Search Results (3,752)

Cascading link failures continue to imperil power grids, transport networks, and cyber-physical systems, yet the relationship between a network’s robustness at the moment of attack and its subsequent resiliency remains poorly understood. We introduce a dynamic framework in which connectivity-based cascades and distributed self-healing act concurrently within each time-step. Failure is triggered when a node’s active-neighbor ratio falls below a threshold $\phi$; healing activates once the global fraction of inactive nodes exceeds trigger $T$ and is limited by budget $B$. Two real data sets—a 332-node U.S. airport graph and a 1133-node university e-mail graph—serve as testbeds. For each graph we sweep the parameter quartet ($\phi ,\hspace{0.17em}B,\hspace{0.17em}T,attackmode$) and record (i) immediate robustness $R$, (ii) 90% recovery time T₉₀, and (iii) cumulative average damage. Results show that targeted hub removal is up to three times more damaging than random failure, but that prompt healing with $B\ge 0.12$ can halve T₉₀. Scatter-plot analysis reveals a non-monotonic correlation: high-$R$ states recover quickly only when $B$ and $T$ are favorable, whereas low-$R$ states can rebound rapidly under ample budgets. A multiplicative fit $T_{90}\propto B^{-\beta }g\left(T\right)h\left(R\right)$ (with$\beta \approx 1$) captures these interactions. The findings demonstrate that structural hardening alone cannot guarantee fast recovery; resource-aware, early-triggered self-healing is the decisive factor. The proposed model and data-driven insights provide a quantitative basis for designing infrastructure that is both robust to failure and resilient in restoration. Full article

This study presents a high-fidelity digital twin (DT) framework designed to evaluate and improve vertiport operations for Advanced Air Mobility (AAM). By integrating Unreal Engine, AirSim, and Cesium, the framework enables real-time simulation of Unmanned Aerial Vehicles (UAVs), including unmanned electric vertical take-off and landing (eVTOL) operations under nominal and disrupted conditions, such as adverse weather and engine failures. The DT supports interactive visualisation and risk-free analysis of decision-making protocols, vertiport layouts, and UAV handling strategies across multi-scenarios. To validate system realism, mixed-reality experiments involving physical UAVs, acting as surrogates for eVTOL platforms, demonstrate consistency between simulations and real-world flight behaviours. These UAV-based tests confirm the applicability of the DT environment to AAM. Intelligent algorithms detect Final Approach and Take-Off (FATO) areas and adjust flight paths for seamless take-off and landing. Live environmental data are incorporated for dynamic risk assessment and operational adjustment. A structured capacity evaluation method is proposed, modelling constraints including turnaround time, infrastructure limits, charging requirements, and emergency delays. Mitigation strategies, such as ultra-fast charging and reconfiguring the layout, are introduced to restore throughput. This DT provides a scalable, drone-integrated, and data-driven foundation for vertiport optimisation and regulatory planning, supporting safe and resilient integration into the AAM ecosystem. Full article

Background: Health promotion programs based on physical activity have gained increasing attention due to their potential to enhance employees’ physical and mental well-being, particularly in university settings, where academic and administrative staff are vulnerable to chronic stress, sedentary lifestyles, and work-related disorders. This study evaluates the effectiveness of the “University on the Move” program, an exercise-based workplace health promotion intervention implemented at the University of L’Aquila, Italy. Methods: An intervention study was conducted on 29 university employees participating in a supervised physical exercise program. Their anthropometric parameters, biochemical markers, cardiovascular risk factors, blood pressure, and work ability index were assessed at baseline (t0), three months (t1), and six months (t2), with a one-sample pre–post-test quasi-experimental design. Results: Significant improvements were observed in the cardiovascular risk factors, particularly in the female subgroup, e.g., the total cholesterol decreased by 20.8 mg/dL (p < 0.01), the LDL cholesterol decreased by 16.1 mg/dL (p < 0.01), and the fasting glucose decreased by 7.4 mg/dL (p < 0.01). Although the body mass index values remained stable, these metabolic improvements indicate beneficial effects independent of weight changes. The work ability index remained stable. The participation rates varied, with lower adherence to the training sessions. Conclusions: The study has some limitations (small sample size, no controlled design), all related to the primary aim of the preventive project targeted at the University employees who freely engaged in the protocol. Despite the low adherence (only about 30%), the metabolic improvements still suggest that structured workplace physical activity programs can positively impact employees’ health, even without significant weight loss, thus supporting the effectiveness of workplace health promotion and primary prevention interventions for an improved quality of life. Further research should explore long-term adherence and the organisational factors influencing participation. Full article

