Search Results (5,774)

This paper presents a structured review of antenna and electromagnetic spectrum monitoring techniques for non-invasive fault detection in electrical and electronic equipment. Electromagnetic emissions from partial discharges, arc faults, insulation degradation, and component ageing carry diagnostic signatures detectable through remote radio-frequency sensing. We review (1) antenna technologies spanning magnetic-field loops to ultra-high-frequency electric-field sensors, including fractal, Vivaldi, spiral, and bio-inspired designs; (2) data acquisition platforms ranging from laboratory oscilloscopes to software-defined radio receivers and IoT edge nodes; (3) signal processing methods including time–frequency analysis, adaptive decomposition, and statistical techniques; and (4) machine learning approaches from classical classifiers to deep learning architectures such as convolutional neural networks, recurrent neural networks, and Transformer-based models. Unlike prior surveys focusing on individual fault types or specific equipment classes, this review connects all five layers of the sensing pipeline—from electromagnetic emission physics through antenna selection, signal acquisition, processing, and intelligent classification—for partial-discharge, arc, and insulation faults and analyses the cross-layer constraints that couple them. Design optimisation techniques based on computational electromagnetic methods (FDTD, FEM) and sensitivity calibration challenges are discussed. Open challenges, including the lack of standardised UHF calibration, cross-equipment generalisation, and the scarcity of open electromagnetic fault datasets, are identified, along with emerging directions in flexible antennas, edge AI, and digital twin integration. Full article

Objectives: Tenascin-C (TNC) is an extracellular matrix protein associated with tissue remodeling, tumor progression, and poor prognosis in breast cancer. Although TNC has attracted interest as a potential stromal biomarker, its baseline histopathological distribution in untreated breast cancer has not been fully characterized. This exploratory pilot study aimed to characterize the immunohistochemical distribution of TNC in representative treatment-naïve breast cancer tissues. Methods: Immunohistochemical staining for TNC was performed in representative breast cancer tissue specimens obtained from 16 treatment-naïve patients encompassing major histological and molecular subtypes. Tumor and non-tumor areas were evaluated descriptively by two board-certified pathologists using consensus assessment. Results: Heterogeneous TNC expression was observed in the stroma surrounding invasive tumors in all cases. In most specimens, TNC staining was predominantly localized to the peritumoral stroma, whereas occasional staining was observed around non-invasive lesions. Non-tumor breast stroma was largely negative, although positive staining was observed in biopsy scars and sclerotic areas. No consistent subtype-specific pattern of TNC distribution or staining intensity was identified. Conclusions: TNC showed heterogeneous stromal expression in treatment-naïve breast cancer and was also detected in biopsy scars and areas of stromal remodeling. These findings provide baseline histopathological information regarding TNC localization in untreated breast cancer. Further studies are required to determine the potential clinical utility of TNC as a stromal biomarker, including its application in the post-neoadjuvant setting. Full article

Hyperspectral imaging (HSI) is a state-of-the-art analytical technique that combines the use of conventional digital imaging and spectroscopy to capture both spatial and spectral information simultaneously in hundreds of narrow, adjacent wavelength bands. In recent decades, the progress in HSI has been rapid, and the technique has been increasingly utilized in forensic sciences, demonstrating its superiority to standard analytical techniques with respect to being non-invasive and contact-free. Although numerous forensic HSI articles have appeared in the literature in recent years, there has yet to emerge a systematic comparison of HSI performance, instrumentation, and cross-domain translational difficulties within forensic science. This review fills this important gap by analyzing the principles, instrumentations, methods of HSI data processing, and potential applications of HSI in forensics in the context of nine important fields: blood stain analysis and estimation of blood age; document authentication; fingerprint detection and enhancement; gunshot residue (GSR) analysis; analysis of trace evidences; detection of biological fluids; postmortem interval (PMI) estimation; determination of bruise age; and multidisciplinary applications. Comparative analysis of over fifty peer-reviewed articles published from 2010 to 2026 in HSI-based forensic sciences is provided herein, with classification accuracies between 81% and 100%. The use of chemometric and machine-learning methods, such as principal component analysis (PCA), support vector machines (SVM), partial least square discriminant analysis (PLS-DA), and Convolutional Neural Networks (CNNs), is carefully analyzed. Some problems concerning standardization, legal acceptance, data sets available, and forensic application are considered alongside future developments of HSI technology. Full article

