Search Results (396)

The squat is a critical component of numerous rehabilitation and functional assessment protocols, playing a significant role in enhancing athletic performance and activities of daily living. Although some of the characteristics gathered during the squat need additional confirmation, Kinovea provides a free two-dimensional squat motion analysis tool that is simple to use in clinical practice. This analytical, cross-sectional reliability study aimed to evaluate the intra-rater and test–retest reliability (with a 20 min interval between performances) of loaded squat kinematics in a sample of women using Kinovea. Twenty women performed a loaded back squat; intra-rater reliability was assessed by re-analyzing the same video one week apart, and test–retest reliability was assessed across two performances separated by 20 min. The results showed good to excellent intra-rater reliability (ICC: 0.75–0.99; SEM: 0.16 cm to 5.14°; MDC: 0.44 cm to 14.24°), and moderate to excellent test–retest reliability (ICC: 0.64–0.98; SEM: 0.36 cm to 14.29°; MDC: 0.99 cm to 39.61°). Variables tracked in the sagittal plane showed high precision. Conversely, the head angle and knee angle in the frontal plane exhibited greater variability, reflected by higher SEM and MDC values. In conclusion, Kinovea is a reliable and accessible tool for clinical kinematic assessment of the squat, particularly in the sagittal plane parameters. However, due to the elevated measurement error observed in head angles and frontal-plane knee dynamics, the integration of 3D motion capture is recommended over 2D digital protocols for these variables. Full article

With the rapid expansion of urban underground space in China, anti-floating has become a critical challenge, and uplift piles are a key solution. Previous studies on composite anchor-cable uplift piles have primarily focused on small-diameter single-pipe types (≤600 mm), often simplifying the pile as an integral component, leaving the multi-interface stress transfer mechanisms of large-diameter piles inadequately understood. This study proposes a back-analysis method based on orthogonal experiments, implemented using Abaqus 3D finite element software, to determine interfacial mechanical parameters for three critical contact pairs (strand-grout, grout-steel pipe, steel pipe-concrete) in large-diameter multi-pipe composite anchor-cable uplift piles. These parameters are then implemented in a refined 3D finite element model to simulate the load-deformation behavior of such piles. Quantitative results show that the back-calculated parameters are highly reliable, with maximum simulation errors for pile head displacement limited to 13.0% and 9.6% for fully bonded and semi-bonded piles, respectively. Unlike conventional piles, stress and strain in this new pile type transfer progressively from the inner steel strands outward and from the top downward, resulting in reduced pile-soil displacement mismatch, fuller mobilization of side interfacial strength, and effective mitigation of concrete cracking. This study provides a systematic parameter-calibration framework and numerical platform, offering theoretical and technical support for optimized design and engineering application of large-diameter composite uplift piles. Full article

This paper presents an application-oriented evaluation of a 130 kW interior permanent magnet synchronous motor (IPMSM) for C-segment electric vehicle (EV) traction by linking sequentially coupled multiphysics analysis with WLTP-based vehicle system-level simulation. Conventional motor performance evaluation is based on single-physics analysis at a limited number of operating points. This approach is insufficient to capture nonlinear characteristic variations under changing operating conditions or to reflect realistic driving environments. To overcome this limitation, sequentially coupled multiphysics analysis incorporating electromagnetic, thermal, and structural characteristics was performed, and the resulting loss data were incorporated into a vehicle system-level simulation model. The WLTP Class 3b driving cycle was applied to quantitatively evaluate energy performance under realistic driving conditions. The results show that the designed IPMSM satisfies the target output power of 130 kW, while its electromagnetic, thermal, and structural characteristics, including torque ripple, back-EMF, winding temperature, permanent magnet temperature, and rotor stress, remain within acceptable limits. The system-level analysis further indicates that the motor operating points during driving are predominantly distributed in the high-efficiency region, and that the final energy economy considering regenerative braking reaches 5.59 km/kWh, with an estimated maximum driving range of 352.58 km on a single charge. These results indicate that the combined motor-level and vehicle-level numerical evaluation can provide useful design-stage information for assessing high-power-density EV traction motors. Full article

