Search Results (61)

Behavioural management strategies used in paediatric dentistry have neurobiological effects. This scoping review aimed to map the existing literature on the neurobiological effects of non-invasive behavioural management strategies used in paediatric dentistry. The study protocol was registered on the Open Science Framework (registration number: OSF.IO/9EZVT). A search was conducted on PubMed, Web of Science, Scopus, Google Scholar, and African Journals Online (AJOL) for studies published up to May 2025. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Studies were included if they assessed non-invasive behavioural strategies in children aged 0–17 years undergoing dental procedures and reported at least one neurobiological or physiological outcome. The data were summarised descriptively, and key findings were thematically synthesised to identify trends in behavioural strategy types and neurobiological outcomes measured. Out of 1720 records retrieved, 35 studies met the inclusion criteria. These included randomised and non-randomised controlled trials and observational studies conducted in 13 countries on five continents involving 2919 children. The behaviour management strategies identified were 18 in number, with distraction (n = 19) and tell–show–do (n = 17) being the most frequently applied. The neurobiological outcomes assessed included anxiety (n = 36), pain perception (n = 8), fear (n = 7), and stress response (n = 1). Their physiological regulation was assessed using heart rate (n = 26), oxygen saturation (n = 10), blood pressure (n = 8), pulse rate (n = 6), cortisol (n = 4), respiratory rate (n = 1), and oxytocin (n = 1). Behavioural assessment tools used were classified into Child-Reported Anxiety and Fear Instruments (n = 23), Pain Perception Instruments (n = 9), Clinician/Observer-Rated Behavioural and Anxiety Scales (n = 18), and Parental and Proxy Reports (n = 2). This review underscores the emerging evidence that non-invasive behavioural strategies may be linked to neurobiology in paediatric dentistry. More studies are needed in new countries to be able to map the possible impact of context and culture on study findings. Full article

Non-invasive, real-time monitoring of plant water status is critical for precision agriculture and plant physiology. However, existing methods often lack continuous in situ measurement capability or are limited by temporal resolution. This paper proposes a novel non-invasive method based on xylem electrical conductivity, inspired by industrial non-contact fluid measurement. As a ground-based complement to remote sensing, this approach demonstrates the feasibility of online, in situ, and non-invasive monitoring of water stress in grapevine stems under controlled laboratory conditions. The industrial C⁴D sensing system is adaptively modified into a specialized Plant-C⁴D sensor with an array-based design for batch signal acquisition. To validate the electrical response to water loss, a gravimetric natural dehydration experiment was conducted, demonstrating a clear correlation between electrical signals and water content changes in detached stem samples. Full-day dynamic experiments are conducted under three conditions: normal water supply, varying water stress, and plant inactivation. Sensitive characteristic parameters are extracted through signal analysis, and a pattern recognition framework is established to eliminate environmental interference and suppress individual differences. Experimental results on 24 plant samples (Shine Muscat) show that the method accurately discriminates viable from inactivated plants with an accuracy of 91.67% (22/24 correct). Furthermore, the Fuzzy C-Means (FCM) clustering algorithm successfully quantifies the severity of water stress in viable plants, yielding results consistent with actual water supply conditions. While these findings demonstrate the capability of Plant-C⁴D sensor to capture stem water status-related information, the current results do not establish full physiological validation, warranting further exploration with in vivo experiments. Full article

Press-pack insulated-gate bipolar transistor (IGBT) devices are key components of modular multilevel converter (MMC)-based HVDC systems, yet the parallel connection of tens of chips inside one sealed housing makes their internal aging difficult to monitor—existing methods cannot determine which chip or thermal interface has degraded without invasive sensing. This paper proposes a two-layer aging condition monitoring framework based solely on non-invasive external case temperature measurements, comprising an online detection layer and a detection layer. For the diagnosis layer, a coupled thermal network state-space model of the press-pack module is established; its observability matrix is shown to be of full rank, proving that aging at any internal location is detectable from external case temperatures, and a steady-state sensitivity analysis reduces the required measurement to the module-center case-temperature pair and yields a failure-signature rule that discriminates five aging modes. A 3D electrothermal finite-element model, validated against fiber Bragg grating (FBG) measurements on an MMC sub-module with deviations below 1.2 °C at all load levels, is then used to build an aging fingerprint database of 270 scenarios that maps a measured case-temperature distribution to the aging location, the affected component, and the severity of any cooling-system degradation. For the detection layer, a deep neural network (DNN) trained only on healthy-state data provides online early warnings through its prediction residual. Experiments on a 2.2 kV/2100 A MMC sub-module platform and a solid-state DC–DC transformer platform confirm that cooling-system degradation is reliably detected and that the detection layer transfers across converter types. Even in the least sensitive aging case, the predicted case-temperature signature (0.036 °C) exceeds the 0.01 °C resolution of standard thermocouple instrumentation, which indicates that genuine device aging would be resolvable as well. The framework provides a non-invasive online health-monitoring solution that can also locate the degraded element in high-power press-pack devices. Full article

