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suppression of host plant defense by bacterial small RNAs packaged in outer membrane vesicles

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Plant Communications 2024年第4期5卷 252-254页

作者： Yan Wu sai Wang Peihong Wang Wenhan Nie Iftikhar ahmad Panagiotis f.sarris Gongyou Chen Bo Zhu shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research station Shanghai Cooperative Innovation Center for Modern Seed Industry School of Agriculture and Biology Shanghai Jiao Tong University Shanghai China Department of Environmental sciences COMSATS University Islamabad Vehari-Campus Vehari 61100 Pakistan Department of Biology University of Crete 714 09 Heraklion Crete Greece shanghai Jiao Tong University Chongqing Research Institute Shanghai China

(Plant Communications 5,100817;April 82024)After a careful,in-depth examination,the authors found some additional errors in the published *** revision,the authors created a mutant DXosr001(in which the full-length Xosr001 was deleted)and a mutant DXosr001’(in which the predicted binding motif of Xosr001 was deleted)as shown in figure s4 of the original *** RNA-fIsH assays,Xosr001 transcript could not be detected in leaves inoculated with DXosr001-OMVs,while leaves inoculated with WT-and DXosr001’-OMVs could emit green fluorescence.

关键词： deleted figure outer

AMAD:Adaptive Mapping Approach for Datacenter Networks,an Energy-friend Resource Allocation framework via Repeated Leader follower Game

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Computers, Materials & Continua 2024年第9期80卷 4577-4601页

作者： ahmad Nahar Quttoum Muteb Alshammari Department of Computer Engineering Faculty of EngineeringThe Hashemite UniversityZarqa13133Jordan Department of Information Technology Faculty of Computing and Information TechnologyNorthern Border UniversityArar91431Saudi Arabia

Cloud Datacenter Network(CDN)providers usually have the option to scale their network structures to allow for far more resource capacities,though such scaling options may come with exponential costs that contradict their utility ***,besides the cost of the physical assets and network resources,such scaling may also imposemore loads on the electricity power grids to feed the added nodes with the required energy to run and cool,which comes with extra costs ***,those CDNproviders who utilize their resources better can certainly afford their services at lower price-units when compared to others who simply choose the scaling *** utilization is a quite challenging process;indeed,clients of CDNs usually tend to exaggerate their true resource requirements when they lease their *** providers are committed to their clients with service Level Agreements(sLAs).Therefore,any amendment to the resource allocations needs to be approved by the clients *** this work,we propose deploying a stackelberg leadership framework to formulate a negotiation game between the cloud service providers and their client *** this,the providers seek to retrieve those leased unused resources from their *** is not expected from the clients,and they may ask high price units to return their extra resources to the provider’s ***,to motivate cooperation in such a non-cooperative game,as an extension to theVickery auctions,we developed an incentive-compatible pricingmodel for the returned ***,we also proposed building a behavior belief function that shapes the way of negotiation and compensation for each *** to other benchmark models,the assessment results showthat our proposed models provide for timely negotiation schemes,allowing for better resource utilization rates,higher utilities,and grid-friend CDNs.

关键词： Data center networks energy-aware resource management resource utilization game-theory mechanisms

A convolutional neural network to detect possible hidden data in spatial domain images

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Cybersecurity 2024年第1期7卷 37-52页

作者： Jean De La Croix Ntivuguruzwa Tohari ahmad Department of Informatics Institut Teknologi Sepuluh Nopember(ITS)Kampus ITS Keputih SukoliloSurabaya60111Indonesia African Center of Excellence in the Internet of Things College of Science and TechnologyUniversity of Rwanda3900KigaliRwanda