Automation of measurement data acquisition is particularly important when digital instruments do not provide a direct communication interface or when long-term measurements require high repeatability and reduced operator involvement. This paper presents a comparative study of two image-based optical reading methods to acquire indications from a digital multimeter. The reference signal was generated using a Fluke calibrator, while the multimeter display was recorded with an industrial camera. The acquired images were processed independently using two different recognition strategies. The first approach was implemented in the Python environment using a You Only Look Once version 8 small (YOLOv8s) deep learning object detection model trained to classify individual display characters. The second approach was implemented in the Laboratory Virtual Instrument Engineering Workbench (LabVIEW) using a template-based optical character recognition (OCR) method prepared in NI Vision Assistant. Acquisition series were performed for different voltage ranges, with 100 samples acquired for each pipeline and measurement case. All image-acquisition experiments were conducted under controlled laboratory conditions using a fixed camera position, a constant region of interest (ROI), and stable illumination. The detected or recognised characters were reconstructed as numerical values and compared with the reference settings of the calibrator on statistical parameters that describe the dispersion within the series and the deviation of the readings. The study evaluates the practical applicability of both approaches and demonstrates the potential of non-invasive optical reading methods for automated acquisition of indications from measurement instruments. Full article

Background: Breast cancer treatment is often based on multimodal approaches in locally advanced stages typically including neoadjuvant chemotherapy (NACT). There are limited options for the assessment of prognosis and early identification of future non-responders, which has led to the study of circulating cell-free DNA (cfDNA) and its tumor-derived subset, circulating tumor DNA (ctDNA), for potential use as non-invasive markers for prediction of response and prognosis associated with NACT. Methods: We have evaluated the literature on approaches to the use of cfDNA and/or ctDNA as potential biomarkers for NACT. Results: Out of 142 references going back to 2010, we found there were 87 original research reports, 39 reviews, 10 clinical trial reports and six case reports. A detailed analysis revealed several distinctive ways that markers were evaluated in a clinical setting. The original studies have focused on cfDNA, especially cfDNA integrity, whereby increasing integrity levels correlate with tumor shrinkage, reductions in proliferation markers, and hence indicate a better prognosis. Similarly, epigenetic alterations have shown promising results, with methylated ctDNA levels decreasing in responders. Further studies demonstrated the utility of ctDNA persistence through the NACT as strongly associated with shorter disease-free and overall survival. The most recent approaches of longitudinal ctDNA monitoring were found to be valuable for early identification of patients at high risk for post-operative recurrence. Conclusions: It should be noted that while most reports indicate the important role of circulating DNA in the assessment of prognosis and early detection of recurrence, there is currently only a limited utility in the prediction of eventual neoadjuvant therapy outcomes. Full article

Background/Objectives: Non-invasive prenatal testing for monogenic disorders (NIPT-MD) provides a safe alternative to invasive procedures. However, its clinical utility is often limited by challenges such as low fetal fractions (FF), technical artifacts, and the difficulty in resolving maternally inherited pathogenic variants from the overwhelming background of maternal cell-free DNA (cfDNA). This study aimed to develop and validate a robust NIPT-MD platform for monogenic disorders, applicable across major common Mendelian inheritance patterns, by enhancing the accuracy of fetal variant detection in cfDNA. Methods: We developed a novel NIPT-MD platform validated using both simulated samples and a retrospective clinical cohort. The workflow involves a single-strand capture library preparation incorporating unique molecular identifiers (UMIs) to mitigate amplification artifacts. FF was precisely quantified using a fixed panel of high-minor-allele-frequency single-nucleotide polymorphisms (SNPs). Fetal genotypes were then inferred by resolving parental haplotypes through a statistical model that integrates weighting of variant allele frequency (VAF) and haplotype-informative SNP counts. Results: The single-strand capture protocol incorporating UMIs significantly reduced amplification biases. Validation of the fetal DNA fraction estimation algorithm revealed strong concordance with a Y-chromosome-derived method and expected spike-in samples. Optimization of the FF estimation panel conferred greater experimental stability. The platform reliably detected both paternally and maternally inherited pathogenic variants. In a retrospective cohort of 35 clinical cases, the NIPT-MD platform achieved high concordance with genotypes determined by invasive testing. Conclusions: These findings present an accurate and robust NIPT-MD platform for monogenic disorders, with high concordance to invasive testing validated in a retrospective cohort of 35 clinical cases. This method holds promise for clinical application in managing families at high risk of monogenic diseases. Full article