Background/Objectives: Chronic low back pain (CLBP) affects approximately 20% of the global population and is a leading cause of years lived with disability. Long-term, real-world evidence for inhaled cannabis in patients refractory to conventional multimodal therapy remains scarce. We assessed the five-year efficacy and safety of inhaled cannabis in CLBP patients who had documented failure of ≥1 year of opioid analgesics, anticonvulsants, antidepressants, NSAIDs, and physiotherapy, with each patient serving as their own historical control. Methods: We analyzed prospectively collected clinical data from 241 consecutive adults with treatment-refractory CLBP (mean age 49.3 ± 14.9 years; 37.8% female; mean pain duration 15.1 years) initiated on inhaled medical cannabis (predominantly smoking, THC 4–22%, CBD 2–22%) in a single-center tertiary orthopedic clinic between 2020 and 2025 (Hasharon Hospital, Rabin Medical Center, Israel; IRB protocols 0807-21-RMC and 0634-25-RMC). Year-0 outcomes during conventional therapy were compared with outcomes at Years 1–5 on cannabis. Primary outcomes were the Numeric Rating Scale (NRS), Oswestry Disability Index (ODI), and Brief Pain Inventory severity/interference (BPI-S/BPI-I). Concomitant-medication trajectories were a secondary outcome. The primary analysis was a mixed model for repeated measures (MMRM) with random intercept and slope, REML estimation, and time as a categorical fixed effect. Multiple imputation (MAR, m = 20, Rubin’s rules) was the primary missing-data approach; complete-case and tipping-point pattern-mixture sensitivity analyses were used. A multivariate Hotelling T² provided a joint test across the four correlated PROMs. Concomitant-medication discontinuation was modeled with GEE logistic regression and exact McNemar tests. Time to discontinuation was estimated by Kaplan–Meier and Cox regression. The Bonferroni-adjusted significance threshold for the four primary outcomes was α = 0.0125. BioWell gas-discharge-visualization (GDV) parameters were exploratory only. Results: Of 241 patients, 238 (98.8%) provided Year-5 data and 224 (92.9%) remained on cannabis at Year 5; only five patients (2.1%) discontinued for adverse events or inefficacy. All four primary PROMs improved markedly and durably. MMRM-estimated Year-5 minus Year-0 changes were: NRS −5.36 (95% CI −5.65, −5.07), ODI −17.68 (95% CI −19.73, −15.63), BPI-S −6.73 (95% CI −6.99, −6.47), and BPI-I −3.41 (95% CI −3.65, −3.16); all four contrasts had |z| ≥ 16.9 and p < 10⁻²⁰. MI-pooled estimates were within 0.05 of MMRM (FMI < 0.03 for all outcomes). Hotelling T² was F(4, 232) = 872.8, p < 10⁻²⁰. At Year 5, 89.2% achieved ≥30% NRS reduction, 77.2% ≥ 50%, and 93.4% met the NRS minimum clinically important difference (MCID); ODI MCID 65.6%, BPI-S MCID (≥1 pt) 98.3%, BPI-I MCID (≥1 pt) 91.3%. Concomitant opioid use fell from 100% at baseline to 4.6% at Year 5 (within-patient absolute risk reduction 95.4%, McNemar exact p = 1.16 × 10⁻⁶⁹), NSAID from 100% to 7.1%, SSRI/SNRI from 80.5% to 5.4%, and gabapentinoid from 38.6% to 2.5%. The ARR-derived NNT for opioid discontinuation was 1.05; this NNT is referenced to each patient’s own documented maximal-conventional-therapy state and is not equivalent to a between-arm randomized-trial NNT. Cannabis dose × time interaction was consistent with no pharmacological tolerance (β = −0.0044 per gram-month per year, p = 0.074). Across 1205 patient-years of cannabis exposure (calculated as 241 patients × 5 follow-up years from Year 1 through Year 5; baseline Year 0 represents pre-cannabis state and is not included in person-time on cannabis), 1338 organ-system AE events were recorded at 1.110/patient-year (Poisson 95% CI 1.05–1.17); 99.8% of graded events were mild (grade 1), with ocular (476 events, 0.40/PY), cognitive (460, 0.38/PY), and gastrointestinal (368, 0.31/PY) reactions predominating. The Year-3 retention dip reflected a documented telemedicine-clinic phenomenon during 2022–2024, with patients returning to in-person follow-up by Year 4–5. BioWell GDV discriminated NRS ≥ 4 only at chance level (BWS AUC 0.574, 95% CI 0.54–0.60; BWV AUC 0.51). Conclusions: In a treatment-refractory CLBP cohort with five-year longitudinal follow-up, inhaled cannabis was associated with large, sustained, and statistically robust improvements in pain, disability, and pain interference, accompanied by near-total displacement of opioids, NSAIDs, antidepressants, and gabapentinoids. These observational associations, although mechanically less susceptible to bias for the binary medication-discontinuation outcomes than for self-reported PROMs, cannot be interpreted causally in the absence of a concurrent randomized control arm and may reflect a combination of pharmacological effect, regression to the mean from a high pre-treatment baseline, expectancy and self-selection effects intrinsic to an actively chosen open-label therapy, and secular trends in pain reporting. The within-patient benefit-risk profile—ARR-derived NNT ≈ 1 for opioid sparing against a predominantly mild adverse-event burden—supports consideration of cannabis as a potentially clinically meaningful, opioid-sparing option in patients who have failed multimodal conventional therapy, pending confirmation in randomized comparative trials. Full article