In proton beam therapy, ideally, beam monitoring should be non-invasive to provide online real-time feedback, such that the total dose delivered to the patient is not significantly affected. The invasiveness of the Supersonic Gas-Curtain-Based Ionization Profile Monitor (SGC-IPM) system was quantified by perturbation in beam current and transverse beam profile parameters induced by the supersonic gas-curtain for a 4.9–5.3 keV electron beam, representing a worst-case scenario where perturbations can be more easily observable. The experimentally measured gas-curtain effects on transverse beam parameters (≤2%), intensity (≤−1%) and beam current (≤−1%) were small in magnitude and largely below resolution limits. To confirm these effects, order-of-magnitude beam–gas interaction approximations were calculated for the experimental energy range, demonstrating negligible energy loss with minor scattering, broadly consistent with the experimental results. Clinical proton beam gas-curtain predictions (70–250 MeV) indicate a further reduction of ∼${10}^4$ compared to the experimental observations. Even under the conservative electron beam conditions used in this study, the observed perturbations were minor or unresolvable and measured effects were significantly smaller than spatial and dosimetry scales relevant to proton radiotherapy. Overall, the experimental measurements and supporting order-of-magnitude estimates demonstrate that the SGC-IPM introduces negligible perturbations to beam parameters and is predicted to provide non-invasive beam profile monitoring for clinical proton beam diagnostics. Full article

The measurement of the magnetic field generated by a flowing current constitutes a non-invasive sensing technique for online energy consumption monitoring. In this work, based on the use of low-cost linear Hall effect sensors, a low-form-factor custom contactless ammeter probe is presented. The differential configuration of the sensor module and the subsequent fully digital programmability in range and sensitivity, together with the included self-calibration and compensation circuits for mismatching, managed by a microcontroller, allow for optimum detection for both continuous and mains current with a resolution of 10 mA for input ranges of 2 A. The proposed ammeter power consumption and measurement accuracy in different scenarios are tested, including the power monitoring of an IoT-based device, obtaining results matched to those featured by a commercial oscilloscope current probe, which validates its suitability and reliability as autonomous low-cost probe for portable contactless power monitoring. Full article

Non-invasive temperature estimation during online operation is a critical challenge in enclosed micro-reaction systems, particularly when the thermal mass of the working fluid varies dynamically or is uncertain. Conventional model-based approaches typically rely on fixed thermal parameters, leading to significant estimation errors when the actual reagent volume deviates from nominal conditions. To address this limitation, this study proposes a volume-adaptive temperature estimation framework applied to an ultrafast quantitative polymerase chain reaction (qPCR) system. By modeling the heat-transfer pathways via a simplified resistance–capacitance (RC) network, a nonlinear least squares (NLS) algorithm within an output-error (OE) framework is employed to identify key thermal parameters online. The framework separates the estimation into an offline calibration stage—where a thermocouple-equipped chip provides ground-truth data—and an online deployment stage that relies solely on non-invasive external measurements. This approach allows the system to explicitly compensate for volume-induced variations in thermal inertia. Validation experiments on an ultrafast qPCR platform with reagent volumes ranging from 100 to 250 $\mathsf{\mu }\mathrm{L}$ and heating rates exceeding 20 °C/s demonstrate that the method achieves robust performance, maintaining a mean absolute error (MAE) of reagent temperature at 0.24 °C and restricting the average volume estimation error to within 1.37 $\mathsf{\mu }\mathrm{L}$. DNA gel electrophoresis results further confirm the biological reliability of the temperature prediction strategy by verifying amplification specificity. This work provides a generalised solution for precise thermal management in micro-systems subject to variable thermal loads. Full article

