Heuristic-Based Automatic Pruning of Deep Neural Networks

The performance of a deep neural network (deep NN) is dependent upon a significant number of weight parameters that need to be trained which is a computational bottleneck. The growing trend of deeper architectures poses a restriction on the training and inference scheme on resource-constrained devices. Pruning is an important method for removing the deep NN\u27s unimportant parameters and making their deployment easier on resource-constrained devices for practical applications. In this paper, we proposed a heuristics-based novel filter pruning method to automatically identify and prune the unimportant filters and make the inference process faster on devices with limited resource availability. The selection of the unimportant filters is made by a novel pruning estimator (γ). The proposed method is tested on various convolutional architectures AlexNet, VGG16, ResNet34, and datasets CIFAR10, CIFAR100, and ImageNet. The experimental results on a large-scale ImageNet dataset show that the FLOPs of the VGG16 can be reduced up to 77.47%, achieving ≈5x inference speedup. The FLOPs of a more popular ResNet34 model are reduced by 41.94% while retaining competitive performance compared to other state-of-the-art methods

EXECUTION TIME – AREA TRADEOFF IN GAUSING RESIDUAL LOAD DECODER: INTEGRATED EXPLORATION OF CHAINING BASED SCHEDULE AND ALLOCATION IN HLS FOR HARDWARE ACCELERATORS

Design space exploration is an indispensable segment of High Level Synthesis (HLS) design of hardware accelerators. This paper presents a novel technique for Area-Execution time tradeoff using residual load decoding heuristics in genetic algorithms (GA) for integrated design space exploration (DSE) of scheduling and allocation. This approach is also able to resolve issues encountered during DSE of data paths for hardware accelerators, such as accuracy of the solution found, as well as the total exploration time during the process. The integrated solution found by the proposed approach satisfies the user specified constraints of hardware area and total execution time (not just latency), while at the same time offers a twofold unified solution of chaining based schedule and allocation. The cost function proposed in the genetic algorithm approach takes into account the functional units, multiplexers and demultiplexers needed during implementation. The proposed exploration system (ExpSys) was tested on a large number of benchmarks drawn from the literature for assessment of its efficiency. Results indicate an average improvement in Quality of Results (QoR) greater than 26 % when compared to a recent well known GA based exploration method

Assessment of Surface Water Quality by Using Water Quality Index of Sanbarish Pond of Morang District, Nepal

A study of surface water of Sanbarish pond has been carried out to examine the quality for drinking and other domestic purpose as well as to evaluate the water pollution status of wetland on the basis of the presence of different physicochemical and microbiological parameters. For calculating the WQI, the following 11 parameters have been considered: Temperature (ambient and water), pH, turbidity, TDS (Total Dissolved Solid), Cl- (chloride), EC (Electric Conductivity), DO (Dissolved Oxygen), TH (Total Hardness), PO4–P (Phosphate – phosphorus), NO3-N (Nitrate – nitrogen), COD (Chemical Oxygen Demand).  The WQI for these samples has been found to be mainly from the higher values of turbidity, DO and PH of the wetland water. The result of WQI has indicated the calculated value (ΣSIi = 95.59) showed the good quality for drinking as per the classification given and needs some proper treatment before consumption, and it also needs to be protected from the risk of contamination. The mean value of fecal coli form recorded was 1166.67 MPN/l00 ml which was crossed the WHO guide line

Multivariate and Online Prediction of Closing Price Using Kernel Adaptive Filtering.

This paper proposes a multivariate and online prediction of stock prices via the paradigm of kernel adaptive filtering (KAF). The prediction of stock prices in traditional classification and regression problems needs independent and batch-oriented nature of training. In this article, we challenge this existing notion of the literature and propose an online kernel adaptive filtering-based approach to predict stock prices. We experiment with ten different KAF algorithms to analyze stocks' performance and show the efficacy of the work presented here. In addition to this, and in contrast to the current literature, we look at granular level data. The experiments are performed with quotes gathered at the window of one minute, five minutes, ten minutes, fifteen minutes, twenty minutes, thirty minutes, one hour, and one day. These time windows represent some of the common windows frequently used by traders. The proposed framework is tested on 50 different stocks making up the Indian stock index: Nifty-50. The experimental results show that online learning and KAF is not only a good option, but practically speaking, they can be deployed in high-frequency trading as well.Peer Reviewe