With the increasing development in urban underground spaces towards greater depth, scale, and complexity, the prediction and control of deformations in deep excavation engineering have become critical challenges in geotechnical engineering. This study investigates the ultra-deep excavation of the Tianjin Metro Line 8 Liulitai Station, analyzing the deformation characteristics of the retaining structure during top-down construction in soft soil based on field monitoring data. The results reveal a typical “bulging” pattern in the horizontal displacement of the diaphragm wall, which accumulates progressively with excavation depth. To enhance deformation prediction accuracy, a self-developed beam-plate finite element method (BPFEM) platform, implemented in Python (version 3.11.9), is introduced. The platform integrates code-specified analytical methods and the incremental approach to simulate the internal forces and deformations of the support system with high precision. By incorporating a dual-parameter back-analysis technique—adjusting both the horizontal subgrade reaction modulus and active earth pressure—the numerical model achieves significantly improved agreement with monitoring data. The proposed method demonstrates strong predictive capability, with a maximum error of only 4.4% in subsequent construction stages, confirming its feasibility and reliability for deformation forecasting in top-down deep excavations. The BPFEM framework and parameter inversion strategy presented herein provide an effective technical basis for intelligent prediction and dynamic control in deep excavation projects under complex geological conditions. Full article

Aiming at the problems of insufficiently tight sealing of all-metal dissolvable frac plugs and the poor fracturing effect in the extraction of shale gas, the effects of structural parameters on the performance of metal dissolvable ball seat sealing rings was analyzed using numerical simulation and an experimental method. The key structural factors affecting performance were identified. The problem of stress concentration at the contact position between the sealing ring and the slip of the existing structure was discovered. To solve the above problems, a combination structure sealing ring was designed. Then the performance comparison analysis of the two structures and optimal structural parameters were carried out. Under the same sealing force, the combination structure sealing ring can be smoothly sealed, and the stress distribution of the upper sealing ring is uniform. This indicates that the performance of the combination structure sealing ring is superior, and the optimal cone angle and thickness obtained are 9° and 17 mm, respectively. Based on the optimized structural parameters, experiments were conducted. After being pressurized at room temperature to 51 MPa and stabilized for 15 min, the pressure gradually decreased to 47.4 MPa, indicating a secondary setting. After unloading, the lower end face of the dissolvable ball seat has no liquid leakage. Under high temperature, a pressure of 51 Mpa was applied; the pressure inside the wellbore remained basically unchanged. During the process of applying pressures of 60 MPa and 70 MPa, there was also a decrease in pressure, indicating the presence of secondary sealing. The above results indicate that the optimized combined metal sealing ring has strict sealing and good pressure-bearing performance. At the same time, the reliability of the simulation results was verified. The designed sealing ring was applied to the shale gas horizontal well deployed in Changning block, China. The application results show that when the displacement remains unchanged, the casing pressure increases from 51 MPa to 60 MPa, and continues to maintain the displacement. The pressure did not fall back to 51 MPa, proving that the formation pressure is released. The successful on-site application once again verifies the safe and reliable performance of the all-metal sealing ring. Full article