The objective of this study was to evaluate the impact of the material (plastic or glass) and color (green or colorless) of extra virgin olive oil (EVOO) and virgin olive oil (VOO) bottles on the acquisition of SORS spectra using portable equipment. Sixteen bottles of EVOO and three bottles of VOO were analyzed, including different volumes. A range of similarity indices was calculated between vial-reference (offline measurements) and bottles (online measurements), including R², COS θ, NEAR, and a new index called WSI (Weighted Similarity Index). WSI is calculated from the pondered linear combination of the previous three, and a threshold of >0.95 is established as high similarity. The results showed that plastic bottles, regardless of color and volume, and colorless glass bottles had WSI values > 0.95. In contrast, green glass bottles demonstrated a lower degree of similarity (WSI < 0.95), which impacted the reliability of their spectral fingerprints. A hierarchical cluster analysis (HCA) was performed by locating EVOO bottles according to their material in two clusters. A study of storage under optimal, non-optimal, and commercial conditions showed that both EVOO and VOO maintain highly similar spectral profiles for 10–18 days (WSI > 0.965), even in bottles purchased in supermarkets. These results demonstrate that the SORS technique is suitable for the direct analysis of olive oils in plastic and colorless glass containers, without the need to open the bottles. The SORS technique is a fast, reliable, non-invasive, and non-destructive tool for quality control of olive oil. Full article

Core body temperature is a critical physiological indicator for assessing and diagnosing animal health status. In bovines, continuously monitoring this metric enables accurate evaluation of their physiological condition; however, traditional rectal measurements are labor-intensive and cause stress in animals. To achieve intelligent, contactless temperature monitoring in cattle, we proposed a non-invasive method based on thermal imaging combined with environmental data fusion. First, thermal infrared images of the cows’ faces were collected, and the You Only Look Once (YOLO) object detection model was used to locate the head region. Then, the YOLO segmentation network was enhanced with the Online Convolutional Re-parameterization (OREPA) and High-level Screening-feature Fusion Pyramid Network (HS-FPN) modules to perform instance segmentation of the eye socket area. Finally, environmental variables—ambient temperature, humidity, wind speed, and light intensity—were integrated to compensate for eye socket temperature, and a random forest algorithm was used to construct a predictive model of rectal temperature. The experiments were conducted using a thermal infrared image dataset comprising 33,450 frontal-view images of dairy cows with a resolution of 384 × 288 pixels, along with 1471 paired samples combining thermal and environmental data for model development. The proposed method achieved a segmentation accuracy (mean average precision, mAP_50–95) of 86.59% for the eye socket region, ensuring reliable temperature extraction. The rectal temperature prediction model demonstrated a strong correlation with the reference rectal temperature (R² = 0.852), confirming its robustness and predictive reliability for practical applications. These results demonstrate that the proposed method is practical for non-contact temperature monitoring of cattle in large-scale farms, particularly those operating under confined or semi-confined housing conditions. Full article

The operational reliability of Insulated Gate Bipolar Transistor (IGBT) modules in demanding transportation applications, such as traction systems, is critically challenged by solder layer and bond wire failures under cyclic thermal stress. To address this, this paper proposes a novel health monitoring framework that innovatively synergizes micro-scale spatial thermal analysis with microsecond electrical dynamics inversion. The method requires only non-invasive temperature measurements on the module baseplate and utilizes standard electrical signals (load current, duty cycle, switching frequency, DC-link voltage) readily available from the converter’s controller, enabling simultaneous diagnosis without dedicated voltage or high-bandwidth current sensors. First, a non-invasive assessment of solder layer fatigue is achieved by correlating the normalized thermal gradient ($\nabla T_{\mathrm{P}}$) on the baseplate with the underlying thermal impedance ($Z_{\mathrm{JC}}$). Second, for bond wire aging, a cost-effective inversion algorithm estimates the on-state voltage ($V_{\mathrm{ce},\mathrm{on}}$) by calculating the total power loss from temperature, isolating the conduction loss ($P_{\mathrm{cond}}$) with the aid of a Foster-model-based junction temperature ($T_{\mathrm{J}}$) estimate, and finally computing $V_{\mathrm{ce},\mathrm{on}}$ at a unique current inflection point ($I_{\mathrm{C},\inf }$) to nullify $T_{\mathrm{J}}$ dependency. Third, the health states from both failure modes are fused for comprehensive condition evaluation. Experimental validation confirms the method’s accuracy in tracking both degradation modes. This work provides a practical and economical solution for online IGBT condition monitoring, enhancing the predictive maintenance and operational safety of transportation electrification systems. Full article

