Adaptive memory reservation strategy for heavy workloads in the Spark environment.

The rise of the Internet of Things (IoT) and Industry 2.0 has spurred a growing need for extensive data computing, and Spark emerged as a promising Big Data platform, attributed to its distributed in-memory computing capabilities. However, practical heavy workloads often lead to memory bottleneck issues in the Spark platform.

PD-ARnet: a deep learning approach for Parkinson's disease diagnosis from resting-state fMRI.

. The clinical diagnosis of Parkinson's disease (PD) relying on medical history, clinical symptoms, and signs is subjective and lacks sensitivity. Resting-state fMRI (rs-fMRI) has been demonstrated to be an effective biomarker for diagnosing PD.

Disentangled self-attention neural network based on information sharing for click-through rate prediction.

With the exponential growth of network resources, recommendation systems have become successful at combating information overload. In intelligent recommendation systems, the prediction of click-through rates (CTR) plays a crucial role. Most CTR models employ a parallel network architecture to successfully capture explicit and implicit feature interactions.

Towards virtual machine scheduling research based on multi-decision AHP method in the cloud computing platform.

Virtual machine scheduling and resource allocation mechanism in the process of dynamic virtual machine consolidation is a promising access to alleviate the cloud data centers of prominent energy consumption and service level agreement violations with improvement in quality of service (QoS). In this article, we propose an efficient algorithm (AESVMP) based on the Analytic Hierarchy Process (AHP) for the virtual machine scheduling in accordance with the measure. Firstly, we take into consideration three key criteria including the host of power consumption, available resource and resource allocation balance ratio, in which the ratio can be calculated by the balance value between overall three-dimensional resource (CPU, RAM, BW) flat surface and resource allocation flat surface (when new migrated virtual machine (VM) consumed the targeted host's resource).

Activation and Role of NACHT, LRR, and PYD Domains-Containing Protein 3 Inflammasome in RNA Viral Infection.

NACHT, LRR, and PYD domains-containing protein 3 (NLRP3) inflammasome activation and effects during ribonucleic acid (RNA) viral infection are the focus of a wide range of research currently. Both the pathogen-associated molecule pattern derived from virions and intracellular stress molecules involved in the process of viral infection lead to activation of the NLRP3 inflammasome, which in turn triggers inflammatory responses for antiviral defense and tissue healing. However, aberrant activation of the NLRP3 inflammasome can instead support viral pathogenesis and promote disease progression.