This study addresses the nonlinear estimation problem in the strapdown inertial navigation system (SINS) and Doppler velocity log (DVL) integrated navigation by proposing an improved filtering algorithm based on $S{E}_2(3)$ Lie group state representation. A dynamic model satisfying the group affine condition is established to systematically construct both left-invariant and right-invariant error state spaces, upon which two nonlinear filtering approaches are developed. Although the fast unscented transformation method is not novel by itself, its first integration with the $S{E}_2(3)$ Lie group model for SINS/DVL integrated navigation represents a significant advancement. Experimental results demonstrate that under large misalignment angles, the proposed method achieves slightly lower attitude errors compared to linear approaches, while also reducing position estimation errors during dynamic maneuvers. The 12,000 s endurance test confirms the algorithm’s stable long-term performance. Compared with conventional unscented Kalman filter methods, the proposed approach not only reduces computation time by 90% but also achieves real-time processing capability on embedded platforms through optimized sampling strategies and hierarchical state propagation mechanisms. These innovations provide an underwater navigation solution that combines theoretical rigor with engineering practicality, effectively overcoming the computational efficiency and dynamic adaptability limitations of traditional nonlinear filtering methods. Full article

The safety-critical functions of autonomous drones heavily rely on Positioning, Navigation and Timing (PNT) information provided by Global Satellite Navigation Systems (GNSSs). This makes GNSS technology a critical element as the PNT solution can be affected by several threats, mostly in urban and suburban environments. In order to evaluate safe and reliable GNSS-based solutions in Urban Air Mobility (UAM) scenarios, a proper GNSS security impact simulator is needed. In this context, the present work details the design, implementation and testing of a GNSS Threat Simulator (GTS) capable of reproducing typical issues within a GNSS system in a UAM environment, such as satellite visibility (i.e., the actual visibility condition of the receiver’s antenna with respect to terrain and ground obstacle), multipath, electromagnetic interference, cyber threats (i.e., spoofing and jamming) and satellites failures. The GTS elaborates and modifies dual-frequency multi-constellation GNSS observables in order to inject the desired threats. The effectiveness of the proposed simulator has been demonstrated through both fast-time and real-time simulations, in which the GTS was used to validate a hybrid navigation unit installed on a drone operating in a representative urban scenario. Full article

Classifying human locomotor activities from wearable sensor data is an important high-level component of control schemes for many wearable robotic exoskeletons. In this study, we evaluated three machine learning models for classifying activity type (walking, running, jumping), speed, and surface incline using input data from body-worn inertial measurement units (IMUs) and e-textile insole pressure sensors. The IMUs were positioned on segments of the lower limb and pelvis during lab-based data collection from 16 healthy participants (11 men, 5 women), who walked and ran on a treadmill at a range of preset speeds and inclines. Logistic Regression (LR), Random Forest (RF), and Light Gradient-Boosting Machine (LGBM) models were trained, tuned, and scored on a validation data set (n = 14), and then evaluated on a test set (n = 2). The LGBM model consistently outperformed the other two, predicting activity and speed well, but not incline. Further analysis showed that LGBM performed equally well with data from a limited number of IMUs, and that speed prediction was challenged by inclusion of abnormally fast walking and slow running trials. Gyroscope data was most important to model performance. Overall, LGBM models show promise for implementing locomotor activity prediction from lower-limb-mounted IMU data recorded at different anatomical locations. Full article

