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Nitrogen mineralization in the oldest climax communities in the eastern Mediterranean region

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Journal of Forestry Research 2024年第1期35卷 213-228页

作者： fatma Selcen Sakar Gürcan Güleryüz Department of Biology Section Ecology GörükleGraduate School of Natural and Applied ScienceUniversity of Bursa Uludağ16059 NilüferBursaTurkey Department of Biology Section Ecology GörükleFaculty of Science and ArtsUniversity of Bursa Uludağ16059 NilüferBursaTurkey

In this study,we investigated how tree species affect N mineralization in connection to some soil properties and seconder metabolite levels of litter,in the soil of the old-est native forest communities.In the oldest pure communi-ties of Pinus nigra(PN),Fagus orientalis(FO),and Abies bornmuelleriana(AB)in the mountain range of Mount Uludağ,Bursa,Turkey,annual net yield and N mineraliza-tion in the 0-5-and 5-20-cm soil layers were determined in a field incubation study over 1 year.Sampling locations were chosen from 1300 to 1600 m a.s.l.,and moisture content(%),pH,water-holding capacity(%),organic C,total N,and C/N ratio,and annual net mineral N yield of the soil and hydro-lyzed tannic acid and total phenolic compounds in litter were compared for these forest communities.F.orientalis had the highest annual net Nmin yield(43.9±4.8 kg ha^(-1) a^(-1)),P.nigra the lowest(30.5±4.2 kg ha^(-1) a^(-1)).Our findings show that in the oldest forest ecosystems,the seasonal soil moisture content and tree species play an essential role in N cycling and that hydrolyzed tannic acids and total phenolic compounds effectively control N turnover.Tannic acid and total phenolics in the litter were found to inhibit nitrification,but total phenolics were found to stimulate ammonification.

关键词： Oldest forest communities Nitrogen mineralization Nitrification Tannic acid Total phenolic Litter

Exploring Sequential Feature Selection in Deep Bi-LSTM Models for Speech Emotion Recognition

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Computers, Materials & Continua 2024年第2期78卷 2689-2719页

作者： fatma Harby Mansor Alohali Adel Thaljaoui Amira Samy Talaat Computer Science Department Future Academy-Higher Future Institute for Specialized Technological StudiesCairo12622Egypt Department of Computer Science and Information College of Science at Zulfi Majmaah UniversityP.O.Box 66Al-Majmaah11952Saudi Arabia Preparatory Institute for Engineering Studies of Gafsa ZarrougGafsa2112Tunisia Computers and Systems Department Electronics Research InstituteCairo12622Egypt

Machine Learning(ML)algorithms play a pivotal role in Speech Emotion Recognition(SER),although they encounter a formidable obstacle in accurately discerning a speaker’s emotional state.The examination of the emotional states of speakers holds significant importance in a range of real-time applications,including but not limited to virtual reality,human-robot interaction,emergency centers,and human behavior assessment.Accurately identifying emotions in the SER process relies on extracting relevant information from audio inputs.Previous studies on SER have predominantly utilized short-time characteristics such as Mel Frequency Cepstral Coefficients(MFCCs)due to their ability to capture the periodic nature of audio signals effectively.Although these traits may improve their ability to perceive and interpret emotional depictions appropriately,MFCCS has some limitations.So this study aims to tackle the aforementioned issue by systematically picking multiple audio cues,enhancing the classifier model’s efficacy in accurately discerning human emotions.The utilized dataset is taken from the EMO-DB database,preprocessing input speech is done using a 2D Convolution Neural Network(CNN)involves applying convolutional operations to spectrograms as they afford a visual representation of the way the audio signal frequency content changes over time.The next step is the spectrogram data normalization which is crucial for Neural Network(NN)training as it aids in faster convergence.Then the five auditory features MFCCs,Chroma,Mel-Spectrogram,Contrast,and Tonnetz are extracted from the spectrogram sequentially.The attitude of feature selection is to retain only dominant features by excluding the irrelevant ones.In this paper,the Sequential Forward Selection(SFS)and Sequential Backward Selection(SBS)techniques were employed for multiple audio cues features selection.Finally,the feature sets composed from the hybrid feature extraction methods are fed into the deep Bidirectional Long Short Term Memory(Bi-LSTM)network to discern emotions.