Background/Objective: Kinesiophobia is a major fear-avoidance concept in chronic low back pain (CLBP); however, its independent contribution to pain, disability, and health-related quality of life (HRQoL) beyond sociodemographic and clinical variables remains unclear. This study aimed to evaluate the associations between kinesiophobia and patient-reported outcomes in adults with chronic low back pain regarding (i) pain intensity, (ii) functional disability, and (iii) HRQoL. Methods: This cross-sectional study included 298 participants with CLBP (average age 38.7 ± 13.2 years; 58.0% female). Kinesiophobia was evaluated using the Tampa Scale of Kinesiophobia (range, 17–68). Outcomes were pain intensity (Numerical Pain Rating Scale; 0–10), functional disability (Roland–Morris Disability Questionnaire; 0–24), and HRQoL (RAND-36; 0–100). Two multivariable linear regression models were used per outcome. Model 1 was adjusted for sex and age, and Model 2 was additionally adjusted for BMI, marital status, education, employment, smoking status, and chronic disease. Hierarchical regression analysis evaluated the incremental variance explained by kinesiophobia (ΔR²) when entered after all covariates. Effects were reported per 10-point increase in Tampa score, with 95% confidence intervals (CI). Results: In the fully adjusted models, higher kinesiophobia was associated with greater pain intensity (B = +1.17 points per 10 Tampa; 95% CI 0.55–1.79, p < 0.001), greater disability (B = +3.24 points; 95% CI 2.05–4.43; p < 0.001), and lower HRQoL (B = −7.98 points; 95% CI −11.1–−4.81; p < 0.001). Hierarchical regression analyses showed that kinesiophobia explained additional variance in pain (ΔR² = 0.11), disability (0.12), and HRQoL (0.11), all p < 0.001. Conclusions: In adults with CLBP, kinesiophobia was associated with greater pain intensity, functional disability, and lower HRQoL, accounting for 11–12% of variance in each outcome beyond demographic and clinical covariates. These findings support routine assessment of kinesiophobia and justify longitudinal and interventional studies to determine temporal relationships and treatment effects. Full article

Vairimorpha ceranae (formerly Nosema ceranae) is an obligate intracellular parasite that poses a major threat to the health of the honey bee. Circular RNAs (circRNAs) have been recognized as key regulators in gene expression and pathogen–host interactions. However, their expression patterns and regulatory roles in V. ceranae infection remain largely unexplored. In this study, we performed circRNA profiling in V. ceranae spores (NcCK) and the midguts of Apis mellifera ligustica workers at 7 d post inoculation (dpi) and 10 dpi (Nc7T and Nc10T) based on transcriptome sequencing, followed by in-depth investigation of the regulatory roles of differentially expressed circRNAs (DEcircRNAs). In total, 243 circRNAs were identified in V. ceranae, with lengths predominantly ranging from 201 to 400 nucleotides. Comparative analysis screened 70 and 192 DEcircRNAs in the NcCK vs. Nc7T and NcCK vs. Nc10T comparison groups, respectively, with a significant majority being downregulated. The parental genes of these DEcircRNAs were significantly enriched in fundamental cellular processes and critical pathways such as protein processing in the endoplasmic reticulum and ribosome biogenesis. Additionally, we constructed a competing endogenous RNA network, suggesting that DEcircRNAs could potentially interact with DEmiRNAs to modulate mRNAs associated with fungal proliferation-relevant signaling pathways like MAPK, PI3K–Akt, and cAMP. Moreover, numerous DEcircRNAs were predicted to contain internal ribosome entry site elements, indicative of their potential for protein coding. The back-splicing junctions and expression trends of selected DEcircRNAs were successfully validated by RT-PCR and qRT-PCR. Our data not only offer a valuable resource for future functional studies but also provide a basis for elucidating the circRNA-mediated mechanisms underlying microsporidian pathogenesis and host–pathogen interactions. Full article

This paper introduces an adaptive prescribed performance control (PPC) methodology designed to achieve appointed-time stabilization for morphing aircraft. The proposed approach ensures accurate attitude tracking despite challenges posed by time-varying dynamic constraints, structural deformation perturbations, abrupt aerodynamic disturbances, and rapid variations in attitude commands. Specifically, a novel appointed-time control law is developed using the back-stepping framework to enable precise adjustment of the stabilization time. Then, an adaptive performance boundary adjustment function is introduced. This function not only constrains the system state error but also adapts based on the distance between the state error and the real-time boundary, as well as command variations. This mitigates the fragility issues associated with traditional PPC methods. To further address the ‘differential explosion’ problem, an adaptive appointed-time filter is constructed in which the filter error can be stabilized for an appointed time. The unknown and total perturbations are estimated via adaptive neural networks. The designed controller is shown to guarantee the appointed time stability for all closed-loop signals and ensure that the system state error stays inside the prescribed bounds based on the stability analysis. Lastly, numerical simulations are performed to verify the advantages and effectiveness of the proposed method. Full article

