Partha Sarathi Mukherjee

Image monitoring is an important research problem that has wide applications in various fields, including manufacturing industries, satellite imaging, medical diagnostics, and so forth. Traditional image monitoring control charts perform rather poorly when the changes occur at very small regions of the image, and when the changes of image intensity values are small in those regions. Their performances get worse if the images contain noise, and the changes occur near the edges of image objects. In applications such as manufacturing industries, the changes in the images are often too small to be detected by human eyes. In this article, we propose a CUSUM-type control chart for online monitoring of grayscale images. Depending on what kind of changes we wish to detect, big or small, we propose to use a certain upper quantile of the local CUSUM statistics. We incorporate a state-of-the-art jump preserving image smoothing technique in the proposed chart that ensures good performance even in presence of low to moderate noise. Theoretical justifications, and superior performance in numerical comparisons ensure that the proposed control chart can be useful to many researchers and practitioners.

Image registration techniques are used for mapping two images of the same scene or image objects to one another. There are several image registration techniques available in the literature for registering rigid body as well as non-rigid body transformations. A very important image transformation is zooming in or out which also called scaling. Very few research articles address this particular problem except a number of feature-based approaches. This paper proposes a method to register two images of the same image object where one is a zoomed-in version of the other. In the proposed intensity-based method, we consider a circular neighborhood around an image pixel of the zoomed-in image, and search for the pixel in the reference image whose circular neighborhood is most similar to that of the neighborhood in the zoomed-in image with respect to various similarity measures. We perform this procedure for all pixels in the zoomed-in image. On images where the features are small in number, our proposed method works better than the state-of-the-art feature-based methods. We provide several numerical examples as well as a mathematical justification in this paper which support our statement that this method performs reasonably well in many situations.

Image registration is a widely used tool for matching two images of the same scene with one another. In the literature, several image registration techniques are available to register rigid‐body and non‐rigid‐body transformations. One such important transformation is zooming. There are very few feature‐based methods that address this particular problem. These methods fail miserably when there are only a limited number of point features available in the image. This paper proposes a feature‐based approach that works with a feature that is readily available in almost all images, for registering two images of the same image object where one is a zoomed‐in version of the other. In the proposed method, we first detect the possible edge points which we consider as features in both the reference and the zoomed image. Then, we map these features of the reference and the zoomed image with one another and find the relationship between them using a mathematical model. Finally, we use the relationship to register the zoomed‐in image. This method outperforms some of the state‐of‐the‐art methods in many occasions. Several numerical examples and some statistical properties justify that this method works well in many applications.

This Review emphasizes the impact of APOE4—the most significant genetic risk factor for Alzheimer’s disease (AD)—on peripheral and neural effects starting in childhood. We discuss major mechanistic players associated with the APOE alleles’ effects in humans to understand their impact from conception through all life stages and the importance of detrimental, synergistic environmental exposures. APOE4 influences AD pathogenesis, and exposure to fine particulate matter (PM_2.5), manufactured nanoparticles (NPs), and ultrafine particles (UFPs) associated with combustion and friction processes appear to be major contributors to cerebrovascular dysfunction, neuroinflammation, and oxidative stress. In the context of outdoor and indoor PM pollution burden—as well as Fe, Ti, and Al alloys; Hg, Cu, Ca, Sn, and Si UFPs/NPs—in placenta and fetal brain tissues, urban APOE3 and APOE4 carriers are developing AD biological disease hallmarks (hyperphosphorylated-tau (P-tau) and amyloid beta 42 plaques (Aβ₄₂)). Strikingly, for Metropolitan Mexico City (MMC) young residents ≤ 40 y, APOE4 carriers have 4.92 times higher suicide odds and 23.6 times higher odds of reaching Braak NFT V stage versus APOE4 non-carriers. The National Institute on Aging and Alzheimer’s Association (NIA-AA) framework could serve to test the hypothesis that UFPs and NPs are key players for oxidative stress, neuroinflammation, protein aggregation and misfolding, faulty complex protein quality control, and early damage to cell membranes and organelles of neural and vascular cells. Noninvasive biomarkers indicative of the P-tau and Aβ₄₂ abnormal protein deposits are needed across the disease continuum starting in childhood. Among the 21.8 million MMC residents, we have potentially 4 million APOE4 carriers at accelerated AD progression. These APOE4 individuals are prime candidates for early neuroprotective interventional trials. APOE4 is key in the development of AD evolving from childhood in highly polluted urban centers dominated by anthropogenic and industrial sources of pollution. APOE4 subjects are at higher early risk of AD development, and neuroprotection ought to be implemented. Effective reductions of PM_2.5, UFP, and NP emissions from all sources are urgently needed. Alzheimer’s Disease prevention ought to be at the core of the public health response and physicians-scientist minority research be supported.

Sustained exposures to ubiquitous outdoor/indoor fine particulate matter (PM_2.5), including combustion and friction ultrafine PM (UFPM) and industrial nanoparticles (NPs) starting in utero, are linked to early pediatric and young adulthood aberrant neural protein accumulation, including hyperphosphorylated tau (p-tau), beta-amyloid (Aβ_{1 − 42}), α-synuclein (α syn) and TAR DNA-binding protein 43 (TDP-43), hallmarks of Alzheimer's (AD), Parkinson's disease (PD), frontotemporal lobar degeneration (FTLD), and amyotrophic lateral sclerosis (ALS). UFPM from anthropogenic and natural sources and NPs enter the brain through the nasal/olfactory pathway, lung, gastrointestinal (GI) tract, skin, and placental barriers. On a global scale, the most important sources of outdoor UFPM are motor traffic emissions. This study focuses on the neuropathology heterogeneity and overlap of AD, PD, FTLD, and ALS in older adults, their similarities with the neuropathology of young, highly exposed urbanites, and their strong link with sleep disorders. Critical information includes how this UFPM and NPs cross all biological barriers, interact with brain soluble proteins and key organelles, and result in the oxidative, endoplasmic reticulum, and mitochondrial stress, neuroinflammation, DNA damage, protein aggregation and misfolding, and faulty complex protein quality control. The brain toxicity of UFPM and NPs makes them powerful candidates for early development and progression of fatal common neurodegenerative diseases, all having sleep disturbances. A detailed residential history, proximity to high-traffic roads, occupational histories, exposures to high-emission sources (i.e., factories, burning pits, forest fires, and airports), indoor PM sources (tobacco, wood burning in winter, cooking fumes, and microplastics in house dust), and consumption of industrial NPs, along with neurocognitive and neuropsychiatric histories, are critical. Environmental pollution is a ubiquitous, early, and cumulative risk factor for neurodegeneration and sleep disorders. Prevention of deadly neurological diseases associated with air pollution should be a public health priority.