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Gut microbiome regulates inflammation and insulin resistance:a novel therapeutic target to improve insulin sensitivity

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Signal Transduction and Targeted Therapy 2024年第3期9卷 825-827页

作者： Dilvin Semo Holger Reinecke Rinesh godfrey Vascular Signalling Molecular CardiologyDepartment of Cardiology I-Coronary and Peripheral Vascular DiseaseHeart FailureUniversity Hospital Münster48149 MünsterGermany

In a recent study published in Nature,Takeuchi et al.used a multiomics strategy in humans to provide compelling evidence that increased carbohydrate metabolism by the gut microbiota contributes to insulin resistance(IR).The authors uncovered a previously unknown link between elevated gut monosaccharides and host inflammatory cytokines and suggest potential intervention opportunities to combat IR by targeting specific gut microbial species.

关键词： metabolism inflammation al.

On the Road To Development

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ChinAfrica 2024年第6期16卷 42-43页

作者： godfrey OLUKYA 不详

Uganda’s President Yoweri Museveni has lamented that his country’s bad roads get easily damaged by heavy rains,while also expressing his confidence in the new roads recently built by Chinese construction companies.

关键词： companies expressing Road

Seeking More Influence In Global Affairs

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ChinAfrica 2024年第3期16卷 40-41页

作者： godfrey OLUKYA 不详

Uganda hosts NAM and G77+China summits with calls to push back against unilateralism.Uganda played host to two important summits in January.The 19th Summit of Heads of State and Government of the Non-Aligned Movement(NAM)on 19 January,and the Third South Summit of the G77+China on 21 January,both took place in the nation’s capital of Kampala.Importantly,it was the first time for the South Summit to be held in Africa.China was well represented at both summits,which attracted over 2,000 leaders and delegates,including over 20 heads of states.

关键词： push Africa G77

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Powering Up

ChinAfrica 2024年第7期16卷 38-39页

作者： godfrey OLUKYA 不详

Uganda launches giant China-constructed hydropower plant to bolster its electricity supply,and also assist South Sudan with theirs Ugandans and South Sudanese have had their lives lit up by the steady flow of electric... 详细信息

关键词： massive electricity Power

Taguchi Full Factorial Design of Experiments Optimisation of Cutting Parameters for Energy Efficiency and Surface Roughness during the Dry Turning of EN19 Material

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World Journal of Engineering and Technology 2024年第2期12卷 438-454页

作者： Nicholas Tayisepi Albert Nkulumo Mnkandla godfrey Tigere Oscar Gwatidzo Winnie Mutenhabundo Emmanuel Ndala Lovelace Makakatanwa Wagoneka Department of Industrial and Manufacturing Engineering National University of Science and Technology Bulawayo Zimbabwe Department of Industrial and Manufacturing Engineering Harare Institute of Technology Harare Zimbabwe

During metal machining, the satisfactoriness of cost-quality-time matrix convergence effectively depends on the supreme selection of cutting parameters. This study investigated the energy use minimisation and quality surface generation through optimised cutting parameters application, as sustainability enhancement during dry turning of EN19 material. Cutting parameter optimisation is a serious challenge confronting the machining industry as they strive to achieve low energy use and better component quality generation from their operations. The utility material, EN19, is a medium-carbon low alloy steel which typically gets applied in the manufacturing of multiple profiled cylindrical machine tool, rail locomotives and motor vehicle component parts, inter alia. Taguchi Full Factorial experimental plan was used to organise the empirical experiments. ANOVA and the main effects plot signal-to-noise ratio optimisation analysis were utilised in the study to establish the influence of process parameters on the response parameters—surface roughness and energy use. The aim was to investigate and determine the correlation of the machining strategy parameters with the outcome of low energy use and quality surface texture of the components as the cutting parameters were varied, and optimised for minimum surface roughness and energy use. Results of the extensive experimental study, produced optimum cutting speed, rake angle variation and feed rate which respectively influence the response parameters positively for energy use minimisation and improved surface quality. Validation experiments confirmed model findings.

关键词： Machining Energy Use ANOVA Sustainable Manufacturing Machining Strategy

Exceptionally high strain hardening via two-dimensional atomic scale faulting

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Science China Materials 2023年第12期66卷 4897-4898页

作者： Andrew godfrey Xiaoxu Huang Laboratory of Advanced Materials School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China International Joint Laboratory for Light Alloys College of Materials Science and EngineeringChongqing UniversityChongqing 400044China

Strain hardening is a characteristic and important property of metals whereby they are strengthened by the introduction of lattice defects during plastic deformation.In general,a high strain hardening ability is desired,both to ensure the safety of metal components under load and to enable high ductility,allowing the formation of complex shapes.The underlying mechanisms of strain hardening have been extensively studied and are related to an increase in the density of linear lattice defects,i.e.,dislocations,and to the interaction between these defects during the evolution of three-dimensional dislocation structures[1±3].Coarse-grained(CG)metals generally show the highest strain hardening and the best tensile ductility due to the more abundant space for storage of dislocations in various forms of patterning.