Background/Objectives: MGUS and smoldering multiple myeloma (SMM) are precursor states of plasma cell disorders with variable risk of progression to multiple myeloma (MM). Yet, current risk stratification models combine clinical and laboratory parameters, including invasive bone marrow assessment, but have limited precision. Methods: We applied free light chain (FLC)-monomer (M)–dimer (D) pattern analysis (FLC-MDPA), a non-invasive Western blot–based serum assay, to detect abnormal FLC M–D patterns associated with early malignant transformation, for predicting progression in MGUS (n = 68) and SMM (n = 40). Among 96 patients with complete data, 50 formed a training set to define criteria for progressive disease and 46 comprised a validation set. Results: FLC-MDPA predicted biochemical progression (sensitivity 0.79, specificity 0.92, NPV 0.86; HR 19.96, 95% CI 4.31–92) and clinical progression (sensitivity 0.84, specificity 0.79; HR 13.5, 95% CI 3.68–49.64), with significantly higher progression rates in patients with abnormal patterns (p < 0.0001). Within this high-risk cohort, FLC-MDPA was associated with higher hazard ratios for both biochemical and clinical progression compared with the 2/20/20 model, while incorporation into a modified 2/20/MDPA model improved sensitivity and negative predictive value. In a multivariable model including MDPA and FLC ratio, MDPA was independently associated with both clinical (p = 0.001) and biochemical progression (p = 0.04). Conclusions: These findings suggest that FLC-MDPA is a promising non-invasive tool for risk stratification in MGUS and SMM, improving sensitivity and negative predictive value while potentially reducing reliance on bone marrow–based assessment. Full article

Precision prevention and control of genetic diseases represent a major public health challenge. This paper provides a structured narrative review of advances in molecular diagnostic technologies across the preconception, preimplantation, and prenatal stages over the past five years. In the preconception phase, next-generation sequencing has become central to carrier screening, while long-read sequencing significantly enhances detection capabilities for complex variants. In the preimplantation phase, research has increasingly focused on non-invasive preimplantation genetic testing, leveraging maternal contamination quantification algorithms and deep learning models to address DNA contamination challenges. During the prenatal phase, stratified diagnostic strategies combining chromosomal microarray analysis and whole-exome sequencing have improved the diagnostic evaluation of fetal structural anomalies. Simultaneously, non-invasive prenatal testing is expanding to include microdeletion/duplication and monogenic disease screening, though positive screening results still require invasive diagnostic confirmation. Future trends lie in multi-technology integration, multi-omics data fusion, and artificial intelligence-assisted decision-making, aiming to enhance resolution while balancing health-economic considerations and ethical standards. Full article

The adsorption behavior of selected volatile sulfur compounds on graphene was examined using density functional theory. The analytes of interest are hydrogen sulfide, methyl mercaptan and dimethyl sulfide, which are found in the exhaled breath of halitosis patients. The human breath contains several volatile compounds that act as chemical fingerprints of what is happening inside the body. This study employs first-principles calculations to investigate the structural, electronic, and adsorption properties of pristine and transition-metal-doped graphene (Fe, Ru, and Os) for the detection of key volatile sulfur compounds relevant to breath analysis and halitosis screening. According to our findings, when a single carbon atom is substituted with an iron, ruthenium or osmium atom in the optimized graphene sheet, which is equivalent to a dopant concentration of 2 mol% in experiments, the adsorption behavior of the system is altered significantly. Based on the resultant adsorption behavior and electronic structure alterations, important sensor properties were examined. This work presents a non-invasive approach for halitosis detection, therapeutic monitoring, and metabolic status observation by analyzing the volatile sulfur compounds present in exhaled breath. Additionally, this study demonstrates how computational modeling can be used as a decision support tool. Full article

To address the need for bubble detection in industrial silicone sealing rings, this paper presents a compact non-invasive ultrasonic monitoring system based on a capacitive micromachined ultrasonic transducer (CMUT) array, aiming to overcome the limitations of conventional X-ray inspection in terms of safety, portability, and real-time in situ monitoring. The system comprises two 8.8 mm × 8.8 mm CMUT arrays with associated transmitting and receiving circuitry. The silicone thickness is determined using the time-of-flight (TOF) method, while bubble size is quantitatively estimated by combining received signal amplitude analysis, which characterizes bubble-induced attenuation, with correlation function evaluation. Experimental measurements on industrial-grade silicone samples and finite element simulations demonstrate that the system achieves a spatial resolution of 0.5 mm and effectively captures attenuation variations caused by bubbles. The integrated strategy of TOF, amplitude analysis, and correlation assessment ensures reliable non-destructive evaluation. Compared with X-ray inspection, the proposed system is safer, more portable, and suitable for real-time on-site monitoring, thereby significantly improving quality control efficiency in silicone manufacturing. This study provides a novel CMUT-array-based solution for quantitative bubble detection in silicone media, offering both high resolution and practical application potential. Full article

