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Analyzing solubility of acid gas and light alkanes in triethylene glycol

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Journal of Natural Gas Chemistry 2008年第1期17卷 51-58页

作者： Alireza bahadori hari.b.vuthaluru Saeid Mokhatab Department of Chemical Engineering Curtin University of TechnologyGPO Box 1987PerthWA 6845Australia Process Technology Manager Tehran Raymand Consulting EngineersTehranIran

Physical solvents such as ethylene glycol （EG）, diethylene glycol （DEG）, and triethylene glycol （TEG） are commonly used in wet gas dehydration processes with TEG being the most popular due to ease of regeneration and low solvent losses. Unfortunately, TEG absorbs significantly more hydrocarbons and acid gases than EG or DEG. Quantifying this amount of absorption is therefore critical in order to minimize hydrocarbon losses or to optimize hydrocarbon recovery depending on the objective of the process. In this article, a new correlation that fully covers the operating ranges of TEG dehydration units is developed in order to determine the solubility of light alkanes and acid gases in TEG solvent. The influence of several parameters on hydrocarbon and acid gas solubility including temperature, pressure, and solvent content is also examined.

关键词： solubility triethylene glycol acid gas hydrocarbon gas dehydration

A novel correlation for estimation of hydrate forming condition of natural gases

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Journal of Natural Gas Chemistry 2009年第4期18卷 453-457页

作者： Alireza bahadori hari. b. vuthaluru Department of Chemical Engineering Curtin University of Technology

An inherent problem with natural gas production or transmission is the formation of gas hydrates, which can lead to safety hazards to production/transportation systems and to substantial economic risks. Therefore, an understanding of conditions where hydrates form is necessary to overcome hydrate related issues. Over the years, several models requiring more complicated and longer computations have been proposed for the prediction of hydrate formation conditions of natural gases. For these reasons, it is essential to develop a reliable and simple-to-use method for oil and gas practitioners. The purpose of this study is to formulate a novel empirical correlation for rapid estimation of hydrate formation condition of sweet natural gases. The developed correlation holds for wide range of temperatures （265 - 298 K）, pressures （1200 to 40000 kPa） and molecular weights （16-29）. New proposed correlation shows consistently accurate results across proposed pressure, temperature and molecular weight ranges. This consistency could not be matched by any of the widely accepted existing correlations within the investigated range. For all conditions, new correlation showed average absolute deviation to be less than 0.2% and provided much better results than the widely accepted existing correlations.

关键词： gas hydrate correlation natural gas

Predicting hydrate forming pressure of pure alkanes in the presence of inhibitors

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Journal of Natural Gas Chemistry 2008年第3期17卷 249-255页

作者： Alireza bahadori hari.b.vuthaluru Saeid Mokhatab Moses O.Tade Department of Chemical Engineering Curtin University of Technology Process Technology Department Tehran Raymand Consulting Engineers

An inherent problem with natural gas production or transmission is the formation of gas hydrates, which can lead to safety hazards for production/transportation systems, and substantial economic risks. Hydrate inhibition with different inhibitors such as, methanol, ethylene glycol （EG）, triethylene glycol （TEG）, and sodium chloride solution continues to play a critical role in many operations. An understanding of when the hydrates form in the presence of these hydrate inhibitors, is therefore necessary to overcome hydrate problems. Several thermodynamic models have been proposed for predicting the hydrate formation conditions in aqueous solutions containing methanol/glycols and electrolytes. However, available models have limitations that include the types of liquid, compositions of fluids, and inhibitors used. The aim of this study is to develop a simple-to-use correlation for accurate prediction of hydrate-forming pressures of pure alkanes in the presence of different hydrate inhibitors, where the obtained results illustrate good agreement with the reported experimental data.

