Search Results (533)

Background: Despite the growing demand for amyloid PET quantification, practical challenges remain. As automated software platforms are increasingly adopted to address these limitations, we evaluated the reliability of commercial tools for Centiloid quantification against the original Centiloid Project method. Methods: This retrospective study included 332 amyloid PET scans (165 [¹⁸F]Florbetaben; 167 [¹⁸F]Flutemetamol) performed for suspected mild cognitive impairments or dementia, paired with T1-weighted MRI within one year. Centiloid values were calculated using three automated software platforms, BTXBrain, MIMneuro, and SCALE PET, and compared with the original Centiloid method. The agreement was assessed using Pearson’s correlation coefficient, the intraclass correlation coefficient (ICC), a Passing–Bablok regression, and Bland–Altman plots. The concordance with the visual interpretation was evaluated using receiver operating characteristic (ROC) curves. Results: BTXBrain (R = 0.993; ICC = 0.986) and SCALE PET (R = 0.992; ICC = 0.991) demonstrated an excellent correlation with the reference, while MIMneuro showed a slightly lower agreement (R = 0.974; ICC = 0.966). BTXBrain exhibited a proportional underestimation (slope = 0.872 [0.860–0.885]), MIMneuro showed a significant overestimation (slope = 1.053 [1.026–1.081]), and SCALE PET demonstrated a minimal bias (slope = 1.014 [0.999–1.029]). The bias pattern was particularly noted for FMM. All platforms maintained their trends for correlations and biases when focusing on subthreshold-to-low-positive ranges (0–50 Centiloid units). However, all platforms showed an excellent agreement with the visual interpretation (areas under ROC curves > 0.996 for all). Conclusions: Three automated platforms demonstrated an acceptable reliability for Centiloid quantification, although software-specific biases were observed. These differences did not impair their feasibility in aiding the image interpretation, as supported by the concordance with visual readings. Nevertheless, users should recognize the platform-specific characteristics when applying diagnostic thresholds or interpreting longitudinal changes. Full article

Background/Objectives: Accurate assessment of speech intelligibility is necessary for individuals with motor speech disorders. Transcription or scaled rating methods by naïve listeners are the most reliable tasks for these purposes; however, they are often resource-intensive and time-consuming within clinical contexts. Automatic speech recognition (ASR) systems, which transcribe speech into text, have been increasingly utilized for assessing speech intelligibility. This study investigates the feasibility of using an open-source ASR system to assess speech intelligibility in Hebrew and English speakers with Down syndrome (DS). Methods: Recordings from 65 Hebrew- and English-speaking participants were included: 33 speakers with DS and 32 typically developing (TD) peers. Speech samples (words, sentences) were transcribed using Whisper (OpenAI) and by naïve listeners. The proportion of agreement between ASR transcriptions and those of naïve listeners was compared across speaker groups (TD, DS) and languages (Hebrew, English) for word-level data. Further comparisons for Hebrew speakers were conducted across speaker groups and stimuli (words, sentences). Results: The strength of the correlation between listener and ASR transcription scores varied across languages, and was higher for English (r = 0.98) than for Hebrew (r = 0.81) for speakers with DS. A higher proportion of listener–ASR agreement was demonstrated for TD speakers, as compared to those with DS (0.94 vs. 0.74, respectively), and for English, in comparison to Hebrew speakers (0.91 for English DS speakers vs. 0.74 for Hebrew DS speakers). Listener–ASR agreement for single words was consistently higher than for sentences among Hebrew speakers. Speakers’ intelligibility influenced word-level agreement among Hebrew- but not English-speaking participants with DS. Conclusions: ASR performance for English closely approximated that of naïve listeners, suggesting potential near-future clinical applicability within single-word intelligibility assessment. In contrast, a lower proportion of agreement between human listeners and ASR for Hebrew speech indicates that broader clinical implementation may require further training of ASR models in this language. Full article

