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Impact of numerous larval diets on the biology of pink bollworm Pectinophora gossypiella(Saunders)(Lepidoptera:Gelechiidae)under laboratory conditions

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Journal of Cotton Research 2024年第1期7卷 69-78页

作者： AKHTAR Shamim ARIF Muhammad Jalal GOGI Muhammad dildar HAQ Imran-ul Department of Entomology University of Agriculture FaisalabadPunjabPakistan Ayub Agricultural Research Institute(Entomological Research Institute) FaisalabadPunjabPakistan Department of Plant Pathology University of AgricultureFaisalabadPunjabPakistan

Background Pink bollworm,Pectinophora gossypiella(Saunders)(Lepidoptera:Gelechiidae)has become a poten-tial pest of cotton by causing substantial yield losses around the world including Pakistan.Keeping in view the facts like limited research investigations,unavailability,and high cost of artificial diet’s constituents and their premixes,the present research investigations on the dietary aspect of P.gossypiella were conducted.The larvae of P.gossypiella were reared on different diets that were prepared using indigenous elements.The standard/laboratory diet com-prised of wheat germ meal 34.5 g,casein 30.0 g,agar–agar 20.0 g,sucrose 10.0 g,brewer’s yeast 5.0 g,α-cellulose 1.0 g,potassium-sorbate1.5 g,niplagin 0.5 g,decavitamin 0.01 g,choline-chloride 0.06 g,maize-oil 3.30 g,honey 2.0 g,and water 730.0 mL.Alternatives to cotton bolls and wheat germ meal were okra seed sprouts,okra fruit,cottonseed meal,and okra seed meals,which were included in the study to introduce an efficient and economic mass-rearing system.Results The larval development completed in 19.68d±0.05 d with a weight of 20.18mg±0.20 mg at the fourth instar fed on the cottonseed meal-based diet instead of wheat germ meal based diet.On the same diet,84.00%±4.00%,17.24 mg±0.03 mg,and 7.76d±0.06 d were recorded as pupae formation,pupal weight,and pupal duration,respectively.Adult emergence,76.00%±1.00%was recorded from pupae collected from larvae raised on cottonseed meal-based diet.These male and female moths lived for 40.25d±0.10 d,and 44.34d±0.11 d,respectively.Females deposited 21.28±0.04 eggs per day with the viability of 65.78%±0.14%.The larval mortal-ity at the fourth instar was 37.20%±1.36%and malformed pupation of 12.00%±1.41%was recorded.Replacement of wheat germ meal with that of local meals(cottonseed and okra seed)in the standard laboratory diet has saved 463.80 to 467.10 PKR with 1.62 to 1.63 cost economic returns,respectively.Conclusion This research is of novel nature as it provides a concise and workable system for the economic and suc-c

关键词： Artificial diets Cottonseed meal Laboratory rearing Pectinophora gossypiella Wheat germ meal

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Frequency Reconfigurable Antenna for Multi Standard Wireless and Mobile Communication Systems

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Computers, Materials & Continua 2021年第8期68卷 2563-2578页

作者： Ikhlas Ahmad haris dildar Wasi Ur Rehman Khan Sadiq Ullah Shakir Ullah Mahmoud AAlbreem Mohammed HAlsharif Peerapong Uthansakul Department of Telecommunication Engineering University of Engineering&TechnologyMardan23200Pakistan Department of Electronics and Communications Engineering A’Sharqiyah UniversityIbra 400Oman Department of Electrical Engineering College of Electronics and Information EngineeringSejong UniversitySeoul05006Korea School of Telecommunication Engineering Suranaree University of TechnologyNakhon RatchasimaThailand