To investigate the axial compressive behavior of double C-section partially encased composite (DCPEC) columns, 10 DCPEC specimens and two back-to-back bare steel C-section specimens were designed and tested under axial compression. The effects of key parameters, including steel wall thickness, member slenderness ratio, connection type of the built-up double C-sections and connection density, on the failure mode, load–displacement response and ultimate load-carrying capacity were examined. The test results showed that, under otherwise identical conditions, the ultimate load of the bolted stub column was 8.4% higher than that of the welded stub column. When the steel wall thickness increased from 2.0 mm to 3.0 mm, the ultimate load increased by approximately 16%. In contrast, when the slenderness ratio increased from 25.98 to 41.57, the ultimate load decreased by approximately 30%. A finite element model was then established in ABAQUS and validated against the experimental results. The numerical analysis further confirmed that increasing the slenderness ratio reduced the axial load-carrying capacity, whereas increasing the steel wall thickness improved the resistance of the member. The results indicate that the proposed DCPEC column can effectively develop the composite action between cold-formed thin-walled steel and lightweight aggregate concrete, thereby improving axial resistance and showing promising potential for engineering applications. Full article

Physics-based simulation of debris flows over complex terrain is essential for hazard assessment, but repeated numerical integration is costly when many scenarios must be explored. We develop a general deep-learning surrogate modelling framework for two-dimensional (2D) debris-flow propagation, here applied to the Morino–Rendinara area (central Italy) using a three-dimensional (3D) Fourier Neural Operator (FNO) trained on synthetic simulations generated by a validated in-house finite-volume shallow-water solver. The solver reproduces debris-flow propagation over complex terrain and is specifically developed for artificial intelligence (AI) applications. It is based on a depth-averaged 2D formulation using the Harten–Lax–van Leer–Contact (HLLC) approximate Riemann solver, hydrostatic reconstruction, positivity-preserving wet–dry treatment, and Voellmy-type basal friction, and was verified through analytical benchmarks, numerical tests, and back-analyses of real events. The dataset was built from four site-specific release settings derived from real topography, combining different released volumes and bulk densities while preserving local geomorphological and rheological characteristics. Each simulation was stored as a full spatio-temporal tensor and used to train an FNO conditioned on coordinates, topography, friction parameters, bulk density, and initial release thickness. Training used a novel loss to emphasize active-flow areas and improve velocity reconstruction, and was performed using a graphics processing unit (GPU). The surrogate shows effective generalization to within-distribution validation samples, with global relative mean squared errors of 5.49% for flow thickness, 5.34% for velocity component u, and 2.60% for v, and mean $R^2$ values of 0.95, 0.94, and 0.97. For a representative sample, the surrogate predicts the full spatio-temporal solution in $0.52$ s, versus about 47 s for the first-order finite-volume solver, corresponding to a speed-up of about $91\times$, with an even larger gap expected for higher-order solvers, since, whilst the computation time of the solver increases as its complexity increases, the computation time of the FNO remains essentially unchanged. These results indicate that the proposed FNO is a reliable site-specific surrogate for rapid approximation of 2D debris-flow dynamics over real terrain, with potential for uncertainty propagation, Monte Carlo analysis, large-ensemble simulation, and hazard-oriented scenario assessment. Full article

Deployable structures offer new solutions in space, and among them, tubular origami-inspired space structures have proven to be a robust solution for packaging problems. This study focuses on the analysis of the Kresling origami pattern, which theoretically offers bi-stability during its folding process. The bi-stability of this pattern is a well-known property for paper models. However, it cannot be generalised for any material or geometry, as this property can be traced back to the manufacturing process and the materials being used. Consequently, we propose and test additive manufacturing models implementing different geometry parameters with the materials of interest. In parallel, a parametrised numerical model was developed in the commercial software Abaqus, replicating the structural behaviour of these test specimens under displacement-controlled compression. The aim is to obtain a final validated numerical model from where the entire behaviour and energetic response of each sample and, thus, their stability can be tested. Combining experimental and numerical results paints a whole picture of bi-stability, verifying this useful property for different space materials and configurations. Full article