This paper presents a structured and experimentally validated approach to the parameter identification, modeling, and real-time speed control of a brushless DC (BLDC) motor. Electrical parameters, including resistance and inductance, were measured through DC and AC testing under controlled conditions, respectively, while mechanical and electromagnetic parameters such as the back electromotive force (EMF) constant and rotor inertia were determined experimentally using an AVL dynamometer. The back EMF was obtained by operating the motor as a generator under varying speeds, and inertia was identified using a deceleration method based on the relationship between angular acceleration and torque. The identified parameters were used to construct a transfer function model of the motor, which was implemented in MATLAB/Simulink R2024b and validated against real-time experimental data using sinusoidal and exponential input signals. The comparison between simulated and measured speed responses showed strong agreement, confirming the accuracy of the model. A proportional–integral (PI) controller was developed and implemented for speed regulation, using a low-cost National Instruments (NI) USB-6009 data acquisition (DAQ) and a Kelly controller. A first-order low-pass filter was integrated into the control loop to suppress high-frequency disturbances and improve transient performance. Experimental tests using a stepwise reference speed profile demonstrated accurate tracking, minimal overshoot, and robust operation. Although the modeling and control techniques applied are well known, the novelty of this work lies in its integration of experimental parameter identification, real-time validation, and practical hardware implementation within a unified and replicable framework. This approach provides a solid foundation for further studies involving more advanced or adaptive control strategies for BLDC motors. Full article

Background/Aim: To date, there have been no data regarding the reproducibility or agreement of meal duration when a test meal is eaten. To confirm the reproducibility and agreement of the meal duration, number of chews, chewing tempo, and number of bites of a test meal, we performed a prospective observation study. Methods: We measured the duration, number of chews, chewing tempo, and number of bites of a test meal (salmon bento) among 33 participants (male: 15; female: 18) aged 20–60 years who ate twice at 2-week intervals to verify the agreement (by Bland-Altman (BA) analysis) and reproducibility (intraclass correlation coefficient (ICC)) by sex. Results: The meal duration (s) and number of bites (times) were significantly greater in the female group (560.4 (128.7) and 731.9 (266.3), p = 0.023; 17.1 (9.9) vs. 26.4 (13.7), p = 0.036), and the number of chews tended to be greater in the female group (752.5 (203.3) vs. 938.1 (375.9), p = 0.083). Meal duration was positively associated with the number of chews (0.64 [0.53, 0.74], p < 0.001) and bites (10.4 [5.1, 15.8], p < 0.001). For both sexes, the % error calculated via BA analysis was high for meal duration, the number of chews, and the chewing tempo (21.4 and 13.4%; 16.5 and 18.5%; and 6.8 and 5.3%, respectively) and low for the number of bites (37.9 and 68.9%). The ICCs were high for meal duration (0.73 and 0.90), the number of chews (0.76 and 0.89), and the chewing tempo (0.76 and 0.90), and low for the number of bites (0.84 and 0.69). Moreover, systematic and proportional errors were found only for the number of bites in the female group (median_difference with 95% CI: −9.00 (−13.00, −2.00); −0.320 (−0.45, −0.093)). Conclusions: Although the sample size was small due to the exploratory nature of the study, meal duration, number of chews, and chewing tempo had high reproducibility and agreement, at least when this test meal was consumed. These measures may indicate individual-specific eating behavior. Full article

Background and Objectives: General-purpose multimodal large language models (LLMs) are increasingly used for medical image interpretation despite lacking clinical validation. This study evaluates the diagnostic reliability of ChatGPT-4o and Claude 2 in photographic assessment of adolescent idiopathic scoliosis (AIS) against radiological standards. This study examines two critical questions: whether families can derive reliable preliminary assessments from LLMs through analysis of clinical photographs and whether LLMs exhibit cognitive fidelity in their visuospatial reasoning capabilities for AIS assessment. Materials and Methods: A prospective diagnostic accuracy study (STARD-compliant) analyzed 97 adolescents (74 with AIS and 23 with postural asymmetry). Standardized clinical photographs (nine views/patient) were assessed by two LLMs and two orthopedic residents against reference radiological measurements. Primary outcomes included diagnostic accuracy (sensitivity/specificity), Cobb angle concordance (Lin’s CCC), inter-rater reliability (Cohen’s κ), and measurement agreement (Bland–Altman LoA). Results: The LLMs exhibited hazardous diagnostic inaccuracy: ChatGPT misclassified all non-AIS cases (specificity 0% [95% CI: 0.0–14.8]), while Claude 2 generated 78.3% false positives. Systematic measurement errors exceeded clinical tolerance: ChatGPT overestimated thoracic curves by +10.74° (LoA: −21.45° to +42.92°), exceeding tolerance by >800%. Both LLMs showed inverse biomechanical concordance in thoracolumbar curves (CCC ≤ −0.106). Inter-rater reliability fell below random chance (ChatGPT κ = −0.039). Universal proportional bias (slopes ≈ −1.0) caused severe curve underestimation (e.g., 10–15° error for 50° deformities). Human evaluators demonstrated superior bias control (0.3–2.8° vs. 2.6–10.7°) but suboptimal specificity (21.7–26.1%) and hazardous lumbar concordance (CCC: −0.123). Conclusions: General-purpose LLMs demonstrate clinically unacceptable inaccuracy in photographic AIS assessment, contraindicating clinical deployment. Catastrophic false positives, systematic measurement errors exceeding tolerance by 480–1074%, and inverse diagnostic concordance necessitate urgent regulatory safeguards under frameworks like the EU AI Act. Neither LLMs nor photographic human assessment achieve reliability thresholds for standalone screening, mandating domain-specific algorithm development and integration of 3D modalities. Full article