In this paper,low profile frequency reconfigurable monopole antenna is designed on FR-4 substrate with a compact size of 30 mm^(3)×20 mm^(3)×1.6 mm^(3).The antenna is tuned to four different modes through three pin diode switches.In Mode 1(SW1 to SW3=OFF),antenna covers a wideband of 3.15–8.51 GHz.For Mode 2(SW1=ON,SW2 to SW3=OFF),the proposed antenna resonates at 3.5 GHz.The antenna shows dual band behavior and covers 2.6 and 6.4 GHz in Mode 3(SW1 and SW2=ON,SW3=OFF).The same antenna covers three different bands of 2.1,5 and 6.4 GHz when operating in Mode 4(SW1 to SW3=ON).The proposed antenna has good radiation efficiency ranges from 70%∼84%,providing adequate average gain of 2.05 dBi in mode 1,1.87 dBi in mode 2,1.4–1.75 dBi in mode 3 and 1.05–1.56 dBi in mode 4.The achieved impedance bandwidths at respective frequencies ranges from 240 to 5000 MHz.The Voltage Standing Waves Ratio(VSWR)of less than 1.5 is achieved for all operating bands.To validate the simulation results,the proposed antenna is fabricated and experimentally tested in antenna measurement laboratory.Due to its reasonably small size and support of multiple bands operation,the proposed antenna can be used in modern communication systems for supporting various applications such as fifth generation(5G)mobile and wireless local area networks(WLAN).

关键词： Reconfigurable antenna pin diode communication systems 5G WLAN

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Nucleation of Boron-Nitrogen on Transition Metal Surface:A First-Principles Investigation

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Chinese Journal of Chemical Physics 2018年第3期31卷 335-340,368页

作者： dildar Ahmed Erjun Kan Department of Applied Physics and Institution of Energy and MicrostructureNanjing University of Science and TechnologyNanjing 210094China

Boron nitrogen(BN)monolayer has attracted considerable attention because of their suc-cessful incorporation with graphene based nanodevices.However,many important aspects of the growth mechanisms are still not well explored.Using density functional theory(DFT)calculations,we found that Cu(111)surface is more suitable to be used as a substrate to grow BN monolayer compared with Ni(111)surface.Moreover,we explored that one-dimensional(1D)BN chain configuration is dominant to the two-dimensional(2D)BN ring formation from one pair to five BN pairs deposited on Cu(111)surface.Energetically stable structure transformation of BN monolayer from 1D BN chain to 2D BN ring occurs when the number of pairs is n>5.It is suggested that,as the number of BN pairs increases the energetically stable structures achieve.

关键词： Growth mechanism Density functional theory BN monolayer

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Lipase inhibitory activity of Lagenaria siceraria fruit as a strategy to treat obesity

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Asian Pacific Journal of Tropical Medicine 2017年第3期10卷 285-290页

作者： Maria Maqsood dildar Ahmed Iqra Atique Wajeeha Malik Department of Chemistry Forman Christian College(A Chartered University)LahorePakistan

Objective:To explore pancreatic lipase inhibitory activity under different extraction conditions in order to track the most potent extract.Methods:The methanolic extract and its fractions in solvents of increasing polarity,ether,chloroform,ethyl acetate,n-butanol and water,were made through cold maceration.Extracts in ethanol,ethyl acetate,acetone and chloroform were similarly prepared.Aqueous extract was prepared through hot decoction method.A reported method was used to determine lipase inhibitory activity of extracts and fractions over wide ranges of concentrations.Results:The extracts and fractions exhibited concentration dependent activity.The IC50(μg/mL)values of methanolic,ethanolic,chloroform,ethyl acetate,acetone,ethyl acetate(after washing with water)and aqueous decoction were 293.40,266.47,157.59,182.12,352.34,257.00,and 190.00,respectively.The activity of chloroform,ethyl acetate and aqueous extracts were close to that of the drug orlistat(IC50 146μg/mL).Out of the fractions of the methanolic extract,the chloroform fraction was most active(IC50 189.6μg/mL).The order of inhibitory activity of the fractions was as follows:chloroform>ether>n-butanolic>aqueous>ethyl acetate.The GC/MS analysis of the most active chloroform faction showed the presence of hexadecanoic acid,methyl hexadecanoate,isopropyl palmitate,methyl 9,12-octadecadienate,and methyl 9,12,15-octadecatrienoate.Conclusions:The study suggests that Lagenaria siceraria has potential to inhibit pancreatic lipase activity,suppressing lipid digestion and thereby diminishing entry of lipids into the body.Regular intake of aqueous decoction of the fruit may therefore be recommended for control of obesity.Fatty acids and their esters may play role as inhibitors of lipase.

