186698 research outputs found
Sort by
Is segmental/multifocal onset a distinct presentation of idiopathic adult-onset dystonia?
No full textBackground: Idiopathic adult-onset dystonia (IAOD) is classically considered to begin focally, although segmental or multifocal onset has been reported in retrospective series. Whether this reflects a true early presentation or recall bias remains uncertain. Objectives: To determine whether segmental/multifocal onset represents a distinct presentation of IAOD and to assess whether these patients differ from those with focal onset. Methods: We analyzed dystonia body distribution at first neurological evaluation in 863 patients from the Italian Dystonia Registry, all examined by expert neurologists within one year of symptom onset to minimize recall bias. Results: Segmental or multifocal onset occurred in 10 % of cases. This proportion remained stable across increasing intervals between symptom onset and first evaluation, arguing against recall bias. Patients with segmental/multifocal onset did not differ from those with focal onset in sex, age at onset, family history of dystonia, frequency of thyroid disease, or subsequent spread to additional body regions. Conclusions: IAOD can present with segmental or multifocal onset, and this is unlikely to reflect recall bias. Moreover, patients with segmental/multifocal onset do not differ in factors potentially linked to disease initiation or subsequent spread compared with those with focal onset. These findings may have implications for prognostic counseling in IAOD
Comprehensive geophysical investigation of a prehistoric site: Favella della Corte (Cosenza, Italy)
No full textThe Neolithic settlement of Favella della Corte (Cosenza, Italy) offered a unique opportunity to study early communities in Southern Italy. This work presents the results of a geophysical investigation of the site, providing non-invasive insights into its stratigraphy and paleo-environmental context. An integrated survey was conducted, including magnetic field measurements, magnetic susceptibility sampling, and electrical resistivity profiling, with the aim of characterising subsurface features and supporting the reconstruction of past environmental conditions.
The magnetic survey comprised 3,000 readings collected with a Proton Precession Magnetometer GEM GSM-19T over an area of 11,600 m2. Magnetic susceptibility data were recorded by a Geofyzika KT-5 handheld kappameter on the stratigraphic units outcropping from exploratory trenches along vertical sections spaced at 20–50 cm. Electrical resistivity measurements were carried out adopting Wenner-Alpha and Beta arrays along nine profiles spaced 20 m apart and extending up to 90 m.
We modelled the magnetic data using an “ad hoc” three-dimensional inversion strategy. The modelling domain was discretized through a single horizontal layer of prismatic bodies and, being the inverse problem non-linear, we relied on the L-BFGS optimization algorithm. Model parameters involved were both the bottom position of prisms and a single magnetic susceptibility contrast value associated to all of them, which were updated every iteration until the L-BFGS algorithm converges. The electrical resistivity data were modelled along two-dimensional sections using Res2dinv based on the smoothness-constrained least-squares method.
Combined modelling of magnetic and electrical resistivity datasets revealed a NE–SW trending linear feature 70 m long crossing the whole survey area, 20 m wide, and reaching depths of about 4 m. The stratigraphic evidence resulting from exploratory trenches allowed us to interpret this anomaly in the geophysical parameters as a paleo-channel incised into the sandy substrate and filled with silty-clayey material. Considering the pronounced rectilinearity of this feature, we interpreted it as an anthropogenic paleo-channel with a drainage function.
The integrated application of magnetic and resistivity techniques proved to be highly effective for assessing the archaeological and paleo-environmental context of the Favella della Corte area, revealing subsurface stratigraphy and past environmental conditions. These findings highlighted the value of integrated geophysical approaches for reconstructing ancient landscapes and informing future research
Isotropic point synthesis of flexures and of compliant mechanisms
No full textIn this paper, the point compliance synthesis method is applied at the output port of a compliant mechanism to determine the points that satisfy the isotropy property. The kinetostatics of the compliant system is described using the ellipse of elasticity theory. According to the proposed modeling approach, based on projective geometry, the position of the isotropic points depends solely on the conic eccentricity, and their coordinates can be obtained through a simple arithmetic expression. Since any compliant system can be modeled by an ellipse of elasticity, the results obtained are of general validity. The synthesis procedure is applied to three case studies: two uniform flexures having axes with constant and variable curvature, and a closed-chain compliant mechanism. Numerical simulations and experimental testing are carried out to validate the procedure and to confirm the isotropy property
Retrospective multicenter cohort study of slow titration of vortioxetine to mitigate early nausea in major depression
