1,720,968 research outputs found
Predicting apparent slip at liquid-liquid interfaces without an interface slip condition
Full text linkWe show that if we include a density-dependent viscosity into the Navier-Stokes equations then we can describe, naturally, the velocity profile in the interfacial region, as we transition from one fluid to another. This requires knowledge of the density distribution (for instance, via Molecular Dynamics [MD] simulations, a diffuse-interface approach, or Density Functional Theory) everywhere in the fluids, even at liquid-liquid interfaces where regions of rapid density variations are possible due to molecular interactions. We therefore do not need an artificial interface condition that describes the apparent velocity slip. If the results are compared with the computations obtained from MD simulations, we find an almost perfect agreement. The main contribution of this work is to provide a simple way to account for the apparent slip at liquid-liquid interfaces without relying upon an additional boundary condition, which needs to be calculated separately using MD simulations. Examples are provided involving two immiscible fluids of varying average density ratios, undergoing simple Couette and Poisseuille flows
Motion Primitives for Low Contact Force Magnetically-Driven Navigation of Endoscopic Capsules
No full textThermodynamic modelling and simulation of geothermal power plants: case studies and environmental impact
Full text linkThe emissions associated with Geothermal power plant (GTPP) due to geothermal fluids represents a compelling challenge addressed in the last decades. The on-line measuring of pollutants generated by GTPP might result in a complicated task to handle. Simulation of GTPP has become an excellent tool to monitor and control the emission of pollutants. In the present work, the pollutant emissions of GTPP of Hellisheidi (Island), Chiusdino, and Castelnuovo (Italy) are modelled and developed with Unisim Design R480 using well understood thermodynamical models implemented in OLI. The presence of brine in the thermodynamical models has been taken into account. Carbon dioxide, methane, and hydrogen sulfide are the chemical pollutants considered for the process simulation. The AQ framework model in OLI is being used for binary mixtures and non-condensable gas. Furthermore, for liquid mixtures containing more than two components, the MSE-SRK Thermodynamic model is desirable depending on the original geothermal fluid source. The simulation process outcome agrees with experimental data for pressure between 30 and 100 bar within 5% deviation. A systematic study of the spatial distribution of the emissions has been made for the area surrounding the GTPP. Furthermore, an economic evaluation overview has been performed to highlight the equipment needed for maintenance and tool substitution
Stochastic Claims Reserve in the Healthcare System: A Methodology Applied to Italian Data
Full text linkOne of the challenges in the healthcare sector is making accurate forecasts across insurance years for claims reserve. Healthcare claims present huge variability and heterogeneity influenced by random decisions of the courts and intrinsic characteristics of the damaged parties, which makes traditional methods for estimating reserves inadequate. We propose a new methodology to estimate claim reserves in the healthcare insurance system based on generalized linear models using the Overdispersed Poisson distribution function. In this context, we developed a method to estimate the parameters of the quasi-likelihood function using a Gauss–Newton algorithm optimized through a genetic algorithm. The genetic algorithm plays a crucial role in glimpsing the position of the global minimum to ensure a correct convergence of the Gauss–Newton method, where the choice of the initial guess is fundamental. This methodology is applied as a case study to the healthcare system of the Tuscany region. The results were validated by comparing them with state-of-the-art measurement of the confidence intervals of the Overdispersed Poisson distribution parameters with better outcomes. Hence, local healthcare authorities could use the proposed and improved methodology to allocate resources dedicated to healthcare and global management
A Proximity Care Paradigm for Cancer Screening with a Mobile Multi-Screening Unit in Inner Areas