Background and Objectives: Coronary artery disease may be difficult to detect by resting echocardiography when left ventricular ejection fraction is preserved and regional wall motion abnormalities are absent. This study aimed to assess whether resting Tissue Doppler Imaging-derived mitral annular velocities can help identify CAD in patients with suspected angina pectoris. Materials and Methods: We conducted a cross-sectional observational study of 92 patients hospitalized with suspected angina pectoris who underwent elective coronary angiography at the Institute of Cardiovascular Diseases in Timișoara (January 2025–February 2026). Patients with conditions known to affect TDI-derived parameters were excluded, including previous acute coronary syndrome or myocardial revascularization, significant valvular disease, cardiomyopathies, relevant arrhythmias or conduction abnormalities, permanent pacing, reduced ejection fraction, and pericardial disease. Laboratory and echocardiographic data were collected. ROC curve analysis, univariable logistic regression and multivariable logistic regression were performed to evaluate the diagnostic performance of TDI-derived parameters and their independent association with coronary artery disease. Results: Patients with CAD had significantly lower average E′ values (7.4 ± 1.9 vs. 8.9 ± 1.8 cm/s, p < 0.001) and average S′ values [7.0 (IQR 6.0–7.5) vs. 9.0 (IQR 8.1–10.0) cm/s, p < 0.001], together with higher E/E′ ratios [9.33 (IQR 8.23–11.15) vs. 7.87 (IQR 5.93–9.51), p = 0.002]. Average S′ showed the highest discriminative ability for coronary artery disease, with an AUC of 0.899 (95% CI: 0.819–0.952, p < 0.0001). The optimal Youden-derived cut-off was ≤7.5 cm/s, yielding 77.42% sensitivity and 93.33% specificity. After adjustment for age, male sex, body mass index, diabetes, smoking status, hypertension and LVEF, dichotomized S′ remained an independent predictor of coronary artery disease (OR = 45.49, 95% CI: 8.03–257.68, p < 0.0001), with an adjusted model AUC of 0.92 and 88.04% correct classification. Conclusions: TDI, particularly S′ velocity, may be a useful resting echocardiographic parameter for identifying CAD in selected patients with preserved LVEF and no resting regional wall motion abnormalities. Rather than serving as a universal diagnostic marker, S′ should be considered a complementary, easily obtainable parameter that may improve non-invasive assessment in this specific clinical setting. Full article

Background: Cervical cancer screening uptake in Romania remains below 20%, with invasive sampling cited as a major participation barrier. Urinary HPV testing is a non-invasive alternative, but data from Eastern European populations are scarce and reporting stratified by histological grade is inconsistent. Objectives: To evaluate the agreement between paired urinary and clinician-collected cervico-vaginal HPV testing, and to assess the diagnostic performance of urinary HPV testing for biopsy-confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+). Methods: Prospective cross-sectional study in three outpatient obstetrics and gynecology clinics (May 2025–May 2026). A total of 230 women aged 25–70 years provided paired cervico-vaginal (PreservCyt^®) and first-void urine (Colli-Pee^®) specimens. To capture the full spectrum of disease probability, participants were recruited across three clinical scenarios: primary screening, cytology triage and HPV-positive triage. A multiplex RT-PCR assay targeted a total of 14 high-risk HPV genotypes, providing separate identification for HPV16 and HPV18, alongside a pooled detection for the remaining 12 high-risk strains. Colposcopy-guided cervical biopsy served as the reference standard. Results: Paired hrHPV testing achieved substantial agreement (κ = 0.696, 95% CI 0.604–0.788), with higher genotype-specific concordance for HPV16 (κ = 0.755) and HPV18 (κ = 0.789). Discordance was directionally asymmetric (30 cervical-positive/urine-negative versus 4 urine-positive/cervical-negative; McNemar p < 0.001). For biopsy-confirmed CIN2+ (59 of 230; 25.7%), urinary hrHPV showed a sensitivity of 86.4% (95% CI 75.5–93.0), specificity 56.7%, positive predictive value 40.8% and negative predictive value 92.4%, compared with 91.5%, 43.3%, 35.8% and 93.7% for cervico-vaginal testing. Urinary HPV positivity increased monotonically with histological severity (25.0% no-lesion, 69.0% CIN1, 86.4% CIN2+; linear-by-linear p < 0.001). Conclusions: Urinary HPV testing demonstrates substantial agreement with clinician-collected sampling, near-equivalent negative predictive value, and a robust dose–response with histological severity. It is a clinically credible non-invasive entry point for a triage cascade in settings such as Romania, where low participation rather than analytical performance is the principal screening barrier. Full article