Hiding secret data in digital multimedia has been essential to protect the ***,attackers with a steganalysis technique may break *** steganalysis methods have good results with conventional Machine Learning(ML)techniques;however,the introduction of Convolutional Neural Network(CNN),a deep learning paradigm,achieved better performance over the previously proposed ML-based *** the existing CNN-based approaches yield good results,they present performance issues in classification accuracy and stability in the network training *** research proposes a new method with a CNN architecture to improve the hidden data detection accuracy and the training phase stability in spatial domain *** proposed method comprises three phases:pre-processing,feature extraction,and ***,in the pre-processing phase,we use spatial rich model filters to enhance the noise within images altered by data hiding;secondly,in the feature extraction phase,we use two-dimensional depthwise separable convolutions to improve the signal-to-noise and regular convolutions to model local features;and finally,in the classification,we use multi-scale average pooling for local features aggregation and representability enhancement regardless of the input size variation,followed by three fully connected layers to form the final feature maps that we transform into class probabilities using the softmax *** results identify an improvement in the accuracy of the considered recent scheme ranging between 4.6 and 10.2%with reduced training time up to 30.81%.

关键词： Information security spatial domain steganalysis Deep learning Convolutional neural network Infrastructure

Novel framework for an Intrusion Detection system Using Multiple feature selection Methods Based on Deep Learning

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Tsinghua science and Technology 2024年第4期29卷 948-958页

作者： A.E.M.Eljialy Mohammed Yousuf Uddin sultan ahmad Department of Information systems College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabiaand also with University Center for Research and Development(UCRD)Department of Computer Science and EngineeringChandigarh UniversityPunjabIndia

Intrusion detection systems (IDss) are deployed to detect anomalies in real time. They classify a network’s incoming traffic as benign or anomalous (attack). An efficient and robust IDs in software-defined networks is an inevitable component of network security. The main challenges of such an IDs are achieving zero or extremely low false positive rates and high detection rates. Internet of Things (IoT) networks run by using devices with minimal resources. This situation makes deploying traditional IDss in IoT networks unfeasible. Machine learning (ML) techniques are extensively applied to build robust IDss. Many researchers have utilized different ML methods and techniques to address the above challenges. The development of an efficient IDs starts with a good feature selection process to avoid overfitting the ML model. This work proposes a multiple feature selection process followed by classification. In this study, the software-defined networking (sDN) dataset is used to train and test the proposed model. This model applies multiple feature selection techniques to select high-scoring features from a set of features. Highly relevant features for anomaly detection are selected on the basis of their scores to generate the candidate dataset. Multiple classification algorithms are applied to the candidate dataset to build models. The proposed model exhibits considerable improvement in the detection of attacks with high accuracy and low false positive rates, even with a few features selected.

关键词： random forest feature selection decision tree software-defined network logistic regression intrusion detection system XGB classifier AdaBoost

Assessing Multidimensional Vulnerability of Rural Areas to flooding:An Index‑Based Approach

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International Journal of Disaster Risk science 2024年第1期15卷 88-106页

作者： samavia Rasool Irfan ahmad Rana Hassam Bin Waseem Department of Urban and Regional Planning School of Civil and Environmental Engineering(SCEE)National University of Sciences and Technology(NUST)Islamabad 44000Pakistan

Vulnerability assessment is essential for understanding and launching effective flood risk reduction *** study aimed to examine the vulnerability of flood-prone rural communities in southern Punjab,Pakistan to external *** concept of vulnerability encompasses a range of dimensions,including physical,social,institutional,environmental,economic,and *** a composite index method,indices were developed for each dimension and combined to create a multidimensional measure of vulnerability.A sample of 365 communities was selected using the Yamane sampling technique,and data were collected through a questionnaire containing 65 indicators across all *** statistics and ANOVA tests were used to analyze the *** results show that communities near the Chenab River had higher attitudinal and institutional vulnerability compared to other *** attitudinal vulnerabilities were as sociated with poorly perceived flood risks and low preparedness measures,whereas institutional vulnerabilities were driven by conventional flood protection strategies,lack of institutional trust,and lack of flood risk *** research provides insights into the various components of vulnerability in flood-prone rural communities in Pakistan and demonstrates a useful methodology that can be applied to other disasters at different spatial scales.

