaction molding with FeSiBCCr/FeNi composite powder, to enhance the overall performance of FeSiBCCr-based amorphous soft magnetic composites (ASMCs) without requiring post-annealing treatment. The results demonstrated that the warm compaction process facilitates effective particle rearrangement, enabling fine FeNi particles to efficiently fill the voids among the large amorphous particles. Moreover, the plastic deformation of FeNi particles during compaction contributes to a significant increase in the density (ρ_c) of the composite, thereby reducing pore-induced magnetic domain wall pinning and substantially improving the soft magnetic properties. With an optimal FeNi content of 30 wt%, the FeSiBCCr/FeNi compound ASMCs exhibit excellent performance. Compared to cold-pressed soft magnetic composites without FeNi fine powder, the effective permeability (μ_e) increases by 55.4% to reach 20.6, with excellent frequency stability. Under the condition of 100 kHz and 50 mT, the total core loss (P_cv) is reduced by 21.8% to 285.6 kW/m³. The DC-bias performance (μ% @ 100 Oe) achieves 94.5%. This study has successfully addressed the key technical challenges hindering the development of the compound ASMCs with high permeability and low core loss for molded inductors, thereby providing a practical and scalable material solution for advanced high-frequency and high-power electronic applications—particularly in emerging domains such as new energy vehicles and artificial intelligence systems. Full article

Rolling-element bearing faults are a primary mechanical failure mode in rotating systems. In Permanent Magnetic DC (PMDC) motor applications operating under variable torque, vibration-based diagnosis is affected by load-dependent excitation and commutation-induced disturbances, which introduce amplitude bias and reduce the reliability of conventional statistical features. This study proposes Cross-Reference Energy Attention (CREA), a physics-guided dual-sensor feature framework for three-class bearing states in PMDC motor systems. CREA isolates fault-relevant content within a hardware-agnostic, empirically selected mid-frequency carrier band and incorporates a spatially separated reference sensor to evaluate transmission consistency. This design suppresses disturbances generated locally by the motor while retaining structurally transmitted bearing signatures. Experiments were conducted on a PMDC motor dynamometer with seeded bearing defects under controlled torque variation. GroupKFold cross-validation was implemented using the acquisition run as the grouping variable to prevent data leakage across runs. Under per-run normalization designed to eliminate amplitude memorization, conventional motor-side baseline features degraded to 0.495 ± 0.110 window-level accuracy, whereas the four-feature CREA representation maintained 0.999 ± 0.002. Systematic ablation and SHAP analysis demonstrate that carrier-band energy features provide the dominant discriminatory contribution, while cross-sensor interaction metrics supply complementary transmission validation consistent with the underlying mechanical model. Full article

This paper presents a comprehensive experimental study addressing the lack of consistent low-temperature data on magnetic materials for high-efficiency cryogenic power electronics. A unified dataset is provided for the first time, covering temperatures from room temperature down to −194 °C, excitation frequencies between 25 kHz and 400 kHz, and technologically relevant flux densities. The investigated materials include MnZn- and NiZn-ferrites, nanocrystalline alloys (Vitroperm, Finemet), and various classes of alloyed powder cores. The characterization comprises magnetic hysteresis behavior, saturation flux density, temperature- and frequency-dependent core losses, permeability, and DC bias performance under cryogenic conditions. The results demonstrate that nanocrystalline materials and selected powder cores (MPP, Edge) exhibit superior cryogenic performance, while ferrites and low-cost powder cores suffer from significant loss increases or magnetic instability at low temperatures. These findings provide a solid basis for the selection and design of magnetic components in next-generation cryogenic power-electronic systems. Full article

TMR-based magnetic encoders provide sensitive SIN/COS signals, but practical accuracy is degraded by channel mismatch and decoder dynamics. This study evaluates an end-to-end embedded implementation on a PMSM (Permanent Magnet Synchronous Motor) bench. We consider amplitude mismatch, quadrature non-orthogonality, and harmonic/noise disturbances in the measured differential channels. We implement a lightweight compensation chain, including fixed-window moving-average filtering, min–max amplitude normalization, and correlation-based quadrature identification with sample-shift correction. We then compare four demodulation configurations under identical sampling and reference alignment to a 24-bit encoder: (A0) conventional second-order PLL (phase locked loop), (A1) compensation + open-loop atan2, (A2) compensation + fixed-${\omega }_n$ third-order PLL, and (A3) compensation + adaptive-${\omega }_n$ third-order PLL. Experiments with a TMR3081 sensor and an STM32 controller show clear differences among A0–A3. In steady operation, A3 removes the DC bias observed with A0 and keeps the angle error within approximately ±0.3° in the evaluated steady window. During commutation and ramp-like segments, PLL-based tracking (A0/A2/A3) is more robust than open-loop atan2 (A1), and bandwidth adaptation in A3 improves the acquisition–noise trade-off within the preset ${\omega }_n$ bounds. These results are reported for this prototype and the tested parameter settings. Full article

