Impact of Segmented Magnetization on the Flagellar Propulsion of Sperm-Templated Microrobots

Technical design features for improving the way a passive elastic filament produces propulsive thrust can be understood by analyzing the deformation of sperm‐templated microrobots with segmented magnetization. Magnetic nanoparticles are electrostatically self‐assembled on bovine sperm cells with nonuniform surface charge, producing different categories of sperm‐templated microrobots. Depending on the amount and location of the nanoparticles on each cellular segment, magnetoelastic and viscous forces determine the wave pattern of each category during flagellar motion. Passively propagating waves are induced along the length of these microrobots using external rotating magnetic fields and the resultant wave patterns are measured. The response of the microrobots to the external field reveals distinct flow fields, propulsive thrust, and frequency responses during flagellar propulsion. This work allows predictions for optimizing the design and propulsion of flexible magnetic microrobots with segmented magnetization

Impact of Segmented Magnetization on the Flagellar Propulsion of Sperm-Templated Microrobots

Technical design features for improving the way a passive elastic filament produces propulsive thrust can be understood by analyzing the deformation of sperm-templated microrobots with segmented magnetization. Magnetic nanoparticles are electrostatically self-assembled on bovine sperm cells with nonuniform surface charge, producing different categories of sperm-templated microrobots. Depending on the amount and location of the nanoparticles on each cellular segment, magnetoelastic and viscous forces determine the wave pattern of each category during flagellar motion. Passively propagating waves are induced along the length of these microrobots using external rotating magnetic fields and the resultant wave patterns are measured. The response of the microrobots to the external field reveals distinct flow fields, propulsive thrust, and frequency responses during flagellar propulsion. This work allows predictions for optimizing the design and propulsion of flexible magnetic microrobots with segmented magnetization.</p

Speech recognition of spoken Italian based on detection of landmarks and other acoustic cues to distinctive features

Modeling the process that a listener actuates in deriving words intended by a speaker, requires setting a hypothesis on how lexical items are stored in memory. Stevens’ model (2002) postulates that lexical items are stored in memory according to distinctive features, and that these features are hierarchically organized. The model highlights the importance of abrupt acoustic events, named landmarks, in the perception process. In this model, the detection of landmarks is primary in human perception, corresponding to the first phase of recognition. The temporal area around the landmark is then further processed by the listener. Based on the above model, the Speech Communication Group of the Massachusetts Institute of Technology (MIT) developed a speech recognition system—for spoken English—over a span of more than 20 years. In the current work (LaMIT project, Lexical access Model for Italian) the above model is applied to Italian. Exploring a new language will provide insight into how Stevens' approach has universal application across languages, with relevant implications for understanding how the human brain recognizes speech. K. N. Stevens “Toward a model for lexical access based on acoustic landmarks and distinctive features,” J. Acoust. Soc. Am., 111(4), 1872–1891 (2002)

Aneurismal subarachnoid hemorrhage during the {COVID}-19 outbreak in a Hub and Spoke system: observational multicenter cohort study in Lombardy, Italy

Background Lombardy was the most affected Italian region by the first phase of the COVID-19 pandemic and underwent urgent reorganization for the management of emergencies, including subarachnoid hemorrhage from a ruptured cerebral aneurysm (aSAH). The aim of the study was to define demographics, clinical, and therapeutic features of aSAH during the COVID-19 outbreak and compare these with a historical cohort. Methods In this observational multicenter cohort study, patients aged 18 years or older, who were diagnosed with aSAH at the participating centers in Lombardy from March 9 to May 10, 2020, were included (COVID-19 group). In order to minimize bias related to possible SAH seasonality, the control group was composed of patients diagnosed with aSAH from March 9 to May 10 of the three previous years, 2017\u20132018-2019 (pre-pandemic group). Twenty-three demographic, clinical, and therapeutic features were collected. Statistical analysis was performed. Results Seventy-two patients during the COVID-19 period and 179 in the control group were enrolled at 14 centers. Only 4 patients were positive for SARS-CoV-2. The \u201cdiagnostic delay\u201d was significantly increased (+68%) in the COVID-19 group vs. pre-pandemic (1.06 vs. 0.63 days, respectively, p-value=0.030), while \u201ctherapeutic delay\u201d did not differ significantly between the two periods (0.89 vs. 0.74 days, p-value=0.183). Patients with poor outcome (GOS at discharge from 1 to 3) were higher during the COVID-19 period (54.2%) compared to pre-pandemic (40.2%, p=0.044). In logistic regression analysis, in which outcome was the dichotomized Glasgow Out-come Scale (GOS), five variables showed p-values&lt;0.05: age at admission, WFNS grade, treatment (none), days in ICU, and ischemia. Conclusions We documented a significantly increased \u201cdiagnostic delay\u201d for subarachnoid hemorrhages during the first COVID-19 outbreak in Lombardy. However, despite the dramatic situation that the healthcare system was experiencing, the Lombardy regional reorganization model, which allowed centralization of neurosurgical emergencies such as SAHs, avoided a \u201ctherapeutic delay\u201d and led to results overall comparable to the control period