Given the fast-evolving context of electrical vertical takeoff and landing vehicles (eVTOL) based on the concept of tiltrotor aircraft, this work describes a framework aimed at the preliminary aerodynamic design and optimization of innovative lifting surfaces of such rotorcraft vehicles. In particular, a multiobjective optimization process was applied to the design of a wing extension representing an innovative feature recently investigated to improve the aerodynamic performance of a tiltrotor aircraft wing. The wing/proprotor configurations, selected using a Design Of Experiment (DOE) approach, were simulated by the mid-fidelity aerodynamic code DUST, which used a vortex-particle method (VPM) approach to model the wing/rotor wakes. A linear regression model accounting for nonlinear interactions was used by an evolutionary algorithm within a multiobjective optimization framework, which provided a set of Pareto-optimal solutions for the wing extension, maximizing both wing and rotor efficiency. Moreover, the present work highlighted how the use of a fast and reliable numerical modeling for aerodynamics, such as the VPM approach, enhanced the capabilities of an optimization framework aimed at achieving a more accurate preliminary design of innovative features for rotorcraft configurations while taking into account the effects of the aerodynamic interaction between wings and proprotors. Full article

The basic tone of the human voice is generated in the larynx, which is reinforced by and derives its distinctive features from the resonance of the oral and nasal cavities An inappropriate ratio between oral and nasal resonance results in a more nasal timbre of the voice, which is referred to as nasality (hypernasality). Nasality is often present in hearing-impaired patients, and various studies have shown that hypoacusis, including partial deafness (PD), causes voice disorders as a result of disturbed control over the complex process of voice production. This study describes our investigation of nasality in 20 adult Polish patients with post-lingual partial deafness. The results show that PD patients developed more nasality in their voices when compared with individuals in the control group. Observations made 9 months after cochlear implantation for partial deafness indicated a reduction in nasality, with the changes in acoustic parameters achieving statistical significance. Background/Objectives: This study aimed to assess whether partial deafness (PD) causes changes in nasal resonance in adult patients and whether partial deafness cochlear implantation (PDCI) influences the level of nasality. Methods: Voice samples from 20 patients attending the Institute of Physiology and Pathology of Hearing in Warsaw with partial deafness were analyzed and compared with samples from 20 individuals with normal hearing. Voice samples from the same patients were comparatively analyzed at 9 months after cochlear implantation. The level of nasality was assessed using the FFT (Fast Fourier Transform) for acoustic analysis, as well as subjective description by two experienced medical professionals (a medical doctor and a clinical acoustician). Pearson analysis was then performed to determine the correlations between the objective and subjective assessments. Paired two-sample t-tests for means were conducted for statistical analysis. All patients of the Institute of Physiology and Pathology of Hearing in Warsaw declared their deliberate consent to all necessary diagnostic and therapeutic procedures upon admittance. Results: The results show that post-lingual partial deafness causes nasality in adult patients when measured both objectively (p = 0.0001) and subjectively. The average objective level of nasality was 21 dB (SD 4.5), while the subjective level was an average grade of 1.25. The level of nasality presented a positive correlation with the duration of partial deafness. The assessment performed 9 months after cochlear implantation showed a reduction in nasality, achieving 17 dB (SD 4.2) in the objective measurement (p = 0.0002) and a grade of 0.5 when assessed subjectively. Pearson analysis showed a weak correlation between the objective measurement and subjective assessment (r = 0.2). Conclusions: Post-lingual partial deafness causes nasality in adults in a manner that is positively correlated with the duration of hearing impairment. Partial deafness cochlear implantation reduced nasality after 9 months of observation, as shown both objectively (MDVP) and subjectively (perceptual assessment). However, the correlation between the objective and subjective results is rather weak; therefore, objective acoustic methods (e.g., MDVP) should preferably be used for a more credible assessment, while the subjective method may only serve as a rough and general tool in everyday clinical use. Full article

