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Competitive interactions between invasive fall armyworm and Asian corn borer at intraspecific and interspecific level on the same feeding guild

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Insect Science 2024年第4期31卷 1313-1325页

作者： Jingfei Guo Jianqin Shi Hailiang Han Ivan Rwomushana abid ali Yeeyee Myint Zhenying Wang State Key Laboratory for Biology of Plant Diseases and Insect Pests Institute of Plant ProtectionChinese Academy of Agricultural SciencesBeijingChina Zhejiang Dongyang Maize Research Institute DongyangZhejiangChina CAB International(CABI) NairobiKenya Department of Entomology University of AgricultureFaisalabadPunjabPakistan Plant Protection Division Department of AgricultureMinistry of AgricultureLivestock and IrrigationYangonMyanmar

Interspecific competition is an important factor in the population dynamics and geographical distribution of insect *** armyworm(FAW),Spodoptera frugiperda,an invasive species,and the Asian corn borer(ACB),Ostrinia furnacalis,a native pest species are major pests on maize in China,posing a threat to maize yield and grain quality.A series of laboratory,greenhouse,and field experiments were conducted to elucidate the competitive interactions between FAW and *** the laboratory experiments,FAW exhibited aggressive behaviors more frequently when compared with ACB,while the latter species exhibited defense behaviors more *** intraspecific competition was recorded in the FAW conspecific rather than in ACB,particularly in the 6th larval *** had a higher interspecific competitive advantage through intraguild predation over ACB,resulting in partial or complete displacement ACB when initially the ratio of the 2 species was 1:*** interspecific competition also had significantly influenced on the population parameters,defensive enzymes,and nutrient of these 2 *** interaction proved that the response of superoxide,catalase,and soluble protein in FAW were significantly increased,whereas the total sugar content in both species was substantially *** rate,and the plant damage that co-infested by both species varied significantly among the sequential combinations under greenhouse and field *** consistently exhibited stronger intraspecific aggression than ACB under laboratory and field conditions when co-existing on the same feeding *** findings contribute to efforts toward the improvement of integrated pest management programs for FAW,in decision making for invasive and native pests’management strategies to reduce the high risks of FAW and ACB outbreaks.

关键词： Asian corn borer defensive enzyme fall armyworm interspecific competition intraspecific competition survival rate

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Deep learning-based radiomics allows for a more accurate assessment of sarcopenia as a prognostic factor in hepatocellular carcinoma

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2024年第1期25卷 83-90页

作者： Zhikun LIU Yichao WU abid ali KHAN Lun LU Jianguo WANG Jun CHEN Ningyang JIA Shusen ZHENG Xiao XU Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province Department of Hepatobiliary and Pancreatic SurgeryAffiliated Hangzhou First People’s HospitalZhejiang University School of MedicineHangzhou310006China Zhejiang University School of Medicine Hangzhou310058China Department of Radiology Easter Hepatobiliary Surgery HospitalNaval Medical UniversityShanghai200438China Department of Hepatobiliary and Pancreatic Surgery the First Affiliated HospitalZhejiang University School of MedicineHangzhou310003China NHC Key Laboratory of Combined Multi-organ Transplantation Hangzhou310003China Department of Hepatobiliary and Pancreatic Surgery Shulan(Hangzhou)HospitalHangzhou310022China

Hepatocellular carcinoma(HCC)is one of the most common malignancies and is a major cause of cancer-related mortalities worldwide(Forner et al.,2018;He et al.,2023).Sarcopenia is a syndrome characterized by an accelerated loss of skeletal muscle(SM)mass that may be age-related or the result of malnutrition in cancer patients(Cruz-Jentoft and Sayer,2019).Preoperative sarcopenia in HCC patients treated with hepatectomy or liver transplantation is an independent risk factor for poor survival(Voron et al.,2015;van Vugt et al.,2016).

