Interpretable dimensionality reduction and classification of mass spectrometry imaging data in a visceral pain model via non-negative matrix factorization.

Mass spectrometry imaging (MSI) is a powerful scientific tool for understanding the spatial distribution of biochemical compounds in tissue structures. In this paper, we introduce three novel approaches in MSI data processing to perform the tasks of data augmentation, feature ranking, and image registration. We use these approaches in conjunction with non-negative matrix factorization (NMF) to resolve two of the biggest challenges in MSI data analysis, namely: 1) the large file sizes and associated computational resource requirements and 2) the complexity of interpreting the very high dimensional raw spectral data.

COVID-19 policy actions and inflation targeting in South Asia.

In this paper, we examine the impact of policy actions undertaken by governments during the COVID-19 pandemic on Consumer Price Index (CPI) in five major South Asian nations, namely, Bangladesh, India, Nepal, Pakistan and Sri Lanka. Using panel fixed effects regression with robust standard errors, we show the relative importance of monetary and financial interventions on reducing CPI while fiscal interventions, direct grants and aid are insignificant. Further, delving into nature of policy interventions, our study finds evidence of negative impact of Credit Support, and Healthcare Support on CPI in South Asian nations.

Removing subject dependencies on Non-Invasive Blood Glucose Measurement using Hybrid Techniques.

Diabetes mellitus is a major health problem which needs regular glucose monitoring for management of the disease. Invasive blood glucose measuring systems with acceptable accuracy are currently used for measurements. Several non- invasive blood glucose measurement techniques are reported in research literature, but most of them are not commercially available due to low accuracy or dependency on individual physiological parameters.