Background: Continuous monitoring of hemoglobin (HB) and hematocrit (HCT) during hemodialysis could improve fluid management and patient safety. The Fresenius 5008 dialysis machine includes an ultrasound-based sensor that estimates HB and HCT values, though its accuracy compared to standard laboratory measurements remains unclear. Methods: This exploratory observational study assessed the agreement between sensor-derived and laboratory-derived HB and HCT values in 20 patients at the start of hemodiafiltration. A total of 177 paired blood samples were collected. Results: Sensor values significantly underestimated laboratory HB (9.61 vs. 11.31 g/dL) and HCT (27% vs. 34%) (p < 8 × 10⁻²⁵). Correlations were strong for both parameters (HB: r = 0.788; HCT: r = 0.876). Regression analyses revealed consistent proportional bias. Applying a fixed correction of +1.69 g/dL for HB and +7.55% for HCT eliminated the statistical differences and reduced intercepts in regression models. Bland–Altman plots confirmed improved agreement post-correction. Albumin levels correlated modestly with error magnitude. Conclusions: HB and HCT values from the Fresenius 5008 sensor are strongly correlated with laboratory data but are systematically underestimated at treatment start, likely due to hemodilution. Applying fixed correction factors improves accuracy and supports the sensor’s use for real-time monitoring. Full article

To characterize a phenomenological model of a mechanical oscillator, it is important to know the properties of the envelope of the three main physical motion variables: deviation from equilibrium, velocity, and acceleration. Experimental data show that friction forces restrict the shape of these functions. A linear, exponential, or more abrupt decay can be observed depending on the different physical systems and conditions. This paper aimed to contribute to clarifying the role that some types of friction forces play in these shapes. Three types of friction—constant sliding friction, pressure drag proportional to the square of velocity, and friction drag proportional to velocity—were considered to characterize the line connecting the maxima and minima of displacement for a generic mechanical harmonic oscillator. The ordinary differential equation (ODE), describing the harmonic oscillator simultaneously containing the three types of dissipative forces (constant, viscous, and quadratic), was numerically solved to obtain energy dissipation, and the extrema of both displacement and velocity. The differential equation ruling the behavior of the amplitude, as a function of the friction force coefficients, was obtained from energy considerations. Solving this equation, we obtained analytical functions, parametrized by the force coefficients that describe the oscillator tail. A comparison between these functions and the predicted oscillator ODE extrema was made, and the results were in agreement for all the situations tested. Information from the velocity extrema and nulls was enough to obtain a second function that rules completely the ODE solution. The correlations obtained allow for the reverse operation: from the identified extremum data, it was possible to identify univocally the three friction coefficients fitting used in the model. Motion equations were solved, and some physical properties, namely energy conservation and work of friction forces, were revisited. Full article

