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Green trading and ecological sustainability under macroeconomic policy framework

Geoscience Frontiers 2024年第3期15卷 50-66页

作者： Yue Hu Binhui Li munir ahmad College of Science&Technology Ningbo UniversityNingbo 315300ZhejiangChina Donghai Academy Ningbo UniversityNingbo 315211ZhejiangChina Research Center for County Industry Digitization College of Science&TechnologyNingbo UniversityNingbo 315300ZhejiangChina College of International Economics&Trade Ningbo University of Finance and EconomicsNingbo 315175ZhejiangChina “Belt and Road”Bulk Commodity Research Center Ningbo University of Finance and EconomicsNingbo 315175ZhejiangChina

When confronted with ecological challenges,trading ecologically friendly products involving renewable technologies,green management practices,and effluent treatment methods could alleviate ecological degradation on a global scale while considering the macroeconomic policy ***,this study determines the effectiveness of fiscal and monetary policy instruments in moderating the relationship between green trade openness(i.e.,trade in environmentally related products)and ecological *** panel quantile regression on data from 20 OECD members from 2003 to 2016,we found that green trade openness supports ecological sustainability through a gains-from-trade *** moderation effects,expenditure-driven fiscal expansion reinforces the favorable influence of green trade openness on ecological sustainability across ecologically less/moderately efficient economies,while it does the reverse for ecologically more efficient ***-driven fiscal contraction promotes ecological sustainability amelioration impact of green trade openness for economies with belowaverage ecological quality and remains neutral for those with average/above-average ecological ***,interest rate-driven monetary contraction proliferates the ecological sustainability enhancement effect of green *** suggest that the fiscal and monetary policies demand unambiguous coordination with the OECD’s trade policy structure for optimal environmental outcomes of trading in environmental *** insights would help OECD’s green trade policies gain momentum to facilitate the attainment of the Climate Action agenda of the United Nations’Sustainable Development Goals.

关键词： Fiscal policy Monetary policy Green trade openness Ecological sustainability OECD

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Multifaceted natural resources and green energy transformation for sustainable industrial development

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Geoscience Frontiers 2024年第6期15卷 367-385页

作者： Desire Wade Atchike munir ahmad Qingyu Zhang School of Civil Engineering and Architecture Taizhou UniversityJiaojiangTaizhou 318000ZhejiangChina College of International Economics&Trade Ningbo University of Finance and EconomicsNingbo 315175ZhejiangChina Belt and RoadBulk Commodity Research Center Ningbo University of Finance and EconomicsNingbo 315175ZhejiangChina College of Management Research Institute of Business Analytics and Supply Chain ManagementShenzhen UniversityShenzhen 518060China

Climate change is the most phenomenal challenge to humanity,and its roots are intervened with unsustainable industrialization,exercising overexploitation of natural ***,the departure from non-renewable to renewables has become inevitable,though *** this respect,we explore how green energy transformation moderates the impacts of multifaceted natural resources on sustainable industrial development in the presence of other covariates involving technological progress,financial development,and economic *** compiled data from Group of Seven(G-7)members over the 19952018 period and applied panel quantile regression(PQREG)to capture the effects across varying levels of quantiles of sustainable industrial *** revealed a positive role of natural gas rents,while coal,forest,and total natural resource rents contributed adverse implications for sustainable industrial ***,the green energy transformation proved to be the game changer because it not only directly induced sustainable industrial development improvement but also turned the unfavorable effects of coal,forest,and total natural resources into favorable ones by interacting with those multifaceted natural ***,financial,and economic progress supported sustainable industrial development in G-7 nations,particularly in members with existing middle and upper scales of sustainable industrial *** findings are robust enough when subjected to different estimation *** light of these outcomes,the interaction between green energy transformation and natural resource policy is inevitably critical to attaining natural resource efficiency for sustainable industrial ***,it is imperative to establish a close policy coordination between advancing green energy technology and allocating natural resource revenue to achieve sustainable development goals(SDGs),with a particular emphasis on SDG-7 and SDG-13。

关键词： Multifaceted natural resources Green energy transformation Sustainable industrial development Technological progress G-7 countries

