bluuebunny/crossref_metadata_2025 huggingface dataset:
Conocimiento de organismos bióticos acuáticos heterotróficos (macroinvertebrados) acumulados en las capas sedimentarias del Lago Cocibolca de los últimos 100 años
Authors: Ráudez Reyes Scarleth Margarita , Cano Espinoza Roberto Antonio , López Palma Jairo Luis
Published: November 2021

El lago Cocibolca es el ecosistema de agua dulce más grande de América Central y recientemente ha ganado la atención de la comunidad científica internacional ante la construcción planeada del canal interoceánico que potencialmente podría cruzar e impactar este sistema. Este estudio pretende realizar una reconstrucción cualitativa utilizando proxies biológicos heterotróficos (macroinvertebrados) y su relación con eventos naturales extremos conocidos, así como actividades antropogénicas claves. A través del análisis de 210Pb se analizaron dos núcleos de alta resolución del lago Cocibolca, para el último siglo ~100 años, los cuales fueron recolectadas: uno en la zona oriental (PLNI), y otro cerca de la Isla de Ometepe (PLNII). Relativo a los chironomidos, se observó un bajo número de restos fósiles, los que concuerdan con los registros limnológicos del Lago, donde esta comunidad exhibe bajas proporciones. Las altas tasa de erosión y sedimentación principalmente en la cuenca sur, aportan al sistema abundante material rico en nutrientes, los que modifican la productividad del ecosistema. En consecuencia, la comunidad de ensamblajes bénticos se ha transformado, favoreciendo a las especies oportunistas y mejor adaptadas a los eventos climatológicos extremos que suman a acrecentar los problemas de enriquecimiento, anudado con las actividades antrópicas que siguen generando cambios y avances en el estado trófico del lago Cocibolca.
MICROSCOPIC AND PHYTOCHEMICAL EVALUATION OF CALOTROPIS GIGANTEA
Authors: Choudhary N. K , Sharma S. , Goyal S. , Dwivedi J. ,   Mandsaur Institute of Pharmacy, Mandsaur - 458 001, Madhya Pradesh, India.
Published: November 2021

In traditional system of medicine, Calotropis gigantea (Akra) has been used for treatment of various diseases. Since, there is no proper information regarding pharmacognostic parameters of flowers of this plant, our efforts were devoted to study the microscopical characters and phytochemical study of flowers of this plant. Microscopic evaluation of gynostegium, sepal/ calyx, petal, ovary and pedicel were undertaken, determination of ash and extractive values, phytochemical screening and TLC for presence of triterpenoids. The microscopic characterization of the parts of the flower i.e. gynostegium, sepal/ calyx, petal, ovary and pedicel of Calotropis gigantea was performed. The physicochemical characterization‘s gave ash values (total ash: 18.60; acid insoluble ash: 5.46; water soluble ash; 13.50) and extraction with petroleum ether, chloroform and 90% ethanol extract gave 2.4, 3.9 and 2.1% w/w, respectively. TLC of chloroform extract showed the presence of triterpenoids. The microscopic study of the flower of Calotropis gigantea give us the foot prints for further study with the presence of triterpenoids in the flowers.
SYNTHESIS, SPECTRAL STUDIES, STRUCTURAL EVALUATION AND ANTIMICROBIAL ACTIVITY OF SOME NOVEL C R(III) COMPLEXES CONTAINING TETRADENTATE MACROCYCLIC LIGANDS
Authors: Shukla S , Gautam S. , Chandra S , Kumar A. ,   Department of chemistry, Dyal singh college, University of Delhi, lodi road, new Delhi - 110 003, India.
Published: November 2021

A string of novel coordination compounds of Cr(III) complexes have been derived and characterized from the macrocyclic ligands (L 1 -L 2 ) carried out by condensation reaction between ligands and the subsequent metal salt. The chemical composition of ligand was determined by analytical and spectral techniques i.e. elemental analysis, IR and Mass spectrocopy. Spectral techniques revealed tetradentate [N 4 ] the nature of ligand and its coordination mode to metal ion through nitrogen donor atoms. Metal complexes were characterized by elemental analyses, molar conductance, magnetic susceptibility measurements, IR, electronic spectra, ePR studies. The geometry of these complexes was ascertained by molecular modelling study by using Gaussian 09 program. All metal complexes were found to exhibit octahedral geometry around the metal ion. The newly synthesized macrocyclic ligands and metal complexes were subjected for antimicrobial screening to determine the inhibition and control against tested microorganisms, bacteria ( S.lutea , S.aureus, S.albus and E.coli ) and fungi ( A.fulviceps, U . hordei, A. niger and P.catinus ) by using disc diffusion method and agar plate technique, respectively. The experimental results suggest that metal complexes exhibit enhanced inhibition zone than free macrocyclic ligand.
EX VIVO PERFORMANCE STUDY OF LEVOFLOXACIN OCULAR NANOPARTICLES
Authors: Kashikar V. , Keche P. , Kulkarni A. ,   Departments of Pharmaceutics, Modern College of Pharmacy (L), Moshi - 412 105, Pune, Maharashtra, India.
Published: November 2021