Background/Objectives: The SENTIREC-endo study identified a safe sentinel lymph node mapping algorithm combined with PET-positive node dissection, matching radical pelvic and paraaortic lymphadenectomy in high-risk endometrial cancer. The present study evaluated the diagnostic accuracy of FDG-PET/CT for lymph node metastases in the same population based on location, size, and Standardised Uptake Value (SUV), in addition to assessing interrater agreement across three Danish centres. Methods: This prospective multicentre study included women with high-risk endometrial cancer from the Danish SENTIREC study database (2017–2023). All patients underwent preoperative FDG-PET/CT. Diagnostic accuracy was evaluated against a pathology-confirmed reference standard. Interrater agreement was evaluated between trained specialists in Nuclear Medicine. Results: Among 227 patients, 52 patients (23%) had lymph node metastases. FDG-PET/CT identified lymph node metastases with 56% sensitivity (95% CI: 42–68) and 91% specificity (95% CI: 86–94). Positive and negative predictive values were 64% and 87%, respectively. Specificity for paraaortic nodes was high (97%), though sensitivity remained limited (56%). Lymph node size and SUVmax had moderate diagnostic value (AUC-ROC ~0.7). Interrater proportion of agreement was 95% and Cohen’s Kappa κ = 0.84 (95% CI: 0.73–0.94), the latter of which was ‘almost perfect’. Conclusions: FDG-PET/CT had limited sensitivity in lymph node staging in high-risk EC, and the diagnostic accuracy of FDG-PET/CT remains complementary to the sentinel node procedure. Due to its high specificity and strong interrater reliability, FDG-PET/CT is recommended for clinical implementation in combination with the sensitive sentinel node biopsy for the targeted dissection of PET-positive lymph nodes, particularly in paraaortic regions. Full article

Objectives: The objective of this study was to evaluate the agreement and clinical interchangeability of intraocular pressure (IOP) measurements obtained with the mechanical Haag-Streit AT900 Goldmann applanation tonometer (mGAT) and the digital Huvitz HT5000 applanation tonometer (dGAT). Methods: This retrospective comparative study included 53 eyes of 28 patients undergoing routine ophthalmologic evaluation. Each eye underwent IOP measurement using both mGAT and dGAT in a randomized sequence. Central corneal thickness (CCT) was also recorded. Pearson’s correlation coefficient was used to determine correlation between paired IOP measurements. Bland–Altman plots were graphed for the analysis of differences for IOP between the instruments. Results: A total of 53 eyes of 28 patients (15 males) were included in the study. The mean age of the patients was 62.6 years. The mean mGAT and dGAT measurements were 16.3 ± 6.6 mmHg (range 9–50) and 16.4 ± 6.2 mmHg (range 8.8–45.9), respectively (p = 0.53). A strong, significant positive correlation was found for paired IOP measurements by the two instruments (r = 0.98; p < 0.0001). Bland–Altman analysis revealed 95% limits of agreement from −2.5 to +2.3 mmHg, with a small but statistically significant proportional bias favoring mGAT at higher IOP levels. Additionally, 91% of paired measurements were within ±2 mmHg. CCT-related differences were statistically and clinically insignificant. Conclusions: IOP measurements obtained with mGAT and dGAT were highly correlated and clinically interchangeable for the range tested. The Huvitz HT5000 may serve as a reliable alternative to the classic Goldmann tonometer in routine clinical settings. Full article

Background/Objectives: The aim of this study was to investigate the relationship between the PRIMARY score derived from [⁶⁸Ga]Ga-PSMA PET/CT and key clinical and pathological parameters of prostate cancer aggressiveness, including the PSA level, ISUP Grade Group, and D’Amico risk classification, in patients with biopsy-proven prostate cancer. A secondary aim was to evaluate the interobserver agreement of the PRIMARY score in routine clinical practice. Methods: This retrospective analysis included 51 patients with histopathologically confirmed prostate adenocarcinoma who underwent [⁶⁸Ga]Ga-PSMA PET/CT imaging for staging. PRIMARY scores were determined based on the intraprostatic uptake pattern, intensity, and zonal localization. These scores were compared with PSA levels, ISUP GG, D’Amico risk classification, and histopathological features such as the cribriform pattern, intraductal carcinoma, perineural invasion, extraprostatic extension, and lymphovascular invasion. The PRIMARY scores were independently assigned by a total of three nuclear medicine physicians, and interobserver agreement was calculated using Fleiss’ kappa analysis. Results: Significant associations were found between the PRIMARY scores and the PSA level, ISUP Grade Group, and D’Amico risk classification. The most prevalent score was PRIMARY 5 (54.9%), which was significantly associated with ISUP GG 5 and the high-risk category in D’Amico classification. Among patients with PRIMARY Score 2, a substantial proportion (64.7%) had ISUP GG ≥ 3, and 58.8% were in the high-risk group, highlighting the limitations of binary PRIMARY classification. No statistically significant correlations were found between the PRIMARY scores and specific histopathologic features. Interobserver agreement was excellent (κ = 0.833). Conclusions: The PRIMARY score demonstrates high reproducibility and clinical relevance in stratifying prostate cancer aggressiveness. However, the findings challenge the reliability of binary classifications, particularly for patients with Score 2, who may still harbor high-grade disease. Integrating imaging-based scores with clinical and histopathological data is essential, particularly for accurate staging and decision-making regarding active surveillance. Full article