Background: Osteosarcoma (OS) is a fast-growing malignant bone tumor that occurs most often in children and teenagers. Development of pulmonary metastasis is the primary cause of treatment failure and mortality. Our previous studies demonstrated that cytoplasmic p27 interacts with PAK1, enhancing PAK1 phosphorylation and promoting OS pulmonary metastasis. However, the cellular functions of p27 and PAK1 are primarily regulated by phosphorylation, and the roles of specific phosphorylation residues in modulating OS metastatic potential remain unclear. Methods: To study tumor invasiveness and lung metastasis, we employed a CRISPR-based knock-in method to introduce specific mutations—p27-T157A, p27-T157D, PAK1-T423E, and PAK1-K299R—into the 143B OS cell line, followed by in vitro invasion and orthotopic xenograft mouse experiments. These residues were selected for their therapeutic potential, as T157 regulates p27 nuclear–cytoplasmic shuttling, while T423 and K299 modulate PAK1 kinase activity. Results: No significant differences in pulmonary metastasis were observed across p27 mutants compared to parental controls. However, the p27-T157D mutant exhibited increased cytoplasmic mislocalization, elevated PAK1-S144 phosphorylation, and enhanced in vitro invasiveness compared to the p27-T157A mutant and parental 143B cells. The PAK1-K299R mutant, designed to be kinase-dead, showed negligible S144 phosphorylation, consistent with loss of kinase activity. Unexpectedly, this mutant displayed increased T423 phosphorylation and in vitro invasiveness, and significantly enhanced pulmonary metastasis in vivo compared to the PAK1-T423E mutant and parental controls. Conclusions: These findings highlight the complexity of targeting specific p27 and PAK1 phosphorylation sites as an anti-metastatic strategy for OS. While p27-T157 phosphorylation influences cytoplasmic localization and invasiveness, it does not significantly alter metastatic outcomes. Conversely, PAK1-T423 phosphorylation is critical in driving OS metastatic potential, and the kinase-dead K299R mutant’s unexpected pro-metastatic effect suggests that kinase-independent mechanisms or compensatory pathways may contribute to metastasis. Our findings suggest the necessity for a more comprehensive understanding of the phosphorylation dynamics of p27 and PAK1 in metastatic OS. They also indicate that conventional kinase inhibition may be insufficient and underscore the potential benefits of alternative or combinatorial therapeutic strategies, such as targeting kinase-independent functions or other upstream kinases involved in these regulatory pathways. Full article

Menopause is a natural and inevitable part of life for women, leading to many physical and psychological changes accompanied by declining estrogen levels. This systematic review aimed to evaluate the effect of curcumin, due to its antioxidant and anti-inflammatory properties, on postmenopausal outcomes in women. This comprehensive analysis of RCTs (randomized controlled trials) published in the last decade was selected through a search of PubMed, Wiley, Scopus, and Web of Science (PROSPERO Identifier: CRD42024549735). Study selection and data extraction were performed using exclusion and inclusion criteria according to the PICOS framework (P: Population, I: Intervention, C: Comparison, O: Outcomes, S: Study designs). Of the twelve studies that met the criteria, 11 had a low-risk bias, but reports were conflicting on serum estradiol levels, bone density markers, and vasomotor symptoms; no significant effects on physical, psychological, or sexual functions were observed. For cardiometabolic biomarkers, short-term curcumin intake showed no significant effects, while long-term interventions using bioavailable forms of curcumin showed improvements in serum fasting glucose, fasting insulin, HOMA-IR (Homeostatic Model Assessment of Insulin Resistance), and lipid parameters. There are a limited number of studies examining the effect of curcumin intake on menopause-related outcomes. While overdose has been observed in some studies attempting to restore estradiol levels, no significant effects have been observed. However, curcumin intake impacts postmenopausal symptoms (e.g., improving symptoms of osteoporosis) through its antioxidant and anti-inflammatory effects. Different forms and doses, combinations, and durations of interventions may influence outcomes. Better-designed studies are needed to understand the potential effects of curcumin intake during menopause. Full article