Polymeric nanoparticles (NPs) of levofloxacin prepared from Eudragit RL 100 and RS 100 have been investigated extensively for ocular delivery. We developed nanoparticles by two techniques viz. 1) solvent displacement method and 2) double emulsion method and characterized for XRD, IR, percent entrapment efficiency, polydispersity, zeta potential, ex vivo transcorneal permeation and stability. The percent transmittance of optimized formulation E1 and A2 was found to be 63.20% and 80.67%, respectively. Particle size of E1 & A2 was found to be 441.70nm and 452.10nm, respectively. The polydispersity was found to be 0.3 and 0.5, respectively. Observed zeta potential values of E1 was +22.00mV and for A2 it was +20.42mV. the values decreased as the concentration of polaxomer increased. The nanoparticles were found to show sustained drug release for more than 7h. The resulting nanoparticles were found to be stable and promising in reducing dose frequency and improving patient compliance for ocular delivery.
GLORIOSA SUPERBA L. – AN ENDANGERED PLANT OF TAMILNADU, YET TO BE EXPLORED AND NEED TO BE CONSERVED
Authors: Rajeswari P. , Samuel P , Sudarmani D. N. P , Amirtharaj K , Deenathayalan R ,   Department of Biotechnology, Ayya Nadar Janaki Ammal College (Autonomous), Sivakasi - 626 123, Tamilnadu, India.
Published: November 2021

Gloriosa superba L. is commonly being called as glory lily. This perennial climber is designated as the State flower of Tamilnadu. It is extensively cultivated for colcichine, an alkaloid obtained from the seed being exploited for its medicinal properties. The present investigation on this climber was started with an intention to bring out the biomedical potentials with special reference to its anticancer properties. The plant was extracted with methanol and ethyl acetate using Soxhlet extraction unit and the extract was concentrated using vacuum rotavapor. The presence of 15 different compounds in methanol fraction and 1 compound in ethyl acetate fraction were determined by GC-MS. Extensive literature survey suggested that few records was available on anticancer properties of Gloriosa superba L. Hence, an attempt was made to evaluate its anticancer potentials The IC50 value of the compound against MCF7 cell line was found to be 84.23μg/mL.
ANALGESIC, ANTIPYRETIC AND ANTI-INFLAMMATORY ACTIVITIES OF MORINGA OLEIFERA
Authors: Swapna Reddy M. , Ramya Kuber B. ,   Dept of Pharmacognosy Sri Padmavathi Mahila Visvavidyalayam, Tirupathi - 506 005, Andhra Pradesh, India.
Published: November 2021

Moringa oleifera is a potent medicinal plant in the Indian system of medicine. It is used in treatment of eye infections, arthritis, fever and as aphrodisiac. In the present study, qualitative chemical tests confirmed the presence of glycosides, amino acids, phytosterols, carbohydrates and phenolic compounds. The petroleum ether, ethyl acetate and methonolic extracts of leaves of Moringa oleifera were studied for its analgesic activity using tail immersion method, anti-pyretic activity by brewer’s yeast induced pyrexia method and anti-inflammatory activity by carragenean induced rat paw oedema method on healthy wistar rats. It was observed that among all the extracts, methanolic extract produced significant effects.
SEARCH FOR ANTIMICROBIAL AGENTS: QUINOXALINE AS A PROMISING TARGET
Authors: Ingle R. G , Wadher S. J. ,   School of Pharmacy, SRTM University, Nanded - 431 606, Maharashtra, India.
Published: November 2021

A set of ten new 2,3-diphenyl-6-sulfonamido quinoxaline derivatives was synthesized and screened for antimicrobial activity by disk diffusion method. Test derivatives R3, R5, R’’1 and R’’2 show promising results against bacterial strains S. aureus gram positive and E. coli gram negative organism with the concentration 1000 μg/mL in disk diffusion method. Rest of the derivatives show sensitivity against the same organisms. All the synthesized derivatives were confirmed by their spectral data.
STEROIDAL CONSTITUENTS AND A FATTY ACID ESTER FROM THE FRUIT PEELS OF CITRUS SINENSIS (L.) OSBECK
Authors: Khan Md. A , Abuzer A , Mohammed A. ,   Montajat Veterinary Pharmaceuticals Co., Ltd., 2nd industrial city, Dammam - 31491, Saudi Arabia.
Published: November 2021

Citrus sinensis (L.) Osbeck (Rutaceae), is distributed in tropical and temperate regions of India, China, Mexico, Congo and East Africa. Its fruit peel is carminative, stomachic, tonic and is used to cure acne, earache, anorexia, colds, coughs and toothache. The essential oil is antiseptic, anti-inflammatory and effective to relieve bronchitis, colic, constipation, cramps, depression, fluid retention, gastritis, motion sickness, mouth ulcers, nervous tension, obesity, and stress. The phytochemical investigation of a methanolic extract of the fruit peels of C. sinensis afforded three new compounds, characterized as 11′β-hydroxyl-n-octadecanyl n-hexacosanoate (11′ β-hydroxyl-n-octadecanyl cerotate, 1), stigmast-5-en- 3α-ol-23-one (sinensisterol, 3) and β-sitosterol-3-O-β-D-glucopyranosyl-2′-laurate (β-sitosterol glucosyl laurate, 5) together with the known compounds n-hexacosanoic acid (cerotic acid, 2) and stigmasterol 3-O-β-D-glucoside (4). The structures of the isolated phytoconstituents were established on the basis of spectral data analysis and chemical reactions.
DEVELOPMENT AND EVALUATION OF BICOMPONENT COCRYSTALS OF ACECLOFENAC FOR EFFICIENT DRUG DELIVERY WITH ENHANCED SOLUBILITY AND IMPROVED DISSOLUTION
Authors: Pekamwar Sanjay S. , Kulkarni Deepak A. ,   a Department of Pharmaceutical Sciences, School of Pharmacy, S.R.T.M. University, Nanded- 431 606, Maharashtra, India
Published: November 2021