关键词： Lagenaria siceraria Obesity Lipase inhibitory activity Bottle gourd

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Artificial Intelligence-Based Semantic Segmentation of Ocular Regions for Biometrics and Healthcare Applications

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Computers, Materials & Continua 2021年第1期66卷 715-732页

作者： Rizwan Ali Naqvi dildar Hussain Woong-Kee Loh Department of Unmanned Vehicle Engineering Sejong UniversitySeoul05006Korea School of Computational Science Korea Institute for Advanced Study(KIAS)Seoul02455Korea Department of Software Gachon UniversitySeongnam13120Korea

Multiple ocular region segmentation plays an important role in different applications such as biometrics,liveness detection,healthcare,and gaze estimation.Typically,segmentation techniques focus on a single region of the eye at a time.Despite the number of obvious advantages,very limited research has focused on multiple regions of the eye.Similarly,accurate segmentation of multiple eye regions is necessary in challenging scenarios involving blur,ghost effects low resolution,off-angles,and unusual glints.Currently,the available segmentation methods cannot address these constraints.In this paper,to address the accurate segmentation of multiple eye regions in unconstrainted scenarios,a lightweight outer residual encoder-decoder network suitable for various sensor images is proposed.The proposed method can determine the true boundaries of the eye regions from inferior-quality images using the high-frequency information flow from the outer residual encoder-decoder deep convolutional neural network(called ORED-Net).Moreover,the proposed ORED-Net model does not improve the performance based on the complexity,number of parameters or network depth.The proposed network is considerably lighter than previous state-of-theart models.Comprehensive experiments were performed,and optimal performance was achieved using SBVPI and UBIRIS.v2 datasets containing images of the eye region.The simulation results obtained using the proposed OREDNet,with the mean intersection over union score(mIoU)of 89.25 and 85.12 on the challenging SBVPI and UBIRIS.v2 datasets,respectively.

关键词： Semantic segmentation ocular regions biometric for healthcare sensors deep learning

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Deep Learning in DXA Image Segmentation

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Computers, Materials & Continua 2021年第3期66卷 2587-2598页

作者： dildar Hussain Rizwan Ali Naqvi Woong-Kee Loh Jooyoung Lee School of Computational Science Korea Institute for Advanced Study(KIAS)85 HoegiroDongdaemun-guSeoul02455South Korea Department of Unmanned Vehicle Engineering Sejong University209Neungdong-roGwangjin-guSeoul05006South Korea Department of Software Gachon UniversitySeongnam13120South Korea

Many existing techniques to acquire dual-energy X-ray absorptiometry(DXA)images are unable to accurately distinguish between bone and soft tissue.For the most part,this failure stems from bone shape variability,noise and low contrast in DXA images,inconsistent X-ray beam penetration producing shadowing effects,and person-to-person variations.This work explores the feasibility of using state-of-the-art deep learning semantic segmentation models,fully convolutional networks(FCNs),SegNet,and U-Net to distinguish femur bone from soft tissue.We investigated the performance of deep learning algorithms with reference to some of our previously applied conventional image segmentation techniques(i.e.,a decision-tree-based method using a pixel label decision tree[PLDT]and another method using Otsu’s thresholding)for femur DXA images,and we measured accuracy based on the average Jaccard index,sensitivity,and specificity.Deep learning models using SegNet,U-Net,and an FCN achieved average segmentation accuracies of 95.8%,95.1%,and 97.6%,respectively,compared to PLDT(91.4%)and Otsu’s thresholding(72.6%).Thus we conclude that an FCN outperforms other deep learning and conventional techniques when segmenting femur bone from soft tissue in DXA images.Accurate femur segmentation improves bone mineral density computation,which in turn enhances the diagnosing of osteoporosis.