Multi-OMICs analysis reveals metabolic and epigenetic changes associated with macrophage polarization

Macrophages (MФ) are an essential immune cell for defense and repair that travel to different tissues and adapt based on local stimuli. A critical factor that may govern their polarization is the cross-talk between metabolism and epigenetics. However, simultaneous measurements of metabolites, epigenetics, and proteins (phenotype) has been a major technical challenge. To address this, we have developed a novel triomics approach using mass spectrometry to comprehensively analyze metabolites, proteins, and histone modifications, in a single sample. To demonstrate this technique, we investigated the metabolic-epigenetic-phenotype axis following polarization of human blood-derived monocytes into either \u27pro-inflammatory M1\u27- or \u27anti-inflammatory M2-\u27 MФs. We report here a complex relationship between arginine, tryptophan, glucose, and the citric acid cycle (TCA) metabolism, protein and histone post-translational modifications, and human macrophage polarization that was previously not described. Surprisingly, M1-MФs had globally reduced histone acetylation levels but high levels of acetylated amino acids. This suggests acetyl-CoA was diverted, in part, towards acetylated amino acids. Consistent with this, stable isotope tracing of glucose revealed reduced usage of acetyl-CoA for histone acetylation in M1-MФs. Furthermore, isotope tracing also revealed MФs uncoupled glycolysis from the TCA cycle, as evidenced by poor isotope enrichment of succinate. M2-MФs had high levels of kynurenine and serotonin which are reported to have immune-suppressive effects. Kynurenine is upstream of de novo NAD+ metabolism which is a necessary cofactor for Sirtuin-type histone deacetylases. Taken together, we demonstrate a complex interplay between metabolism and epigenetics that may ultimately influence cell phenotype

Human Macrophages Exhibit GM-CSF Dependent Restriction of Mycobacterium tuberculosis Infection via Regulating Their Self-Survival, Differentiation and Metabolism

GM-CSF is an important cytokine that regulates the proliferation of monocytes/macrophages and its various functions during health and disease. Although growing evidences support the notion that GM-CSF could play a major role in immunity against tuberculosis (TB) infection, the mechanism of GM-CSF mediated protective effect against TB remains largely unknown. Here in this study we examined the secreted levels of GM-CSF by human macrophages from different donors along with the GM-CSF dependent cellular processes that are critical for control of M. tuberculosis infection. While macrophage of different donors varied in their ability to produce GM-CSF, a significant correlation was observed between secreted levels of GM-CSF, survial of macrophages and intra-macrophage control of Mycobacterium tuberculosis bacilli. GM-CSF levels secreted by macrophages negatively correlated with the intra-macrophage M. tuberculosis burden, survival of infected host macrophages positively correlated with their GM-CSF levels. GM-CSF-dependent prolonged survival of human macrophages also correlated with significantly decreased bacterial burden and increased expression of self-renewal/cell-survival associated genes such as BCL-2 and HSP27. Antibody-mediated depletion of GM-CSF in macrophages resulted in induction of significantly elevated levels of apoptotic/necrotic cell death and a simultaneous decrease in autophagic flux. Additionally, protective macrophages against M. tuberculosis that produced more GM-CSF, induced a stronger granulomatous response and produced significantly increased levels of IL-1β, IL-12 and IL-10 and decreased levels of TNF-α and IL-6. In parallel, macrophages isolated from the peripheral blood of active TB patients exhibited reduced capacity to control the intracellular growth of M. tuberculosis and produced significantly lower levels of GM-CSF. Remarkably, as compared to healthy controls, macrophages of active TB patients exhibited significantly altered metabolic state correlating with their GM-CSF secretion levels. Altogether, these results suggest that relative levels of GM-CSF produced by human macrophages plays a critical role in preventing cell death and maintaining a protective differentiation and metabolic state of the host cell against M. tuberculosis infection

