Search Results (293)

Electrochemotherapy is a minimally invasive treatment based on the principle of reversible electroporation of target cells in pathologic tissues in order to increase the local effect of chemotherapeutic agents. The mechanism of action relies on temporarily increasing cell permeability to increase the uptake of cytotoxic drugs in the intracellular space. Originally developed for the treatment of cutaneous malignancies, electrochemotherapy has significantly evolved over the past few decades, thanks to advancements in electrode design and image guidance, finding fertile ground in musculoskeletal oncological pathologies, such as bone and soft tissue tumors and different kinds of vascular malformations. Moreover, initial experiences have reported on the treatment of other soft tissue tumors such as desmoid fibromatosis. The aim of this review is to summarize the literature on the role of electrochemotherapy across a variety of musculoskeletal conditions, starting from established oncologic indications, such as metastatic bone or soft tissue tumors, to emerging evidence on primary musculoskeletal pathology, with particular attention paid to the results of the leading studies relating to the efficacy, complications, and recurrence rate. Full article

This paper presents a numerical investigation studying the response of a new grounding system when submitted to different lightning current waveforms. This grounding system features an electrically conductive concrete (ECON) or geopolymer (ECG) square section with a standard steel rebar as an encased electrode (EE) at the center to potentially replace conventional copper or galvanized steel grounding grids in HV substations. Due to the specificity of this new grounding system called ECON/ECG-EE, we decided to perform different transient simulations using the RF module of the general FEM software Comsol Multiphysics 6.2 version. In the first step, both frequency (FD) and temporal domain (TD) analyses were validated using three grounding systems extracted from the literature. Next, several numerical new grounding system simulations were performed and compared with a conventional HV substation copper grid of the same dimensions equipped with vertical rods. We investigated the influence of several parameters, such as ECON/ECG and soil electrical conductivity, the rise-time in current lightning waveform and the frequency dependency of soil parameters. The numerical results obtained demonstrate that ECON/ECG-EE grounding systems submitted to lightning current pulse present a smaller peak impedance than conventional SGSs equipped with vertical rods, particularly in cases with high soil resistivity. Moreover, it was also demonstrated that with faster lightning current pulse, the ECON/ECG system’s peak impedance becomes significantly lower than those obtained for a copper grid with vertical rods. Full article

Drowsy driving contributes to roughly 20% of traffic fatalities, yet most detection systems rely on behavioral cues that appear only after impairment has set in. Here we ask whether first and second derivatives of heart rate variability (HRV) can detect pre-crash states earlier than conventional approaches. Twenty-five participants completed 49 driving simulator sessions while we recorded cardiac activity through capacitive ECG electrodes embedded in the seat backrest—a non-contact method that avoids the privacy concerns of camera-based monitoring. To prevent circular evaluation, ground truth labels were based solely on crash proximity rather than HRV-derived scores. The combined HRV feature set (conventional metrics plus derivatives) achieved AUC = 0.863 for pre-crash prediction; derivatives alone reached only AUC = 0.573, indicating their value as complementary rather than standalone features. Driving performance indicators remained the strongest predictors (AUC = 0.999). Temporally, derivative-based detection preceded behavioral manifestations by 5–8 min and crash events by 6.8 ± 2.3 min. Across 1591 crashes and 6.78 million data points, we found that HRV derivatives capture physiological changes that precede overt impairment, though their utility depends on integration with other feature types. Full article

