Biomedical and Health Sciences

The emergence of SARS-CoV-2 lineages derived from Omicron, including BA.2.86 (nicknamed “Pirola”) and its relative, JN.1, has raised concerns about their potential impact on public and personal health due to numerous novel mutations. Despite this, predicting their implications based solely on mutation counts proves challenging. Empirical evidence of JN.1’s increased immune evasion capacity in relation to previous variants is mixed.

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This dataset contains RF (Radio Frequency) signals obtained from simulations, which model ultrasound propagation in cortical bone.

The simulations were designed to provide insights into the behaviour of ultrasound waves in cortical bone tissues, both in intact and pathological conditions. The dataset covers a wide range of parameters, including varying thickness (1-8 mm), porosity (1-20%), and frequency (1-8 MHz), allowing to explore the impact of these factors on ultrasound signal characteristics.

 

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Problems of neurodegenerative disorder patients can be solved by developing Brain-Computer Interface (BCI) based solutions. This requires datasets relevant to the languages spoken by patients. For example, Marathi, a prominent language spoken by over 83 million people in India, lacks BCI datasets based on the language for research purposes. To tackle this gap, we have created a dataset comprising Electroencephalograph (EEG) signal samples of selected common Marathi words.

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223 Views

Background: The endpoint of liposuction surgery in a current clinical dilemma. The liposuction volume (LV) should be individualized according to each patient's objective and subjective needs.

Objectives: To create a mathematical model to quantitatively predict the change ratio of thigh circumference to LV.

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This data set consists of 10 half-hour EEG recordings, obtained from 10 volunteers, as described below.

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328 Views

Objective: As one branch of human-computerinteraction, affective Brain-Computer Interfaces (aBCI) interpretand utilize electroencephalogram (EEG) signalsto achieve real-time monitoring and recognition of individualemotional states, opening new possibilities foremotion-aware technologies and applications. However,the challenge of individual differences in EEG emotiondata severely constrains the effectiveness and generalizationcapability of existing models.

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Objective: As one branch of human-computerinteraction, affective Brain-Computer Interfaces (aBCI) interpretand utilize electroencephalogram (EEG) signalsto achieve real-time monitoring and recognition of individualemotional states, opening new possibilities foremotion-aware technologies and applications. However,the challenge of individual differences in EEG emotiondata severely constrains the effectiveness and generalizationcapability of existing models.

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19 Views

MS-BioGraphs are a family of sequence similarity graph datasets with up to 2.5 trillion edges. The graphs are weighted edges and presented in compressed WebGraph format. The dataset include symmetric and asymmetric graphs. The largest graph has been created by matching sequences in Metaclust dataset with 1.7 billion sequences. These real-world graph dataset are useful for measuring contributions in High-Performance Computing and High-Performance Graph Processing.

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276 Views

Healthcare 4.0 introduces the groundbreaking notion of the "Digital Twin (DT)," utilizing a digital model to encompass an individual's biological traits. This technology allows for the development of tailored treatment approaches, supports timely interventions, monitors respiratory issues, and offers decision-making assistance to healthcare professionals, ultimately advancing healthcare capabilities.

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136 Views

We investigated the effect of CW radiation at 0.6 THz on pathological protein aggregates in the form of amyloid fibrils, i.e. ordered protein complexes linked to neurodegenerative diseases such as Parkinson's and Frontotemporal Dementia. To monitor the effect of THz irradiation we exploited mid-infrared (mid-IR) vibrational spectroscopy in the amide-I band range, whose lineshape is known to depend on the protein conformation and on how proteins arrange into ordered supramolecular complexes such as fibrils.

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86 Views

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