关键词： cancer patients

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基于影像组学的深度学习评估肌少症对肝癌切除和移植患者预后的影响（中文）

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2024年第1期 83-95页

作者：刘治坤吴逸超 abid ali KHAN 陆伦王建国陈峻贾宁阳郑树森徐骁浙江省肿瘤融合与智能医学实验室浙江大学医学院附属杭州市第一人民医院肝胆胰外科国家卫健委多器官联合移植重点实验室浙江大学医学院海军医科大学东方肝胆外科医院放射科浙江大学医学院附属第一附属医院肝胆胰外科树兰(杭州)医院肝胆胰外科

肌少症是指因持续骨骼肌含量流失、强度和功能下降引起的综合征，且与包括肝细胞癌（HCC）在内的肿瘤患者预后密切相关。目前该病的检测手段局限且无统一标准。本文旨在利用基于影像组学的深度学习（DL）技术评估肌少症，用于肝癌患者... 详细信息

肌少症是指因持续骨骼肌含量流失、强度和功能下降引起的综合征，且与包括肝细胞癌（HCC）在内的肿瘤患者预后密切相关。目前该病的检测手段局限且无统一标准。本文旨在利用基于影像组学的深度学习（DL）技术评估肌少症，用于肝癌患者行肝脏部分切除术或肝移植术的预后预测。本研究回顾性纳入浙大一院肝癌手术切除492例（训练集+内部验证集）与肝癌肝移植173例患者（外部LT验证集），东方肝胆医院肝癌切除患者161例（外部验证集），并收集患者术前一个月内的腹部计算机断层扫描（CT）平扫期影像与临床资料；单中心肝切除术组入组患者按7:3随机分为训练集和内部验证集（训练集345例，验证集147例），肝移植组及第二中心肝癌切除组作为外部验证集，经训练集建立预测模型，并利用内部和外部验证集验证预测模型的预测性能；对训练集患者CT图像中第3腰椎骨（L3）层面的骨骼肌（SM）及腰大肌（PM）轮廓进行人工勾画；抽提SM与PM影像组学特征，随后利用自编码器（Auto Encoder）压缩特征，TFDeep Surv生存分析网络构建DL预后预测模型，预测HCC术后无瘤生存率（RFS）与总体生存时间（OS）；最后计算时间依赖性受试者工作特征曲线（ROC）的曲线下面积（AUC）和一致性指数（Cindex），采用应用净重新分类改善指数（NRI）和临床决策曲线（DCA）评价模型预测性能。最终从勾画的CT图像L3层面的SM及PM中采集相应肌肉中1343个影像组学特征。经Auto Encoder将此高阶影像组学特征降维至100个特征。运用TFDeep Surv生存分析网络完成DL预测模型的构建，将HCC患者根据预后的差异分为高危组和低危组，高危组HCC患者行肝部分切除手术后预后显著低于低危组患者。此外，通过Kaplan-Meier生存曲线分析等方法证实DL模型在内部及外部验证集、外部LT验证集中均可对肝癌患者术后的预后进行准确预测，一致性指数分别达0.775和0.613。NRI和DCA同样显示DL模型具有较高的预测性能。本研究创新性地提出了基于影像组学的DL技术构建的预后预测模型；该模型可在术前对肝癌手术切除和肝移植术后的生存风险进行个体化预测，从而实现对肝癌患者OS的早期预判，有助于制定合理的临床决策和指导临床实践。

关键词：影像组学深度学习肌少症肝细胞肝癌肝部分切除术肝移植

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A Novel Lightweight Image Encryption Scheme

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Computers, Materials & Continua 2023年第4期75卷 2137-2153页

作者： Rawia Abdulla Mohammed Maisa’a abid ali Khodher Ashwak Alabaichi Department of Computer Science University of TechnologyBaghdadIraq Department of Biomedical Engineering University of KerbalaKerbalaIraq

Encryption algorithms are one of the methods to protect dataduring its transmission through an unsafe transmission medium. But encryptionmethods need a lot of time during encryption and decryption, so itis necessary to find encryption algorithms that consume little time whilepreserving the security of the data. In this paper, more than one algorithmwas combined to obtain high security with a short implementation time. Achaotic system, DNA computing, and Salsa20 were combined. A proposed5D chaos system was used to generate more robust keys in a Salsa algorithmand DNA computing. Also, the confusion is performed using a new *** proposed chaos system achieves three positive Lyapunov *** results demonstrate of the proposed scheme has a sufficient peak signalto-noise ratio, a low correlation, and a large key space. These factors makeit more efficient than its classical counterpart and can resist statistical anddifferential attacks. The number of changing pixel rates (NPCR) and theunified averaged changed intensity (UACI) values were 0.99710 and UACI33.68. The entropy oscillates from 7.9965 to 7.9982 for the tested encryptedimages. The suggested approach is resistant to heavy attacks and takes lesstime to execute than previously discussed methods, making it an efficient,lightweight image encryption scheme. The method provides lower correlationcoefficients than other methods, another indicator of an efficient imageencryption system. Even though the proposed scheme has useful applicationsin image transmission, it still requires profound improvement in implementingthe high-intelligence scheme and verifying its feasibility on devices with theInternet of Things (IoT) enabled.

