scholarly journals User preference for a portable syringe pump for iloprost infusion

2015 ◽  
pp. 139
Author(s):  
Alberto Farina ◽  
antonella laria ◽  
Alfredo Maria Lurati ◽  
katia re ◽  
mariagrazia marrazza ◽  
...  
Keyword(s):  
User Preference ◽  
Syringe Pump ◽  
Iloprost Infusion

scholarly journals Iloprost infusion by a new device as a portable syringe pump: safety, tolerability and agreement

2012 ◽  
Author(s):  
Paola Faggioli ◽  
Alba Sciascera ◽  
Leopoldo Giani ◽  
Antonino Mazzone
Keyword(s):  
Pulmonary Hypertension ◽  
Traditional Method ◽  
Arterial Disease ◽  
Therapeutic Effects ◽  
Peristaltic Pump ◽  
Syringe Pump ◽  
New Device ◽  
Peripheral Arterial ◽  
Iloprost Infusion ◽  
Secondary Raynaud’S Phenomenon

Background Iloprost, prostacyclin (PGI2) analogue, effective in treatment of peripheral arterial disease, secondary Raynaud's phenomenon (RP) to connective tissue disease (CTD), vasculitis, pulmonary hypertension, is usually infused through peristaltic pump, or recently through a flow regulator.Materials and methods We tested a new portable syringe pump (Pompa Infonde®, Italfarmaco S.p.A., Cinisello Balsamo, Milano) on 120 patients affected by RP to CTD and cryoglobulinaemia, in iloprost therapy with a flow regulator.Results Iloprost infused through portable syringe pump is better tolerated, better appreciated by the patients and nurses and no difference was observed on therapeutic effects, with a lower incidence of side effects statistically significant. Only 3 patients were unable to tolerate the device (2 for changes in pressure and 1 for fear) and shifted to traditional method of iloprost infusion.Conclusions Iloprost infusion through the portable syringe Pompa Infonde® appears to be safe, better tolerated, more acceptable and equally effective compared to infusion through a flow regulator.

Analysis of athletes’ stadium stress source based on improved layered K-means algorithm

2020 ◽  
Vol 39 (4) ◽  
pp. 5905-5914
Author(s):  
Chen Gong
Keyword(s):  
Experimental Data ◽  
Machine Learning Algorithms ◽  
User Preference ◽  
Experimental Comparison ◽  
Actual Situation ◽  
Medical Field ◽  
Pressure Source ◽  
Preference Model ◽  
Related Research ◽  
Analysis System

Most of the research on stressors is in the medical field, and there are few analysis of athletes’ stressors, so it can not provide reference for the analysis of athletes’ stressors. Based on this, this study combines machine learning algorithms to analyze the pressure source of athletes’ stadium. In terms of data collection, it is mainly obtained through questionnaire survey and interview form, and it is used as experimental data after passing the test. In order to improve the performance of the algorithm, this paper combines the known K-Means algorithm with the layering algorithm to form a new improved layered K-Means algorithm. At the same time, this paper analyzes the performance of the improved hierarchical K-Means algorithm through experimental comparison and compares the clustering results. In addition, the analysis system corresponding to the algorithm is constructed based on the actual situation, the algorithm is applied to practice, and the user preference model is constructed. Finally, this article helps athletes find stressors and find ways to reduce stressors through personalized recommendations. The research shows that the algorithm of this study is reliable and has certain practical effects and can provide theoretical reference for subsequent related research.

UBAR

2021 ◽  
Vol 20 (3) ◽  
pp. 1-25
Author(s):  
Elham Shamsa ◽  
Alma Pröbstl ◽  
Nima TaheriNejad ◽  
Anil Kanduri ◽  
Samarjit Chakraborty ◽  
...  
Keyword(s):  
Resource Management ◽  
Quality Of Experience ◽  
State Of The Art ◽  
State Of Charge ◽  
User Preference ◽  
Management Approach ◽  
High Quality ◽  
Trade Off ◽  
Run Time

Smartphone users require high Battery Cycle Life (BCL) and high Quality of Experience (QoE) during their usage. These two objectives can be conflicting based on the user preference at run-time. Finding the best trade-off between QoE and BCL requires an intelligent resource management approach that considers and learns user preference at run-time. Current approaches focus on one of these two objectives and neglect the other, limiting their efficiency in meeting users’ needs. In this article, we present UBAR, User- and Battery-aware Resource management, which considers dynamic workload, user preference, and user plug-in/out pattern at run-time to provide a suitable trade-off between BCL and QoE. UBAR personalizes this trade-off by learning the user’s habits and using that to satisfy QoE, while considering battery temperature and State of Charge (SOC) pattern to maximize BCL. The evaluation results show that UBAR achieves 10% to 40% improvement compared to the existing state-of-the-art approaches.

Enriching the branching of Au@PdAu core–shell nanocrystals using a syringe pump: kinetics control meets lattice mismatch

CrystEngComm ◽  
2021 ◽  
Vol 23 (13) ◽  
pp. 2582-2589
Author(s):  
Gongguo Zhang ◽  
Yanyun Ma ◽  
Xiaowei Fu ◽  
Wenjun Zhao ◽  
Feng Liu ◽  
...  
Keyword(s):  
Reaction Kinetics ◽  
Surface Diffusion ◽  
Lattice Mismatch ◽  
Core Shell ◽  
Syringe Pump ◽  
Seeded Growth ◽  
Gold Nanocrystals

Gold@palladium–gold nanocrystals with a tunable branched shape are prepared via seeded growth, where the use of a syringe pump allows the manipulation over reaction kinetics as coupled by surface diffusion and strain caused by lattice mismatch.

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