关键词： strain ductility dimensional

Logistic Regression Trust–A Trust Model for Internet-of-Things Using Regression Analysis

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Computer Systems Science & Engineering 2023年第2期44卷 1125-1142页

作者： Feslin Anish Mon Solomon godfrey Winster Sathianesan R.Ramesh Department of CSE Saveetha Engineering CollegeChennaiIndia Department of CSE SRM Institute of Science and TechnologyChennaiIndia Department of ECE Saveetha Engineering CollegeChennaiIndia

Internet of Things(IoT)is a popular social network in which devices are virtually connected for communicating and sharing information.This is applied greatly in business enterprises and government sectors for delivering the services to their customers,clients and citizens.But,the interaction is success-ful only based on the trust that each device has on another.Thus trust is very much essential for a social network.As Internet of Things have access over sen-sitive information,it urges to many threats that lead data management to risk.This issue is addressed by trust management that help to take decision about trust-worthiness of requestor and provider before communication and sharing.Several trust-based systems are existing for different domain using Dynamic weight meth-od,Fuzzy classiﬁcation,Bayes inference and very few Regression analysis for IoT.The proposed algorithm is based on Logistic Regression,which provide strong statistical background to trust prediction.To make our stand strong on regression support to trust,we have compared the performance with equivalent sound Bayes analysis using Beta distribution.The performance is studied in simu-lated IoT setup with Quality of Service(QoS)and Social parameters for the nodes.The proposed model performs better in terms of various metrics.An IoT connects heterogeneous devices such as tags and sensor devices for sharing of information and avail different application services.The most salient features of IoT system is to design it with scalability,extendibility,compatibility and resiliency against attack.The existing worksﬁnds a way to integrate direct and indirect trust to con-verge quickly and estimate the bias due to attacks in addition to the above features.

关键词： LRTrust logistic regression trust management internet of things

User Centric Block-Level Attribute Based Encryption in Cloud Using Blockchains

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Computer Systems Science & Engineering 2022年第8期42卷 605-618页

作者： S.godfrey Winster A.Siva Kumar R.Ramesh Department of Computer Science and Engineering School of ComputingCollege of Engineering and TechnologySRM Institute of Science and TechnologyChengalpattu603203India Department of Information Technology Sri Sai Ram Engineering CollegeChennai600044India Department of Electronics and Communication Engineering Saveetha Engineering CollegeChennai602105India

Cloud computing is a collection of distributed storage Network which can provide various services and store the data in the efficient manner.The advantages of cloud computing is its remote access where data can accessed in real time using Remote Method Innovation(RMI).The problem of data security in cloud environment is a major concern since the data can be accessed by any time by any user.Due to the lack of providing the efficient security the cloud computing they fail to achieve higher performance in providing the efficient service.To improve the performance in data security,the block chains are used for securing the data in the cloud environment.However,the traditional block chain technique are not suitable to provide efficient security to the cloud data stored in the cloud.In this paper,an efficient user centric block level Attribute Based Encryption(UCBL-ABE)scheme is presented to provide the efficient security of cloud data in cloud environment.The proposed approach performs data transaction by employing the block chain.The proposed system provides efficient privacy with access control to the user access according to the behavior of cloud user using Data Level Access Trust(DLAT).Based on DLAT,the user access has been restricted in the cloud environment.The proposed protocol is implemented in real time using Java programming language and uses IBM cloud.The implementation results justifies that the proposed system can able to provide efficient security to the data present in and cloud and also enhances the cloud performance.

关键词： Cloud blockchain data security ABE block-level

Integrated Approach to Detect Cyberbullying Text:Mobile Device Forensics Data

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Computer Systems Science & Engineering 2022年第3期40卷 963-978页

作者： G.Maria Jones S.godfrey Winster P.Valarmathie Department of Computer Science and Engineering Saveetha Engineering CollegeChennai602105India Department of Computer Science and Engineering School of ComputingSRM Institute of Science and TechnologyChengalpattu603203India Department of Information Technology Saveetha Engineering CollegeChennai602105India

Mobile devices and social networks provide communication opportunities among the young generation,which increases vulnerability and cybercrimes activities.A recent survey reports that cyberbullying and cyberstalking constitute a developing issue among youngsters.This paper focuses on cyberbullying detection in mobile phone text by retrieving with the help of an oxygen forensics toolkit.We describe the data collection using forensics technique and a corpus of suspicious activities like cyberbullying annotation from mobile phones and carry out a sequence of binary classification experiments to determine cyberbullying detection.We use forensics techniques,Machine Learning(ML),and Deep Learning(DL)algorithms to exploit suspicious patterns to help the forensics investigation where every evidence contributes to the case.Experiments on a real-time dataset reveal better results for the detection of cyberbullying content.The Random Forest in ML approach produces 87%of accuracy without SMOTE technique,whereas the value of F1Score produces a good result with SMOTE technique.The LSTM has 92%of validation accuracy in the DL algorithm compared with Dense and BiLSTM algorithms.

关键词： Mobile forensics cyberbullying machine learning investigation model suspicious pattern