关键词： Segmentation deep learning osteoporosis dual-energy X-ray absorptiometry

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Exploring polyamines:Functions in embryo/fetal development

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Animal Nutrition 2017年第1期3卷 7-10页

作者： Tarique Hussain Bi'e Tan Wenkai Ren Najma Rahu dildar Hussain Kalhoro Yulong Yin National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production Institute of Subtropical AgricultureKey Laboratory of Agro-EcologyInstitute of Subtropical AgricultureThe Chinese Academy of Sciences University of Chinese Academy of Sciences Hunan Collaborative Innovation Center for Utilization of Botanical Functional Ingredients Hunan Collaborative Innovation Center of Animal Production Safety Department of Veterinary Microbiology Faculty of Animal Husbandry and Veterinary SciencesSindh Agriculture University

Polyamines such as putrescine, spermidine, spermine and agmatine are aliphatic polycationic compounds present in all living cells, and are derived from amino acids, intestinal bacteria, exfoliated enterocytes and supported from diet. Polyamines as the key compounds play essential role in cell proliferation, growth and differentiation. They also exert significant effects on embryonic development,implantation, embryonic diapause, placentation, angiogensis and fetal development. This review paper summarizes the functions of polyamines and embryo/fetus development and its regulatory mechanism which should help to provide some evidences for clinic.

关键词： Polyamines Polyamine biosynthesis Embryo/fetus development

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Roman Urdu News Headline Classification Empowered with Machine Learning

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Computers, Materials & Continua 2020年第11期65卷 1221-1236页

作者： Rizwan Ali Naqvi Muhammad Adnan Khan Nauman Malik Shazia Saqib Tahir Alyas dildar Hussain Department of Unmanned Vehicle Engineering Sejong UniversitySeoul05006Korea Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan School of Computational Sciences Korea Institute for Advanced StudySeoul02455Korea

Roman Urdu has been used for text messaging over the Internet for years especially in Indo-Pak Subcontinent.Persons from the subcontinent may speak the same Urdu language but they might be using different scripts for writing.The communication using the Roman characters,which are used in the script of Urdu language on social media,is now considered the most typical standard of communication in an Indian landmass that makes it an expensive information supply.English Text classification is a solved problem but there have been only a few efforts to examine the rich information supply of Roman Urdu in the past.This is due to the numerous complexities involved in the processing of Roman Urdu data.The complexities associated with Roman Urdu include the non-availability of the tagged corpus,lack of a set of rules,and lack of standardized spellings.A large amount of Roman Urdu news data is available on mainstream news websites and social media websites like Facebook,Twitter but meaningful information can only be extracted if data is in a structured format.We have developed a Roman Urdu news headline classifier,which will help to classify news into relevant categories on which further analysis and modeling can be done.The author of this research aims to develop the Roman Urdu news classifier,which will classify the news into five categories(health,business,technology,sports,international).First,we will develop the news dataset using scraping tools and then after preprocessing,we will compare the results of different machine learning algorithms like Logistic Regression(LR),Multinomial Naïve Bayes(MNB),Long short term memory(LSTM),and Convolutional Neural Network(CNN).After this,we will use a phonetic algorithm to control lexical variation and test news from different websites.The preliminary results suggest that a more accurate classification can be accomplished by monitoring noise inside data and by classifying the news.After applying above mentioned different machine learning algorithms,results have shown that Multinomial

关键词： Roman urdu news headline classification long short term memory recurrent neural network logistic regression multinomial naïve Bayes random forest k neighbor gradient boosting classifier

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Intelligent Breast Cancer Prediction Empowered with Fusion and Deep Learning

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Computers, Materials & Continua 2021年第4期67卷 1033-1049页

作者： Shahan Yamin Siddiqui Iftikhar Naseer Muhammad Adnan Khan Muhammad Faheem Mushtaq Rizwan Ali Naqvi dildar Hussain Amir Haider School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan School of Computer Science Minhaj University LahoreLahore54000Pakistan Department of Computer Science&Information Technology Superior UniversityLahore54000Pakistan Department of Computer Science Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Information Technology Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Department of Unmanned Vehicle Engineering Sejong UniversitySeoul05006Korea School of Computational Sciences Korea Institute for Advanced Study(KIAS)85 HoegiroDongdaemunguSeoul02455Korea Department of Intelligent Mechatronics Engineering Sejong UniversitySeoul05006Korea