This research work was intended to improve the solubility and dissolution of aceclofenac by the development of bicomponent cocrystals. Bicomponent cocrystals of aceclofenac were prepared with ten different cocrystal formers (CCF) by neat grinding techniques. Solubility analysis of cocrystals showed that aceclofenac-salicylic acid cocrystals have comparatively better solubility than the other cocrystals. The solubility of pure aceclofenac (309.23 µg/mL) was found to be improved by seven folds (2424.61 µg/mL) due to the formation of bicomponent crystalline form with salicylic acid. In vitro dissolution also revealed that the immediate release tablet of aceclofenac showed a release of 58.87±1.39 %, while aceclofenacsalicylic acid cocrystal tablet showed drug release of 92.65±1.21 % after 60 minutes. Results of Differential Scanning Colorimetry (DSC), Powdered X-Ray Diffraction (PXRD) and Raman spectroscopic analysis also justified the formation of the novel crystalline form. The developed bicomponent cocrystals of aceclofenac improved the solubility and dissolution of aceclofenac to a significant extent.
Floristic composition, biological spectrum and conservation status of a sacred grove from Jhargram district, West Bengal, India
Authors: Sen U. , Bhakat R.
Published: November 2021

Social practices play a crucial role in the conservation of the environment and biodiversity. The present study was carried out to explore the plant resources, their biological spectrum, leaf size spectra, conservation status and management of the existing vegetation of a sacred grove, namely Kalua Sarnd Than (KST) in the Jhargram district of West Bengal in India. Floristic elements of the study area revealed that the vegetation was diverse and composed of 150 species belonging to 141 genera distributed over 60 families under 31 orders according to APG IV classification. The study area being a sacred grove is fairly undisturbed and protection of germplasm in the grove is maintained through the traditional beliefs. The present study, thus, could be used as an inspiring example in India for other sacred groves for phytoclimatic study.
Acmella radicans (Jacq.) R.K. Jansen (Asteraceae): An addition to the flora of Bihar
Authors: Kumar Anand , Biswa Shyam , Krishna Gopal
Published: November 2021

Acmella radicans (Jacq.) R.K. Jansen is reported first time from Bihar. Detailed description, photo plate, notes and key to species from Bihar, are provided here for easy identification in the field.
Abutilon pannosum (G. Forst.) Schlect. (Malvaceae)- A New Addition to the Flora of Bihar, India
Authors: Singh Harish , Mishra M. , Dhole P.
Published: November 2021

Abutilon pannosum (G.Forst.) Schlect. (Malvaceae) is reported as a new distributional record for the flora of Bihar state. Updated nomenclature, brief description, phenology, distribution along with field photographs are provided for easy identification in the field.
Cynanchum corymbosum Wight: A New Plant Record For Arunachal Pradesh, India
Authors:   University of Patanjali, Haridwar, Uttarakhand, India, PIN : 249405, Balkrishna Acharya ,   Patanjali Herbal Research Department, Patanjali Research Institute, Haridwar, Uttarakhand, India, PIN : 249405, Srivastava Anupam ,   Patanjali Herbal Research Department, Patanjali Research Institute, Haridwar, Uttarakhand, India, PIN : 249405, Shankar Rama ,   Patanjali Herbal Research Department, Patanjali Research Institute, Haridwar, Uttarakhand, India, PIN : 249405, Prajapati Uday Bhan ,   Patanjali Herbal Research Department, Patanjali Research Institute, Haridwar, uttarakahnd, India, PIN : 249405, Mishra Rajesh Kumar ,   Patanjali Herbal Research Department, Patanjali Research Institute, Haridwar, Uttarakhand, India, PIN : 249405, Kumar Aashish ,   Patanjali Herbal Research Department, Patanjali Research Institute, Haridwar, Uttarakhand, India, PIN : 249405, . Aqib ,   Patanjali Herbal Research Department, Patanjali Research Institute, Haridwar, Uttarakhand, India, PIN : 249405, Sharma Sangam ,   Patanjali Herbal Research Department, Patanjali Research Institute, Haridwar, Uttarakhand, India, PIN : 249405, Kumar Amit ,   Patanjali Herbal Research Department, Patanjali Research Institute, Haridwar, Uttarakhand, India, PIN : 249405, Joshi Bhasker ,   Patanjali Herbal Research Department, Patanjali Research Institute, Haridwar, Uttarakhand, India, PIN : 249405
Published: November 2021

The present paper deals with the new record of Cynanchum corymbosum Wight (Apocynaceae), for Arunachal Pradesh, India, with detailed taxonomic citation, botanical description, phenology along with ecological notes of the species.
An Inventory of Flowering Plants of Ameenpur Lake - A Biological Heritage Site, Telangana State
Authors: Sailu G. , Devi B. , Chandramohan K.
Published: November 2021

Ameenpur Lake is located in Medak district of Telangana State. It was recently declared as “Biological heritage” site in state of Telangana under section-37 of the Biological Diversity Act, 2002. This lake is breeding habitat for the migratory birds in the winter season, keeping this in view, it was declared as biological heritage site. The present inventory of floral resources was carried out during the period 2016-18 around the Ameenpur Lake. During the study period an intensive exploration was done and all flowering plant species were documented. The study revealed the occurrence of 180 flowering plant species belonging to 62 families.
Proposed Risk Diagnosing Methodology for ERP Implementation Project in SMEs
Authors:   Faculty of Computer Science, Misr International University (MIU), Egypt, .. Abdel Nasser H. ,   Dept. Decision Support, Faculty of Computers and Informatics, Zagazig University (ZU), Egypt, Mohmed Shaimaa
Published: November 2021

