Notes

Your Retornus-2 study: effect regarding breathing muscle tissue learning subacute cerebrovascular accident people along with dysphagia, review process of your double-blind randomized controlled trial.
Radiation therapy is integral to cancer treatments for more than half of patients. Pencil beam scanning (PBS) proton therapy is the latest radiation therapy technology that uses a beam of protons that are magnetically steered and delivered to the tumor. One of the limiting factors of PBS accuracy is the beam cross-sectional size, similar to how a painter is only as accurate as the size of their brush allows. To address this, collimators can be used to shape the beam along the tumor edge to minimize the dose spread outside of the tumor. Under development is a dynamic collimation system (DCS) that uses two pairs of nickel trimmers that collimate the beam at the tumor periphery, limiting dose from spilling into healthy tissue. Herein, we establish the dosimetric and mechanical acceptance criteria for the DCS based on a functioning prototype and Monte Carlo methods, characterize the mechanical accuracy of the prototype, and validate that the acceptance criteria are met. From Monte Carlo simulations, we found that the trimmers must be positioned within ±0.5 mm and ±1.0 deg for the dose distributions to pass our gamma analysis. We characterized the trimmer positioners at jerk values up to 400 m/s3 and validated their accuracy to 50 μm. We measured and validated the rotational trimmer accuracy to ±0.5 deg with a FARO® ScanArm. Lastly, we calculated time penalties associated with the DCS and found that the additional time required to treat one field using the DCS varied from 25-52 s.Medical robots provide enhanced dexterity, vision, and safety for a broad range of procedures. In this article, we present a handheld, robotic device capable of performing peripheral catheter insertions with high accuracy and repeatability. The device utilizes a combination of ultrasound imaging, miniaturized robotics, and machine learning to safely and efficiently introduce a catheter sheath into a peripheral blood vessel. Here, we present the mechanical design and experimental validation of the device, known as VeniBot. Additionally, we present results on our ultrasound deep learning algorithm for vessel segmentation, and performance on tissue-mimicking phantom models that simulate difficult peripheral catheter placement. Overall, the device achieved first-attempt success rates of 97 ± 4% for vessel punctures and 89 ± 7% for sheath cannulations on the tissue mimicking models (n = 240). The results from these studies demonstrate the viability of a handheld device for performing semi-automated peripheral catheterization. In the future, the use of this device has the potential to improve clinical workflow and reduce patient discomfort by assuring a safe and efficient procedure.Cortical neurons emit seemingly erratic trains of action potentials or "spikes," and neural network dynamics emerge from the coordinated spiking activity within neural circuits. These rich dynamics manifest themselves in a variety of patterns, which emerge spontaneously or in response to incoming activity produced by sensory inputs. In this Review, we focus on neural dynamics that is best understood as a sequence of repeated activations of a number of discrete hidden states. These transiently occupied states are termed "metastable" and have been linked to important sensory and cognitive functions. In the rodent gustatory cortex, for instance, metastable dynamics have been associated with stimulus coding, with states of expectation, and with decision making. In frontal, parietal, and motor areas of macaques, metastable activity has been related to behavioral performance, choice behavior, task difficulty, and attention. In this article, we review the experimental evidence for neural metastable dynamics together with theoretical approaches to the study of metastable activity in neural circuits. These approaches include (i) a theoretical framework based on non-equilibrium statistical physics for network dynamics; (ii) statistical approaches to extract information about metastable states from a variety of neural signals; and (iii) recent neural network approaches, informed by experimental results, to model the emergence of metastable dynamics. By discussing these topics, we aim to provide a cohesive view of how transitions between different states of activity may provide the neural underpinnings for essential functions such as perception, memory, expectation, or decision making, and more generally, how the study of metastable neural activity may advance our understanding of neural circuit function in health and disease.Whether we live in a world of autonomous things, or a world of interconnected processes in constant flux, is an ancient philosophical debate. Modern biology provides decisive reasons for embracing the latter view. How does one understand the practices and outputs of science in such a dynamic, ever-changing world - and particularly in an emergency situation such as the COVID-19 pandemic, where scientific knowledge has been regarded as bedrock for decisive social interventions? We argue that key to answering this question is to consider the role of the activity of reification within the research process. Reification consists in the identification of more or less stable features of the flux, and treating these as constituting stable things. As we illustrate with reference to biological and biomedical research on COVID-19, reification is a necessary component of any process of inquiry and comes in at least two forms (1) means reification (phenomena-to-object), when researchers create objects meant to capture features of the world, or phenomena, in order to be able to study them; and (2) target reification (object-to-phenomena), when researchers infer an understanding of phenomena from an investigation of the epistemic objects created to study them. We note that both objects and phenomena are dynamic processes and argue that have no reason to assume that changes in objects and phenomena track one another. We conclude that