关键词： Chaotic system lightweight confusion diffusion encryption Salsa20

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Intelligent Transmission Control for Efficient Operations in SDN

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Computers, Materials & Continua 2022年第5期71卷 2807-2825页

作者： Reem Alkanhel abid ali Faisal Jamil Muzammil Nawaz Faisal Mehmood Ammar Muthanna Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Computer Science University of Engineering and TechnologyTaxila47080Pakistan Department of Computer Science Govt.Akhtar Nawaz Khan(Shaheed)Degree College KTSHaripur22620Pakistan Department of Computer Engineering Jeju National UniversityJeju-siJeju Special Self-Governing Province63243Korea School of Information and Communication Engineering Zhengzhou UniversityChina Department of Telecommunication Networks and Data Transmission The Bonch-Bruevich Saint-Petersburg State University of Telecommunications193232Saint PetersburgRussia Peoples Friendship University of Russia(RUDN University)6 Miklukho-Maklaya St Moscow117198Russian Federation

Although the Software-Defined Network(SDN)is a well-controlled and efficient network but the complexity of open flow switches in SDN causes multiple *** solutions have been proposed so far for the prevention of errors and mistakes in it but yet,there is still no smooth transmission of pockets from source to destination specifically when irregular movements follow the destination host in SDN,the errors include packet loss,data compromise *** accuracy of packets received at their desired destination is possible if networks for pockets and hosts are monitored instead of analysis of network snapshot statistically for the state,as these approaches with open flow switches,discover bugs after their *** article proposes a design to achieve the said objective by defining the Intelligent Transmission Control Layer(ITCL)*** monitors all the connections of end hosts at their specific locations and performs necessary settlements when the connection state changes for one or multiple *** layer informs the controller regarding any state change at one period and controller collects information of end nodes reported via ***,updates flow tables accordingly to accommodate a location-change scenario with a routechange *** is organized on prototype-based implementation using the popular POX *** this paper,it has been discovered that ITCL produces efficient performance in the trafficking of packets and controlling different states of SDN for errors and packet loss.

关键词： Software-defined network ITCL POX open flow

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DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants

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Molecular Plant 2023年第1期16卷 279-293页

作者： Kelin Wang Muhammad ali abid Awais Rasheed Jose Crossa Sarah Hearne Huihui Li Institute of Crop Sciences Chinese Academy of Agricultural Sciences(CAAS)CIMMYT-China Office12 Zhongguancun South StreetBeijing 100081China Nanfan Research Institute CAASSanyaHainan 572024China Department of Plant Sciences Quaid-i-Azam UniversityIslamabad 45320Pakistan International Maize and Wheat Improvement Center(CIMMYT) Apdo.Postal 6-641TexcocoD.F.06600Mexico

Genomic prediction is an effective way to accelerate the rate of agronomic trait improvement in *** methods typically use linear regression models with clear assumptions;such methods are unable to capture the complex relationships between genotypes and ***-linear models(e.g.,deep neural networks)have been proposed as a superior alternative to linear models because they can capture complex non-additive *** we introduce a deep learning(DL)method,deep neural network genomic prediction(DNNGP),for integration of multi-omics data in *** trained DNNGP on four datasets and compared its performance with methods built with five classic models:genomic best linear unbiased prediction(GBLUP);two methods based on a machine learning(ML)framework,light gradient boosting machine(LightGBM)and support vector regression(SVR);and two methods based on a DL framework,deep learning genomic selection(DeepGS)and deep learning genome-wide association study(DLGWAS).DNNGP is novel in five ***,it can be applied to a variety of omics data to predict ***,the multilayered hierarchical structure of DNNGP dynamically learns features from raw data,avoiding overfitting and improving the convergence rate using a batch normalization layer and early stopping and rectified linear activation(rectified linear unit)***,when small datasets were used,DNNGP produced results that are competitive with results from the other five methods,showing greater prediction accuracy than the other methods when large-scale breeding data were ***,the computation time required by DNNGP was comparable with that of commonly used methods,up to 10 times faster than ***,hyperparameters can easily be batch tuned on a local *** with GBLUP,LightGBM,SVR,DeepGS and DLGWAS,DNNGP is superior to these existing widely used genomic selection(GS)***,DNNGP can generate robust assessments from diverse datasets,including omics data