关键词： gas hydrates pure alkanes methanol: ethylene glycol triethylene glycol sodium chloride

Intrumer:A Multi Module Distributed Explainable IDS/IPS for Securing Cloud Environment

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Computers, Materials & Continua 2025年第1期82卷 579-607页

作者： Nazreen banu A S.K.b.Sangeetha Department of Computer Science and Engineering SRM Institute of Science and TechnologyVadapalani CampusChennai600026Tamil NaduIndia

The increasing use of cloud-based devices has reached the critical point of cybersecurity and unwanted network *** environments pose significant challenges in maintaining privacy and *** approaches,such as IDS,have been developed to tackle these ***,most conventional Intrusion Detection System(IDS)models struggle with unseen cyberattacks and complex high-dimensional *** fact,this paper introduces the idea of a novel distributed explainable and heterogeneous transformer-based intrusion detection system,named INTRUMER,which offers balanced accuracy,reliability,and security in cloud settings bymultiplemodulesworking together within *** traffic captured from cloud devices is first passed to the TC&TM module in which the Falcon Optimization Algorithm optimizes the feature selection process,and Naie bayes algorithm performs the classification of *** selected features are classified further and are forwarded to the Heterogeneous Attention Transformer(HAT)*** this module,the contextual interactions of the network traffic are taken into account to classify them as normal or malicious *** classified results are further analyzed by the Explainable Prevention Module(XPM)to ensure trustworthiness by providing interpretable *** the explanations fromthe classifier,emergency alarms are transmitted to nearby IDSmodules,servers,and underlying cloud devices for the enhancement of preventive *** experiments on benchmark IDS datasets CICIDS 2017,Honeypots,and NSL-KDD were conducted to demonstrate the efficiency of the INTRUMER model in detecting network trafficwith high accuracy for different *** outperforms state-of-the-art approaches,obtaining better performance metrics:98.7%accuracy,97.5%precision,96.3%recall,and 97.8%*** results validate the robustness and effectiveness of INTRUMER in securing diverse cloud environments against sophisticated cyber threats.

关键词： Cloud computing intrusion detection system transformers and explainable artificial intelligence(XAI)

Neuroinflammation revisited through the microglial lens

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Neural Regeneration Research 2025年第7期20卷 1989-1990页

作者： Renato Socodato João b.Relvas Institute of Research and Innovation in Health(i3S)and Institute for Molecular and Cell biology(IbMC) University of PortoPortoPortugal Department of biomedicine Faculty of Medicine of the University of Porto(FMUP)PortoPortugal

Neuroimmunology is emerging as a pivotal field,shedding light on the intricate dialogues between the central nervous system(CNS)and the immune *** exploration is particularly significant in understanding microglia,the CNS’s innate immune cells,beyond the conventional conflation of“neuroinflammation”and“microglial activation.”This conflation has clouded the true complexity of these processes,potentially stalling scientific progress and the development of new *** challenge the long-standing perspectives that have oversimplified these interactions,advocating for a deeper exploration of the dynamic relationship between neuroinflammation and microglial *** dissecting specific molecular pathways,we aim to illuminate their elaborate roles in neuroinflammatory responses,especially in the context of Alzheimer’s disease(AD).Here,neuroinflammation is not merely a passive observer or a direct antagonist but a complex agent in the disease’s *** article calls for a significant paradigm shift towards an integrative,multi-omics approach to *** such a comprehensive framework is crucial for advancing our understanding of neuroinflammatory conditions and paving the way for targeted therapeutic strategies for brain diseases.