failure to acknowledge these forms of reification and their epistemic role in scientific inquiry can have dire consequences for how the resulting knowledge is interpreted and used.2020 was globally greatly affected by the Covid-19 pandemic caused by SARS-CoV-2, which is still today impacting and profoundly changing life globally for people but also for firms. In this context, the need for timely and accurate information has become vital in every area of business management. The spread of the Covid-19 global pandemic has generated an exponential increase and extraordinary volume of data. In this domain, Big Data is one of the digital innovation technologies that can support business organizations during these complex times. Based on these considerations, the aim of this paper is to analyze the managerial literature concerning the issue of Big Data in the management of the Covid-19 pandemic through a systematic literature review. The results show a fundamental role of Big Data in pandemic management for businesses. The paper also provides managerial and theoretical implications.The SARS-CoV-2 pandemic, since the beginning of 2020, has had a strong effect on many industry sectors including maritime transport. In this context, the passenger transport industry was the most affected and it is still in a very critical situation. Starting from the "No Sail Order" issued in March 2020, cruise companies stopped their operations. Besides the international regulatory bodies issued several guidelines for the prevention and management of pandemics onboard in order to safely resume cruises. The present work addresses this topic, aiming to discuss procedures and best practices to reduce the risk of uncontrolled spreading of SARS-CoV-2 infection on large cruise vessels. Starting from the lessons learned from the representative case of Diamond Princess, here the tools developed in the framework of Industry 4.0 have been used to highlight and handle the criticalities risen on the internal layout of passenger vessels, opening new opportunities to operate existing vessels and improve the design new buildings for outbreaks prevention and control.The COVID-19 pandemic has forced a sudden change of traditional office works to smart working models, which however force many workers staying at home with a significant increase of sedentary lifestyle. Metabolic disorders, mental illnesses, and musculoskeletal injuries are also caused by the physical inactivity and chronic stress at work, threatening office workers' physical and physiological health. In the modern vision of smart workplaces, cyber-physical systems play a central role to augment objects, environments, and workers with integrated sensing, data processing, and communication capabilities. In this context, a work engagement system is proposed to monitor psycho-physical comfort and provide health suggestion to the office workers. Recognizing their activity, such as sitting postures and facial expressions, could help assessing the level of work engagement. In particular, head and body posture could reflects their state of engagement, boredom or neutral condition. In this paper we proposed a method to recognize such activities using an infrared sensor array by analyzing the sitting postures. The proposed approach can unobstructively sense their activities in a privacy-preserving way. To evaluate the performance of the system, a working scenario has been set up, and their activities were annotated by reviewing the video of the subjects. We carried out an experimental analysis and compared Decision Tree and k-NN classifiers, both of them showed high recognition rate for the eight postures. As to the work engagement assessment, we analyzed the sitting postures to give the users suggestions to take a break when the postures such as lean left/right with arm support, lean left/right without arm support happens very often.This work examines whether the increase of single parenthood in Italy and Spain, specifically amongst women in an unfavourable socioeconomic position, has repercussions for child well-being, understood here as material deprivation. In particular, our main objective is to analyse the possible differential impact of single parenthood on children's material deprivation in relation to mothers' level of education. https://www.selleckchem.com/products/en450.html Using the 2014 EU-SILC Module on material deprivation, we identify five areas of child deprivation based on the EU-MODA approach nutrition, clothing, education, leisure, and social life. In the case of Italy, our main results indicate that, compared to children from two-parent households, children of single mothers with a low level of education have a higher risk of nutrition and clothing deprivation. In Spain, living in a single-parent household is associated with a higher risk of deprivation in terms of social life for those children whose mothers do not have a high level of education. Therefore, the findings suggest that in both countries the growth of single parenthood amongst women with a lower educational level may have an impact on child well-being inequality. This article contributes empirical data to the growing literature on the rise of child poverty in Southern European countries.The purpose of this study is to explore the clinicopathological features of Kikuchi-Fujimoto disease (KFD) following vaccination against coronavirus disease 2019 (COVID-19). One case of KFD following vaccination against COVID-19 was examined clinically, histologically, and immunohistochemically. The patient was a 36-year-old Chinese man who suffered from fever and cervical lymph node swelling following simultaneous administration of the COVID-19 vaccine. The patient was diagnosed with KFD based on the histopathological findings of a lymph node core needle biopsy, and his fever and swelling resolved 2 months later without therapy. Although the exact pathogenesis of the development of KFD following immunization remains unknown, this information should be added to the list of potential triggers or factors associated with the development of KFD.
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