This article focuses on the synthesis and characterization of an amorphous carbon derived from spent coffee grounds converted into a porous amorphous carbon (Cp₁) by carbonization up to 900 °C and subsequently combined with aluminum via mechanochemical treatment to obtain the composite Al@Cp₁. Powder X-Ray diffraction, Raman spectroscopy, and X-Ray photoelectron spectroscopy indicate turbostratic carbon domains (ID/IG ≈ 1.04) and an Al–O/Al–OH surface layer (Al₂O₃/Al(OH)₃) with a minor metallic Al contribution. Electrochemical performance in Li half-cells was evaluated by cyclic voltammetry, galvanostatic cycling, rate capability tests, and electrochemical impedance spectroscopy. At 0.02 A g⁻¹, Al@Cp₁ delivers 212.1 mAh g⁻¹, compared with 83.0 mAh g⁻¹ for Cp₁, with an initial coulombic efficiency of ~44%. Across increasing current densities, Al@Cp₁ retains higher reversible capacities than Cp₁ and shows stable cycling over extended tests (>160 cycles). Impedance analysis indicates a reduced interfacial/charge transfer resistance after electrode conditioning, consistent with interfacial stabilization by the Al-containing surface layer. These results demonstrate a simple, scalable route to upgrade coffee waste carbon into a higher-performance lithium-ion battery anode through mechanochemical interfacial engineering. Full article

Many studies have demonstrated that a reduction in ground impedance value occurs under high-impulse current magnitudes, due to the ionisation process in soil. The degree of the ionisation process was found to be influenced by several factors, such as soil resistivity, the ground electrode’s configuration/size, impulse polarity, voltage/current magnitudes and impulse polarity, while in several publications, there was no clear influence of these factors on the ionisation process in soil. Given the uncertainty in the characterisations of grounding systems under high-impulse conditions, it can be difficult to relate the impulse characteristics to the design of grounding systems. This, however, may be possible to achieve if adequate data is obtained, with more tests and analytical studies being performed. Furthermore, as the use of enhancement materials (EMs) has been shown to reduce ground resistance values, the relevant data, which have been found to be limited, are the impulse characteristics of EMs. The effectiveness of these EMs is mostly presented at low-voltage and low-frequency currents, and so far, there is limited available data on their performance with various water contents (WCs) subjected to high-impulse currents. This paper aims to provide the impulse characteristics of soil mixed with various EMs and WCs. Three types of EM were used, and the initial results show that the performance of EMA has an advantage over the others, due to having the lowest Z_imp, current rise and discharge times, and breakdown voltage and times in comparison to other EMs tested in this work. Full article

Background: Through the direct electrical stimulation of spiral ganglion neurons (SGNs) of the hearing nerve, cochlear implants overcome functionally impaired or missing hair cells in patients with profound to severe hearing loss. In routine clinical fitting, regions with severe local SGN degeneration (modiolar “dead regions”) cannot be identified. As a result, the electrical fields of neighboring electrodes are broadened, which can lead to increased channel interaction and, consequently, poorer speech understanding and hearing. The objective of this study was to ascertain whether neural health status can be evaluated by using cochlear implants’ inbuilt measures. Methods: Electrode impedance (MP1-, MP2-, MP1/MP2-, common ground mode), transimpedance matrix (TIM) and electrically evoked compound action potential (eCAP) measurements were performed before and after laser-induced induction of lesions on the modiolus of the guinea pig. Laser treatment-related shifts in impedance, TIM, and eCAP characteristics (threshold, amplitude, and a modified version of the failure index, referred to as the efficiency index (EI)) were correlated with the histologically assessed damage in three predefined areas of the basal modiolus within the electrode region. Results: Modiolar damage resulted in a significant reduction in the electrode impedance in MP2- and MP1/2-mode, the eCAP amplitude, and the EI. In contrast, TIM values and eCAP thresholds were significantly elevated. MP1, MP1/MP2 electrode impedance, TIM, and the eCAP thresholds were not correlated with the extent of modiolar damage. The shifts in eCAP amplitudes and the EI were significantly correlated with the damage at all regions of the basal modiolus. Conclusions: The eCAP amplitude and the EI are both capable of objectively evaluating the neural health status of the cochlea. Thus, a modiolar dead region could be expected from a local drop in eCAP amplitude values or the modified EI within the electrode array. Full article