Breast cancer is the most frequently detected tumor that eventually could result in a significant increase in female mortality globally.According to clinical statistics,one woman out of eight is under the threat of breast cancer.Lifestyle and inheritance patterns may be a reason behind its spread among women.However,some preventive measures,such as tests and periodic clinical checks can mitigate its risk thereby,improving its survival chances substantially.Early diagnosis and initial stage treatment can help increase the survival rate.For that purpose,pathologists can gather support from nondestructive and efficient computer-aided diagnosis(CAD)systems.This study explores the breast cancer CAD method relying on multimodal medical imaging and decision-based fusion.In multimodal medical imaging fusion,a deep learning approach is applied,obtaining 97.5%accuracy with a 2.5%miss rate for breast cancer prediction.A deep extreme learning machine technique applied on feature-based data provided a 97.41%accuracy.Finally,decisionbased fusion applied to both breast cancer prediction models to diagnose its stages,resulted in an overall accuracy of 97.97%.The proposed system model provides more accurate results compared with other state-of-the-art approaches,rapidly diagnosing breast cancer to decrease its mortality rate.

关键词： Fusion feature breast cancer prediction deep learning convolutional neural network multi-modal medical image fusion decision-based fusion

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Relationship between gut microbiota and host-metabolism:Emphasis on hormones related to reproductive function

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Animal Nutrition 2021年第1期7卷 1-10页

作者： Tarique Hussain Ghulam Murtaza dildar H.Kalhoro Muhammad S.Kalhoro Elsayed Metwally Muhammad I.Chughtai Muhammad U.Mazhar Shahzad A.Khan Animal Sciences Division Nuclear Institute for Agriculture and Biology CollegePakistan Institute of Engineering and Applied Sciences(NIAB-CPIEAS)Faisalabad38000Pakistan Department of Animal Reproduction Faculty of Animal Husbandry and Veterinary SciencesSindh Agriculture UniversityTandojamSindh70050Pakistan Department of Veterinary Microbiology Faculty of Animal Husbandry and Veterinary SciencesSindh Agriculture UniversityTandojamSindh70050Pakistan Department of Animal Products Technology Faculty of Animal Husbandry and Veterinary SciencesSindh Agriculture UniversityTandojamSindh70050Pakistan Department of Cytology&Histology Faculty of Veterinary MedicineSuez Canal UniversityIsmailia41522Egypt Faculty of Animal Husbandry and Veterinary Sciences University of PoonchRawalakot12350Pakistan

It has been well recognized that interactions between the gut microbiota and host-metabolism have a proven effect on health.The gut lumen is known for harboring different bacterial communities.Microbial by-products and structural components,which are derived through the gut microbiota,generate a signaling response to maintain homeostasis.Gut microbiota is not only involved in metabolic disorders,but also participates in the regulation of reproductive hormonal function.Bacterial phyla,which are localized in the gut,allow for the metabolization of steroid hormones through the stimulation of different enzymes.Reproductive hormones such as progesterone,estrogen and testosterone play a pivotal role in the successful completion of reproductive events.Disruption in this mechanism may lead to reproductive disorders.Environmental bacteria can affect the metabolism,and degrade steroid hor-mones and their relevant compounds.This behavior of the bacteria can safely be implemented to eliminate steroidal compounds from a polluted environment.In this review,we summarize the meta-bolism of steroid hormones on the regulation of gut microbiota and vice-versa,and also examined the significant influence this process has on various events of reproductive function.Altogether,the evidence suggests that steroid hormones and gut microbiota exert a central role in the modification of host bacterial action and impact the reproductive efficiency of animals and humans.

关键词： Gut microbiota Host-metabolism Steroid hormone Reproductive function

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