Politecnio die Bari - Catalogo di prodotti della Ricerca
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Room-Temperature and Atmospheric Pressure Coupling of Carbon Dioxide with Epoxides Catalyzed by Iodide Ions Confined in Nanopores of Periodic Mesoporous Organosilica
No full textEffect of Middle Ear Prosthesis Diameter in Platinotomy and Partial Platinectomy on Hearing Gain: A Finite Element Study
No full textThis study investigates, for the first time, using finite element analysis (FEA), the differential impact of middle ear prosthesis diameter on hearing gain in two distinct surgical techniques: stapedotomy and partial stapedectomy. The model represented the cochlea as two fluid-filled straight channels separated by the basilar membrane and considered pistons of 0.4 mm and 0.6 mm diameters. The results demonstrated that in stapedotomy, a 0.6 mm diameter piston yielded a significantly better reduction in ABG (8.31 dB) compared to the 0.4 mm piston (10.67 dB), indicating improved hearing gain. Conversely, in partial stapedectomy, the smaller 0.4 mm piston was more effective, reducing ABG to 11.2 dB versus 12.12 dB with the larger piston. These findings highlight that the optimal prosthesis diameter varies according to surgical technique, emphasizing the need for tailored prosthesis selection
Geotechnical subsoil modelling of a slope from the interpretation of ambient noise measurements and 2D site response analyses
No full textWithin the context of seismic risk assessment, the prediction of the dynamic response of natural slopes is strictly related to the accurate definition of the geotechnical subsoil model. This aspect is particularly challenging for those slopes characterised by the presence of buried morphologies, for which the vertical and lateral heterogeneities of the subsoil setting may predispose them to additional risks during seismic events. The paper proposes a methodological procedure aimed at identifying preliminary subsoil models of areas characterised by uneven topography and buried lithological bodies of uncertain morphology, through the comparison of parametric site response analyses and site-specific geophysical surveys. The procedure, tested with reference to the prototype case study of Costa del Canneto slope in Southern Italy, proves to be a useful tool to reduce the uncertainties associated with the presence of complex subsoil settings, including potential buried morphologies. Indeed, over several geotechnical models tested, the numerical analyses provide amplification profiles of the fundamental frequency reasonably comparable with data from ambient vibration measurements only for few of them. This allows to restrict the number of possible slope models and can be used to guide the design of additional in-situ geotechnical investigations needed to better characterise the stratigraphy of the area and constrain the geometry of the expected buried morphologies
Pharmacometric and Digital Twin modeling for adaptive scheduling of combination therapy in advanced gastric cancer
No full textBackground and Objective: Combining targeted therapeutics can significantly help address the dynamic changes in cancer biology abnormalities and thus improve the duration of response and outcome. However, the efficacy of such approaches is highly dependent on the combination, interactions, and timing between the administered drugs. Current clinical trials can test only a low number of schedules with fixed designs. Pharmacometric tools can assist in exploring and selecting the most effective drug dosages and schedules by modeling traits of patients with different clinical and biological characteristics. Methods: This study proposes a pharmacokinetic–pharmacodynamic model describing the networked system of tumor development and angiogenesis under the control of antiangiogenic and cytotoxic, i.e., Ramucirumab and Paclitaxel second-line combination therapy. A two-step scalable algorithm is proposed to calibrate model parameters and match virtual to real population therapy outcomes, followed by fine-tuning directly on the Progression-free Survival (PFS)-2 Kaplan–Meier curve. Two cohorts of advanced gastric cancer patients were considered: a calibration cohort from South Korea, and an external verification cohort from IRCCS “S. De Bellis”, an Italian research hospital. These real-world patients had heterogeneous clinical starting conditions. We perform prospective evaluations of new combination regimens that adhere to pharmacological constraints that are paramount for clinical translation, in which the administration time of the cytotoxic agent is triggered by the normalization window opening, monitored by a tumor microenvironment digital biomarker. Results: The calibration procedure led to the discovery of a new mathematical biomarker describing the influence of intrinsic tumor growth and angiogenesis on treatment outcomes. The predictive value was assessed through the log-rank test between two PFS-2 groups, which exhibited different (p-value <0.0001) therapy response trends. Our results showcase a new regimen that, by using 33% less cytotoxic drug, achieves indistinguishable PFS-2. Additionally, we present another regimen that extends PFS-2 from 49.2% to 60.9% after 121 days of therapy (p-value <0.0001), by using the same dosing as the standard protocol. Conclusions: This study proposes an in-silico quantitative platform for virtual expansion of real-world patient cohorts. Furthermore, the estimation of the efficacy of adaptive dose schedules of a combined therapy can complement and inform clinical trial design
Detecting label noise in longitudinal Alzheimer’s data with explainable artificial intelligence