No full textBackground Vortioxetine, a multimodal antidepressant, has been extensively documented for its efficacy and safety. The medication is typically well tolerated, with nausea being the most common adverse effect. Gradual titration with the oral solution may further enhance the medication's tolerability. Methods This retrospective, uncontrolled multicenter study evaluated 188 adult patients with major depressive disorder (MDD) who were treated with vortioxetine oral drop solutions. Patients initiated treatment with vortioxetine at a dosage of one or two drops per day (equivalent to 1 mg or 2 mg, respectively) and underwent a gradual increase in dosage, with each subsequent dose increased by one or two drops, up to the target dose. The subjects were observed for a minimum of eight weeks. The primary objective was to assess tolerability, with particular attention paid to the incidence and progression of nausea. The efficacy of the treatment was evaluated using the Montgomery-Asberg Depression Rating Scale (MADRS) and the Clinical Global Impression (CGI) scale at the outset of the study and at weeks 1, 2, 4, and 8. Adverse events were recorded through patient reports at weeks 1, 2, 4, and 8 and documented by clinicians. Results The administration of vortioxetine following a slow titration treatment protocol was found to markedly reduce the prevalence of nausea observed in 9.6 % of patients at week 1, 5.9 % at week 2, 2.7 % at week 4, and 1.7 % at week 8. The incidence of other adverse events exhibited a comparable decline over time. Despite the gradual dosing approach, patients exhibited a progressive improvement in their clinical status, as evidenced by a reduction in MADRS scores from a mean of 29.22 (SD 7.71) at baseline to 11.89 (SD 6.35) at week 8. At the end of the treatment period, 72 % of patients were classified as good responders for MADRS and 71 % for CGI (change ≥50 %) while 46 % achieved remission according to MADRS criteria (MADRS ≤10). Conclusions In our cohort, the slow titration of vortioxetine oral drop solutions resulted in an enhancement in tolerability, accompanied by a decline in nausea compared to the rates documented in prior studies utilizing standard tablet formulations. This approach did not compromise the efficacy of the treatment. This flexible titration strategy represents a promising approach to the mitigation of adverse effects while maintaining clinical effectiveness. Further research should be conducted to investigate the long-term benefits of this method and to compare it to other titration protocols
Assessing the Multitarget Therapeutic Potential of Novel 9-Aminoacridine Derivatives for Alzheimer's Disease
No full textThe escalating number of Alzheimer's disease (AD) cases and the limitations of current therapies pose a significant threat to human health, necessitating the discovery of novel drugs with innovative modes of action. To address this challenge, we pursued multitarget ligand strategy with the expectation of improved disease management. Continuing our efforts to discover new multitarget agents for AD, we decorated the planar 6-Cl-2-OCH3-9-aminoacridine core with basic heterocyclic or benzyl side chains as polar and hydrophobic structural features, respectively. All the compounds inhibited acetylcholinesterase, and in several cases also inhibited butyrylcholinesterase, with potencies comparable to or exceeding those of reference drugs. Exploring activity against MAO isoforms, heterocyclic derivatives 2, 5, 6, 9, 11, and 12 proved to be selective MAO-A inhibitors, while the 3,4-dichlorobenzyl derivative 20 provided balanced inhibition of both MAO-A and MAO-B enzymes. Favorable predicted blood-brain barrier permeability and low toxicity toward SH-SY5Y neuronal cells were also observed. Intriguingly, compounds 4, 12 and 20 altered the aggregation morphology of the neurotoxic A beta 42 peptide, revealing distinct inhibition profiles likely reflecting the different nature of the side chain. Based on these findings, the planar 6-Cl-2-OCH3-9-aminoacridine ring emerges as a valuable scaffold for future development of multitargeted anti-AD agents
Partecipazione Pubblica e Apprendimento Organizzativo: il ruolo degli Enti Locali
No full textPublic participation represents a strategic lever for strengthening local democracy and improving the quality of public policies, particularly in contexts marked by increasing social and institutional complexity. At the same time, organizational learning represents a key factor in public administrations’ ability to adapt, innovate, and respond effectively to citizens’ needs. Positioned at the intersection of these two fields of research, this study examines public participation as a potential driver of organizational learning in Italian local governments, adopting Peter Senge’s (1990) Learning Organization framework as its theoretical foundation.
The research is based on a mixed-methods design articulated into two studies. Study 1, exploratory and descriptive in nature, employs a desk analysis of participatory processes in Italy using data drawn from the Participedia platform, with the aim of mapping initiatives at the municipal level and analyzing their main structural, functional, and design-related characteristics. Study 2 adopts a qualitative approach and is based on semi-structured interviews with local administrators, analyzed through Template Analysis, to explore representations, practices, and critical issues of public participation in relation to organizational learning processes.
The findings indicate that participatory processes can support organizational learning when they foster dialogue, reflexivity, and the construction of shared meanings, in line with key dimensions of Senge’s (1990) Learning Organization. However, this potential is strongly contingent upon organizational and political conditions, including leadership style, the degree of institutionalization of participation, and the willingness to share decision-making power.
