scholarly journals Spatiotemporal evolution of resistance state in simulated memristive networks

2021 ◽  
Vol 119 (19) ◽  
pp. 193502
Author(s):  
F. Di Francesco ◽  
G. A. Sanca ◽  
C. P. Quinteros
2020 ◽  
Author(s):  
Thomas Herzog ◽  
Naomi Weitzel ◽  
Sebastian Polarz

<div><div><div><p>One of the fascinating properties of metal-semiconductor Schottky-barriers, which has been observed for some material combinations, is memristive behavior. Memristors are smart, since they can reversibly switch between a low resistance state and a high resistance state. The devices offer a great potential for advanced computing and data storage, including neuromorphic networks and resistive random-access memory. However, as for many other cases, the presence of a real interface (metal - metal oxide) has numerous disadvantages. The realization of interface-free, respectively Schottky-barrier free memristors is highly desirable. The aim of the current paper is the generation of nanowire arrays with each nanorod possessing the same crystal phase (Rutile) and segments only differing in composition. The electric conductivity is realized by segments made of highly-doped antimony tin oxide (ATO) transitioning into pure tin oxide (TO). Complex nanoarchitectures are presented, which include ATO-TO, ATO-TO-ATO nanowires either with a stepwise distribution of antimony or as a graded functional material. The electrical characterization of the materials reveals that the introduction of memristive properties in such structures is possible. The special features observed in voltage-current (IV) curves are correlated to the behavior of mobile oxygen vacancies (VO..) at different values of applied electrical potential.</p></div></div></div>


Author(s):  
Pierre Danneels ◽  
Maria Concetta Postorino ◽  
Alessio Strazzulla ◽  
Nabil Belfeki ◽  
Aurelia Pitch ◽  
...  

Introduction. Treatment of Haemophilus influenzae (Hi) pneumonia is on concern because resistance to amoxicillin is largely diffused. This study describes the evolution of resistance to amoxicillin and amoxicillin/clavulanic acid (AMC) in Hi isolates and characteristics of patients with Hi severe pneumonia. Methods. A monocentric retrospective observational study including patients from 2008 to 2017 with severe pneumonia hospitalized in ICU. Evolution of amoxicillin and AMC susceptibility was showed. Characteristics of patients with Hi pneumonia were compared to characteristics of patients with Streptococcus pneumoniae (Sp) pneumonia, as reference. Risk factors for amoxicillin resistance in Hi were investigated. Results. Overall, 113 patients with Hi and 132 with Sp pneumonia were included. The percentages of AMC resistance among Hi strains decreased over the years (from 10% in 2008-2009 to 0% in 2016-2017) while resistance to amoxicillin remained stable at 20%. Also, percentages of Sp resistant strains for amoxicillin decreased over years (from 25% to 3%). Patients with Hi pneumonia experienced higher prevalence of bronchitis (18% vs. 8%, p=0.02, chronic obstructive pulmonary disease (43% vs. 30% p=0.03), HAP (18% vs. 7%, p=0.01, ventilator-associated pneumonia (27% vs. 17%, p=0.04, and longer duration of mechanical ventilation (8 days vs. 6 days, p=0.04) than patients with Sp pneumonia. Patients with Sp pneumonia had more frequently local complications than patients with Hi pneumonia (17% vs. 7%, p=0.03). De-escalation of antibiotics was more frequent in patients with Sp than in patients with Hi (67% vs. 53%, p=0.03). No risk factors were associated with amoxicillin resistance among patients with Hi pneumonia. Conclusions. Amoxicillin resistance was stable over time, but no risk factors were detected. AMC resistance was extremely low, suggesting that AMC could be used for empiric treatment of Hi pneumonia, as well as other molecules, namely, cephalosporins. Patients with Hi pneumonia had more pulmonary comorbidities and severe diseases than patients with Sp pneumonia.


2018 ◽  
Vol 612 ◽  
pp. 1141-1148 ◽  
Author(s):  
Min Zhang ◽  
Yuanling Zhang ◽  
Qi Shu ◽  
Chang Zhao ◽  
Gang Wang ◽  
...  

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