Background: Brain–Computer Interfaces (BCIs) based on Steady-State Visually Evoked Potentials (SSVEPs) and Extended Reality (XR) offer promising solutions for highly wearable applications, but their classification performance can be affected by systematic effects in stimulus presentation. Novelty: This study introduces a novel online compensation method to compensate for systematic effects in the Refresh Rate (RR) of XR displays, enhancing SSVEP classification without requiring additional training or invasive measurements. Methods: A non-invasive monitoring module was incorporated into the developed BCI pipeline to measure frame rate variations in the XR display, allowing deviations between nominal RR and measured values to be automatically detected and compensated for. Classification performance was evaluated using Filter Bank Canonical Correlation Analysis (FBCCA). Statistical significance was assessed using Student’s t-test. Materials: Two datasets were used: a dataset based on Moverio BT-350, including 9 subjects, and a dataset based on HoloLens 2, including 30 subjects, all collected by the authors. Results: The proposed compensation method led to significant improvements in SSVEP classification accuracy, proportional to the magnitude of fps deviations. In some cases, classification accuracy increased by up to 300% relative to its original value. Statistical analyses confirmed the reliability of the results across subjects and datasets. Conclusions: These findings show that the proposed method effectively enhances SSVEP-based BCIs in XR environments and provides a robust foundation for practical applications requiring high reliability. Full article

This study evaluates the feasibility of Near-Infrared (NIR) spectroscopy combined with chemometric modeling for monitoring twin-screw melt granulation. Lactose monohydrate was used as a model excipient and polyethylene glycol (PEG 6000) (Sistemas Analíticos S.A, Buenos Aires, Argentina) as a meltable binder. Granules were produced under different processing conditions by varying binder content, screw configuration (kneading or conveying elements), and measurement temperature. NIR spectra were acquired on-line on a conveyor belt and analyzed using Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression. The regression models showed excellent predictive performance for PEG 6000 content in lactose-based granules, with coefficients of determination higher than 0.998 for both raw and preprocessed spectral data. PCA successfully discriminated between granulated and non-granulated materials, as well as between granules produced with different screw configurations, demonstrating the sensitivity of the technique to processing conditions and granule formation mechanisms. In addition, spectral differences associated with measurement temperature were detected, with derivative-based preprocessing improving the discrimination between warm and cooled granules. Overall, the results demonstrate that NIR spectroscopy, coupled with multivariate analysis, is a robust and non-invasive tool for real-time monitoring of twin-screw melt granulation, with strong potential to enhance process understanding, control, and product consistency in continuous pharmaceutical manufacturing. Full article

Background/Objectives: Genicular artery embolization (GAE) is an emerging, minimally invasive treatment for symptomatic osteoarthritis. This study assesses global online search trends for GAE compared with traditional knee replacement using Google Trends data. Methods: This retrospective observational study analyzed global search trends for osteoarthritis treatments using the publicly accessible Google Trends platform. Monthly relative search volumes (RSV; scaled 0–100) for English-language queries were retrieved from January 2018 to December 2024. Three emerging minimally invasive terms (“genicular artery embolization”, “knee embolization”, “interventional radiology”), and three traditional surgical terms (“knee arthroplasty”, “knee replacement”, “total knee replacement”) were included. Temporal trends were evaluated using linear and non-linear regression models, with model fit evaluated using coefficients of determination (R²), ANOVA, and accuracy measures. Statistical significance was defined as p < 0.05. Results: GAE-related terms demonstrated significant growth over time. “Genicular artery embolization” increased by 0.9% per month (R² = 0.795, p < 0.001), and “knee embolization” increased at 0.9% per month (R² = 0.627, p < 0.001) in a linear model. Traditional terms showed slower growth rates of 0.13–0.23% per month (R² = 0.159–0.271). Exponential and quadratic models confirmed these patterns. Mean RSV values over the study period were higher for traditional procedures (e.g., “total knee replacement”: 83.13) than for GAE-related terms (e.g., “genicular artery embolization”: 22.5). Conclusions: Global online interest in GAE-related terms is increasing at a substantially faster rate than interest in traditional knee replacement. Rapidly growing search interest highlights the need for accurate and accessible online patient education regarding emerging treatments. Full article