Accurately characterizing the structural state of membrane reflector antennas (MRA) remains challenging due to the difficulty in determining stress distribution through geometric measurement alone. Although photogrammetry provides high-precision geometric data, it falls short of capturing mechanical pre-tension and is notably influenced by gravity, which limits its utility in guiding surface accuracy adjustments. This paper proposed an integrated approach combining photogrammetry with a nonlinear finite element method (NFEM) to achieve high-fidelity imaging and effective shape adjustment of electrostatically formed MRA, explicitly accounting for gravity effects during ground-based measurement and shape control. The proposed method establishes a mechanical model that incorporates real-world geometric data under gravity and performs force–shape matching to reconcile discrepancies between physical and simulation models. Experimental validation demonstrates that the gravity-corrected NFEM model closely aligns with the physical antenna, with a deviation in surface accuracy within 9.9%. Using this refined model, we successfully optimized electrode voltages and cable tensions, improving the surface accuracy of the physical model from an initial 0.7033 mm to 0.5723 mm. This work provides a reliable and efficient strategy for the shape control and adjustment of membrane space structures under gravity, with potential applications in large deployable antennas, solar sails, and other tension-controlled flexible systems. Full article

Persistent Idiopathic Dentoalveolar Pain (PIDAP) is a persistent idiopathic toothache that frequently remains unresponsive to medical therapy. Precise targeting of the infraorbital nerve is essential for successful intervention, yet anatomical variability often limits the consistency of conventional radiofrequency ablation (RFA). This report describes a medial-to-lateral ultrasound- and computed tomography-guided approach, intended to align with the natural orientation of the infraorbital canal and potentially enhance electrode–nerve contact. A 48-year-old woman with refractory maxillary incisor pain underwent RFA after only transient benefit from a diagnostic nerve block. Ultrasound enabled accurate identification of the infraorbital foramen and confirmed the canal’s medial-to-lateral course, which then guided CT-assisted needle advancement into the orbitomaxillary segment. The patient experienced immediate analgesia. Pain reduction was maintained at the one-month follow-up. At the two-month assessment, although a mild symptom rebound was observed, no procedure-related complications were noted. This trajectory-based medial-to-lateral technique offers an anatomically grounded alternative for infraorbital nerve RFA and may represent a valuable option for refractory PIDAP. Full article

Redox mediators are central to electrochemical biosensors, enabling electron transfer between deeply buried enzymatic cofactors and electrode surfaces when direct electron transfer is kinetically inaccessible. Among all design parameters, the reversibility of mediator redox cycling remains the most decisive yet under-examined factor governing biosensor stability, drift and long-term reproducibility. This review establishes reversibility as a unifying framework grounded in inorganic and organometallic redox chemistry, with particular emphasis on coordination environments, ligand-field effects and outer-sphere electron-transfer pathways. Recent advances (2010–2025) in ruthenium and osmium polypyridyl complexes, cobalt macrocycles, hexacyanoferrates and Prussian Blue analogues are examined alongside ferrocene derivatives and other organometallic mediators, which together define the upper limits of reversible behaviour. Organic mediator families, including quinones, phenazines, indophenols, aminophenols and viologens, are discussed as mechanistic contrasts that highlight the structural and thermodynamic constraints that limit long-term cycling in aqueous media. Mechanistic indicators of reversibility, including peak separation, current ratios and heterogeneous electron-transfer rate constants, are linked to mediator architecture, coordination chemistry and immobilisation environment. By integrating molecular electrochemistry with applied sensor engineering, this review provides a mechanistically grounded basis for selecting or designing redox mediators that sustain efficient electron transfer, minimal fouling and calibration stability across diverse sensing platforms. Full article