The implementation of ERP projects is a specific case of information system projects that require modifying pre-produced software according to the condition specified for an organization to fulfill particular benefits. ERP systems adoption is a complicated, lengthy, risky, and costly process for all sizes of organizations that usually faces critical failures and challenges. Especially for SMEs with limited capabilities and resources, they lack the experience of requirement specification and ERP implementation. This failure could be costly and may cause corporate bankruptcy. This study proposes a Risk Diagnosing Methodology for implementing ERP projects in SMEs (RDMERP). The proposed methodology is systematic and a global road to proactively identify, assess, analyze, and treat the various risks associated with any ERP implementation through all the phases for protecting the SMEs’ assets and mission and meeting the ERP project objectives.
Feature Selection Optimization Model for Business Risk Assessment Model
Authors:   College of Business Administration, American University in the Emirates, Dubai, UAE, Metawa Noura ,   College of Computer and Information Technology, American University in the Emirates, Dubai, UAE, Elhoseny Mohamed
Published: November 2021

Financial risk assessment becomes a hot research topic among financial firms or companies to assess the financial status and thereby avoid future crises. Earlier studies have focused on statistical models for the assessment of financial risks and the recently developed machine learning (ML) models find useful to improve the assessment performance. In this aspect, this study introduces a novel Butterfly Optimization based Feature Selection with Classification Model for Financial Risk Assessment (BOFS-CFRA) technique. The proposed BOFS-CFRA technique involves pre-processing at the primary stage to get rid of unwanted data. In addition, K-means clustering approach is developed to group the financial data into clusters. Then, the BOFS technique is applied to choose the subset of features from the clustered data. Finally, the classification of financial risks takes place by the use of functional link neural network (FLNN). In order to ensure the enhanced performance of the BOFS-CFRA technique, a series of simulations were carried out and the results are inspected under various measures. The simulation outcome portrayed the supremacy of the BOFS-CFRA technique over the other financial risk assessment models in terms of several performance measures.
A Blockchain-Based Voting System for E-Elections in Totalitarian States
Authors:   Department of Computer Engineering, Science and Research Branch, Islamic Azad  University, Tehran, Iran, shafiabadi Mohammad Hossin ,   Department of Computer Engineering, IslamShahhr Branch, Islamic Azad University, IslamShahr, Iran, shafiabadi Mohammad Hossin
Published: November 2021

The purpose of the present research was to introduce a blockchain-based voting system so that any state, including totalitarian states, can show interest in using it. In this method, a hybrid voting system with two centralized and distributed systems was used. Its centralized system is one of the most common voter identification and polling models, and its distributed system, which is designed with Ethereum public blockchain, is voting for voters. Totalitarian states are not interested in announcing the results online. Also, the lack of trust in E-voting systems by both states and voters has led to E-voting in important political elections in most states as support for manual or paper voting. Based on the results of field research with this voting system, it was possible to create a 7 min break between the end of the voting process and the announcement of the results for political considerations. This break can be increased by agreement. The results of the votes cannot be manipulated in any way. Survey results should also be communicated to voters before the voting process. This voting system can improve the level of democracy and maximum participation. It is hoped that the spread of distributed technologies, especially the blockchain, will pave the way for the spread of justice and democracy around the world.
The Impact of Free Cash Flows to the Financial Flexibility of the Banks listed in the Colombo Stock Exchange
Authors:   University of Kelaniya, SRI LANKA, .. Nadhira ,   College of Business Administration, Delta University for Science and Technology, Gamasa City, Dakhliya, Egypt, Metawea Maha Saad
Published: November 2021

There are considerable arguments in favour of and against the positive relationship between free cash flows (FCF) and financial flexibility. The aim of the study is to determine the impact of free cash flows on the financial flexibility of the banks listed in the Colombo Stock Exchange (CSE). The free cash flow will measure according to the model in Journal of Finance: Agency costs and ownership structure in 2000 and financial flexibility will determine using the financial leverage based on the model captured according to the Accounting Horizons Journal: Financial flexibility and investment decisions in 2007 . The population of the study is the banks listed in the CSE. The sample consists of 60 observations covering 12 banks for a period of over 05 years from 2015 to 2019. The panel regression model has been used to test hypotheses. The results indicate that there is a positive significant relationship between free cash flows and the financial flexibility of the banks listed in CSE.
Parameter Tuned Machine Learning based Decision Support System for Bank Telemarketing
Authors:   Faculty of Commerce, Mansoura University, Egypt, Metawa Noura ,   Faculty of Commerce, Damietta University, Egypt, Elshimy Amany Ahmed
Published: November 2021

