Path integral formalism for the free Dirac propagator in spherical coordinates

The relativistic Green's function of a free spin-1/2 fermion is derived using the Feynman path integral formalism in spherical coordinates. The Green's function is reduced to an exactly solvable path integral by an appropriate coordinate transformation. The result is given in terms of spherical Bessel functions and spherical spinors, and agrees with previous solutions of the problem

Vacuum polarization correction to atomic energy levels in the path integral formalism

Vacuum polarization corrections to the energy levels of bound electrons are calculated using a perturbative path integral formalism. We apply quantum electrodynamics in a framework which treats the strong binding nuclear field to all orders. The effective potential, derived from the Dyson-Schwinger equation for the photon propagator, is then considered pertubatively. Expressions for the vacuum polarization shift of binding energies is obtained from the poles of the spectral function up to second order. Numerical results are provided to select candidates for novel tests of strong-field quantum electrodynamics by means of precision mass spectrometry

Neuron Segmentation Using Deep Complete Bipartite Networks

In this paper, we consider the problem of automatically segmenting neuronal cells in dual-color confocal microscopy images. This problem is a key task in various quantitative analysis applications in neuroscience, such as tracing cell genesis in Danio rerio (zebrafish) brains. Deep learning, especially using fully convolutional networks (FCN), has profoundly changed segmentation research in biomedical imaging. We face two major challenges in this problem. First, neuronal cells may form dense clusters, making it difficult to correctly identify all individual cells (even to human experts). Consequently, segmentation results of the known FCN-type models are not accurate enough. Second, pixel-wise ground truth is difficult to obtain. Only a limited amount of approximate instance-wise annotation can be collected, which makes the training of FCN models quite cumbersome. We propose a new FCN-type deep learning model, called deep complete bipartite networks (CB-Net), and a new scheme for leveraging approximate instance-wise annotation to train our pixel-wise prediction model. Evaluated using seven real datasets, our proposed new CB-Net model outperforms the state-of-the-art FCN models and produces neuron segmentation results of remarkable qualityComment: miccai 201

UG^2: a Video Benchmark for Assessing the Impact of Image Restoration and Enhancement on Automatic Visual Recognition

Advances in image restoration and enhancement techniques have led to discussion about how such algorithmscan be applied as a pre-processing step to improve automatic visual recognition. In principle, techniques like deblurring and super-resolution should yield improvements by de-emphasizing noise and increasing signal in an input image. But the historically divergent goals of the computational photography and visual recognition communities have created a significant need for more work in this direction. To facilitate new research, we introduce a new benchmark dataset called UG^2, which contains three difficult real-world scenarios: uncontrolled videos taken by UAVs and manned gliders, as well as controlled videos taken on the ground. Over 160,000 annotated frames forhundreds of ImageNet classes are available, which are used for baseline experiments that assess the impact of known and unknown image artifacts and other conditions on common deep learning-based object classification approaches. Further, current image restoration and enhancement techniques are evaluated by determining whether or not theyimprove baseline classification performance. Results showthat there is plenty of room for algorithmic innovation, making this dataset a useful tool going forward.Comment: Supplemental material: https://goo.gl/vVM1xe, Dataset: https://goo.gl/AjA6En, CVPR 2018 Prize Challenge: ug2challenge.or

An Extreme Value Theory Model of Cross-Modal Sensory Information Integration in Modulation of Vertebrate Visual System Functions

We propose a computational model of vision that describes the integration of cross-modal sensory information between the olfactory and visual systems in zebrafish based on the principles of the statistical extreme value theory. The integration of olfacto-retinal information is mediated by the centrifugal pathway that originates from the olfactory bulb and terminates in the neural retina. Motivation for using extreme value theory stems from physiological evidence suggesting that extremes and not the mean of the cell responses direct cellular activity in the vertebrate brain. We argue that the visual system, as measured by retinal ganglion cell responses in spikes/sec, follows an extreme value process for sensory integration and the increase in visual sensitivity from the olfactory input can be better modeled using extreme value distributions. As zebrafish maintains high evolutionary proximity to mammals, our model can be extended to other vertebrates as well

Tumor-Shed PGE2 Impairs IL2Rγc-Signaling to Inhibit CD4+ T Cell Survival: Regulation by Theaflavins