Driver monitoring systems are increasingly relying on physiological signals to assess cognitive and emotional states for improved safety and user experience. Electrodermal activity (EDA) is a particularly informative biomarker of arousal but is conventionally measured with skin-contact electrodes, limiting its applicability in vehicles. This work explores the feasibility of non-contact EDA estimation using Light Detection and Ranging (LiDAR) as a novel sensing modality. In a controlled laboratory setup, LiDAR reflection intensity from the forehead was recorded simultaneously with conventional finger-based EDA. Both classification and regression tasks were performed as follows: feature-based machine learning models (e.g., Random Forest and Extra Trees) and sequence-based deep learning models (e.g., CNN, LSTM, and TCN) were evaluated. Results demonstrate that LiDAR signals capture arousal-related changes, with the best regression model (Temporal Convolutional Network) achieving a mean absolute error of 14.6 on the normalized arousal factor scale (–50 to +50) and a correlation of r = 0.85 with ground-truth EDA. While random split validations yielded high accuracy, performance under leave-one-subject-out evaluation highlighted challenges in cross-subject generalization. The algorithms themselves were not the primary research focus but served to establish feasibility of the approach. These findings provide the first proof-of-concept that LiDAR can remotely estimate EDA-based arousal without direct skin contact, addressing a central limitation of current driver monitoring systems. Future research should focus on larger datasets, multimodal integration, and real-world driving validation to advance LiDAR towards practical in-vehicle deployment. Full article

Developing flexible, cost-effective, and durable sensors is a key challenge for integrating Cyber–Physical–Human Systems (CPHSs) into smart homes. This paper introduces a flexible pressure sensor array designed for CPHS applications, addressing the need for cost-effective and durable sensors in smart homes. Our approach combines flexible piezoelectric materials with Swept Frequency Capacitive Sensing (SFCS). Unlike previous pressure sensors made of flexible piezoelectric materials, which can only measure dynamic pressure due to charge leakage, by using SFCS, the piezoelectric material is not directly in the circuit, and our sensor can effectively measure static pressure. While traditional arrays require multiple I/O ports or a matrix configuration, our design measures four distinct locations using only a single I/O port. The sensor is also mechanically flexible and exhibits high durability, capable of functioning even after being cut or torn, provided the electrode contact area remains largely intact. To decode the complex, multiplexed signal from this single channel, we developed a two-stage deep learning pipeline. We utilized data from thin-film resistive pressure sensors as ground truth. A classification model determines which of the four sensors are being touched. Then a regression model uses this touch-state information to estimate the corresponding pressure values. This pipeline employs a hybrid architecture that integrates Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The results show that the system can estimate pressure values at each location. To demonstrate its application, the sensor system was integrated into a power recliner, thereby transforming the chair into an interactive tool for daily exercise designed to improve the well-being of older adults. This successful implementation establishes a viable pathway for the development of intelligent, interactive furniture for in-home exercise and rehabilitation within the CPHS paradigm. Full article

Ancient underground voids present non-trivial hazards to urban redevelopment, particularly where groundwater conditions change during construction. We propose a staged, groundwater-aware workflow that integrates in-void mapping with area-scale geophysics and explicitly links water state to imaging performance. Following exposure of an undocumented masonry tunnel in a foundation pit in Wuhan (China), we acquired underwater CCTV and sonar during water-filled conditions, and, after drainage, collected ground-penetrating radar (GPR, 75–150 MHz) and ultra-high-density electrical resistivity tomography (UHD-ERT, 1 m electrode spacing) data. Calibration lines over the breach anchored the depth/geometry and reduced interpretational non-uniqueness. Analytical estimates using Archie-type and CRIM relations, together with observed signatures, indicate that drainage increased resistivity and reduced electromagnetic attenuation, improving UHD-ERT contrast and GPR penetration. The merged evidence resolves a straight-walled arch (~1.8 m wide × ~1.9 m high) at ~4–5 m depth with a sealed end 4 m south of the breach. Sonar confirms a northward segment measuring 45 ± 2 m to a sealed wall; a GPR void-type anomaly at ~57 m along trend represents a candidate continuation that remains unverified with current access. Within the resolution and sensitivity of the 2D survey, no additional voids were detected elsewhere on site. This case demonstrates that coupling in-void CCTV/sonar with post-drainage GPR and UHD-ERT, organized by hydrologic stage, yields engineering-grade constraints for risk control. The workflow and boundary conditions provide a transferable template for water-influenced, urban environments. Full article