The buckling and post-buckling responses of carbon fibre-reinforced polymer (CFRP) structures are strongly affected by geometric imperfections, boundary conditions, and material nonlinearities, making their reliable numerical prediction challenging. This work presents an integrated experimental–numerical investigation of a stiffened CFRP panel subjected to compressive loading, with the aim of improving model validation in instability regimes. The experimental campaign combines full-field measurements obtained through digital image correlation with local strain data from strain gauges, adopting a back-to-back configuration to capture the strain reversal associated with global buckling. The experimental results are compared with nonlinear finite element simulations incorporating intralaminar damage based on Hashin’s failure criteria. A good agreement between the numerical and experimental results is observed in the pre-buckling and early post-buckling regimes. However, increasing discrepancies arise at higher load levels, mainly due to manufacturing imperfections and uncertainties in boundary conditions, which influence the onset and evolution of localized deformation. Statistical indicators are employed to quantitatively assess the correlation between the experimental and numerical responses. The analysis focuses on the key response parameters, including the load–displacement behaviour, out-of-plane displacements, strain evolution, and damage initiation, enabling a comprehensive comparison of experimental and numerical results. The results demonstrate the effectiveness of combining full-field and point-wise measurements for validating numerical models of composite structures. Furthermore, the study highlights the limitations of idealized modelling assumptions and provides insights into the sensitivity of CFRP structures to imperfections in post-buckling and failure regimes. Full article

The primary objective of this research is to quantitatively isolate the complex driving factors of slope deformation and explicitly reveal the long-term creep mechanism induced by early excavation unloading, thereby providing a theoretical basis for long-term stability evaluation. To achieve this, this study adopts a combined approach of multivariate statistical regression and numerical simulation inversion based on long-sequence monitoring data. First, a multivariate statistical regression model incorporating time-dependent, rainfall, temperature, valley width, and excavation components was constructed to quantitatively separate the contribution weights of each factor. Second, by introducing a rock–soil creep constitutive model, a refined finite element model was established to perform back-analysis of creep parameters and numerical simulation. The results indicate that two large-scale slope-cutting excavations were the direct triggers for the deformation, resulting in shear dislocation of the deep ancient sliding zone and superficial slippage. The dominant factors exhibit distinct phasic and spatial differences: before impoundment, the time-dependent component was absolutely dominant (>80%); after impoundment, low-elevation areas were significantly affected by valley width shrinkage (>60%), while high-elevation areas remained dominated by time-dependent deformation (>74%). Numerical simulation confirmed that the nature of the deformation is “excavation unloading-induced creep along the ancient sliding zone,” and the simulation results considering creep effects accurately reproduced the actual deformation characteristics observed in situ. It is concluded that the rheological effects induced by early excavation unloading are central to the control of long-term stability. Full article

The power system is the backbone of the energy network, and overhead lines are its vital structures. Weather threats may jeopardise the reliability of lines and make them a weak link. In particular, heavy rainfall episodes can cause failures, especially in mountain areas. Current climate changes may exacerbate the effects on the ground, intensifying rainfall episodes and increasing the frequency of extreme events. In this context, debris flows triggered by rather intense precipitation and characterised by fast kinematics can destroy pylons and electric connections, affecting the infrastructures not only in the upper ridges but also downstream across the fan apex, where powerlines are much more distributed. This study presents an in-depth back-analysis of two debris flow events triggered in concomitance with a heavy cloudburst that occurred in Talamona (Sondrio Province, Italy) in July 2008 and in Campo Tartano (Sondrio Province, Italy) in April 2024. These events hit onsite powerlines, causing blackouts and showing the potential vulnerabilities of the local electricity system. An analysis of rainfall-induced landslide failure is carried out using the numerical model CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment) and MIST-DF (Modelling Impulsive Sediment Transport—Debris Flow) with the aim of reconstructing the dynamics of the first (i.e., Talamona) geo-hydrological event. Powerline vulnerability is also investigated against debris flow dynamics, discussing possible strategies to reduce pylon exposure and to increase the resilience of the local electro-energetic network. Since, under climate change scenarios, heavy rainfall episodes are projected to intensify, an alternative approach based on rainfall-threshold curves is presented and applied to both cases of study. The latter, already implemented for civil protection purposes, could be useful in early-warning procedures against potential debris flow hazards. For both methodologies, the findings from the study confirm the strength of the approaches and foster their application in different situations (back-analysis and early warning) to reduce powerlines’ geo-hydrological risks. Full article