关键词： Artificial intelligence application multi features sequential selection speech emotion recognition deep Bi-LSTM

Phenolic Profile and Volatiles of in vitro Propagated Lavandula angustifolia Mill.Seedlings

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Phyton-International Journal of Experimental Botany 2024年第3期93卷 427-444页

作者： Mir Abdullatif Yahya fatma Tunali Dilek Killi Atalay Sökmen Biotechnology Department Konya Food and Agriculture UniversityKonya42080Türkiye Plant Production and Technologies Department Konya Food and Agriculture UniversityKonya42080Türkiye

An effective in vitro propagation protocol was designed for Lavandula angustifolia Miller,a medicinal aromatic plant that is a prominent source of volatile organic compounds(VOCs).Murashige and Skoog media were supplemented with various concentrations of Plant Growth Regulators(PGRs),and the growth parameters of the nodal segments were examined.Nodal explants formed callus when they were supplemented with 2 mg/L of 6-Benzylaminopurine(BAP).The superior hormonal concentration of Murashige and Skoog(MS)media for the proliferation of shoots from callus cultures(39.33%)was 5 mg/L of 2-Isopentenyl adenine(2iP),and the favorable media for the growth of L.angustifolia callus cultures was 1 and 2 mg/L of BAP,with a 98%for-mation rate in each case.The callus cultures and in vitro propagated L.angustifolia seedlings obtained from var-ious PGR concentrations of MS media were exposed to qualitative and quantitative analysis in terms of phenolic proﬁles,ﬂavonoids,High-performance liquid chromatography(HPLC)analysis of phenolic acids,and headspace-SPME analysis for volatiles.Such analysis revealed that micropropagated seedlings grown in media containing 1 mg/L of 6-Furfurylaminopurine(KIN)accumulated the highest yield(11.95±0.01 mg GAE/g)of phenolic acids.In contrast,the lowest concentration(2.17±0.04 mg GAE/g)was detected in 0.5 mg/L of BAP+0.5 mg/L of Naphthaleneacetic acid(NAA)media.The plantlets grown in 0.5 mg/L of BAP+0.5 mg/L of NAA media showed the highestﬂavonoid yield(31.67±0.06μg/g QE/g).In contrast,callus samples exhibited the lowest yield(11.59±0.02μg/g QE/g)ofﬂavonoids in MS media supplemented with a concentration of 0.5 mg/L of BAP.HPLC analysis revealed the variability of phenolic acid contents within the callus cultures as well as plantlets,with gallic acid,4-OH benzoic acid,chlorogenic acid,vanillic acid,caffeic acid,cinnamic acid,and rosmarinic acid being the prominent constituents.The presence of twenty-two chemicals was revealed by headspace-SPME analysis.Eucalyptol,nonanal,borneol,carvone,andβ-caryophylle

关键词： Lavender indirect organogenesis micropropagation This

Aggravation of Cancer,Heart Diseases and Diabetes Subsequent to COVID-19 Lockdown via Mathematical Modeling

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 485-512页

作者： fatma Nese Efil Sania Qureshi Nezihal Gokbulut Kamyar Hosseini Evren Hincal Amanullah Soomro Near East University Department of MathematicsNicosia99010North Cyprus Mehran University of Engineering and Technology Department of Basic Sciences and Related StudiesJamshoro76090Pakistan Department of Computer Science and Mathematics Lebanese American UniversityP.O.Box 13-5053BeirutLebanon Near East University Mathematics Research CenterNicosia99010North Cyprus

The global populationhas beenandwill continue to be severely impacted by theCOVID-19 epidemic.The primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer,heart disease,and diabetes.Here,using ordinary differential equations(ODEs),two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart disease.After that,we highlight the stability assessments that can be applied to these models.Sensitivity analysis is used to examine how changes in certain factors impact different aspects of disease.The sensitivity analysis showed that many people are still nervous about seeing a doctor due to COVID-19,which could result in a dramatic increase in the diagnosis of various ailments in the years to come.The correlation between diabetes and cardiovascular illness is also illustrated graphically.The effects of smoking and obesity are also found to be significant in disease compartments.Model fitting is also provided for interpreting the relationship between real data and the results of thiswork.Diabetic people,in particular,need tomonitor their health conditions closely and practice heart health maintenance.People with heart diseases should undergo regular checks so that they can protect themselves from diabetes and take some precautions including suitable diets.The main purpose of this study is to emphasize the importance of regular checks,to warn people about the effects of COVID-19(including avoiding healthcare centers and doctors because of the spread of infectious diseases)and to indicate the importance of family history of cancer,heart diseases and diabetes.The provision of the recommendations requires an increase in public consciousness.