Background/Objectives: In septic shock, microcirculatory dysfunction contributes to organ failure and mortality. While sidestream dark-field (SDF) imaging is the reference method for assessing microvascular perfusion, its complexity limits routine use. This study evaluates near-infrared spectroscopy (NIRS) with vascular occlusion testing (VOT) as a potential bedside tool for monitoring microcirculatory changes following fluid resuscitation. Methods: Sixty-three fluid-responsive patients with sepsis were randomized to receive either 20% albumin or crystalloid. NIRS-VOT and sublingual SDF measurements were obtained at baseline and 60 min post-resuscitation. The reoxygenation slope (ReOx) derived from NIRS was calculated and compared with clinical severity scores and SDF-derived microcirculatory parameters. Results: ReOx significantly increased from baseline to 60 min in the albumin group (p = 0.025), but not in the crystalloid group. However, between-group differences at 60 min were not statistically significant. ReOx at 60 min was inversely correlated with APACHE II score (ρ = −0.325) and lactate (ρ = −0.277) and showed a weak inverse trend with norepinephrine dose. AUROC for ICU survival based on ReOx was 0.616. NIRS ReOx showed weak correlations with SDF parameters, including the number of crossings (p = 0.03) and the consensus proportion of perfused vessels (CPPV; p = 0.004). Conclusions: NIRS-VOT detected microcirculatory trends after albumin administration but showed limited agreement with SDF imaging. These findings suggest that NIRS and SDF assess different physiological domains. Further studies are warranted to define the clinical utility of NIRS as a microcirculation monitoring tool (Clinicaltrials.gov: NCT05357339). Full article

Parkinson’s disease (PD) is a neurodegenerative disorder commonly marked by upper limb tremors that interfere with daily activities. Wearable devices, such as smartwatches, represent a promising solution for continuous and objective monitoring in PD. This study aimed to develop and validate a tremor-detection algorithm using smartwatch sensors. Data were collected from 21 individuals with PD and 27 healthy controls using both a commercial inertial measurement unit (G-Sensor, BTS Bioengineering, Italy) and a smartwatch (Apple Watch Series 3). Participants performed standardized arm movements while sensor signals were synchronized and processed to extract relevant features. Statistical analyses assessed discriminant and concurrent validity, reliability, and accuracy. The algorithm demonstrated moderate to strong correlations between smartwatch and commercial IMU data, effectively distinguishing individuals with PD from healthy controls showing associations with clinical measures, such as the MDS-UPDRS III. Reliability analysis demonstrated agreement between repeated measurements, although a proportional bias was noted. Power spectral density (PSD) analysis of accelerometer and gyroscope data along the x-axis successfully detected the presence of tremors. These findings support the use of smartwatches as a tool for detecting tremors in PD. However, further studies involving larger and more clinically impaired samples are needed to confirm the robustness and generalizability of these results. Full article

Objective: This study aimed to evaluate the reliability and validity of a Food Frequency Questionnaire (FFQ) designed for use in epidemiological studies among populations in Fujian, China. Methods: From September to December 2023, adults aged 18 years and above residing in Fujian Province, southeastern China, were recruited via online survey promotion. Participants completed the FFQ twice with a one-month interval and also completed a 3-day 24 h dietary recall (3d-24HDR), covering two weekdays and one weekend day, during the same period. The reliability of the FFQ was assessed by comparing the average intake of food groups and nutrients between the two FFQs, using Spearman correlation coefficients, intraclass correlation coefficients (ICCs), and weighted Kappa coefficients based on tertile classification. Validity was evaluated by comparing the average intake values from the FFQs and the 3d-24HDR using similar methods, including Spearman correlation, weighted Kappa statistics, and Bland–Altman analysis. Results: A total of 152 participants completed two FFQs (for reliability assessment), and 142 participants completed the 3d-24HDR (for validity assessment). Spearman correlation coefficients for food group intake between the two FFQs ranged from 0.60 to 0.80, with ICCs ranging from 0.53 to 0.91. For energy and nutrient intake, Spearman coefficients ranged from 0.66 to 0.96, and ICCs ranged from 0.57 to 0.97. After tertile classification, less than 15% of participants were misclassified into distant categories. The weighted Kappa coefficients for food groups and nutrients ranged from 0.37 to 0.71 and 0.43 to 0.88, respectively. In comparison with the 3d-24HDR, Spearman correlations for food groups and nutrients ranged from 0.41 to 0.72 and 0.40 to 0.70, respectively. The proportion of participants classified into the same or adjacent tertile was 78.8–95.1%. Weighted Kappa coefficients and Bland–Altman plots indicated acceptable agreement between the FFQ and 3d-24HDR for most nutrients. Conclusions: The FFQ used in this study demonstrated good reliability and moderate-to-good validity. It is suitable for use in dietary assessment in gastric cancer epidemiological studies in Fujian, China. Full article