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Gut microbiome therapeutic modulation to alleviate drug-induced hepatic damage in COVID-19 patients

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World Journal of Gastroenterology 2023年第11期29卷 1708-1720页

作者： Khansa Ahsan munir ahmad Anwar Nayla Munawar Department of Chemistry United Arab Emirates UniversityAl Ain 15551United Arab Emirates Industrial Biotechnology Division National Institute for Biotechnology and Genetic Engineering CollegePakistan Institute of Engineering and Applied Sciences(NIBGE-CPIEAS)Faisalabad 38000Pakistan

Coronavirus disease 2019(COVID-19)infection caused by the severe acute respiratory syndrome coronavirus 2 virus,its symptoms,treatment,and post-COVID-19 effects have been a major focus of research since *** addition to respiratory symptoms,different clinical variants of the virus have been associated with dynamic symptoms and multiorgan diseases,including liver *** release of cytokines by the activation of innate immune cells during viral infection and the high doses of drugs used for COVID-19 treatment are considered major drivers of liver injury in COVID-19 *** degree of hepatic inflammation in patients suffering from chronic liver disease and having COVID-19 could be severe and can be estimated through different liver chemistry abnormality *** microbiota influences liver chemistry through its *** dysbiosis during COVID-19 treatment can promote liver ***,we highlighted the bidirectional association of liver physiology and gut microbiota(gut-liver axis)and its potential to manipulate drug-induced chemical abnormalities in the livers of COVID-19 patients.

关键词： COVID-19 Gut-liver axis Probiotics Prebiotics Cytokines Gut microbiome

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Carbon potentials of different biochars derived from municipal solid waste in a saline soil

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Pedosphere 2022年第2期32卷 283-293页

作者： Hamna SALEEM Mahtab ahmad Jamshaid RASHID munir ahmad Mohammad I.AL-WABEL Memuna AMIN Department of Environmental Sciences Faculty of Biological SciencesQuaid-i-Azam UniversityIslamabad 45320Pakistan Soil Sciences Department College of Food&Agricultural SciencesKing Saud UniversityP.O.Box 2460Riyadh 11451Saudi Arabia

There are numerous studies conducted on biochar for its carbon (C) sequestration potential;however,there are limited studies available on the behavior of salt-affected soils related to biochar ***,more studies are needed to elucidate the mechanisms through which biochar affects saline soil *** this study,biochars were produced from solid waste at pyrolysis temperatures of 300,500,and 700?C (BC300,BC500,and BC700,respectively)and applied to a saline soil to evaluate their impacts on soil carbon dioxide (CO_(2)) efflux,C sequestration,and soil quality.A soil incubation experiment lasting for 107 d was *** results showed that soil CO_(2) efflux rate,cumulative CO_(2) emission,active organic C (AOC),and organic matter (OM)significantly increased with BC300 application to a greater extent than those with BC500 and BC700 as compared to those in the no-biochar control (CK).However,soil C non-lability did not significantly increase in the treatments with biochars,except BC700,as compared to that in *** improving the soil quality by increasing the soil AOC and OM,BC300 showed positive impacts in terms of increasing CO_(2) emission from the saline soil,while BC500 and BC700 showed greater potentials of sequestering C in the saline soil by increasing the soil non-labile C *** recalcitrance index (R50) values of BC500 and BC700 were>0.8,indicating their high stability in the saline *** could be concluded that biochars pyrolyzed at high temperatures (?500?C)could be suitable in terms of C sequestration,while biochars pyrolyzed at low temperatures (?300?C) could be suitable for improving saline soil quality.

关键词： carbon sequestration carbon storage climate change CO_(2)efflux CO_(2)emission pyrolysis temperature recalcitrance index soil quality

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Peripheral memory T cells specific for Arginase-1

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Cellular & Molecular Immunology 2019年第8期16卷 718-719页

作者： Evelina Martinenaite Shamaila munir ahmad Inge Marie Svane Mads Hald Andersen Center for Cancer Immune Therapy(CCIT) Copenhagen University HospitalHerlevDenmark Department of Immunology and Microbiology University of CopenhagenCopenhagenDenmark

Increased arginase-1(Arg-1)activity is one of the common mechanisms of immune inhibition in patients with ***-1 is an enzyme catalyzing the first step in L-arginine metabolism and is expressed by various immunosuppressive myeloid cells as well as by cancer ***-1-associated deprivation of L-arginine downregulates the expression of the T cell receptorζchain and decreases cytokine production and proliferation of activated T cells.