The study of ancient sculptural polychromy increasingly relies on non-invasive analytical approaches capable of identifying pigments and reconstructing original decorative schemes while preserving the integrity of archaeological objects. This paper presents the investigation of the polychromy, extraordinarily preserved, on two Roman marble statues discovered in the forum of Formia (southern Latium) and currently housed in the National Archaeological Museum of Formia: a togate statue (inv. 147614) and a headless draped female figure (inv. 147680). Both sculptures retain exceptionally well-preserved traces of pigments, offering a rare opportunity to investigate materials and painting techniques applied to Roman marble statuary. The analytical protocol combined multiband imaging (Visible-Induced Luminescence and Ultraviolet Luminescence), optical microscopy, Fiber Optic Reflectance Spectroscopy (FORS), portable X-ray Fluorescence (XRF), and Surface Enhanced Raman Spectroscopy (Raman-SERS) applied to two micro-samples. The analyses allowed the identification of Egyptian blue, iron-based pigments, gilding, and an organic red lake on the palettes used for the statues. Raman-SERS measurements provided additional information on the composition of the organic lake detected on the female statue’s himation, supporting its attribution to a natural vegetal-derived dye, as madder lake. The results highlight the success of integrated non-destructive methodologies for the study of Roman sculptural polychromy and contribute to the reconstruction of complex decorative schemes on marble statuary. Full article

Soil ecosystems generate a wide variety of biological and physical sounds, yet the temporal organization of soil acoustic environments remains poorly understood. This study investigated seasonal and daily dynamics of soil acoustic activity using continuous recordings collected over an entire calendar year at four soil stations subjected to different vegetation management regimes. Custom-built piezoelectric probes were used to record vibrations within the upper soil layer. Two complementary analytical approaches were applied. Conventional Acoustic Features (Root Mean Square, Zero Crossing Rate, Spectral Centroid, Spectral Bandwidth, Spectral Entropy, and Mel-Frequency Cepstral Coefficients) were used to characterize monthly and solar-phase variability, whereas Sonic Heterogeneity Indices (SHI_ft and SHI_tf) were employed to investigate seasonal organization and climatic forcing. Climatic variables and solar phases were analyzed using correlation analyses, clustering procedures, machine learning models, and seasonal and sinusoidal frameworks. Acoustic Features revealed a clear seasonal organization, with winter and early spring months forming coherent acoustic regimes across most stations. Responses to solar phases were detectable but strongly dependent on local site conditions. SHI_ft and SHI_tf metrics showed higher heterogeneity during autumn and winter than during spring and summer. Climatic variables emerged as important drivers of acoustic heterogeneity, while sinusoidal models generally described annual SHI_tf dynamics better than conventional seasonal classifications. These findings indicate that soil acoustic environments are structured by interacting seasonal, climatic, and astronomical processes operating across multiple temporal scales and support the development of soil ecoacoustics as a non-invasive tool for investigating ecosystem functioning. Full article

Continuous and noninvasive blood pressure (BP) monitoring is important for hypertension screening and long-term cardiovascular management. Continuous BP estimation using photoplethysmography (PPG) and electrocardiography (ECG) has become a promising alternative to conventional cuff-based measurements. However, handcrafted feature-based methods are sensitive to fiducial point detection, while end-to-end deep models often require large labeled datasets and may ignore subject-specific BP baselines. This study proposes a personalized calibration and hybrid feature fusion framework for continuous BP estimation from ECG and PPG signals. The framework integrates physiologically interpretable handcrafted features, self-supervised waveform representations, and subject-specific prior BP information to predict systolic and diastolic BP. The handcrafted branch extracts pulse transit time, heart rate variability, and PPG morphological descriptors, whereas a masked reconstruction-based self-supervised encoder learns latent waveform embeddings without BP labels. Personalized calibration incorporates base BP from the earliest calibration file through an alpha-weighted strategy, and the fused representation is fed into XGBoost regressors. The framework was evaluated on a private dataset and the BP-UCI dataset, achieving SBP/DBP MAEs of 7.25/3.98 mmHg and 7.85/4.02 mmHg, respectively. Comparative and ablation results indicate improved baseline performance in the current experimental setting, suggesting the methodological feasibility of the proposed framework for small-sample continuous BP estimation. Further validation with larger and more diverse cohorts is still required. Full article