The high-voltage system of high-speed trains is now in the form of combined electrical apparatus, which has a high probability of insulation breakdown due to frequent overvoltage during operation. To solve this issue, an electric field simulation model of the high-voltage combined electrical system was established, the electric field distribution of the high-voltage box electrode under overvoltage operating conditions was analyzed, and the air breakdown characteristics under field action were studied. The study shows that under overvoltage conditions, the electric field intensity near the small electrodes of the combined electrical unit is higher than the air breakdown field intensity, and the statistical time delay is approximately 5.94 μs when 150 kV voltage is applied. When the size of the connected electrode is doubled and 150 kV voltage is applied, the statistical delay is about 7.20 μs and the probability of discharge is reduced. Further installation of an insulating partition between the circuit breaker and the ground switch completely solved the problem of low electrical gap insulation capacity. Combined with impulse withstand tests, the effectiveness of the electrode size design was verified, and the research results provided theoretical support for the miniaturization and high-reliability design of vehicle-mounted high-voltage electrical appliances. Full article

This paper investigates the capacitance characteristics of a glass-embedded interdigitated capacitive sensor (IDCS) for touch-sensing applications. The study analyzes both baseline (no-touch) and touch-induced capacitance variations through a combination of analytical modeling and experimental validation. A multilayer analytical model is first employed to calculate the baseline capacitance of the proposed structure, followed by experimental measurements for model verification. Subsequently, an equivalent circuit model of the touched state is introduced to represent the interaction between the human fingertip, sensor electrodes, and earth-ground, explaining the observed capacitance reduction during a finger touch. Sensor prototypes with electrode finger widths of 1.4, 2.0, 2.4, and 3.0 mm were fabricated within a 40 × 40 mm² sensing area. The baseline capacitance decreased from 28.6 pF at 1.4 mm to 12 pF at 3.0 mm electrode finger width, while the capacitance change upon touch ranged from 0.6–0.9 pF. Touch sensitivity for three test persons increased from about 1.7–4.6% at 1.4 mm to 5–7.6% at 3.0 mm electrode finger width. The results confirm that narrower-electrode designs yield higher absolute capacitance, whereas wider electrodes enhance touch sensitivity and provide greater uniformity within the defined sensing area. Overall, the findings validate the proposed IDCS configuration as a practical approach for realizing glass-integrated touch sensors and offer practical guidelines for optimizing electrode geometry in touch-based smart-glass applications. Full article

The elevated needs for high-performance energy storage, dictated by electrification, renewable sources integration, and the global increase in interconnected devices, have placed batteries to the forefront of technological research. Additive manufacturing is increasingly recognized as a compelling approach to advance battery research and application by enabling tailored control over design, pore geometry, materials, and integration. This perspective work examines the opportunities and challenges associated with utilizing additive manufacturing as an enabling battery manufacturing technology. Recent advances in the additive fabrication of electrodes, electrolytes, separators, and integrated devices are examined, exhibiting the potential to acheive electrochemical performance, design adaptability, and sustainability. At the same time, key challenges—including materials formulation, reproducibility, economic feasibility, and regulatory uncertainty—are discussed as limiting factors that must be addressed for achieving the expected results. Rather than being viewed as a replacement for conventional gigafactory-scale production, additive manufacturing is positioned as a complementary fabrication technique that can deliver value in niche, distributed, and application-specific contexts. This work concludes by outlining research and policy priorities that could accelerate the maturation of 3D-printed batteries, stressing the importance of hybrid manufacturing, multifunctional printable materials, circular economy integration, and carefully phased timelines for deployment. Moreover, by enabling customized form factors, improved device–user interfaces, and seamless integration into smart, automated environments, additive manufacturing has the potential to significantly enhance user experience across emerging battery applications. In this context, this perspective provides a grounded assessment of how additive fabrication methods may contribute to next-generation battery technologies that not only improve electrochemical performance but also enhance user interaction, reliability, and seamless integration within automated and control-driven systems. Full article