Background: The early detection of type 1 diabetes (T1D) through screening for major islet autoantibodies is receiving increasing attention as a public health strategy, exemplified by the recent implementation of a pilot pediatric screening program in Italy. The transition from research-based screening to large-scale population initiatives needs automated and standardized assays that are capable of processing extensive sample volumes. Hence, this study aimed to evaluate the analytical performance and comparability of a fully automated chemiluminescence immunoassay (CLIA) compared to a conventional enzyme-linked immunosorbent assay (ELISA) for the detection of three classes of major islet antibodies—anti-GAD (GADA), anti-IA-2 (IA-2A), and anti-ZnT8 (ZnT8A). Methods: A total of 104 serum specimens were analyzed for each autoantibody using both ELISA (RSR and Medyzim, DYNES, DSX) and CLIA (MAGLUMI 800). Assay precision and linearity were assessed through intra-assay variability studies and dilution protocols. Methods agreement was evaluated with Passing–Bablok regression, Spearman’s correlation, Bland–Altman analysis, and Cohen’s kappa statistics. Results: The CLIA showed good precision and excellent linearity across clinically relevant concentration ranges of all islet antibodies. Correlation coefficients and categorical agreement between CLIA and ELISA were high (r > 0.96 and Cohen’s kappa >0.8 for all), with ZnT8A exhibiting the highest concordance. However, proportional biases were found, as CLIA systematically underestimated GADA and ZnT8A levels, while overestimated IA-2A compared to the ELISA. Conclusions: The CLIA displayed satisfactory precision and agreement with ELISA for GADA, IA-2A, and ZnT8A detection. Our findings support the use of these automated immunoassays in large-scale population initiatives for diagnosing T1D, but we also highlight the need for further efforts to achieve better inter-assay harmonization. Full article

Defective phononic crystals (PnCs) have garnered significant attention for their ability to localize and amplify elastic wave energy within defect sites or to perform narrowband filtering at defect-band frequencies. The necessity for continuously tunable defect characteristics is driven by the variable excitation frequencies encountered in rotating machinery. Conventional tuning methodologies, including synthetic negative capacitors or inductors integrated with piezoelectric defects, are constrained to fixed, offline, and incremental adjustments. To address these limitations, the present study proposes an active feedback approach that facilitates online, wide-range steering of defect bands in a one-dimensional PnC. Each defect is equipped with a pair of piezoelectric sensors and actuators, governed by three independently tunable feedback gains: displacement, velocity, and acceleration. Real-time sensor signals are transmitted to a multivariable proportional controller, which dynamically modulates local electroelastic stiffness via the actuators. This results in continuous defect-band frequency shifts across the entire band gap, along with on-demand sensitivity modulation. The analytical model that incorporates these feedback gains has been demonstrated to achieve a level of agreement with COMSOL benchmarks that exceeds 99%, while concurrently reducing computation time from hours to seconds. Displacement- and acceleration-controlled gains yield predictable, monotonic up- or down-shifts in defect-band frequency, whereas the velocity-controlled gain permits sensitivity adjustment without frequency drifts. Furthermore, the combined-gain operation enables the concurrent tuning of both the center frequency and the filtering sensitivity, thereby facilitating an instantaneous remote reconfiguration of bandpass filters. This framework establishes a new class of agile, adaptive ultrasonic devices with applications in ultrasonic imaging, structural health monitoring, and prognostics and health management. Full article