关键词： deep learning genomic selection multi-omics data prediction method

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Experimental Study on Heat Storage Properties Comparison of Paraffin/Metal Foams Phase Change Material Composites

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Journal of Thermal Science 2024年第2期33卷 469-478页

作者： Waqar AHMED abid HUSSAIN Hanzla SHAHID Imran ali Hafiz Muhammad ali Department of Mechanical Engineering University of Engineering and TechnologyTaxila47080Pakistan Department of Mechanical Engineering Institute of Space TechnologyIslamabadPakistan Department of Mechanical Mechatronics and Manufacturing EngineeringUniversity of Engineering and Technology LahoreFaisalabad CampusPunjabPakistan Mechanical Engineering Department King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia

Heat storage properties of phase change materials(PCMs) are essential characteristics that perform a key role in thermal heat energy storage *** thermal properties of PCMs can be improved by developing metal foam/PCM *** addition of metal foam in PCMs has a significant effect on the thermal characteristics of *** this paper,the heat storage properties of two different metal foam/PCM composites were experimentally *** behavior of paraffin in metal foam(copper and iron-nickel)/paraffin composites concerning pure paraffin at a constant heat flux of 1000 W/m^(2) in three directions simultaneously(x,y,and z) was *** was infiltrated into copper and iron-nickel foams to develop composite materials which resulted in enhancing the thermal conductivity of the paraffin.A comparative analysis is made on the heat storage properties of paraffin in copper and iron-nickel foams/paraffin *** temperature distribution during the phase transition process is experimentally *** comparison indicates that temperature uniformity in copper foam/paraffin composite is better than in iron-nickel foam/paraffin composite and pure paraffin at the same heat *** results show that at heat flux of 1000 W/m^(2),the heat storage time for copper foam/paraffin composite is 20.63% of that of iron-nickel foam/paraffin composite.

关键词： heat storage capacity paraffin/metal foam composite temperature uniformity heat storage rate phase transition process

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Effectively Handling Network Congestion and Load Balancing in Software-Defined Networking

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Computers, Materials & Continua 2022年第1期70卷 1363-1379页

作者： Shabir Ahmad Faisal Jamil abid ali Ehtisham Khan Muhammad Ibrahim Taeg Keun Whangbo Department of I.T.Convergence Engineering Gachon UniversitySujeong-GuSeongnam-Si461-701Gyeonggi-DoKorea Department of Computer Engineering Jeju National UniversityJeju-Si63243JejuKorea University of Engineering and Technology Taxila47080Pakistan The University of Haripur Haripur22620Pakistan

The concept of Software-Defined Networking(SDN)evolves to overcome the drawbacks of the traditional networks with Internet Protocol(I.P.)packets sending and packets *** SDN structure is one of the critical advantages of efficiently separating the data plane from the control plane tomanage the network configurations and network *** there aremultiple sending devices inside the SDNnetwork,theOpenFlow switches are programmed to handle the limited number of requests for their *** the recommendations are exceeded from the specific threshold,the load on the switches also *** research article introduces a new approach named LBoBS to handle load balancing by adding the load balancing server to the SDN ***,it is used to maximize SDN’s reliability and *** also works in coordination with the controller to effectively handle the load balancing *** load balancing server is implemented to manage the switches load *** are evaluated on the NS-3 simulator for packet delivery,bandwidth utilization,latency control,and packet decision ratios on the OpenFlow *** has been found that the proposed method improved SDN’s load balancing by 70%compared to the previous state-of-the-art methods.

