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Age norms for grating acuity and contrast sensitivity measured by Lea tests in the first three years of life

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International Journal of Ophthalmology(English edition) 2017年第7期10卷 1150-1153页

作者： Amal A.Elgohary Manal H.Abuelela adel Alei Eldin Department of Vision Science Research Institute of Ophthalmology Department of Public Health Research Institute of Ophthalmology Department of Ophthalmology Research Institute of Ophthalmology

AIM： To determine age norms in the first three years of life for grating visual acuity and contrast sensitivity obtained with Lea grating test and Hiding Heidi low contrast face test. METHODS： Lea grating test was used to estimate binocular grating acuity and Hiding Heidi low contrast face test was used to estimate contrast sensitivity in 600 healthy infants and children. Age ranged from 3 to 36 mo subdivided into 12 groups subjected for full ophthalmologic and pediatric ***： The grating acuity developed along the first three years of life. It ranged from 1.88±0.32 c/d at 3mo to 30.95±0.77 c/d at 36 mo. The most rapid development was during the first 12 mo and the slowest development was from 30 to 36 mo. The contrast sensitivity showed rapid development in the first two years of life. Its mean value ranged from 4.23±1.17 at 3mo to 78.26±8.21 at 24 mo. It was constant at the highest score（80） ***： Age norms for grating acuity along with contrast sensitivity offer a more comprehensive measure of spatial vision and should be incorporated in clinical practice for better visual assessment in preverbal and nonverbal children.

关键词： grating acuity contrast sensitivity age norms Lea tests preverbal children

Palmitic Acid-Lauric Acid/Expanded Graphite as Form-Stable Composite Phase Change Material for Low-Temperature Energy Storage Applications

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Journal of Harbin Institute of Technology(New Series) 2022年第5期29卷 41-48页

作者： adel Elgadi Chan Mieow Kee Tan Yong Chai Center for Advanced Materials Research and Manufacturing Processes Faculty of Engineering and the Built EnvironmentSEGi UniversityPetaling Jaya 47810SelangorMalaysia

Low thermal conductivity of binary fatty acid mixture of palmitic and lauric acids(PA-LA)within the value range of 0.15-0.17 W/(m·K)restricts its wide utilization as thermal energy storage material in the active regime of solar heating applications at low operating ***,this mixture as phase change material(PCM)has a suitable phase-change temperature and heat of 36℃and 176.3 J/g,***,the objective of this study is to formulate a novel form-stable composite PCM with the PA-LA mixture and expanded graphite(EG)as a thermal ***-LA eutectic mixture with varied concentrations of EG was prepared and *** thermal conductivity of PA-LA/EG increased gradually with the mass of *** thermal properties were observed in PA-LA/(5%EG)composite,where its melting(T_(m)),freezing temperature(T_(t)),latent melting heat and thermal conductivity was 35.53℃,34.84℃,174 J/g,and 1.19 W/(m·K),***,the composite PCM is characterized by good chemical-thermal stability and thermal reliability for long-term *** conclusion,it can be utilized as a prospective form-stable PCM for thermal energy storage in solar heating systems,overheat treatment systems,and other thermal storage applications at low operating temperatures.

关键词： binary mixture PCM of fatty acid expanded graphite thermal conductivity thermal reliability and stability

Time and Quantity Based Hybrid Consolidation Algorithms for Reduced Cost Products Delivery

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Computers, Materials & Continua 2021年第10期69卷 409-432页

作者： Muhammad Ali Memon Asadullah Shaikh adel Sulaiman Abdullah Alghamdi Mesfer Alrizq Bernard Archimède Department of Information Technology University of SindhJamshoroSindh76090Pakistan College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia University of Toulouse INP-ENIT47 Avenue d’AzereixBP1629F-65016Tarbes CedexFrance