Antibody-Mediated LILRB2-Receptor Antagonism Induces Human Myeloid-Derived Suppressor Cells to Kill Mycobacterium tuberculosis

Tuberculosis is a leading cause of death in mankind due to infectious agents, and Mycobacterium tuberculosis (Mtb) infects and survives in macrophages (MФs). Although MФs are a major niche, myeloid-derived suppressor cells (MDSCs) are an alternative site for pathogen persistence. Both MФs and MDSCs express varying levels of leukocyte immunoglobulin-like receptor B (LILRB), which regulate the myeloid cell suppressive function. Herein, we demonstrate that antagonism of LILRB2 by a monoclonal antibody (mab) induced a switch of human MDSCs towards an M1-macrophage phenotype, increasing the killing of intracellular Mtb. Mab-mediated antagonism of LILRB2 alone and its combination with a pharmacological blockade of SHP1/2 phosphatase increased proinflammatory cytokine responses and phosphorylation of ERK1/2, p38 MAPK, and NF-kB in Mtb-infected MDSCs. LILRB2 antagonism also upregulated anti-mycobacterial iNOS gene expression and an increase in both nitric oxide and reactive oxygen species synthesis. Because genes associated with the anti-mycobacterial function of M1-MФs were enhanced in MDSCs following mab treatment, we propose that LILRB2 antagonism reprograms MDSCs from an immunosuppressive state towards a pro-inflammatory phenotype that kills Mtb. LILRB2 is therefore a novel therapeutic target for eradicating Mtb in MDSCs

Human M1 macrophages express unique innate immune response genes after mycobacterial infection to defend against tuberculosis

Mycobacterium tuberculosis (Mtb) is responsible for approximately 1.5 million deaths each year. Though 10% of patients develop tuberculosis (TB) after infection, 90% of these infections are latent. Further, mice are nearly uniformly susceptible to Mtb but their M1-polarized macrophages (M1-MΦs) can inhibit Mtb in vitro, suggesting that M1-MΦs may be able to regulate anti-TB immunity. We sought to determine whether human MΦ heterogeneity contributes to TB immunity. Here we show that IFN-γ-programmed M1-MΦs degrade Mtb through increased expression of innate immunity regulatory genes (Inregs). In contrast, IL-4-programmed M2-polarized MΦs (M2-MΦs) are permissive for Mtb proliferation and exhibit reduced Inregs expression. M1-MΦs and M2-MΦs express pro- and anti-inflammatory cytokine-chemokines, respectively, and M1-MΦs show nitric oxide and autophagy-dependent degradation of Mtb, leading to increased antigen presentation to T cells through an ATG-RAB7-cathepsin pathway. Despite Mtb infection, M1-MΦs show increased histone acetylation at the ATG5 promoter and pro-autophagy phenotypes, while increased histone deacetylases lead to decreased autophagy in M2-MΦs. Finally, Mtb-infected neonatal macaques express human Inregs in their lymph nodes and macrophages, suggesting that M1 and M2 phenotypes can mediate immunity to TB in both humans and macaques. We conclude that human MФ subsets show unique patterns of gene expression that enable differential control of TB after infection. These genes could serve as targets for diagnosis and immunotherapy of TB

Enteroviruses in Patients with Acute Encephalitis, Uttar Pradesh, India

An outbreak of viral encephalitis occurred in northern India in 2006. Attempts to identify an etiologic agent in cerebrospinal fluid by using reverse transcription–PCR showed positivity to enterovirus (EV) in 66 (21.6%) of 306 patients. Sequencing and phylogenetic analyses of PCR products from 59 (89.3%) of 66 specimens showed similarity with EV-89 and EV-76 sequences

Enteroviruses in Patients with Acute Encephalitis, Uttar Pradesh, India

An outbreak of viral encephalitis occurred in northern India in 2006. Attempts to identify an etiologic agent in cerebrospinal fluid by using reverse transcription–PCR showed positivity to enterovirus (EV) in 66 (21.6%) of 306 patients. Sequencing and phylogenetic analyses of PCR products from 59 (89.3%) of 66 specimens showed similarity with EV-89 and EV-76 sequences