Overall, this research contributes to a deeper understanding of the relationship between public participation and organizational learning in the public sector and offers practical insights for the design of participatory processes capable of combining democratic legitimacy, administrative effectiveness, and continuous learning within local governments
Sostenibilità e rischio finanziario: evidenze empiriche sulla resilienza delle aziende europee
No full textL’articolo si pone come obiettivo quello di comprendere se le aziende europee, caratterizzate da score ESG elevati, si siano mostrate più resilienti in termini di indicatori di rischio finanziario. L’indagine empirica è stata svolta su un campione delle 600 più rappresentative aziende, suddivise in 25 settori industriali, in un periodo di dieci anni, considerando nove fattori di rischio finanziario
Toward Autonomous Soft-Tissue Minimal Invasive Surgery: Integrating Learning, Reasoning, Perceiving for Adaptive Surgical Robot Autonomy
No full textThis thesis investigates the foundations required to achieve adaptive autonomy in soft-tissue surgical robotics.
Soft-tissue procedures are defined by continuous, unpredictable anatomical deformation, making autonomous execution dependent on the integration of learned surgical skills, real-time perception, adaptive reasoning, and precise robotic action. To address these challenges, this work develops a unified framework based on four interconnected pillars—Learning, Reasoning, Perceiving, and Acting (LRPA)—and demonstrates its feasibility on clinically inspired phantom scenarios.
The first pillar, Learning, focuses on extracting expert surgical competence directly from demonstrations. A domain-adaptive imitation learning framework is developed to recover fine tool trajectories, orientations, and task states for tumor cutting and tissue manipulation. Policies are trained first in high-fidelity simulation, then transferred to real silicone phantoms, achieving an average positional error of 0.2 cm and generalizing to novel anatomical variations.
The second pillar, Reasoning, establishes the geometric and anatomical logic needed for autonomous decision-making. This thesis introduces a complete reasoning pipeline for selective vascular clamping in partial nephrectomy, including the extraction of clamping candidates along the arterial tree and the formalization of surgical target points that must remain valid despite intraoperative anatomical motion.
The third pillar, Perceiving, provides the system with real-time awareness of soft-tissue behavior. A fast, RGB-D–based deformation tracking method is developed to estimate dense non-rigid motion on organ surfaces. The resulting deformation field enables continuous updates to surgical targets, trajectories, and anatomical landmarks.
Validation on CT-derived phantoms demonstrates robust performance under external perturbations and visually challenging conditions.
Finally, Acting is enabled through the design of a custom actuated surgical tool capable of controlled cutting, grasping, and clamping. Integrated with the perception and reasoning modules, the system performs deformation-aware tumor cutting and dynamically updated path following, establishing the first demonstration of adaptive execution on deformable phantom organs.
Together, these contributions create a cohesive framework for perceptually informed, adaptively controlled surgical robotics. The results outline a clear path toward safe, intelligent autonomy in soft-tissue surgery and provide essential building blocks for future deployment in real clinical environments
Simulation of flame development in a glass furnace with hydrogen enriched natural gas
No full textThe glass manufacturing industry is energy demanding and has significant environmental impacts due to the high temperatures required for melting raw materials, resulting in pollutant emissions. With the EU's goal of climate neutrality by 2050, reducing energy consumption and emissions in glass production is a key priority. Integrating some quantities of hydrogen in the fuel mixture can offer a promising solution for decarbonization. While hydrogen is being explored in industries like steel, its potential as a clean fuel for glass furnaces still requires further research. This study focuses on the impact of introducing hydrogen into the fuel mixture for glass furnace combustion. Using an innovative CFD framework that overcomes the limitations of existing models—where combustion is typically treated with oversimplified approaches and the glass tank is solved separately via iterative coupling between domains—this work introduces a fully coupled simulation of both the combustion space and the glass bath within a single computational environment. The reactive flow is resolved using a reduced chemical kinetic mechanism in combination with the EDC (eddy dissipation concept) turbulence–chemistry interaction model, enabling an accurate representation of combustion development. This advanced setup is employed to assess the effect of hydrogen enrichment while maintaining the same overall thermal input power as the natural-gas-only baseline case. The results demonstrate that a 30 % hydrogen addition (by energy) can achieve a substantial reduction in CO2 emissions of nearly 30 % and a decrease in NO emissions of approximately 40 %, highlighting the significant environmental benefits of hydrogen enrichment, while simultaneously introducing serious flame stability challenges that must be carefully managed. This behaviour has been thoroughly analyzed, with particular focus on flame patterns, heat flow distribution and glass surface temperature. To address this challenge, some strategies are proposed to stabilize combustion, restoring stable flame conditions akin to those observed with natural gas. The study aims to explore hydrogen's potential in decarbonizing the glass industry, offering practical solutions for integrating hydrogen into production processes with promising results. This contributes to reducing industrial carbon emissions and supports the transition to a more sustainable energy system