关键词： inflammation simplified activation

Novel approaches for the prediction of density of glycol solutions

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Journal of Natural Gas Chemistry 2008年第3期17卷 298-302页

作者： A.bahadori Y.Hajizadeh H.b.vuthaluru M.O.Tade S.Mokhatab Department of Chemical Engineering Curtin University of Technology Institute of Petroleum Engineering Heriot-Watt University Process Technology Department Tehran Raymand Consulting Engineers

Two new approaches for the accurate prediction of densities of the commonly used glycol solutions in the gasprocessing industry are presented in the article. The first approach is based on developing a simple-to-use polynomial correlation for an appropriate prediction of density of glycol solutions as a function of temperature and weight percent of glycols in water, where the obtained results show very good agreement with the reported experimental data. The second approach, however, is based on the artificial neural networks （ANN） methodology, wherein the results demonstrate the ability of the introduced method to predict reasonably accurate densities of glycols under operating conditions. Comparisons of the two novel approaches indicated that the simple-to-use correlation appears to be superior owing to its simplicity and clear numerical background, wherein the relevant coefficients can be retuned if new and more accurate data are available in the future. The average deviation of the new proposed polynomial correlation results from reported data is 0.64 kg/m^3 whereas the average deviation of artificial neural networks （ANN） methodology from reported data is 1.1 kg/m^3.

关键词： glycols density polynomial correlation artificial neural networks gas processing

Federated Learning’s Role in Next-Gen TV Ad Optimization

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Computers, Materials & Continua 2025年第1期82卷 675-712页

作者： Gabriela Dobrita Simona-Vasilica Oprea Adela bâra Department of Economic Informatics and Cybernetics Bucharest University of Economic StudiesBucharest010374Romania

In the rapidly evolving landscape of television advertising,optimizing ad schedules to maximize viewer engagement and revenue has become *** methods often operate in silos,limiting the potential insights gained from broader data analysis due to concerns over privacy and data *** article introduces a novel approach that leverages Federated Learning(FL)to enhance TV ad schedule optimization,combining the strengths of local optimization techniques with the power of global Machine Learning(ML)models to uncover actionable insights without compromising data *** combines linear programming for initial ads scheduling optimization with ML—specifically,a K-Nearest Neighbors(KNN)model—for predicting ad spot *** into account the diversity and the difficulty of the ad-scheduling problem,we propose a prescriptivepredictive approach in which first the position of the ads is optimized(using Google’s OR-Tools CP-SAT)and then the scheduled position of all ads will be the result of the optimization ***,this output becomes the target of a predictive task that predicts the position of new entries based on their characteristics ensuring the implementation of the scheduling at large scale(using KNN,Light Gradient boosting Machine and Random Forest).Furthermore,we explore the integration of FL to enhance predictive accuracy and strategic insight across different broadcasting networks while preserving data *** FL approach resulted in 8750 ads being precisely matched to their optimal category placements,showcasing an alignment with the intended diversity ***,there was a minimal deviation observed,with 1133 ads positioned within a one-category variance from their ideal placement in the original dataset.

关键词： Ad scheduling prescriptive-predictive approach federated learning KNN

Modification of Hole Transport Layers for Fabricating High Performance Non-fullerene Polymer Solar Cells

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Chinese Journal of Chemistry 2020年第8期38卷 817-822页

作者： b.hari babu Chengkun Lyu Hongwei Zhang Zhihao Chen Fenghong Li Lin Feng Xiao-Tao Hao School of Physics State Key Laboratory of Crystal MaterialsShandong UniversityJinanShandong 250100China State Key Laboratory of Supramolecular Structure and Materials Institute of Theoretical ChemistryJilin UniversityChangchunJilin 130012China ARC Centre of Excellence in Exciton Science School of ChemistryUniversity of MelbourneParkvilleVictoria 3010Australia