关键词： COVID-19 mathematical modeling cancer diabetes heart diseases sensitivity analysis

Epidemiological and histopathological characteristics of thyroid carcinoma in a Tunisian health care center

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World Journal of Otorhinolaryngology-Head and Neck Surgery 2024年第1期10卷 37-42页

作者： Maissa Ben Thayer fatma Khanchel Imen Helal Dorra Chiboub Hedhli Raoueh Ehsen Ben Brahim Raja Jouini Aschraf Chadli-Debbiche Faculty of Medicine of Tunis Tunis El Manar UniversityTunisTunisia Depatment of Pathology Habib Thameur's HospitalTunisTunisia Department of Otorhinolaryngology-Head and Neck surgery Habib Thameur's HospitalTunisTunisia

Background:Thyroid carcinoma(TC)accounts for almost 0.5%–1%of total malignancies.Its incidence is increasing rapidly worldwide.Several studies have drawn up the epidemiological profile of TC and its clinical and pathological features.However,to date,no similar studies have been conducted in Tunisia.Aims:To establish an epidemiological profile of TC in a Tunisian health care institute and to analyze its clinical and histopathological characteristics in our institute.Materials and Methods:We present a retrospective study reviewing the cases of TC diagnosed in our institution in a 4-year period.Results:We collected a sample of 192 cases of TC.It consisted of 31 males and 161 females(83.8%)with a sex-ratio M/F of 0.19.The mean age was 46.4 years.Papillary thyroid carcinoma was the most frequent histological subtype.The multifocality rate was 33.8%.The mean size of TC was 2.2±1.9 cm.60.9%of TC were staged pT1 and 20.3%had nodal involvement.Papillary thyroid microcarcinomas were noted in 37.5%of cases.Conclusion:Our results were consistent with those of the literature.A high proportion of pT1 and pN0 tumors were noted in our series,suggesting that TC's diagnosis and management was performed at an early stage of the disease in our institution.In addition,our study enabled us to notice the impact of the Coronavirus disease 19 crisis on the management of TC in our institution.Further studies are needed to establish the epidemiological profile of TC in Tunisia and to assess its clinical and pathological features.

关键词： coronavirus disease 19 epidemiology papillary thyroid carcinoma papillary thyroid microcarcinoma pathology thyroid carcinoma

Revolutionizing Healthcare—The Integration of Virtual Worlds, AR, and Metaverse Technology

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Open Journal of Applied Sciences 2024年第1期14卷 27-37页

作者： fatma Kilic The View Hospital Doha Qatar

This paper explores the transformative impact of virtual worlds, augmented reality (AR), and the metaverse in the healthcare sector. It delves into the ways these technologies are reshaping patient care, medical education, and research, while also addressing the challenges and opportunities they present. The paper highlights the potential benefits of these technologies and emphasizes the need for comprehensive regulatory frameworks and ethical guidelines to ensure responsible integration. Finally it outlines their transformative impact and discusses the challenges and opportunities they present for the future of healthcare provision.

关键词： Virtual Worlds Augmented Reality Metaverse Healthcare Patient Care Medical Education Research Transformative Technologies Regulatory Frameworks Ethical Guidelines

A Hybrid Cybersecurity Algorithm for Digital Image Transmission over Advanced Communication Channel Models

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Computers, Materials & Continua 2024年第4期79卷 201-241页

作者： Naglaa F.Soliman fatma E.Fadl-Allah Walid El-Shafai Mahmoud I.Aly Maali Alabdulhafith Fathi E.Abd El-Samie Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

The efficient transmission of images,which plays a large role inwireless communication systems,poses a significant challenge in the growth of multimedia technology.High-quality images require well-tuned communication standards.The Single Carrier Frequency Division Multiple Access(SC-FDMA)is adopted for broadband wireless communications,because of its low sensitivity to carrier frequency offsets and low Peak-to-Average Power Ratio(PAPR).Data transmission through open-channel networks requires much concentration on security,reliability,and integrity.The data need a space away fromunauthorized access,modification,or deletion.These requirements are to be fulfilled by digital image watermarking and encryption.This paper ismainly concerned with secure image communication over the wireless SC-FDMA systemas an adopted communication standard.It introduces a robust image communication framework over SC-FDMA that comprises digital image watermarking and encryption to improve image security,while maintaining a high-quality reconstruction of images at the receiver side.The proposed framework allows image watermarking based on the Discrete Cosine Transform(DCT)merged with the Singular Value Decomposition(SVD)in the so-called DCT-SVD watermarking.In addition,image encryption is implemented based on chaos and DNA encoding.The encrypted watermarked images are then transmitted through the wireless SC-FDMA system.The linearMinimumMean Square Error(MMSE)equalizer is investigated in this paper to mitigate the effect of channel fading and noise on the transmitted images.Two subcarrier mapping schemes,namely localized and interleaved schemes,are compared in this paper.The study depends on different channelmodels,namely PedestrianAandVehicularA,with a modulation technique namedQuadratureAmplitude Modulation(QAM).Extensive simulation experiments are conducted and introduced in this paper for efficient transmission of encrypted watermarked images.In addition,different variants of SC-FDMA based on the Discrete Wavelet Transform(DWT),Discre

关键词： Cybersecurity applications image transmission channel models modulation techniques watermarking and encryption