In today’s competitive business environment,the cost of a product is one of the most important considerations for its *** are heavily involved in research strategies to minimize the cost of elements that can impact on the final price of the *** is one such *** products arrive from diverse locations to consumers in today’s digital era of online ***,the logistics sector faces several dilemmas from order attributes to environmental changes in this *** has specially been noted during the ongoing Covid-19 pandemic where the demands on online businesses have increased several ***,the methodology to optimise delivery cost and its impact on environmental focus by reducing CO_(2) emissions has gained *** resultant strategy of Shipment Consolidation that has evolved is an approach that combines one or more transport orders in the same vehicle for *** Consolidation has been categorized in three order scheduling approaches:Time based consolidation,Quantity based consolidation,and a Hybrid(Time-Quantity)based *** this paper,a new Hybrid Consolidation approach is *** the Hybrid approach,it has been shown that order delivery can be facilitated by taking into account not only the order pick up time,but also the total order *** results have shown that if a time window is available in respect of the order delivery time,then the order can be delayed from pickup to consolidate it with other orders for cost *** hybrid approach is based on four consolidation principles,two of which work on fixed departure and two,on demand *** of these rules have been implemented and tested here with an application case *** analysis of the results is illustrated with different planning evaluation *** Result analyses indicate that consolidation of orders is increased with each implemented rule hence motivating us towards t

关键词： Consolidation transportation supply chain cost minimization

SBOOSP for Massive Devices in 5G WSNs Using Conformable Chaotic Maps

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Computers, Materials & Continua 2022年第6期71卷 4591-4608页

作者： Chandrashekhar Meshram Agbotiname Lucky Imoize Sajjad Shaukat Jamal Amer Aljaedi adel R.Alharbi Department of Post Graduate Studies and Research in Mathematics Jayawanti Haksar Government Post-Graduation CollegeCollege of Chhindwara UniversityBetul460001M.P.India Department of Electrical and Electronics Engineering Faculty of EngineeringUniversity of LagosAkoka100213LagosNigeria Department of Electrical Engineering and Information Technology Institute of Digital CommunicationRuhr University44801BochumGermany Department of Mathematics College of ScienceKing Khalid UniversityAbhaSaudi Arabia College of Computing and Information Technology University of TabukTabuk 71491Saudi Arabia

The commercialization of the fifth-generation(5G)wireless network has *** devices are being integrated into 5G-enabled wireless sensor networks(5GWSNs)to deliver a variety of valuable services to network ***,there are rising fears that 5GWSNs will expose sensitive user data to new security *** secure end-to-end communication,key agreement and user authentication have been ***,when billions of massive devices are networked to collect and analyze complex user data,more stringent security approaches are *** integrity,nonrepudiation,and authentication necessitate special-purpose subtree-based signature mechanisms that are pretty difficult to create in *** address this issue,this work provides an efficient,provably secure,lightweight subtreebased online/offline signature procedure(SBOOSP)and its aggregation(Agg-SBOOSP)for massive devices in 5G WSNs using conformable chaotic *** SBOOSP enables multi-time offline storage access while reducing processing *** a result,the signer can utilize the pre-stored offline information in polynomial *** feature distinguishes our presented SBOOSP from previous online/offline-signing procedures that only allow for one ***,the new procedure supports a secret key during the pre-registration process,but no secret key is necessary during the offline *** suggested SBOOSP is secure in the logic of unforgeability on the chosen message attack in the random ***,SBOOSP and Agg-SBOOSP had the lowest computing costs compared to other contending ***,the suggested SBOOSP outperforms several preliminary security schemes in terms of performance and computational overhead.

关键词： Subtree-based online/offline signature procedure(SBOOSP) 5G WSNs provably secure scheme massive devices conformable chaotic maps

Exploiting Deep Learning Techniques for Colon Polyp Segmentation

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Computers, Materials & Continua 2021年第5期67卷 1629-1644页

作者： Daniel Sierra-Sosa Sebastian Patino-Barrientos Begonya Garcia-Zapirain Cristian Castillo-Oleam adel Elmaghraby Department of Computer Science and Engineering University of LouisvilleLouisvilleKYUSA Centro de Computacion Cientifica Apolo at Universidad EAFIT MedelinColombia eVida Research Group University of DeustoBilbaoSpain