Interfacial engineering is expected to be a feasible strategy to improve the charge transport properties of the hole transport layer(HTL),which is of crucial importance to boost the device performance of organic solar cells(OSCs).In this study,two types of alcohol soluble materials,2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane(F4-TCNQ)and di-tetrabutylammoniumcis-bis(isothiocyanato)bis(2,2'-bipyridyl-4,4'-dicarboxylato)ruthenium(ll)(N719)dye were selected as the dopant for *** doping of F4-TCNQ and N719 dye in poly(ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)with and without integrating a graphene quantum-dots(G-QDs)layer has been explored in poly[[2,6'-4-8-di(5-ethylhexylthienyl)benzo[1,2-b:3,3-b]dithiophene][3-fluoro-2[(2-ethylhexyl)carbonyl]thieno[3,4-b]thio-phenediyl:(2,2'-((2Z,2'Z)-(((4,4,9,9-tetrakis(4-hexylphenyl)-4,9-dihydro-s-indaceno[1,2-b:5,6-b']dithiophene-2,7-diyl)bis(4-((2-ethylhexyl)oxy)thiophene-5,2-diyl))bis(methanylylidene))bis(5,6-difluoro-3-oxo-2,3-dihydro-1H-indene-2,1-diylidene))dimalononitrile(PTb7-Th:IEICO-4F)*** power conversion efficiency of the non-fullerene OSCs has been increased to 10.12%from 8.84%.The influence of HTL modification on the nano-morphological structures and photophysical properties is analyzed based on the comparative studies performed on the control and modified *** use of chemical doping and bilayer strategy optimizes the energy level alignment,nanomorphology,hole mobility,and work-function of HTL,leading to considerable reduction of the leakage current and recombination *** work demonstrates that the doping of HTL and the incorporation of G-QDs layer to constitute a bilayer HTL is an promising strategy to fabricate high performance non-fullerene polymer solar cells.

关键词： doping Solar dye

Deep learning identification of novel autophagic protein-protein interactions and experimental validation of beclin 2-Ubiquilin 1 axis in triple-negative breast cancer

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Oncology research 2025年第1期33卷 67-81页

作者： Xiang Li Wenke Jin Lifeng Wu Huan Wang Xin Xie Wei Huang b O Liu State Key Laboratory of Southwestern Chinese Medicine Resources School of Pharmacy and College of Medical Technology Chengdu University of Traditional Chinese Medicine Chengdu 611137 China. Department of biotherapy Cancer Center and State Key Laboratory of Biotherapy West China Hospital Sichuan University Chengdu 610041 China.

background:Triple-negative breast cancer (TNbC), characterized by its lack of traditional hormone receptors and HER2, presents a significant challenge in oncology due to its poor response to conventional therapies. Autophagy is an important process for maintaining cellular homeostasis, and there are currently autophagy biomarkers that play an effective role in the clinical treatment of tumors. In contrast to targeting protein activity, intervention with protein-protein interaction (PPI) can avoid unrelated crosstalk and regulate the autophagy process with minimal interference pathways.Methods:Here, we employed Naive bayes, Decision Tree, and k-Nearest Neighbors to elucidate the complex PPI network associated with autophagy in TNbC, aiming to uncover novel therapeutic targets. Meanwhile, the candidate proteins interacting with beclin 2 were initially screened in MDA-Mb-231 cells using beclin 2 as bait protein by immunoprecipitation-mass spectrometry assay, and the interaction relationship was verified by molecular docking and CO-IP experiments after intersection. Colony formation, cellular immunofluorescence, cell scratch and 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) tests were used to predict the clinical therapeutic effects of manipulating candidate PPI.Results:by developing three PPI classification models and analyzing over 13,000 datasets, we identified 3733 previously unknown autophagy-related PPIs. Our network analysis revealed the central role of beclin 2 in autophagy regulation, uncovering its interactions with 39 newly identified proteins. Notably, the CO-IP studies identified the substantial interaction between beclin 2 and Ubiquilin 1, which was anticipated by our model and discovered in immunoprecipitation-mass spectrometry assay results. Subsequently, investigations showed that overexpressing beclin 2 increased Ubiquilin 1, promoted autophagy-dependent cell death, and inhibited proliferation and metastasis in MDA-Mb-231 cells.

关键词： Artificial intelligence (AI) Autophagy beclin 2 Protein-protein interactions (PPI) Triple-negative breast cancer (TNbC) Ubiquilin 1