关键词： metabolism Arg cytokine

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Cloud-Based Diabetes Decision Support System Using Machine Learning Fusion

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Computers, Materials & Continua 2021年第7期68卷 1341-1357页

作者： Shabib Aftab Saad Alanazi munir ahmad Muhammad Adnan Khan Areej Fatima Nouh Sabri Elmitwally School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science Virtual University of PakistanLahore54000Pakistan College of Computer and Information Sciences Jouf UniversitySakaka72341Saudi Arabia Riphah School of Computing&Innovation Riphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Faculty of Computers and Articial IntelligenceCairo University12613Egypt

Diabetes mellitus,generally known as diabetes,is one of the most common diseases *** is a metabolic disease characterized by insulin deciency,or glucose(blood sugar)levels that exceed 200 mg/dL(11.1 ml/L)for prolonged periods,and may lead to death if left uncontrolled by medication or insulin *** is categorized into two main types—type 1 and type 2—both of which feature glucose levels above“normal,”dened as 140 mg/*** is triggered by malfunction of the pancreas,which releases insulin,a natural hormone responsible for controlling glucose levels in blood *** and comprehensive analysis of this potentially fatal disease necessitate application of techniques with minimal rates of *** primary purpose of this research study is to assess the potential role of machine learning in predicting a person’s risk of developing ***,research has supported the use of various machine algorithms,such as naïve Bayes,decision trees,and articial neural networks,for early diagnosis of ***,to achieve maximum accuracy and minimal error in diagnostic predictions,there remains an immense need for further research and innovation to improve the machine-learning tools and techniques available to healthcare ***,in this paper,we propose a novel cloud-based machine-learning fusion technique involving synthesis of three machine algorithms and use of fuzzy systems for collective generation of highly accurate nal decisions regarding early diagnosis of diabetes.

关键词： Machine learning fusion articial neural network decision trees naïve Bayes diabetes prediction

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Rice Leaves Disease Diagnose Empowered with Transfer Learning

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Computer Systems Science & Engineering 2022年第9期42卷 1001-1014页

作者： Nouh Sabri Elmitwally Maria Tariq Muhammad Adnan Khan munir ahmad Sagheer Abbas Fahad Mazaed Alotaibi College of Computer and Information Sciences Jouf UniversitySakaka72341Saudi Arabia Department of Computer Science Faculty of Computers and Artificial IntelligenceCairo University12613Egypt School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia

In the agricultural industry,rice infections have resulted in significant productivity and economic *** infections must be recognized early on to regulate and mitigate the effects of the *** diagnosis of disease severity effects or incidence can preserve production from quantitative and qualitative losses,reduce pesticide use,and boost ta country’s *** the health of a rice plant through its leaves is usually done as a manual ocular *** this manuscript,three rice plant diseases:Bacterial leaf blight,Brown spot,and Leaf smut,were identified using the Alexnet *** research shows that any reduction in rice plants will have a significant beneficial impact on alleviating global food hunger by increasing supply,lowering prices,and reducing production's environmental impact that affects the economy of any *** would be able to get more exact and faster results with this technology,allowing them to administer the most acceptable treatment *** Using Alex Net,the proposed approach achieved a 99.0%accuracy rate for diagnosing rice leaves disease.