Gestational diabetes mellitus (GDM) is a frequently encountered medical complication during pregnancy that is increasing at a rapid pace globally, posing significant public health concerns. Similarly, there is a rising trend in the number of women who have utilized assisted reproductive technology (ART). Numerous studies have been carried out to investigate the relationship between GDM and ART. This comprehensive systematic review seeks to identify potential biomarkers for the early diagnosis of GDM in pregnancies conceived through ART. We conducted a PubMed search covering the past five years to identify studies that explore biomarkers associated with the development of GDM in pregnancies conceived through ART. The outcome measures included human chorionic gonadotropin (HCG), the body mass index (BMI), the Follicle Stimulating Hormone to Luteinizing Hormone (FSH/LH) ratio, increased hemoglobin A1c levels, fasting insulin concentrations, homeostatic model assessment of insulin resistance (HOMA-IR), triglyceride levels, total cholesterol levels, low-density lipoprotein cholesterol concentrations, low-density lipoprotein/high-density lipoprotein (LDL/HDL), total cholesterol to high-density lipoprotein (TC/HDL), the estradiol/follicle ratio, soluble fms-like tyrosine kinase-1 (sFlt-1), Placental Growth Factor (PLGF), endometrial thickness, and psychological stress. Seventeen studies were included. The identification and development of serum or ultrasound biomarkers for the early detection of GDM in pregnancies conceived through ART pose considerable challenges. These challenges arise from the multifactorial nature of GDM, the methodological variations in ART, and the limited availability of relevant studies. The most promising biomarker identified was the estradiol/follicle ratio. Women with a higher estradiol/follicle ratio exhibited significantly lower rates of GDM. There is a pressing necessity for biomarkers to enable the early detection of GDM in pregnancies conceived through ART. E2 levels, β-hCG, and the E2/F ratio, along with the TC/HDL and LDL/HDL ratios, show potential as reliable biomarkers for identifying GDM. Full article

Developing advanced receiver autonomous integrity monitoring (ARAIM) for ground real-time precise positioning applications such as autonomous vehicles presents computational challenges, particularly in calculating real-time protection levels (PLs) that bound possible positioning errors under an acceptable integrity risk. This study proposes an enhanced method for fast PL estimation by introducing a segmentation approach to the Gershgorin circle theorem-based technique for computing standard deviation upper bounds (UBs). This method divides satellites into segments based on normalised geometry mapping coefficients, allowing multiple UBs instead of a single bound for all subsets within each fault-tolerant mode. The approach is implemented for PPP-RTK with an improved Classification Adaptive Kalman Filter (CAKF). Testing is conducted using a network of 10 continuously operating reference stations (CORSs) employing dual-frequency multi-constellation GNSS data. Results show that when monitoring single fault mode, the PL ranges from 0.05 to 0.1 m with a PL-to-PE ratio of 30:1, while dual fault modes monitoring yields PL from 1 to 10 m with a ratio of 3700:1. The segmentation method achieves 1–5% tighter PLs, i.e., better integrity monitoring (IM) availability, compared to the classical single UB approach while maintaining the same computational efficiency by reducing processed subsets from 325 to 1 for dual fault modes. While the method provides slight improvement in PL tightness, it can be more computationally efficient when having geometries with dominant off-diagonal correlation that fails the computation of a UB. Full article

The APSIM (Agricultural Production Systems Simulator)-Wheat model has been widely used to simulate wheat growth, but the sensitivity characteristics of the model parameters at different soil moisture levels in arid regions are unknown. Based on 2023~2025 winter wheat field data from the Changji Experimental Site, Xinjiang, China, this study conducted a global sensitivity analysis of the APSIM-Wheat model using Morris and EFAST methods. Twenty-one selected parameters were perturbed at ±50% of their baseline values to quantify the sensitivity of the aboveground total dry matter (WAGT) and yield to parameter variations. Parameters exhibiting significant effects on yield were identified. The calibrated APSIM model performance was evaluated against field observations. The results indicated that the order of influential parameters varied slightly across different soil moisture levels. However, the WAGT output was notably sensitive to accumulated temperature from seedling to jointing stage (T1), accumulated temperature from the jointing to the flowering period (T2), accumulated temperature from grain filling to maturity (T4), and crop water demand (E1). Meanwhile, yield output showed greater sensitivity to number of grains per stem (G1), accumulated temperature from flowering to grain filling (T3), potential daily grain filling rate during the grain filling period (P1), extinction coefficient (K), T1, T2, T4, and E1. The sensitivity indices of different soil moisture levels under Morris and EFAST methods showed highly significant consistency. After optimization, the coefficient of determination (R²) was 0.877~0.974, the index of agreement (d-index) was 0.941~0.995, the root mean square error (RMSE) was 319.45~642.69 kg·ha^–1, the mean absolute error (MAE) was 314.69~473.21 kg·ha^–1, the residual standard deviation ratio (RSR) was 0.68~0.93, and the Nash–Sutcliffe efficiency (NSE) was 0.26~0.57, thereby enhancing the performance of the model. This study highlights the need for more careful calibration of these influential parameters to reduce the uncertainty associated with the model. Full article