No full textReliable classification of cognitive states in longitudinal Alzheimer’s Disease (AD) studies is critical for early diagnosis and intervention. However, inconsistencies in diagnostic labeling, arising from subjective assessments, evolving clinical criteria, and measurement variability, introduce noise that can impact machine learning (ML) model performance. This study explores the potential of explainable artificial intelligence to detect and characterize noisy labels in longitudinal datasets. A predictive model is trained using a Leave-One-Subject-Out validation strategy, ensuring robustness across subjects while enabling individual-level interpretability. By leveraging SHapley Additive exPlanations values, we analyze the temporal variations in feature importance across multiple patient visits, aiming to identify transitions that may reflect either genuine cognitive changes or inconsistencies in labeling. Using statistical thresholds derived from cognitively stable individuals, we propose an approach to flag potential misclassifications while preserving clinical labels. Rather than modifying diagnoses, this framework provides a structured way to highlight cases where diagnostic reassessment may be warranted. By integrating explainability into the assessment of cognitive state transitions, this approach enhances the reliability of longitudinal analyses and supports a more robust use of ML in AD research
LiNbO3-based Photonic FFT Processor: an Enabling Technology for SAR On-Board Processing
No full textIn the context of space applications, Synthetic Aperture Radar (SAR) systems can benefit from photonic systems, aiming to ensure higher performance and new functionalities, along with much greater compactness and lightness compared to commercial SAR systems, as required by New Space Economy constraints. To guarantee high spatial resolution imaging, which is essential in Earth Observation (EO), photonic SAR payloads are under development, and continuous investigation is underway to improve their performance. SAR payloads are realized by cascading microwave (MW) chirp generators, I/Q modulators, frequency up-converters, amplifiers, beamforming networks, Phased-Array Antennas (PAAs), and A/D converters for both transmission and receiving sections. To achieve a full-optical SAR, the A/D conversion in the receiving arm should be replaced by an optical system capable of performing processing directly onboard without passing through electronics. To elaborate SAR echoes several algorithms have been proposed exploiting Fast Fourier Transform (FFT) on digital samples. This paper introduces a novel photonic architecture able to realize an 8-bit Optical FFT (OFFT) overcoming the need for A/D conversion and reducing the overall Size, Weight, and Power Consumption (SWaP). The proposed solution has been investigated by taking into consideration features and constraints of current SAR payloads, guaranteeing 256 channels spaced 300 MHz apart in the Ka-band, with low propagation losses (2.8 dB/m), maximum insertion loss of 12 dB, maximum applied voltage of 7 V. maximum time delay of 0.98 ns, and tuners' length of 4.1 mm
Constraints on the Higgs boson self-coupling from the combination of single and double Higgs boson production in proton-proton collisions at s=13TeV
No full textThe Higgs boson (H) trilinear self-coupling, λ3, is constrained via its measured properties and limits on the HH pair production using the proton-proton collision data collected by the CMS experiment at s=13TeV. The combination of event categories enriched in single-H and HH events is used to measure κλ, defined as the value of λ3 normalized to its standard model prediction, while simultaneously constraining the Higgs boson couplings to fermions and vector bosons. Values of κλ outside the interval −1.2<κλ<7.5 are excluded at 2σ confidence level, which is compatible with the expected range of −2.0<κλ<7.7 under the assumption that all other Higgs boson couplings are equal to their standard model predicted values. Relaxing the assumption on the Higgs couplings to fermions and vector bosons the observed (expected) κλ interval is constrained to be within −1.4<κλ<7.8 (−2.3<κλ<7.8) at 2σ confidence level
Localization of RFID Tags through Real-Time Angle-of-Arrival Estimation
No full textRadio Frequency IDentification (RFID) is an enabling technology for many applications of the Internet-of-Things (IoT). The most interesting one is its use for localization and tracking purposes. Among all the possible localization techniques, Angle-of-Arrival (AoA) estimation performed through phase interferometry proved to be accurate and lightweight in terms of complexity, allowing operation in real-time. In this letter, we propose an approach to UHF RFID tag localization by real-time AoA estimation through a dedicated digital architecture. After introducing the idea and its underlying principles, we discuss a preliminary validation campaign using a Software-Defined Radio (SDR) and a custom RF front-end aiming to demonstrate the accuracy consistency varying the path loss and the signal power levels
Progettazione di circuiti logici ternari basati su CNTFET per applicazioni nel campo dell’elettronica portatile
No full textThe field of portable electronics and smart devices has seen a significant shift towards multi-valued logic (MVL), especially ternary logic, due to its potential to reduce circuit complexity and power consumption. In this paper we show how carbon nanotube field-effect transistors (CNTFETs) can be used in the design of ternary logic gates. The obtained results are encouraging and demonstrate that CNTFET-based ternary logic gates can be a viable approach for the design of low-power, high-speed circuits