关键词： Chenab River flood hazard Indus River Pakistan-Rural areas:Vulnerability to flooding

(sm/Eu/Tm)^(3+) doped tantalum semiconductor system for photovoltaic and electrochemical functionality amplification

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Journal of Rare Earths 2024年第8期42卷 1586-1594,I0007页

作者： shaan Bibi Jaffri Khuram shahzad ahmad Isaac Abrahams Ibrahim A.A Materials and Environmental Chemistry Lab Lab-E21Department of Environmental SciencesFatima Jinnah Women UniversityRawalpindiPakistan school of Physical and Chemical sciences Queen Mary University of LondonLondonUnited Kingdom Department of Botany and Microbiology College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

This work reports the synthesis,characterization,and energy focused applications of the novel lanthanides co-doped tantalum pentoxide hetero-system(sm^(3+)-Eu^(3+)-Tm^(3+):Ta_(2)O_(5)).Ln^(3+)-doped Ta_(2)O_(5) express excellent opto-electronic features reflected by the narrow band gap energy of 3.87 *** vibrations confirm the presence of Ta-O-Ta and Ta-O *** synthesized system possesses orthorhombic geometry with 59.46 nm particle *** the smoother and compact morphology,the synthesized material succeeds in augmenting the performance of different systems aimed at energy *** ambient perovskite solar cell device fabricated with the Ln^(3+)-doped Ta_(2)O_(5) as an electron transport layer excels in achieving an efficiency and fill factor of 14.17% and 76% under artificial *** device was marked by the negligible hysteresis behavior showing profound photovoltaic *** electrochemical activity of the Ln^(3+)-doped Ta_(2)O_(5) decorated electrode was evaluated for electrical charge storage potential with pseudocapacitive behavior,With the highest specific capacitance of 355.39 f/g and quicker ionic diffusion rate,the designed electrode excels conventionally used ***-catalysis of water with Ln^(3+)-doped Ta_(2)O_(5) material indicates its capacity for H_(2) production with the lowest overpotential and Tafel slope values of 148 and 121.2 mV/dec,while the O_(2) generation is comparatively *** the stable electrochemical output,this rare earth modified material has the potential to replace conventionally used environmentally perilous and costly materials.

关键词： Lanthanide doping Rare earth materials Perovskite solar cells supercapacitors Water splitting

An Improved Lung Cancer segmentation Based on Nature-Inspired Optimization Approaches

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Computer Modeling in Engineering & sciences 2024年第2期138卷 1051-1075页

作者： shazia shamas surya Narayan Panda Ishu sharma Kalpna Guleria Aman singh ahmad Ali AlZubi Mallak ahmad AlZubi Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpuraPunjab140401India Higher Polytechnic school Universidad Europea del AtlánticoC/Isabel Torres 21Santander39011Spain Department of Engineering Universidad Internacional IberoamericanaAreciboPR00613USA Uttaranchal Institute of Technology Uttaranchal UniversityDehradunUttarakhand248007India Computer science Department King Saud UniversityRiyadhSaudi Arabia faculty of Medicine Jordan University of Science and TechnologyIrbidJordan

The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis andplanning intervention. This research work addresses the major issues pertaining to the field of medical imageprocessing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposesan improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. Thebetter resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In thisprocess, the visual challenges of the K-means are addressed with the integration of four nature-inspired swarmintelligent techniques. The techniques experimented in this paper are K-means with Artificial Bee Colony (ABC),K-means with Cuckoo search Algorithm (CsA), K-means with Particle swarm Optimization (PsO), and Kmeanswith firefly Algorithm (ffA). The testing and evaluation are performed on Early Lung Cancer ActionProgram (ELCAP) database. The simulation analysis is performed using lung cancer images set against metrics:precision, sensitivity, specificity, f-measure, accuracy,Matthews Correlation Coefficient (MCC), Jaccard, and *** detailed evaluation shows that the K-means with Cuckoo search Algorithm (CsA) significantly improved thequality of lung cancer segmentation in comparison to the other optimization approaches utilized for lung cancerimages. The results exhibit that the proposed approach (K-means with CsA) achieves precision, sensitivity, and fmeasureof 0.942, 0.964, and 0.953, respectively, and an average accuracy of 93%. The experimental results prove thatK-meanswithABC,K-meanswith PsO,K-meanswith ffA, andK-meanswithCsAhave achieved an improvementof 10.8%, 13.38%, 13.93%, and 15.7%, respectively, for accuracy measure in comparison to K-means segmentationfor lung cancer images. further, it is highlighted that the proposed K-means with CsA have achieved a significantimprovement in accuracy, hence can be utilized by resea

