The Novel Multi-layered Approach to Enhance Sorting Performance of Healthcare Analysis

Emergence of big data in today’s world leads to new challenges for sorting strategies to analyze the data in a better way. For most of the analyzing technique, sorting is considered as an implicit attribute of the technique used. The availability of huge data has changed the way data is analyzed across industries. Healthcare is one of the notable areas where data analytics is making big changes. An efficient analysis has the potential to reduce costs of treatment and improve the quality of life in general. Healthcare industries are collecting massive amounts of data and look for the best strategies to use these numbers. This research proposes a novel non-comparison based approach to sort a large data that can further be utilized by any big data analytical technique for various analyses.

Multi-layered electrospinning and electrospraying approach: Effect of polymeric supplements on chondrocyte suspension

Articular cartilage was expected to be one of the first tissues to be successfully engineered, but replicating the complex fibril architecture and the cellular distribution of the native cartilage has proven difficult. While electrospinning has been widely used to reproduce the depth-dependent fibre architecture in 3D scaffolds, the chondrocyte-controlled distribution remains an unsolved problem. To incorporate cells homogeneously through the depth of scaffolds, a combination of polymer electrospinning and cell seeding is necessary. A multi-layer approach alternating between polymer electrospinning with chondrocyte electrospraying can be a solution. Still, the success of this process is related to the survival rate of the electrosprayed chondrocytes embedded within the electrospun mesh. In this regard, the present study investigated the impact of the multi-layered process and the supplementation of the electrospray chondrocyte suspension with different concentrations of Gelatin and Alginate on the viability of electrosprayed chondrocytes embedded within a Polycaprolactone/Gelatin electrospun mesh and on the mechanical properties of the resulting meshes. The addition of Gelatin in the chondrocyte suspension did not increase significantly ( p > 0.05) the percentage of viable electrosprayed chondrocytes (25%), while 3 wt% Alginate addition led to a significant ( p < 0.05) increase in chondrocyte viability (50%) relative to the case without polymer supplement (15%). Furthermore, the addition of both polymer supplements increased the mechanical properties of the multi-layer construct. These findings imply that this multi-layered approach can be applied to cartilage TE allowing for automated chondrocyte integration during scaffolds creation.

Analysis on the Application of Multimedia-Assisted Music Teaching Based on AI Technology

In order to improve the effect of modern music teaching, this paper combines AI technology to construct a multimedia-assisted music teaching system, combines music teaching data processing requirements to improve the algorithm, proposes appropriate music data filtering algorithms, and performs appropriate data compression processing. Moreover, the functional structure analysis of the intelligent music teaching system is carried out with the support of the improved algorithm, and the three-tier framework technology that is currently more widely used is used in the music multimedia teaching system. Finally, in order to realize the complex functions of the system, the system adopts a layered approach. From the experimental research results, it can be seen that the multimedia-assisted music teaching system based on AI technology proposed in this paper can effectively improve the effect of modern music teaching.

A three-layer system to win the war against COVID-19 and invest in health systems of the future

The COVID-19 pandemic taught us many lessons, most critically that its human and economic toll would have been significantly smaller if countries had in place strong layers of defence that would have either prevented the spillover of the SARS-CoV-2 into a human population in the first place, or, failing that, contained the outbreak to avert its global spread. Further, the brunt of COVID-19 impacts on some countries considered ‘most prepared’ for pandemics underscored the need for an integrated approach to ensure resilience to future epidemics. Consequently, as countries plan ahead to prevent future pandemics, they should give priority to investments that transform their systems, particularly in the precrises phase, to preparedness and response through a multilayered defence. We propose a three-layered approach for post-COVID-19 investments in public health functions and service delivery, particularly at the community and precrises levels. This framework highlights the interventions that enable countries to better prevent, detect and contain epidemic threats, and that strengthen the efficient use of limited resources towards high-impact precrises systems.

Beyond Bias: Critical Analysis and Layered Reading of Mao-Era Sources

Scholars of Mao-era history adopt a wide range of approaches to the selection and treatment of source material. Some scholars regard published sources as propaganda, and therefore as biased and unreliable. For many, archival sources are the gold standard; others question the reliability even of the archive and favor materials that escaped the filtering fingers of the state to be found in flea markets or garbage piles. Avoiding the false choice of either accepting sources as received wisdom or dismissing them as biased, the author argues that how scholars read their sources is more important than which they keep and which they throw away. She advocates for a layered approach that accounts for contexts of production and circulation, and further emphasizes the need to make this process of reading sources visible in our writing. A critical, layered reading of three unlikely sources demonstrates the myriad possibilities for analysis that combines the empirical, the discursive, and the self-reflexive.

Healthcare Digitalisation and the Changing Nature of Work and Society

Digital technologies have profound effects on all areas of modern life, including the workplace. Certain forms of digitalisation entail simply exchanging digital files for paper, while more complex instances involve machines performing a wide variety of tasks on behalf of humans. While some are wary of the displacement of humans that occurs when, for example, robots perform tasks previously performed by humans, others argue that robots only perform the tasks that robots should have carried out in the very first place and never by humans. Understanding the impacts of digitalisation in the workplace requires an understanding of the effects of digital technology on the tasks we perform, and these effects are often not foreseeable. In this article, the changing nature of work in the health care sector is used as a case to analyse such change and its implications on three levels: the societal (macro), organisational (meso), and individual level (micro). Analysing these transformations by using a layered approach is helpful for understanding the actual magnitude of the changes that are occurring and creates the foundation for an informed regulatory and societal response. We argue that, while artificial intelligence, big data, and robotics are revolutionary technologies, most of the changes we see involve technological substitution and not infrastructural change. Even though this undermines the assumption that these new technologies constitute a fourth industrial revolution, their effects on the micro and meso level still require both political awareness and proportional regulatory responses.