In banking sectors, telemarketing is the major support of selling the products or services. Banking advertisement and marketing are mainly depending upon the comprehensive knowledge of objective data regarding the market and the actual client requirements for the bank gainful way. Decision Support Systems (DSS) play a vital part in telemarketing sector, which determines a specific class of automized facts to assist the company to make decisions. Machine learning (ML) is commonly used in the DSS which integrates the data and computer application for precise prediction of results. This paper presents an effective parameter tuned ML based DSS (PTML-DSS) for bank telemarketing sector. The proposed PTML-DSS technique follows a three-level process namely preprocessing, classification, and parameter optimization. Initially, the marketing data is preprocessed to get rid of unwanted information. In addition, gradient boosting decision tree (GBDT) based classifier model is used to classify the data. Besides, firefly algorithm (FFA) is applied for tuning the parameters involved in the GBDT model. In order to verify the improved performance of the PTML-DSS technique, a series of simulations were performed, and the results are inspected under varying aspects. The resultant values reported the improved performance of the PTML-DSS technique over the other techniques.
Intelligent Differential Evolution based Feature Selection with Deep Neural Network for Intrusion Detection in Wireless Sensor Networks
Authors:   Faculty of Computers and Information, Mansoura University, Egypt, EL-Hasnony Ibrahim M. EL
Published: November 2021

Wireless sensor network (WSN) is mainly utilized for data gathering and surveillance applications. As WSN is majorly deployed in harsh and hostile environments, security remains a critical issue which needs to be resolved. An intrusion detection system (IDS) is one of the proficient ways used to determine the presence of abnormal behaviors (i.e. intrusions) in the network. Earlier studies have focused on the design of machine learning (ML) and deep learning (ML) models to design IDS. With this motivation, this paper presents an intelligent differential evolution based feature selection with deep neural network (IDEFS-DNN) for intrusion detection in WSN. The proposed IDEFS-DNN model aims to select optimum set of features and classify the intrusions in the network. In addition, the IDEFS-DNN technique involves the design of IDEFS technique to choose a subset of optimum features. Moreover, the chosen features are fed into the DNN technique for classification purposes. The usage of IDEFS technique helps to reduce the complexity and increase the classifier outcome. In order to portray the improved performance of the IDEFS-DNN technique, wide ranging experiments take place on benchmark datasets and the results are inspected under varying aspects. The simulation results ensured the enhanced intrusion detection performance of the IDEFS-DNN technique over the other IDS models.
A comparative study on Internet of Things (IoT): Frameworks, Tools, Applications and Future directions
Authors:   Information Systems Department, The Higher Technological Institute, Egypt, Mohamed Mona
Published: November 2021

The proliferation of the smart and sensing devices in the field of communicating networks support in to develop the so-called Internet of Things (IoT). IoT considers a new paradigm for evolutionary of internet connectivity. IoT refers to connect objects around the real world with the Internet to accomplish the common goals and monitor these objects via wire/wireless communications. It plays a large and important role in human life through its use in many applications of human interest. Through using a variety of enabling wireless technologies as Wireless Sensor Networks (WSN), Radio Frequency Identification (RFID), Near Filed Communication (NFC), and barcode in the applications. These technologies will support IoT to transform the internet into a fully integrated future internet. This paper attempts to provide a comprehensive survey of the available literature related to IoT technologies and its applications in many areas of modern-day living. Identify the trend and directions of future research in IoT applications, depend on a comprehensive literature review and the discussion of the achievements of the researchers.
A survey on gel images analysis software tools
Authors:   Computer Science Department, Faculty of Computers and Informatics, Zagazig University, H.Alnamoly Mahmoud , Alzohairy Ahmed M. ,   Genetics Department, Faculty of agriculture, Zagazig University, El-Henawy Ibrahim M. ,   Computer Science Department, Faculty of Computers and Informatics, Zagazig University, Egypt
Published: November 2021

One of the most severe sources of information for a molecular biologist is the gel image generated by using gel electrophoresis during the experiment of issr-pcr, sds-pages, and rapd-pcr. DNA and protein gel images are obtained through the gel electrophoresis separations techniques of DNA and protein fragments. The separation of the polymorphic bands is based on the sizes of the negatively charged DNA fragments running from the negative cathode toward the positive anode. Each gel image has some vertical lanes; each lane corresponds to one sample and has several horizontal bands. The resulting images produced by Gel electrophoresis are sometimes difficult to interpret so that it was important to develop software tools to analyze the gel images to help biologists in the process of analyzing gel image as they draw their conclusions according to the results that generated from gel image analyzer software. In this article, we present a survey of some commercial and non-commercial software tools that are used for analyzing gel images. We develop a novel software for processing and analyzing the gel electrophoresis images, computing the molecular weights, saving them as excel sheet, clustering the bands based on their molecular weights using k-means algorithm, Applying band matching using a tolerance value entered by the user, determine the similarities between samples, drawing the corresponding phylogenetic tree, saving a report of the experiment as a pdf, and printing this report. The novel software will provide the biologist with the ability of manual processing, automatic processing, and semi-automatic processing.
Autism Spectrum Diagnosis using Adaptive Learning Algorithm for Multiple MLP Classifier
Authors:   Department of Computer Engineering, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran, Safara Fatemeh
Published: November 2021

A medical condition that causes disability and early neurological and cognitive condition is autism spectrum disorder (ASD). Gene expression and environment have an impact on this medical condition. Development of diagnostic instruments and skills improved the autism recognition and increased the society awareness about it. To cope with this disorder collaboration between families, service providers, and autistic individuals is a necessity. Early diagnosis of ASD could help in lessening stress, increase adaptation, and support welfare in healthcare systems. Therefore, a large body of research is attempting to provide an intelligent medical diagnostic system to identify and diagnose ASD in early stages using machine learning methods. In this paper, several multilayer perceptron neural network is proposed for ASD detection in healthcare systems. The learning rate is adaptively tuned to achieve the best results. The results show that the approach proposed in this study achieved 99.6% accuracy, which indicates the superiority of the proposed method in identifying and detecting autism disorder in comparison with similar previous methods.
ECG signal monitoring based on Covid-19 patients: Overview
Authors:   Laboratory of Systems Engineering and Information Technology LISTI, National School of Applied Sciences, Ibn Zohr University Agadir, Morocco, Bella Amine Saddik *, Rachid Latif  and Abdoullah
Published: November 2021