Background/Objectives: Transcranial direct current stimulation (tDCS) is increasingly used by athletes, yet sport-performance-enhancement findings are mixed and often small, with outcomes depending on stimulation target, timing, and task demands. Aim: This scoping review mapped and synthesized the soccer-specific trial evidence to identify (i) which tDCS targets and application schedules have been tested in soccer players, (ii) which soccer-relevant outcomes show the most consistent immediate (minutes–hours) or training-mediated benefits, and (iii) where evidence gaps persist. Methods: We conducted a scoping review of clinical trials in footballers, following review best-practice guidance (PRISMA-informed) and a preregistered protocol. Searches (August 2025) spanned PubMed/MEDLINE, ResearchGate, Google Scholar, and Cochrane, using combinations of “football/soccer” and “tDCS/transcranial direct current stimulation,” with inclusion restricted to trials from 2008–2025. Dual independent screening was applied. Of 47 records identified, 21 studies met the criteria. Across these, the total N was 593 (predominantly male adolescents/young adults; wide range of levels). Results: Prefrontal protocols—most commonly left-dominant dorsolateral prefrontal cortex (DLPFC) (+F3/−F4, ~2 mA, ~20 min)—most consistently improved post-match recovery status/well-being (e.g., fatigue, sleep quality, muscle soreness, stress, mood), and when repeated and/or paired with practice, shortened decision times and promoted more efficient visual search. Effects on classic executive tests were inconsistent, and bilateral anodal DLPFC under fatigue increased risk-tolerant choices. Motor-cortex targeting (C3/C4/Cz) rarely changed rapid force–power performance after a single session—e.g., multiple well-controlled trials found no immediate CMJ gains—but when paired with multi-week training (core/lumbar stability, plyometrics, HIIT, sling), it augmented strength, jump height, sprint/agility, aerobic capacity, and task-relevant EMG. Autonomic markers (exercise HR, early HR recovery) showed time-dependent normalization without specific tDCS effects in single-session, randomized designs. In contrast, a season-long applied program that added prefrontal stimulation to standard recovery reported significantly reduced creatine kinase. Across studies, protocols and masking were athlete-friendly and rigorous (~2 mA for ~20 min; robust sham/blinding), with only mild, transient sensations reported and no serious adverse events. Conclusions: In soccer players, tDCS shows a qualified pattern of benefits that follows a specificity model: prefrontal stimulation can support post-match recovery status/well-being and decision efficiency, while M1-centered stimulation is most effective when coupled with structured training to bias neuromuscular adaptation. Effects are generally modest and heterogeneous; practitioners should treat tDCS as an adjunct, not a stand-alone enhancer, and align montage × task × timing while monitoring individual responses. Full article

Introduction: Stroke is a leading cause of adult-onset disability. Non-invasive brain stimulation (NIBS) techniques such as repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), and transcutaneous vagus nerve stimulation (tVNS) are promising adjuncts to upper limb rehabilitation. The use of functional neuroimaging through task functional MRI (fMRI) or functional near-infrared spectroscopy (fNIRS) allows the visualisation of cortical activation patterns associated with stroke-related impairment and recovery. The present study comprehensively reviews the evidence base for the effects of NIBS on clinical and functional neuroimaging outcomes after stroke. Methods: Systematic searches were carried out in MEDLINE and EMBASE via Ovid. Inclusion criteria were clinical trials of adults with stroke and arm weakness undergoing NIBS, with clinical measures of arm function and neuroimaging outcome measures that included either task fMRI or task fNIRS. Two authors independently carried out study screening, risk of bias assessments, and data collection for clinical and neuroimaging outcomes pre- and post-intervention. Results: A total of 17 studies (12 rTMS, 5 tDCS), including 495 participants, met the inclusion criteria. Fifteen studies used task fMRI and four used task fNIRS. Improvements in arm-related motor activity were observed following both rTMS and tDCS. Most studies reported increased activation in ipsilesional sensorimotor areas alongside reductions in contralesional activation. Discussion: rTMS and tDCS may improve upper limb recovery in people with stroke. The increase in the laterality index towards activation of the ipsilesional hemisphere suggests that these NIBS techniques may facilitate neural reorganisation and restoration of motor networks in the affected hemisphere. Full article