As colon cancer is among the top causes of death, there is a growinginterest in developing improved techniques for the early detection of colonpolyps. Given the close relation between colon polyps and colon cancer,their detection helps avoid cancer cases. The increment in the availability ofcolorectal screening tests and the number of colonoscopies have increasedthe burden on the medical personnel. In this article, the application of deeplearning techniques for the detection and segmentation of colon polyps incolonoscopies is presented. Four techniques were implemented and evaluated:Mask-RCNN, PANet, Cascade R-CNN and Hybrid Task Cascade (HTC).These were trained and tested using CVC-Colon database, ETIS-LARIBPolyp, and a proprietary dataset. Three experiments were conducted to assessthe techniques performance: (1) Training and testing using each databaseindependently, (2) Mergingd the databases and testing on each database independently using a merged test set, and (3) Training on each dataset and testingon the merged test set. In our experiments, PANet architecture has the bestperformance in Polyp detection, and HTC was the most accurate to segmentthem. This approach allows us to employ Deep Learning techniques to assisthealthcare professionals in the medical diagnosis for colon cancer. It is anticipated that this approach can be part of a framework for a semi-automatedpolyp detection in colonoscopies.

关键词： Colon polyps deep learning image segmentation

Branched-chain amino acids partially recover the reduced growth of pigs fed with protein-restricted diets through both central and peripheral factors

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Animal Nutrition 2021年第3期7卷 868-882页

作者： Mohammad Habibi Cedrick Shili Julia Sutton Parniyan Goodarzi Excel Rio Maylem Leon Spicer adel Pezeshki Department of Animal and Food Sciences Oklahoma State UniversityStillwaterOK74078USA

The objective of this study was to assess the growth efficiency of pigs fed with protein-restricted diets supplemented with branched-chain amino acids(BCAA)and limiting amino acids(LAA)above the rec-ommended *** 2 weeks of adaptation,48 young barrows were weight matched and randomly assigned to 6 treatments(8 pigs/treatment)for 4 weeks:positive control(PC)with standard protein,negative control(NC)with very low protein containing LAA(i.e.,Lys,Met,Thr and Trp)at rec-ommended levels,and NC containing LAA 25%(L25),LAA 50%(L50),LAA+BCAA(i.e.,Leu,Ile and Val)25%(LB25)and LAA+BCAA 50%(LB50)more than *** intake(FI)and body weight(BW)were measured daily and weekly,*** week 6,blood samples were collected,all pigs euthanized and tissue samples *** data were analyzed by univariate GLM or mixed procedure(SPSS)and the means were separated using paired Student's t-test followed by Benjamini-Hochberg *** to PC,NC had decreased FI,BW,unsupplemented plasma essential amino acids,serum insulin-like growth factor-I(IGF-I)and hypothalamic neuropeptide Y(NPY)(P<0.01).Compared to NC,L25 or L50,LB50 had increased BW and serum IGF-I and decreased plasma serotonin and both LB25 and LB50 had higher FI,plasma BCAA,hypothalamic 5-hydroxytryptamine-receptor 2A and NPY and jejunal 5-hydroxytryptamine-receptor 7(P<0.01).Overall,supplementation of protein-restricted diets with increased levels of dietary BCAA partially recovered the negative effects of these diets on growth through improved IGF-I concentration and FI,which was associated with changed expression of serotonin receptors,blood AA and hypothalamic NPY.

关键词： Branched-chain amino acid Very low protein diet NPY insulin-like growth factor-Ⅰ Serotonin Pig

WEIGHTED PSEUDO ALMOST-PERIODIC SOLUTIONS OF SHUNTING INHIBITORY CELLULAR NEURAL NETWORKS WITH MIXED DELAYS

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Acta Mathematica Scientia 2016年第6期36卷 1662-1682页

作者： Mohammed Salah M'HAMDI Chaouki AOUITI Abderrahmane TOUATI adel M. ALIMI Vaclav SNASEL Department of Mathematics University of Carthage Faculty of Sciences of Bizerta BP W 7021 Zarzouna Bizerta Tunisia REGIM-lab: Research Groups on Intelligent Machines University of Sfax National Engineering School of Sfax (ENIS) BP 1173 Sfax 3038 Tunisia VSB Technical University of Ostrava Czech Republic

In this paper, we prove the existence and the global exponential stability of the unique weighted pseudo almost-periodic solution of shunting inhibitory cellular neural networks with mixed time-varying delays comprising different discrete and distributed time delays. Some sufficient conditions are given for the existence and the global exponential stability of the weighted pseudo almost-periodic solution by employing fixed point theorem and differential inequality techniques. The results of this paper complement the previously known ones. Finally, an illustrative example is given to demonstrate the effectiveness of our results.