The treatment of adolescent idiopathic scoliosis (AIS) requires the use of orthopedic braces. However, few current designs provide real-time monitoring or inform clinicians about the precise adjustment of therapeutic pressure. The objective of this study is to develop a low-cost open-system prototype capable of providing future researchers with objective information regarding brace adherence and adjustment. For adherence evaluation, a market study was conducted to identify temperature-measuring devices and a custom system was developed to measure adjustment. Cor-Esc-25 was developed to monitor brace adherence using a non-invasive temperature sensor which connects via Bluetooth to the parents’ smartphone, which runs an app that uploads the data to an online platform accessible to clinicians. In addition, a custom-designed pressure sensing device was created. This system uses three patches connected to an acquisition board and are installed on the brace each time the patient visits the clinic. It connects to a customized application where clinicians can view all the information. Cor-Esc-25 represents a first step toward the creation of personalized consultations, where AIS treatment monitoring is based on objective criteria that consider both adherence and brace adjustment. Its design allows for easy integration into clinical settings, thereby improving the ability of researchers and clinicians to assess the effectiveness of brace treatment. Full article

Background/Objectives: Cystic fibrosis-associated liver disease (CFLD) is a significant complication in individuals with cystic fibrosis (CF), contributing to morbidity and mortality, with no universally accepted, reliable, non-invasive diagnostic tool for early detection. Current diagnostic methods, including liver biopsy and imaging, remain resource-intensive and invasive. Non-invasive biomarkers like the Fibrosis-4 (FIB-4) index have shown promise in diagnosing liver fibrosis in various chronic liver diseases. This study explores the potential of the FIB-4 index to predict CFLD in an adult CF population and assesses its correlation with transient elastography (TE) as a potential diagnostic tool. The aim of this study is to evaluate the diagnostic performance of the FIB-4 index for CFLD in adults with CF and investigate its relationship with TE-based liver stiffness measurements (LSM). Methods: The study was conducted in a regional cystic fibrosis unit, including 261 adult CF patients. FIB-4 scores were calculated using an online tool (mdcalc.com) based on patient age, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and platelet count. In parallel, 29 patients underwent liver stiffness measurement using TE (Fibroscan^®). Statistical analyses included non-parametric tests for group comparisons and Pearson’s correlation to assess the relationship between FIB-4 scores and TE results. Results: The mean FIB-4 score in patients diagnosed with CFLD was higher (0.99 ± 0.83) compared to those without CFLD (0.64 ± 0.38), although the difference was not statistically significant (p > 0.05). TE results for CFLD patients (5.9 kPa) also did not show a significant difference compared to non-CFLD patients (4.2 ± 1.6 kPa, p > 0.05). However, a positive correlation (r = 0.401, p = 0.031) was found between FIB-4 scores and TE-based LSM, suggesting a potential complementary diagnostic role. Conclusions: The FIB-4 index, while not sufficient as a standalone diagnostic tool for CFLD in adults with CF, demonstrates potential when used in conjunction with other diagnostic methods like TE. This study introduces a novel approach for integrating non-invasive diagnostic markers in CF care, offering a pathway for future clinical practice. The combination of FIB-4 and TE could serve as an accessible, cost-effective alternative to invasive diagnostic techniques, improving early diagnosis and management of CFLD in the CF population. Additionally, future research should explore the integration of these tools with emerging biomarkers and clinical features to refine diagnostic algorithms for CFLD, potentially reducing reliance on liver biopsies and improving patient outcomes. Full article

Invasive, non-native species are recognised as a global problem, and their dispersal and introduction are controversial topics. However, a source of particular interest is that of human–nature interactions and consequent perceptions of natives and non-natives, an issue complicated by misunderstandings of history and sometimes of science. Furthermore, there are only few studies on the perceptions of exotic species by people living in a region subject to invasion. The research compared local stakeholder responses to a non-native invasive bird (ring-necked parakeet Psittacula krameri Scopoli) in two areas with contrasting scenarios regarding the history of establishment, their spread, and their current status. In both locations, parakeets were considered by respondents to be attractive, but where long-established, they were also viewed as a nuisance. Desire for or tolerance of active control measures also increased in areas with a well-established population in comparison to where parakeets were still viewed as a novelty. Increased encounters between native birds and invasive parakeets influenced attitudes towards possible controls. An online survey gathered stakeholder responses, and long-term citizen science and action research were combined with data from Local Environmental Records Centres and ornithological recording groups for each region. Full article