This paper proposes an optimized digital predistortion (DPD) framework. Firstly, a peak-detection-based loop-delay estimation is developed by leveraging the unique peak distribution of Orthogonal Frequency Division Multiplexing (OFDM) signals. It reduces the required number of samples to as small as two without compromising estimation accuracy. Then, a Biased Memory Polynomial (BMP) model is proposed for power amplifier modeling. It addresses low-power inaccuracies caused by circuit imperfections (e.g., DC offsets) by adding a bias term to conventional memory polynomials, improving linearization accuracy in low-power regime. Last, to improve the accuracy of coefficient derivation, Memory-Clustering Biased Memory Polynomial (MBMP) is proposed by grouping signals into clusters based on memory-attenuated input vectors and processing them with dedicated sub-models. It improves linearization accuracy in high-power regime. Experimental results demonstrate that the MBMP model reduces normalized mean square error (NMSE) by 16.12 dB, and reduces adjacent channel power ratio (ACPR) by about 12 dBm compared to conventional MP. Full article

Objective: This systematic review aimed to analyze if polywave light curing units can polymerize Bulk Fill resin composites better than monowave. Materials and methods: Inclusion criteria were in vitro studies that evaluated the polymerization of Bulk Fill resin composites by monowave and/or polywave light curing units. Selection of studies, data extraction, and risk-of-bias analysis were performed. Data from selected studies were qualitatively analyzed. A systematic search was performed in May 2025 using PubMed/Medline, EBSCO/Medline, Scopus, and ISI Web of Science databases and grey literature in English, and 788 studies were found. Results: A total of 65 studies were included in the qualitative analysis. Seventeen of them were investigating both monowave and polywave light-curing units for the polymerization of Bulk Fill resin composites. The evidence was graded as medium quality due to the medium risk of bias for most studies. Polywave LED LCUs improved the microhardness ratio, or DC, of Bulk Fill resin composite compared to monowave in 3 of the included studies, while 3 studies revealed that monowave LED LCUs demonstrated a favorable microhardness ratio, or DC, compared to polywave, and the rest of the 11 studies presented material-dependent results. Due to the heterogeneity of the studies included, a meta-analysis was not performed. Conclusion: The existing studies, with their limitations, revealed that polywave light curing units do not seem to have an advantage over monowave in the polymerization of Bulk Fill resin composites. Full article

With the advancement of smart management technologies, research on self-powered silicon PIN photodetectors has become increasingly important. In this paper, a triboelectric nanogenerator (TENG)-driven silicon PIN photodetector based on power management circuitry is proposed. Through rectification and filtering, the pulse signal from the TENG is converted into stable DC voltage, providing reverse bias for the photodetector. With a 5 MΩ sampling resistor, the system generates a voltage of 0.4 V in the absence of light, which gradually increases to 7.3 V and saturates as the light intensity increases to 300 Lux, demonstrating good compatibility and near independence from the TENG rotation speed. Additionally, a light communication system is constructed, with the TENG-driven silicon PIN photodetector as the receiver unit and a signal transmission unit consisting of a finger-pressed TENG combined with an LED. This system successfully transmits Morse code signals such as “SOS” and “TENG”. Full article

Alternating-current poling (ACP) is becoming a mainstream method because of its stronger ability in promoting the piezoelectric performance of ferroelectric single crystals than that of direct-current poling (DCP). A novel approach was developed by incorporating alternating-current poling and direct-current poling as modified alternating-current poling (MACP). According to the comparison of performance differences between AC-poled and DC-poled single crystals, the properties of MACP single crystals under specific conditions were systematically investigated. The improvement of single crystal performance by MACP is manifested by the multi-peak increase in piezoelectric coefficient ($d_{33}$) and relative dielectric permittivity (${\epsilon }_{33}^T/{\epsilon }_0$), and the coupling factor ($k_t$) value under higher DC bias is higher than that under DC polarization, rather than a direct superposition of DCP and ACP. Two optimal polarization windows were found: 0.2–0.25 kV/mm and 0.35–0.6 kV/mm. Compared with DCP, MACP increases the $d_{33}$, ${\epsilon }_{33}^T/{\epsilon }_0$ and $k_t$, of single crystals by up to 45.67%, 21.62%, and 24.54%, respectively. This significant performance improvement, combined with its complexity, provides a new direction for customizing the performance of single crystals. Full article

This study investigates the impact of the self-heating effect (SHE) on single-event transient (SET) sensitivity in triple-layer stacked nanosheet transistors, using technology computer-aided design (TCAD) simulations. The results demonstrate that SHE significantly elevates the channel lattice temperature under DC bias, leading to notable degradation in DC performance metrics, including the drive current (I_ON) and the on/off current ratio. By employing a finer time resolution in the AC simulation, we observed that the device reaches thermal equilibrium on a picosecond timescale. Crucially, SHE is found to exacerbate SET sensitivity markedly. Compared to simulations without SHE, the presence of self-heating increases both the peak transient current and the collected charge at the drain terminal following heavy-ion strikes. Furthermore, the transient response is shown to depend on the thermal history; longer pre-strike heating times amplify the SET peak magnitude, whereas longer cooling times attenuate it. These findings underscore the critical importance of co-optimizing thermal management and radiation hardening in the design of advanced nanosheet technologies. Full article