No full textThis paper addresses the challenges associated with the cancer screening program in the “Valle del Serchio, Lucca” health district, a mountainous inner area in Tuscany, Italy. With a population characterized by high cancer mortality rates and low screening adherence, a novel approach to screening administration is introduced, which advocates for minimizing travel distances for citizens while maximizing screening participation through the deployment of a mobile multi-screening unit. The mobile unit combines breast, cervical, colorectal, and melanoma screening procedures, providing a unified and accessible point of access for residents. In this paper, the authors contribute to the existing literature by presenting the innovative design and technical data management solutions implemented for the mobile multi-screening unit, emphasizing its adaptability to several geographical and infrastructural requirements. The mobile unit was tested in five municipalities of the investigated area, i.e. inner areas of Lucca province, Italy. Results from the first implementation phase, with over 500 individuals participating, demonstrated the success in delivering cancer screenings, hence highlighting the effectiveness of the proposed unprecedented design of the mobile unit. The interdisciplinary collaboration between healthcare professionals, engineers, designers, IT specialists, and healthcare managers was crucial for the mobile unit’s design, training, and adaptation to unforeseen challenges. Finally, showing in this paper the design of the mobile multi-screening unit and the preliminary results of the pilot study, future work will focus on refining and optimizing the proposed screening paradigm based on implementation insights, ensuring its sustained success and scalability in diverse geographical areas
Decision-Making Algorithm and Predictive Model to Assess the Impact of Infectious Disease Epidemics on the Healthcare System: The COVID-19 Case Study in Italy
No full textTo improve decision-making strategies and prediction based on epidemiological data, so far biased by highly-variable criteria, algorithms using unbiased morbidity parameters, i.e. Intensive Care Units (ICU) and Ordinary Hospitalizations (OH), are proposed. ICU/OH acceleration and velocities are mathematically modeled using available and official data to derive two thresholds, alerting on 30 % ICU and 40 % OH of COVID-19 daily occupancy settled by the Italian Minister of Health, as a case of study. A predictive model is also proposed to estimate the daily occupancy of ICU and OH in hospitals for each region, using a Susceptible-Infected-Recovered-Death (SIRD) epidemic model to further extend occupancy prediction in each regional district. Computed data validated the proposed models in Italy after almost two years of pandemic, obtaining agreements with the Italian Presidential Decree regardless of the different regional trends of epidemic waves. Therefore, the decision-making algorithm and prediction model resulted valuable tools, retrospectively, to be tested prospectively in sustainable strategies to curb the impact of COVID-19, or of any other pandemic threats with any aggregate of data, on local healthcare systems
Slip at liquid-liquid interfaces
Full text linkWe address a problem of fundamental importance in the physics of interfaces, which is central to the description of multiphase fluid dynamics. This work is important to study interfaces in systems such as polymer melts and solutions, where velocity jumps have been observed and interpreted as a manifestation of slip. This is in violation of classical interfacial conditions that require continuity of velocity and has been remedied in the literature via use of ad hoc models, such as the so-called Navier slip condition. This paper suggests that it is possible to obviate completely the need for such an approach. Instead, we show that one simply requires knowledge of the density field and the molar fraction of the fluid components and the dependence of the viscosity on the density. This information can be obtained easily through molecular dynamics simulations
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Digital health for environmentally sustainable cancer screening
Full text linkAbstract This study explores the role of digital health in promoting environmental sustainability through a pilot study performed in rural areas in Tuscany (Italy). A multi-screening model, based on a mobile multi-screening unit (MMSU) and digital health tools, was deployed to reduce the travelled distances required for cancer screening. Serving 19 municipalities in a mountainous area, the MMSU reduced patient and caregivers’ travel, cutting CO2-equivalent emissions by over 90% compared to conventional healthcare models. The project demonstrates how integrating digital health technologies, such as telemedicine for data transmission and centralised reporting, can enhance healthcare accessibility and environmental sustainability. By consolidating multiple screenings into one visit, the MMSU model offers a scalable solution for reducing healthcare’s carbon footprint while addressing barriers to care in underserved areas. This pilot study highlights the potential of digital health to align service delivery with environmental objectives, contributing to the broader discourse on sustainable healthcare innovation
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