ECG signal monitoring is a very important step for patients. Especially for those infected by covid-19. This pandemic has shown that the use of artificial intelligence helps to control the propagation of this virus. Particularly the high spread of this virus influences the number of the infected population. As well as the fact that this virus attacks the respiratory system which influences the cardiac system. Therefore, an ECG signal monitoring is mandatory. Our work presents an overview based on various approaches developed for ECG signal monitoring. These techniques are based on non-contact monitoring approaches. These approaches will help to avoid frequent contact with patients and doctors. As well as non-contact ECG signal monitoring is based on low-cost techniques, which reduces the price compared to other sensors. After the revision, we can conclude that the most suitable solution for heart rate monitoring is based on image processing using RGB cameras. These solutions are accurate, low cost, and protect the doctors.
Solving the Problem of Target k-Coverage in WSNs Using Fuzzy Clustering Algorithm
Authors:   Department of Computer Engineering, IslamShahhr Branch, Islamic Azad University, IslamShahr, Iran, .. Mohammad Hossein ,   Department of Computer Engineering, Adiban Institute of Higher Education, Garmsar, Semnan, Iran,   Department of Computer Engineering, Science and Research Branch, Islamic Azad  University,Tehran, Iran, .. Zohre , Esfandyari Mohammad Reza
Published: November 2021

The purpose of the present research was to introduce an algorithm to solve the coverage problem in wireless multimedia networks that can be used to optimize energy consumption and network lifetime. In this regard, the problem of target k-coverage in WSNs was solved by dividing the environment into the proportional area and random selection. This can be done using a fuzzy clustering algorithm. It is worth noting that the results of the proposed algorithm were compared with previous methods such as genetic and annealing algorithm. The simulation results and comparison with other algorithms show a 27% superiority of the proposed algorithm. It is hoped that this method can be used in networks with larger dimensions in the future
A Novel Artificial Intelligence Based Internet of Things for Fall Detection of Elderly Care Monitoring
Authors:   Department of Biomedical Engineering, VelTech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai, India, Gopinath Gopinath ,   Department of Biomedical Engineering, VelTech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai, India.,   Department of Biomedical Engineering, VelTech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai, India,   Department of Biomedical Engineering, VelTech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai, India,   Department of Biomedical Engineering,L.D. College of Engineering, Ahmedabad.India,   Bharath Institute of Higher Education and Research,Chennai, India, G.V. Kirubasri G. , Sasikumar Haritha , .. Yazhini , Patil Jagruti , Gopinath Gopinath
Published: November 2021

A fall of an older adult often leads to severe injuries and is found to be a significant reason for the death due to post-traumatic complications. Many falls happen in the home atmosphere and prevail unrecognized. Thus, the need for reliable early fall detection is necessary for fast help. Lately, the emergence of wearables, smartphones, IoT, etc., made it possible to develop systems fall detection which aids in the remote monitoring of the elderly. The goal is to allow intelligent algorithms and smartphones to detect falls for elderly care and to monitor them regularly. This work presents the Artificial Intelligence of Things for Fall Detection (AIOTFD) system using a slime mould algorithm (SMA) to optimize the final data. The features extracted using SqueezeNet further CNN based SMA used for data optimization. The validation of the AIOTFD model performance is evaluated through the Multiple Cameras Fall Dataset (MCFD) and UR Fall Detection dataset (URFD). The empirical results accentuated the assuring realization of the model compared to other state-of the art methods.The obtained results shows our proposed AIOTFD attains accuracy of 99.82% and 99.79% and databases can be used for additional investigation and optimizations to increase the recognition rate to enhance the independent life of the elderly.
Optimized Resource Allocation Algorithm for Crowd-Creation Space Computing Based on Cloud Computing Environment
Authors:   Digital Charging Solutions GmbH, Germany, .. Mustafa El ,   University of Technology and Applied Science, Shinas, Oman, Y.Kraidi Aaras Y
Published: November 2021

The crowd-creation space is a manifestation of the development of innovation theory to a certain stage. With the creation of the crowd-creation space, the problem of optimizing the resource allocation of the crowd-creation space has become a research hotspot. The emergence of cloud computing provides a new idea for solving the problem of resource allocation. Common cloud computing resource allocation algorithms include genetic algorithms, simulated annealing algorithms, and ant colony algorithms. These algorithms have their obvious shortcomings, which are not conducive to solving the problem of optimal resource allocation for crowd-creation space computing. Based on this, this paper proposes an In the cloud computing environment, the algorithm for optimizing resource allocation for crowd-creation space computing adopts a combination of genetic algorithm and ant colony algorithm and optimizes it by citing some mechanisms of simulated annealing algorithm. The algorithm in this paper is an improved genetic ant colony algorithm (HGAACO). In this paper, the feasibility of the algorithm is verified through experiments. The experimental results show that with 20 tasks, the ant colony algorithm task allocation time is 93ms, the genetic ant colony algorithm time is 90ms, and the improved algorithm task allocation time proposed in this paper is 74ms, obviously superior. The algorithm proposed in this paper has a certain reference value for solving the creative space computing optimization resource allocation.
Intelligent System for Forecasting Failure of Agile Projects
Authors:   Nova Information Management School, Universidade Nova de Lisboa, 1070-312, Lisboa, Portugal, Abdelaziz Ahmed ,   Nova Information Management School, Universidade Nova de Lisboa, 1070-312, Lisboa, Portugal, Mahmoud Alia N
Published: November 2021