BACKGROUND:Many tumors are associated with decreased cellular immunity and elevated levels of prostaglandin E2 (PGE2), a known inhibitor of CD4+ T cell activation and inducer of type-2 cytokine bias. However, the role of this immunomodulator in the survival of T helper cells remained unclear. Since CD4+ T cells play critical roles in cell-mediated immunity, detail knowledge of the effect tumor-derived PGE2 might have on CD4+ T cell survival and the underlying mechanism may, therefore, help to overcome the overall immune deviation in cancer. METHODOLOGY/PRINCIPAL FINDINGS:By culturing purified human peripheral CD4+ T cells or Jurkat cells with spent media of theaflavin- or celecoxib-pre-treated MCF-7 cells, we show that tumor-shed PGE2 severely impairs interleukin 2 receptor gammac (IL2Rgammac)-mediated survival signaling in CD4+ T cells. Indeed, tumor-shed PGE2 down-regulates IL2Rgammac expression, reduces phosphorylation as well as activation of Janus kinase 3 (Jak-3)/signal transducer and activator of transcription 5 (Stat-5) and decreases Bcl-2/Bax ratio thereby leading to activation of intrinsic apoptotic pathway. Constitutively active Stat-5A (Stat-5A1 6) over-expression efficiently elevates Bcl-2 levels in CD4+ T cells and protects them from tumor-induced death while dominant-negative Stat-5A over-expression fails to do so, indicating the importance of Stat-5A-signaling in CD4+ T cell survival. Further support towards the involvement of PGE2 comes from the results that (a) purified synthetic PGE2 induces CD4+ T cell apoptosis, and (b) when knocked out by small interfering RNA, cyclooxygenase-2 (Cox-2)-defective tumor cells fail to initiate death. Interestingly, the entire phenomena could be reverted back by theaflavins that restore cytokine-dependent IL2Rgammac/Jak-3/Stat-5A signaling in CD4+ T cells thereby protecting them from tumor-shed PGE2-induced apoptosis. CONCLUSIONS/SIGNIFICANCE:These data strongly suggest that tumor-shed PGE2 is an important factor leading to CD4+ T cell apoptosis during cancer and raise the possibility that theaflavins may have the potential as an effective immunorestorer in cancer-bearer

Development and Evaluation of Active Case Detection Methods to Support Visceral Leishmaniasis Elimination in India.

As India moves toward the elimination of visceral leishmaniasis (VL) as a public health problem, comprehensive timely case detection has become increasingly important, in order to reduce the period of infectivity and control outbreaks. During the 2000s, localized research studies suggested that a large percentage of VL cases were never reported in government data. However, assessments conducted from 2013 to 2015 indicated that 85% or more of confirmed cases were eventually captured and reported in surveillance data, albeit with significant delays before diagnosis. Based on methods developed during these assessments, the CARE India team evolved new strategies for active case detection (ACD), applicable at large scale while being sufficiently effective in reducing time to diagnosis. Active case searches are triggered by the report of a confirmed VL case, and comprise two major search mechanisms: 1) case identification based on the index case's knowledge of other known VL cases and searches in nearby houses (snowballing); and 2) sustained contact over time with a range of private providers, both formal and informal. Simultaneously, house-to-house searches were conducted in 142 villages of 47 blocks during this period. We analyzed data from 5030 VL patients reported in Bihar from January 2018 through July 2019. Of these 3033 were detected passively and 1997 via ACD (15 (0.8%) via house-to-house and 1982 (99.2%) by light touch ACD methods). We constructed multinomial logistic regression models comparing time intervals to diagnosis (30-59, 60-89 and ≥90 days with =90 days compared to the referent of <30 days for ACD vs PCD were 0.88, 0.56 and 0.42 respectively. These ACD strategies not only reduce time to diagnosis, and thus risk of transmission, but also ensure that there is a double check on the proportion of cases actually getting captured. Such a process can supplement passive case detection efforts that must go on, possibly perpetually, even after elimination as a public health problem is achieved

VLSI design & implementation for system-on-chip applications

System-on-a-Chip Integrated Circuits are becoming increasingly popular in today’s world. The Memory Management Unit of these System-on-Chip circuits manage the virtual to physical address translation process. The main component within the Memory Management Unit managing this translation is called the Translation Lookaside Buffer which stores the recently used physical address translations. The requirement of the Translation Lookaside Buffer is to provide fast address translations. The behavior of the Translation Lookaside Buffer is characterized by hit & miss – when the address translation information is present and absent. In the Final Year Project, two types of Translation Lookaside Buffers have been successfully designed – one following the Synchronous design principles and the other Asynchronous. The replacement policy of the Translation Lookaside Buffer is also important in determining its efficiency. In this project, the Least Recently Used replacement policy has been implemented in the design of the Translation Lookaside Buffer. The synchronous and asynchronous design schematics and simulation results have been shown.Bachelor of Engineerin