Advanced flamelet modelling of turbulent non-premixed and partially premixed combustion

Current work focuses on the development and performance evaluation of advanced flamelet models for turbulent non-premixed and partially premixed combustion in RANS and large eddy simulation (LES) based modelling. A RANS-based combustion modelling strategy which has the ability to capture the detailed structure of turbulent non-premixed flames, including the pollutant NO, and account for the effects of radiation heat loss and transient evolution of NO, has been developed and incorporated into the in-house RANS code. The strategy employs an 'enthalpy defect'-based non-adiabatic flamelet model in conjunction with steady or unsteady nonadiabatic flamelets based NO submodels. [Continues.

Performance of PIXE Technique through a Geochemical Analysis of High Grade Rocks

It has been an argument that some of the elements present in geological material by using PIXE analysis are purely determined or could not be determined at all, due to various reasons including the matrix. It is felt that a systematic investigation needs to be designed and implemented to understand the limitation of PIXE in certain elements. The high-grade rocks selected are analyzed both by PIXE as well as AAS and the results are authenticated by using a USGS reference material, Basalt, studies of literature. It is believed that the accuracy of problematic elements, especially from high grade rock can be improved and the conditions of PIXE can be standardized for various elements under different combinations. The reasons behind the poor performance of Proton Induced X- ray Emission in case of certain elements have been established

Laminar flamelet model prediction of NOx formation in a turbulent bluff-body combustor

A bluff-body combustor, with recirculation zone and simple boundary conditions, is ideal as a compromise for an industrial combustor for validating combustion models. This combustor, however, has proved to be very challenging to the combustion modellers in a number of previous studies. In the present study, an improved prediction has been reported through better representation of turbulence effect by Reynolds stress transport model and extended upstream computational domain. Thermo-chemical properties of the flame have been represented by a laminar flamelet model. A comparison among reduced chemical kinetic mechanism of Peters and detailed mechanisms of GRI 2.11, GRI 3.0, and San Diego has been studied under the laminar flamelet modelling framework. Computed results have been compared against the well-known experimental data of Sydney University bluff-body CH4/H2 flame. Results show that the laminar flamelet model yields very good agreement with measurements for temperature and major species with all the reaction mechanisms. The GRI 2.11 performs better than the other reaction mechanisms in predicting minor species such as OH and pollutant NO. The agreement achieved for NO is particularly encouraging considering the simplified modelling formulation utilized for the kinetically controlled NO formatio

Blockchain-Enabled On-Path Caching for Efficient and Reliable Content Delivery in Information-Centric Networks

As the demand for online content continues to grow, traditional Content Distribution Networks (CDNs) are facing significant challenges in terms of scalability and performance. Information-Centric Networking (ICN) is a promising new approach to content delivery that aims to address these issues by placing content at the center of the network architecture. One of the key features of ICNs is on-path caching, which allows content to be cached at intermediate routers along the path from the source to the destination. On-path caching in ICNs still faces some challenges, such as the scalability of the cache and the management of cache consistency. To address these challenges, this paper proposes several alternative caching schemes that can be integrated into ICNs using blockchain technology. These schemes include Bloom filters, content-based routing, and hybrid caching, which combine the advantages of off-path and on-path cachings. The proposed blockchain-enabled on-path caching mechanism ensures the integrity and authenticity of cached content, and smart contracts automate the caching process and incentivize caching nodes. To evaluate the performance of these caching alternatives, the authors conduct experiments using real-world datasets. The results show that on-path caching can significantly reduce network congestion and improve content delivery efficiency. The Bloom filter caching scheme achieved a cache hit rate of over 90% while reducing the cache size by up to 80% compared to traditional caching. The content-based routing scheme also achieved high cache hit rates while maintaining low latency

A Comprehensive Analysis on Risk Prediction of Heart Disease using Machine Learning Models

Most of the deaths worldwide are caused by heart disease and the disease has become a major cause of morbidity for many people. In order to prevent such deaths, the mortality rate can be greatly reduced through regular monitoring and early detection of heart disease. Heart disease diagnosis has grown to be a challenging task in the field of clinically provided data analysis. Predicting heart disease is a highly demanding and challenging task with pure accuracy, but it is easy to figure out using advanced Machine Learning (ML) techniques. A Machine Learning approach has been shown to predict heart disease in this approach. By doing this, the disease can be predicted early and the mortality rate and severity can be reduced. The application of machine learning techniques is advancing significantly in the medical field. Interpreting these analyzes in this methodology, which has been shown to specifically aim to discover important features of heart disease by providing ML algorithms for predicting heart disease, has resulted in improved predictive accuracy. The model is trained using classification algorithms such as Decision Tree (DT), K-Nearest Neighbors (K-NN), Random Forest (RF), Support Vector Machine (SVM). The performance of these four algorithms is quantified in different aspects such as accuracy, precision, recall and specificity. SVM has been shown to provide the best performance in this approach for different algorithms although the accuracy varies in different cases

Ubiquitous Aberration in Cholesterol Metabolism Across Pancreatic Ductal Adenocarcinoma

Pancreatic cancer (PC) is characterized by metabolic deregulations that often manifest as deviations in metabolite levels and aberrations in their corresponding metabolic genes across the clinical specimens and preclinical PC models. Cholesterol is one of the critical metabolites supporting PC, synthesized or acquired by PC cells. Nevertheless, the significance of the de novo cholesterol synthesis pathway has been controversial in PC, indicating the need to reassess this pathway in PC. We utilized preclinical models and clinical specimens of PC patients and cell lines and utilized mass spectrometry-based sterol analysis. Further, we also performed in silico analysis to corroborate the significance of de novo cholesterol synthesis pathway in PC. Our results demonstrated alteration in free sterol levels, including free cholesterol, across in vitro, in vivo, and clinical specimens of PC. Especially, our sterol analyses established consistent alterations in free cholesterol across the different PC models. Overall, this study demonstrates the significance and consistency in deviation of cholesterol synthesis pathway in PC while showing the aberrations in sterol metabolite intermediates and the related genes using preclinical models, in silico platforms, and the clinical specimens