The gut microbiota plays a significant role in metabolic diseases such as obesity. We extracted and purified a new type of pectin polysaccharide (mango peel pectin, MPP) from mango (Mangifera indica L.) peel. The structural analysis results reveal that MPP has a molecular weight (Mw) of 6.76 × 10⁵ Da and the mass fractions of the main components were galacturonic acid (21.36%), glucose (8.85%), and arabinose (5.97%). The results of methylation and NMR analyses reveal that the backbone of MPP consisted of →6)-α-D-GalpAOMe-(1→ and →4)-β-D-Glcp-(1→ linkages. Based on the above structural analysis, we further explored the therapeutic effect of MPP on high-fat diet-induced obese mice. The results demonstrate that MPP significantly suppressed body weight and dyslipidemia, reduced liver damage and lipid accumulation, attenuated changes in adipocyte hypertrophy, and improved glucose homeostasis and insulin resistance, with fasting blood glucose (FBG) levels decreasing by more than 12.8%. Furthermore, the modulatory impact of MPP on gut microbiota composition was investigated. MPP treatment significantly enhanced the levels of short-chain fatty acids (SCFAs) by decreasing the amount of Bacillota and reducing the Bacillota/Bacteroidota ratio, especially with an increase in the total SCFA content of over 64%. Meanwhile, MPP treatment encouraged beneficial bacteria to grow (e.g., Bacteroidota, Akkermansia, and Nanasyncoccus), altered the gut microbiome profiles in mice, and decreased the abundance of harmful bacteria (e.g., Paralachnospira, Coproplasma, Pseudoflavonifractor, Parabacteroides, Acetatifactor, and Phocaeicola). Overall, the findings demonstrate for the first time that MPP treats obesity by alleviating dyslipidemia, improving insulin resistance, and regulating gut microbiota to improve the intestinal environment. Full article

Periprosthetic joint infection (PJI) is a devastating complication of joint arthroplasty surgery that is difficult to both diagnose and treat. Misdiagnosing a prosthetic infection has terrible consequences for both the patient and healthcare system. No currently used diagnostic test fulfills the requirements to be considered a gold standard. This shortcoming has been overcome through the implementation of multi-criteria diagnostic protocols elaborated by societies including the Infectious Diseases Society of America, International Consensus Meeting and European Bone and Joint Infection Society, using a combination of clinical, paraclinical and molecular findings in order to achieve the best accuracy in diagnosing PJI. This review aims to survey the current state of the techniques and technologies used for the diagnosis of PJI, investigating the accuracies of serum biomarkers (e.g., C-reactive protein, Interleukin-6, procalcitonin, D-dimers, Serum Intercellular Adhesion Molecule-1), synovial biomarkers (e.g., Antimicrobial peptides, lipocalin-2, leukocyte esterase, calprotectin), tissue biomarkers (e.g., Toll-like receptors, CD15) and advanced molecular techniques (e.g., Polymerase chain reaction, Metagenomic next-generation sequencing), as well as describing their ongoing limitations. In the search for an accurate, inexpensive and fast diagnostic test for PJI, we conclude that the accuracies of the currently studied biomarkers could be further enhanced through the development of novel detection technologies. Full article