关键词： Rice bacterial leaf blight brown spot leaf smut machine learning alexnet

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Alzheimer Disease Detection Empowered with Transfer Learning

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Computers, Materials & Continua 2022年第3期70卷 5005-5019页

作者： Taher M.Ghazal Sagheer Abbas Sundus munir M.A.Khan munir ahmad Ghassan F.Issa Syeda Binish Zahra Muhammad Adnan Khan Mohammad Kamrul Hasan Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan Malaysia(UKM)43600 BangiSelangorMalaysia School of Information Technology Skyline University CollegeUniversity City Sharjah1797SharjahUAE School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea

Alzheimer’s disease is a severe neuron disease that damages brain cells which leads to permanent loss of memory also called *** people die due to this disease every year because this is not curable but early detection of this disease can help restrain the ***’s ismost common in elderly people in the age bracket of 65 and *** automated system is required for early detection of disease that can detect and classify the disease into multiple Alzheimer *** learning and machine learning techniques are used to solvemanymedical problems like *** proposed system Alzheimer Disease detection utilizes transfer learning on Multi-class classification using brain Medical resonance imagining(MRI)working to classify the images in four stages,Mild demented(MD),Moderate demented(MOD),Non-demented(ND),Very mild demented(VMD).Simulation results have shown that the proposed systemmodel gives 91.70%*** also observed that the proposed system gives more accurate results as compared to previous approaches.

关键词： Convolutional neural network(CNN) alzheimer’s disease(AD) medical resonance imagining mild demented

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Joint Channel and Multi-User Detection Empowered with Machine Learning

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Computers, Materials & Continua 2022年第1期70卷 109-121页

作者： Mohammad Sh.Daoud Areej Fatima Waseem ahmad Khan Muhammad Adnan Khan Sagheer Abbas Baha Ihnaini munir ahmad Muhammad Sheraz Javeid Shabib Aftab College of Engineering Al Ain UniversityAbu Dhabi112612UAE Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of Software EngineeringGachon UniversitySeongnam13557South Korea Department of Computer Science College of Science and TechnologyWenzhou Kean University325060USA Department of Computer Science Hameeda Rasheed Institute of Science and TechnologyMultan66000Pakistan

The numbers of multimedia applications and their users increase with each passing *** multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the future generation of network *** this article,a fuzzy logic empowered adaptive backpropagation neural network(FLeABPNN)algorithm is proposed for joint channel and multi-user detection(CMD).FLeABPNN has two *** first stage estimates the channel parameters,and the second performsmulti-user *** proposed approach capitalizes on a neuro-fuzzy hybrid systemthat combines the competencies of both fuzzy logic and neural *** study analyzes the results of using FLeABPNN based on a multiple-input andmultiple-output(MIMO)receiver with conventional partial oppositemutant particle swarmoptimization(POMPSO),total-OMPSO(TOMPSO),fuzzy logic empowered POMPSO(FL-POMPSO),and FL-TOMPSO-based MIMO *** FLeABPNN-based receiver renders better results than other techniques in terms of minimum mean square error,minimum mean channel error,and bit error rate.

关键词： Channel and multi-user detection minimum mean square error multiple-input and multiple-output minimum mean channel error bit error rate

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Content Based Automated File Organization Using Machine Learning Approaches

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Computers, Materials & Continua 2022年第10期73卷 1927-1942页

作者： Syed Ali Raza Sagheer Abbas Taher M.Ghazal Muhammad Adnan Khan munir ahmad Hussam Al Hamadi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science GC University LahorePakistan Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangiSelangorMalaysia School of Information Technology Skyline University CollegeUniversity City SharjahSharjah1797UAE Riphah School of Computing&Innovation Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan Department of Software Pattern Recognition and Machine Learning LabGachon UniversitySeongnam13120GyeonggidoKorea Cyber-Physical Systems Khalifa UniversityAbu Dhabi127788UAE

In the world of big data,it’s quite a task to organize different files based on their *** with heterogeneous data and keeping a record of every single file stored in any folder is one of the biggest problems encountered by almost every computer *** of file management related tasks will be solved if the files on any operating system are somehow categorized according to their ***,the browsing process can be performed quickly and *** research aims to design a system to automatically organize files based on their similarities in terms of *** proposed methodology is based on a novel strategy that employs the charactaristics of both supervised and unsupervised machine learning approaches for learning categories of digital files stored on any computer *** results demonstrate that the proposed architecture can effectively and efficiently address the file organization challenges using real-world user *** results suggest that the proposed system has great potential to automatically categorize almost all of the user files based on their *** proposed system is completely automated and does not require any human effort in managing the files and the task of file organization become more efficient as the number of files grows.

关键词： File organization natural language processing machine learning

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