关键词： SDN control plane load balancing decision tree CPU utilization

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Eco-friendly biodegradable polyurethane based coating for antibacterial and antifouling performance

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Chinese Journal of Chemical Engineering 2023年第2期54卷 80-88页

作者： abid ali Bilal Ul Amin Wenwu Yu Taijiang Gui Weiwei Cong Kai Zhang Zheming Tong Jiankun Hu Xiaoli Zhan Qinghua Zhang College of Chemical and Biological Engineering Provincial Key Laboratory of Advanced Chemical Engineering Manufacture TechnologyZhejiang UniversityHangzhou 310027China Institute of Mold Technology Changzhou Vocational Institute of Mechatronic TechnologyChangzhou 213164China State Key Laboratory of Marine Coatings Marine Chemical Research Institute Co.LtdQingdao 266072China Quzhou Research Institute Zhejiang UniversityQuzhou 324000China

Biofouling, which comprises the absorption of proteins and the adhesion of bacteria to the surface of living entities, is a severe concern for the maritime sector since it ultimately leads to hydrodynamic drag,resulting in a higher increase in fuel consumption. As a result, polymer resins are crucial in the marine sector for anti-biofouling coatings. In this work, the poly(caprolactone-ethylene glycol-caprolactone)-p olyurethane(PECL-PU) are prepared through ε-caprolactone(CL), poly(ethylene glycol)(PEG), 4,4'-methylene bis(cyclohexyl isocyanate) and 1,4 butanediol. Our study demonstrate that the PECL-PU copolymer degraded in artificial seawater(5.21%), enzymatic solution(12.63%), and seawater(13.75%)due to the presence of PEG segments in the laboratory-based test under static condition. Because the addition of PEG segments are increased the polymer's amorphous area and decreased the crystallization of the polycaprolactone(PCL) in the copolymer, as demonstrated by differential scanning calorimetry, X-ray diffraction, and water contact angle studies. Therefore, the hydrolysis rates of PECL-PU were higher than the caprolactone-co-polyurethane(CL-PU). The antifouling test showed that PECL-PU3 copolymer had about 90.29% protein resistance, 85.2% Escherichia coli(E. coli) reduction and 94.61% marine diatom Navicula incerta reduction comparison to the control. We have developed an eco-friendly and inexpensive promising degradable polyurethane for reduction of bacterial biofilm, which can preserve the formation of biofouling on marine coating under practical sea conditions.

关键词： Caprolactone PEG segments Biodegradable polyurethane Biofouling Hydrolytic degradation

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Towards Intelligent Detection and Classification of Rice Plant Diseases Based on Leaf Image Dataset

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Computer Systems Science & Engineering 2023年第11期47卷 1385-1413页

作者： Fawad ali Shah Habib Akbar abid ali Parveen Amna Maha Aljohani Eman A.Aldhahri Harun Jamil Department of IT The University of HaripurHaripur22620Pakistan Department of Computer Science University of Engineering and TechnologyTaxila47080Pakistan Department of Computer Science GANK(S)DC KTS HaripurHaripur22620Pakistan College of Pharmacy Gachon University Medical CampusNo.191HambakmoeroYeonsu-guIncheon21936Korea Software Engineering Department College of Computer Science and EngineeringUniversity of JeddahJeddah23218Saudi Arabia College of Computer Sciences and Engineering Department of Computer Science and Artificial IntelligenceUniversity of JeddahJeddahSaudi Arabia Department of Computer Engineering Jeju National UniversityJejusi63243Korea

The detection of rice leaf disease is significant because,as an agricultural and rice exporter country,Pakistan needs to advance in production and lower the risk of *** this rapid globalization era,information technology has increased.A sensing system is mandatory to detect rice diseases using Artificial Intelligence(AI).It is being adopted in all medical and plant sciences fields to access and measure the accuracy of results and detection while lowering the risk of *** Neural Network(DNN)is a novel technique that will help detect disease present on a rice leave because DNN is also considered a state-of-the-art solution in image detection using sensing *** in this paper,the adoption of the mixed-method approach Deep Convolutional Neural Network(Deep CNN)has assisted the research in increasing the effectiveness of the proposed *** CNN is used for image recognition and is a class of deep-learning neural *** is popular and mostly used in the field of image recognition.A dataset of images with three main leaf diseases is selected for training and testing the proposed *** the image acquisition and preprocessing process,the Deep CNN model was trained to detect and classify three rice diseases(Brown spot,bacterial blight,and blast disease).The proposed model achieved 98.3%accuracy in comparison with similar state-of-the-art techniques.

关键词： Rice plant disease detection convolution neural network image classification biological classification

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