Tunneling in a cavity

The mechanism of coherent destruction of tunneling found by Grossmann et al. [Phys. Rev. Lett. 67, 516 (1991)] is studied from the viewpoint of quantum optics by considering the photon statistics of a single mode cavity field which is strongly coupled to a two-level tunneling system (TS). As a function of the interaction time between TS and cavity the photon statistics displays the tunneling dynamics. In the semi-classical limit of high photon occupation number $n$, coherent destruction of tunneling is exhibited in a slowing down of an amplitude modulation for certain parameter ratios of the field. The phenomenon is explained as arising from interference between displaced number states in phase space which survives the large $n$ limit due to identical $n^{-1/2}$ scaling between orbit width and displacement.Comment: 4 pages Revtex, 2 PS-figures, appears in The Physical Review

Negativity of the Wigner function as an indicator of nonclassicality

A measure of nonclassicality of quantum states based on the volume of the negative part of the Wigner function is proposed. We analyze this quantity for Fock states, squeezed displaced Fock states and cat-like states defined as coherent superposition of two Gaussian wave packets.Comment: 10 pages, 7 figure

Disruption of FDPS/Rac1 Axis Radiosensitizes Pancreatic Ductal Adenocarcinoma by Attenuating DNA Damage Response and Immunosuppressive Signalling

BACKGROUND: Radiation therapy (RT) has a suboptimal effect in patients with pancreatic ductal adenocarcinoma (PDAC) due to intrinsic and acquired radioresistance (RR). Comprehensive bioinformatics and microarray analysis revealed that cholesterol biosynthesis (CBS) is involved in the RR of PDAC. We now tested the inhibition of the CBS pathway enzyme, farnesyl diphosphate synthase (FDPS), by zoledronic acid (Zol) to enhance radiation and activate immune cells. METHODS: We investigated the role of FDPS in PDAC RR using the following methods: in vitro cell-based assay, immunohistochemistry, immunofluorescence, immunoblot, cell-based cholesterol assay, RNA sequencing, tumouroids (KPC-murine and PDAC patient-derived), orthotopic models, and PDAC patient\u27s clinical study. FINDINGS: FDPS overexpression in PDAC tissues and cells (P \u3c 0.01 and P \u3c 0.05) is associated with poor RT response and survival (P = 0.024). CRISPR/Cas9 and pharmacological inhibition (Zol) of FDPS in human and mouse syngeneic PDAC cells in conjunction with RT conferred higher PDAC radiosensitivity in vitro (P \u3c 0.05, P \u3c 0.01, and P \u3c 0.001) and in vivo (P \u3c 0.05). Interestingly, murine (P = 0.01) and human (P = 0.0159) tumouroids treated with Zol+RT showed a significant growth reduction. Mechanistically, RNA-Seq analysis of the PDAC xenografts and patients-PBMCs revealed that Zol exerts radiosensitization by affecting Rac1 and Rho prenylation, thereby modulating DNA damage and radiation response signalling along with improved systemic immune cells activation. An ongoing phase I/II trial (NCT03073785) showed improved failure-free survival (FFS), enhanced immune cell activation, and decreased microenvironment-related genes upon Zol+RT treatment. INTERPRETATION: Our findings suggest that FDPS is a novel radiosensitization target for PDAC therapy. This study also provides a rationale to utilize Zol as a potential radiosensitizer and as an immunomodulator in PDAC and other cancers. FUNDING: National Institutes of Health (P50, P01, and R01)

ST6GalNAc-I Promotes Lung Cancer Metastasis by Altering MUC5AC Sialylation

Lung cancer (LC) is the leading cause of cancer-related mortality. However, the molecular mechanisms associated with the development of metastasis is poorly understood. Understanding the biology of LC metastasis is critical to unveil the molecular mechanisms for designing targeted therapies. We developed two genetically engineered LC mouse models- KrasG12D ;Trp53R172H/+ ;Ad-Cre (KPA) and KrasG12D ; Ad-Cre (KA). Survival analysis showed significantly (P=0.0049) shorter survival in KPA tumor-bearing mice as compared to KA, suggesting the aggressiveness of the model. Our transcriptomic data showed high expression of St6galnac-I in KPA compared to KA tumors. ST6GalNAc-I is an O-glycosyltransferase, which catalyzes the addition of sialic acid (SA) to the initiating GalNAc residues forming sialyl Tn (STn) on glycoproteins, such as mucins. Ectopic expression of species-specific p53 mutants in the syngeneic mouse and human LC cells led to increased cell migration and high expression of ST6GalNAc-I, STn, and MUC5AC. Immunoprecipitation of MUC5AC in the ectopically expressing p53R175H cells exhibited higher affinity towards STn. In addition, ST6GalNAc-I knockout (KO) cells also showed decreased migration, possibly due to reduced glycosylation of MUC5AC as observed by low STn on the glycoprotein. Interestingly, ST6GalNAc-I KO cells injected mice developed less liver metastasis (P=0.01) compared to controls, while co-localization of MUC5AC and STn was observed in the liver metastatic tissues of control mice. Collectively, our findings support the hypothesis that mutant p53R175H mediates ST6GalNAc-I expression, leading to the sialyation of MUC5AC, and thus contribute to LC liver metastasis