关键词： weighted pseudo almost-periodic solution shunting inhibitory cellular neuralnetworks mixed delays global exponential stability

Automatic Detection of COVID-19 Using a Stacked Denoising Convolutional Autoencoder

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Computers, Materials & Continua 2021年第12期69卷 3259-3274页

作者： Habib Dhahri Besma Rabhi Slaheddine Chelbi Omar Almutiry Awais Mahmood adel M.Alimi College of Applied Computer Sciences(CACS) King Saud UniversityRiyadh11543Saudi Arabia Faculty of Sciences and Technology of Sidi Bouzid University of KairouanKairouanTunisia National School of Engineers(ENIS) University of SfaxTunisia Department of Computer Sciences College of Sciences and Arts in UnaizahQassim UniversityAl-QassimKingdom of Saudi Arabia

The exponential increase in new coronavirus disease 2019(COVID-19)cases and deaths has made COVID-19 the leading cause of death in many ***,in this study,we propose an efficient technique for the automatic detection of COVID-19 and pneumonia based on X-ray images.A stacked denoising convolutional autoencoder(SDCA)model was proposed to classify X-ray images into three classes:normal,pneumonia,and *** SDCA model was used to obtain a good representation of the input data and extract the relevant features from noisy *** proposed model’s architecture mainly composed of eight autoencoders,which were fed to two dense layers and SoftMax *** proposed model was evaluated with 6356 images from the datasets from different *** experiments and evaluation of the proposed model were applied to an 80/20 training/validation split and for five cross-validation data splitting,*** metrics used for the SDCA model were the classification accuracy,precision,sensitivity,and specificity for both *** results demonstrated the superiority of the proposed model in classifying X-ray images with high accuracy of 96.8%.Therefore,this model can help physicians accelerate COVID-19 diagnosis.

关键词： Stacked autoencoder augmentation multiclassification COVID-19 convolutional neural network

Toward cost-effective residential energy reduction and community impacts: A data-based machine learning approach

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能源与人工智能(英文) 2021年第2期4卷 66-79页

作者： adel Naji Badr Al Tarhuni Jun-Ki Choi Salahaldin Alshatshati Seraj Ajena Department of Mechanical Engineering University of DaytonDaytonOH 45469-0238USA Department of Chemical Engineering University of DaytonDaytonOH 45469-0238USA

Many *** incentivize residential energy reduction through rebates,often in response to state mandates for energy reduction or from a desire to reduce demand to mitigate the need to grow generating *** assumption built into incentive programs is that the least efficient residences will be more likely take advantage of the ***,however,is not always the *** main goal of this study was to determine the potential for prioritized incentivization,i.e.,prioritizing incentives that deliver the greatest energy savings per invest-ment through an entire *** uses a data mining approach that leverages known building and energy characteristics for predicting energy consumption of houses that collectively can be considered representative of all residences within an entire *** this model,it estimates natural gas consumption and savings,and corresponding implementation costs associated with the adoption of the most impactful energy reduction *** resulting savings and cost estimates allow us to develop a sequential energy reduction strategy whereby the most economic measures within the whole utility district are *** results show that an energy reduction of 36%can be achieved at a levelized cost of less than$14 per mmBTU($14,780 per MJ),demonstrating the strong potential of this approach.A corresponding Economic Input–Output Analysis captures the cascading community economic impacts of this *** results show that for the roughly 45,000 single-family residences in the studied region,an initial energy efficiency investment of$26M could result in a total cascading multiplier economic impact of$41M and additional economic impacts of$2.2M for the lifetime of the considered energy efficiency measures.

关键词： Building energy efficiency Data mining Machine learning Levelized cost of energy saving Energy reduction strategy Economic input-output analysis