Revealing the failure of agile software projects is a great challenge faced by software companies. This paper focuses on the using of intelligent techniques such as fuzzy logic, multiple linear regressions, support vector machine, neural network to address this challenge. This paper also presents a review of some works related to this area of interest. In this paper, the researchers propose an approach for revealing the failure of agile software projects based on two intelligent techniques: fuzzy logic and multiple linear regressions (MLR). MLR is used to determine crucial failure factors of agile software projects. Fuzzy logic is used for revealing failure of agile software projects.
Automated Deep Learning based Video Summarization Approach for Forest Fire Detection
Authors:   Artificial Intelligence Department, Dubai Police, Dubai, UAE, Al-Masri Ahmed N. Al ,   American University in the Emirates, Dubai, UAE, Al-Masri Ahmed N. Al
Published: November 2021

Due to the exponential increase in video data, an automated examination of videos has become essential. A significant requirement is the capability of the automated video summarization process, which is helpful in vast application areas from surveillance to security. It assists in monitoring the user application with reduced memory and time. Therefore, this paper designs an automated deep learning-based video summarization approach for forest fire detection (ADLVS-FFD). The ADLVS-FFD technique aims to summarize the captured videos and detects the existence of forest fire in it. In addition, the ADLVS-FFD technique involves different subprocesses such as frame splitting, feature extraction, and classification. Besides, a merged Gaussian mixture model (MGMM) is used to extract keyframes and features. Moreover, the long short-term memory (LSTM) model is employed to detect and classify input images into normal and forest fire images. To ensure the better performance of the ADLVS-FFD technique, a comprehensive experimental validation process takes place on a benchmark video dataset. The resultant experimental validation process highlighted the supremacy of the ADLVS-FFD technique over the recent methods.
The IMPLEMENTATION OF SYSTEM DOOR ACCES USING FACE RECOGNITION AND FINGER PRINT FOR MUNITIONS WAREHOUSE WITH A BASE HAAR CASSCADE
Authors: Asari M. Sofyan , Minggu Desyderius , Mahfudi Isa
Published: November 2021

Abstract: Technology in the military world has been growing with the existence of technological innovations that are used to secure munitions warehouses. This is done to reduce the negligence of the munitions warehouse guard personnel if they lose the key from the munitions warehouse it can be monitored in real-time to find out who is around the munitions warehouse door. Thus, face recognition and fingerprint technology were created as a system for securing munitions warehouses, as well as the function is to be a CCTV. So, they can be monitored in real-time. This research method uses an experimental method to obtain quantitative data to prove the hypothesis data that use the Haar Cascade. The results of this study indicate that this security system has a very important role to limit access to and from the munitions warehouse and reduce the occurrence of theft or misuse of munitions. In the tests carried out, the minimum detection distance was 20 cm and the maximum distance that was able to detect was 110 cm. this is influenced by the focus of the camera and testing of the intensity of light in the morning, afternoon, evening, and night can be detected except detection at night without light and must use a fingerprint.
SC Pegasianum
Authors: Aličić Samir
Published: November 2021

The paper discusses a senate’s decision made in the 1st century AD upon the proposal of jurist Pegasus, which regulated the matter of fideicommissa. In addition to other public duties, it is likely that this jurist, about whose origin and life we know little about, was for a certain period of time the governor of the province of Dalmatia (Illyricum) under Emperor Vespasian, several decades after Publius Cornelius Dolabella. The author explores the reasons for  enactment of SC Pegasianum, and seeks to prove that the senate decision was  part of a wider project to reform the Roman testament in the 1 st  century. He also deals with the legal consequences of the adoption and implementation of the senate’s decision.
Veri Artırımı için Yarı-Denetimli Bağlamsal Anlam Belirsizliği Giderme
Authors: TORUNOGLU SELAMET Dilara , CEBİROĞLU ERYİĞİT Gülşen
Published: November 2021