关键词： Lesion lung cancer segmentation medical imaging meta-heuristic Artificial Bee Colony(ABC) Cuckoo search Algorithm(CsA) Particle swarm Optimization(PsO) firefly Algorithm(ffA) segmentation

Artificial Intelligence Based Meteorological Parameter forecasting for Optimizing Response of Nuclear Emergency Decision support system

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原子能科学技术 2024年第10期58卷 2068-2076页

作者： BILAL Ahmed Khan HAsEEB ur Rehman QAIsAR Nadeem MUHAMMAD ahmad Naveed Qureshi JAWARIA Ahad MUHAMMAD Naveed Akhtar AMJAD farooq MAsROOR ahmad Pakistan Institute of Engineering and Applied sciences Islamabad 44000Pakistan

This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRf) *** meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support *** of meteorological conditions during nuclear emergencies using the conventional WRf model is very complex and ***,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological *** evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-south *** performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological *** show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single ***,accuracy is slightly compromised when predicting wind speed *** mean square error (RMsE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of *** conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.

关键词： prediction of meteorological parameters weather research and forecasting model artificial neural networks nuclear emergency support system

Elevating haptic interfaces:Dual-rate sampling and field programmable gate array implementation for multi-degree-of-freedom performance enhancement

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International Journal of Mechanical system Dynamics 2024年第2期4卷 171-187页

作者： Majid Koul suhail Khosa Babar ahmad Mechanical Engineering Islamic University of Science and TechnologyKashmirJammu and KashmirIndia Mechanical Engineering National Institute of Technology SrinagarJammu and KashmirIndia

In this work,our primary focus centered on exploring the adaptability of the dualrate sampling scheme proposed earlier to enhance the performance of multi-degreeof-freedom(multi-DOf)impedance-based haptic *** scheme employed independent sampling rates in a haptics controller,effectively mitigating the issue of reduced Z-width at higher sampling rates.A key aspect of our investigation was the intricate implementation of the dual-rate sampling scheme on a field programmable gate array(fPGA).This implementation on a logic hardware fPGA was challenging and led to the effective comparison of the uniform-rate and dual-rate sampling schemes of the multi-DOf haptic *** used an in-house developed two-DOf pantograph as the haptic interface and an fPGA for implementing the controller ***-based implementation presented challenges that were vital in testing controller performances at higher sampling *** wall experiments were conducted to determine the stable and unstable interactions with the virtual *** complement the experimental results,we simulated the haptics force law for multi-DOf system on simulink/***,the dual-rate sampling approach maintained the Z-width of the two-DOf haptic interface,even at higher controller sampling rates,distinguishing it from the conventional two-DOf uniform-rate control *** example,employing a dual-rate sampling combination of 20–2 kHz consistently ensured the stable rendering of a maximum virtual stiffness of approximately 700 N/mm and maintained a reliable virtual damping range spanning from 0 to 5 Ns/*** contrast,the 20 kHz uniform-rate sampling approach failed to ensure interface stability in the presence of virtual damping,ultimately resulting in the unsuccessful implementation of any virtual stiffness at higher sampling *** work,therefore,establishes the potential of dual-rate sampling in the realm of haptic technology,with practical applications in multi-DOf systems.

关键词： control fPGA haptic device simulation virtual reality Z-width