Effects of Moringa oleifera aqueous extract on the growth performance,blood characteristics,and histological features of gills and livers in Nile tilapia

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Aquaculture and Fisheries 2024年第1期9卷 85-92页

作者： Mahamoud A.Emam Ramy M.Shourbela Waleed N.El-Hawarry Seham Y.Abo-Kora fatma Abdel-Monem Gad Ashraf M.Abd El-latif Mahmoud A.O.Dawood Histology Department Faculty of Veterinary MedicineBenha UniversityBenha13511Egypt Department of Animal Husbandry and Animal Wealth Development Faculty of Veterinary MedicineAlexandria UniversityAlexandria22758Egypt Pharmacology Department Faculty of Veterinary MedicineBenha UniversityBenha13511Egypt Clinical Pathology Department Faculty of Veterinary MedicineBenha UniversityBenha13511Egypt Department of Aquatic Animal Diseases and Management Faculty of Veterinary MedicineBenha UniversityBenha13511Egypt Animal Production Department Faculty of AgricultureKafrelsheikh UniversityKafr El-Sheikh33511Egypt The Center for Applied Research on the Environment and Sustainability The American University in CairoCairo11835Egypt

Moringa oleifera is well known as a highly nutritious plant and a water purifier in fish culture.Tilapia fish has many impressive qualities making them very suitable for aquaculture.Therefore,this study aimed to evaluate the effect of supplementation of Moringa oleifera aqueous extract(MOAE)at varying concentrations(0,100,200,and 400 mg/kg diet for 90 days)on growth performance,hematological,and some biochemical parameters of Nile tilapia.Additionally,histological changes and immunohistochemical expression of caspase 3 in gills and livers were evaluated.Significant enhancements(P<0.05)in the final weight,weight gain,specific growth rate,red blood cells,hemoglobin,packed cell volume,white blood cells,and total serum protein were observed in fish fed 200 mg MOAE/kg diet compared with other groups.However,a significant reduction(P<0.05)of liver and kidney function tests and non-significant changes in lipid profile were recorded.On the other hand,fish fed 400 mg MOAE/kg diet revealed disturbance in the corresponding parameters.Severe histological degenerative changes were detected in the gills and liver of fish fed 400 mg MOAE/kg diet.In comparison,fish fed 200 mg MOAE/kg diet showed the best histo-architectures of these organs compared with other groups.Concomitant immune expressions of caspase 3 were determined where gills and liver of fish fed 400 mg MOAE/kg diet revealed extensive number of positive caspase 3 cells indicating severe apoptotic features.Accordingly,a dietary MOAE at 200 mg/kg diet is recommended to improve the growth performance,hematological parameters,liver and kidney functions in Nile tilapia.Meanwhile,caution must be considered when using MOAE at a concentration over 200 mg/kg diet.

关键词： Growth performance Liver Gills Moringa oleifera Nile tilapia

CNN Channel Attention Intrusion Detection SystemUsing NSL-KDD Dataset

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Computers, Materials & Continua 2024年第6期79卷 4319-4347页

作者： fatma S.Alrayes Mohammed Zakariah Syed Umar Amin Zafar Iqbal Khan Jehad Saad Alqurni Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer and Information Sciences King Saud UniversityRiyadh11362Saudi Arabia College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Educational Technologies College of EducationImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

Intrusion detection systems(IDS)are essential in the field of cybersecurity because they protect networks from a wide range of online threats.The goal of this research is to meet the urgent need for small-footprint,highly-adaptable Network Intrusion Detection Systems(NIDS)that can identify anomalies.The NSL-KDD dataset is used in the study;it is a sizable collection comprising 43 variables with the label’s“attack”and“level.”It proposes a novel approach to intrusion detection based on the combination of channel attention and convolutional neural networks(CNN).Furthermore,this dataset makes it easier to conduct a thorough assessment of the suggested intrusion detection strategy.Furthermore,maintaining operating efficiency while improving detection accuracy is the primary goal of this work.Moreover,typical NIDS examines both risky and typical behavior using a variety of techniques.On the NSL-KDD dataset,our CNN-based approach achieves an astounding 99.728%accuracy rate when paired with channel attention.Compared to previous approaches such as ensemble learning,CNN,RBM(Boltzmann machine),ANN,hybrid auto-encoders with CNN,MCNN,and ANN,and adaptive algorithms,our solution significantly improves intrusion detection performance.Moreover,the results highlight the effectiveness of our suggested method in improving intrusion detection precision,signifying a noteworthy advancement in this field.Subsequent efforts will focus on strengthening and expanding our approach in order to counteract growing cyberthreats and adjust to changing network circumstances.

关键词： Intrusion detection system(IDS) NSL-KDD dataset deep-learning machine-learning CNN channel Attention network security