Yapay zekâ alanında son dönemlerde öne çıkan derin öğrenme mimarilerinin, doğal dil işleme konusunun önemli problemlerinden biri olan Anlam Belirsizliği Giderme (ABG) çalışmalarında kayda değer gelişmelere yol açtığı gözlemlenmektedir. Denetimli yöntemler rakiplerine göre daha yüksek performans sergilemektedirler. Bunun en büyük nedeni kullanılan eğitim verilerinin büyüklükleridir. ABG problemi için İngilizce dili üzerinde elle-etiketlenmiş çok miktarda veri çevrim içi olarak erişilebilir durumdadır. Ancak düşük-kaynaklı diller (DKD’ler) probleme uygun veri eksikliği yaşamaktadırlar. Yeterli derecede probleme uygun veri toplamak ve etiketlemek vakit alıcı ve yüksek maliyet gerektiren bir iştir. Bu probleme değinmek ve aşmak üzere, bu çalışmada yarı-denetimli bağlamsal anlam belirsizliği giderme yaklaşımının veri artırımı için (daha sonra denetimli öğrenmede eğitim verisi olarak kullanılmak üzere) kullanılabileceğinin gösterilmesi amaçlanmıştır. Bu bağlamda özellikle DKD’lerde ABG problemi için test verisi bulmanın zor olması nedeniyle yaklaşımın doğruluğunu ve ilerleyen dönemlerde DKD’lerde kullanılabilirliğini ispatlamak amacıyla çevrimiçi bulunan elle-etiketlenmiş İngilizce ABG verisi kullanılmıştır. Oluşturulan yarı-denetimli yöntemde öbek kümesi (seed set) ve bağlam vektörleri (context embeddings) kullanılmaktadır. Yapılan çalışma 9 farklı bağlamsal dil modelinde (ELMo, BERT, RoBERTa vb.) test edilmiş ve her bir dil modelinin ABG problemi üzerindeki etkileri raporlanmıştır. İlk temel yaklaşıma göre sonuçlar üzerinde %28 doğruluk oranında performans artışı sağlanmıştır. (ELMo ile ilk temel yaklaşım ile %50,39 ve ELMo Anlam Öbek Esaslı Ortalama Benzerlik Modeli ile %78,06). Alınan ilk sonuçlara neticesinde, önerilen yaklaşımın özellikle DKD’ler yönelik ABG veri kümesi oluşturmak için gelecek vaat eden ettiği gösterilmiştir. Bu makale [18]’deki çalışmamızın genişletilmiş bir versiyonudur.
Op het snijvlak van het rechtspersonen- en overeenkomstenrecht
Authors: Karapetian A.
Published: November 2021

Op het snijvlak van het rechtspersonen- en overeenkomstenrecht. Reactie op de bijdrage van K.A.M. van Vught aan de bundel Bestuursbesluiten

De auteur bespreekt een aantal onderdelen over de doorwerking van overeenkomsten in bestuursbesluiten uit de bijdrage van K.A.M. van Vught in de bundel Bestuursbesluiten.
Motiveren rechters het gevaar?
Authors: de Vries Max
Published: November 2021

Do judges provide reasons when establishing dangerousness?

The imposition or extension of a tbs-order requires that the offender is dangerous. This article reports on a quantitative analysis of case law about whether judges provide reasons in their judgment when establishing that an offender is dangerous. The analysis shows that this often is not the case. For example, only one third of the examined judgments explain why the legal criterion for dangerousness is met. The author recommends that judges more often provide reasons for their decision about the dangerousness of the offender.
Identifying the Dimensions and Components of Quality Improvement of Education and Rural Health Workers’ Performance in Hormozgan, Iran
Authors: Bagheri Mehdi , Shamsaei Beheshteh , Ghourchian Nader Gholi , Jafari Parivash
Published: November 2021

Background: Education focuses on strengthening the performance of employees while improvement prepares them for other positions in the organization. Objectives: The present study aimed to identify the dimensions and components of quality improvement of education and rural health workers in Hormozgan, Iran. Methods: The current applied-descriptive study reviewed education and improvement of rural healthcare workers (called “behvarz” in Persian) based on document study and Delphi methods. To this end, 10 researchers in the fields of rural healthcare workers, health experts, and skilled rural health workers were asked to participate. The sampling was based on the snowball method; the data were obtained and refined through the fuzzy Delphi method. Results: The results showed that the experts had an appreciable inclination for the design and implementation of education in the first phase with a mean of 0.8538, followed by social, cultural, and professional improvement with a mean of 0.8396. Also, among other dimensions, the highest level of education agreement was 0.840. In the second phase, the design and implementation component of education with a mean of 0.84 was in the first place. For the improvement component, the social, cultural, and professional improvement yielded a mean of 0.8521. Conclusions: The impact of both education and improvement on people’s general health should be highlighted more than ever. However, theoretical and practical deep study of qualitative education toward improving and promoting the health system is required.
Trends in dermoscopy use in the UK: results from surveys in 2003 and 2012
Authors: Butler Thomas D. , Matin Rubeta N. , Affleck Andrew G. , Fleming Colin J. , Bowling Jonathan C.
Published: November 2021

Background: Dermoscopy is a useful tool to aid diagnosis of pigmented and non-pigmented skin lesions, as well as many other dermatological conditions. Use of dermoscopy is increasing worldwide, but to date, there are no reported data on attitudes of dermatologists in the United Kingdom (UK) towards dermoscopy.

Objective: To determine current attitudes of UK dermatologists towards dermoscopy and assess how these attitudes have changed over the last decade.

Methods: In October 2012, an online survey was sent to members of British Association of Dermatologists over a 12-week period. Data were subsequently compared with data from a similar UK nationwide paper questionnaire distributed to members in 2003.

Results: The 2003 survey collected 292 responses (uptake 42%), and in 2012 there were 209 responses (22%), predominantly from consultants and registrars. In 2012, 86% respondents reported increased use of dermoscopy over the previous decade with 98.5% of respondents reporting regular clinical use of dermoscopy, compared with 54% in 2003. Overall, 81% respondents in 2012 had received dermoscopy training, mainly from UK-based courses (62% of respondents) but increasingly via Internet-based resources (30% vs. 7% in 2003). However, 39% respondents lacked confidence when making a diagnosis based on their interpretation of dermoscopy findings. 

Conclusions: Over the last decade, use of dermoscopy has increased amongst UK dermatologists and the majority of respondents now employ dermoscopy in daily clinical practice. However, the use of dermoscopy in the dermatology community overall is not known and for those individuals there is a continued need for education.