Search results for: 3D plant data

Authors: Rajrupa Ghosh, Abhijit Mitra

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Future use of animal protein sources in prawn feeds is expected to be considerably reduced as a consequence of increasing economical, environmental and safety issues. Of main concern has been the use of expensive marine protein sources, such as fish meal which often results in fouling of water quality and disease outbreak in cultured species. To determine prawn capacity to use practical feeds with plant proteins as replacement ingredients to animal protein sources, 8-months growth trial was conducted in two sets of ponds using juvenile (0.02 gm) Macrobrachium rosenbergii. Among the two sets, one set (comprising of three ponds) is experimental pond included formulated feed prepared with 30% Porteresia coarctata dust along with other general ingredients and another set (comprising of another three ponds) is control pond with commercial feed. Mean final weight, percent weight gain, final net yield, feed conversion ratio and survival were evaluated. Higher condition index values, survival rate and gain in prawn weight were observed in experimental pond compared to control pond. Low FCR values were observed in the experimental pond than the control pond. Evaluation of production parameters at the end of the study demonstrated significant differences (P ≥ 0.05) among two ponds. The variation may be attributed to specially formulated plant based feed that not only boosted up the growth of prawns, but also upgraded the ambient aquatic health. These results indicate that fish meal can be replaced with algal protein sources in diets without affecting prawn growth and production.

Keywords: macrobrachium rosenbergii, porteresia coarctata, Indian sundarbans, feed

Procedia PDF Downloads 355

Authors: Abdulrahman K. Alshegaifi, Chun-Hsi Huang

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Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.

Keywords: hit rate, locality of program, stack cache, stack data

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Authors: Wajahat Munir, Muhammad Haseeb, Adeel Anjum, Basit Raza, Ahmad Kamran Malik

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Databases are the key components of the software systems. Due to the exponential growth of data, it is the concern that the data should be accurate and available. The data in databases is vulnerable to internal and external threats, especially when it contains sensitive data like medical or military applications. Whenever the data is changed by malicious intent, data analysis result may lead to disastrous decisions. Autonomic self-healing is molded toward computer system after inspiring from the autonomic system of human body. In order to guarantee the accuracy and availability of data, we propose a technique which on a priority basis, tries to avoid any malicious transaction from execution and in case a malicious transaction affects the system, it heals the system in an isolated mode in such a way that the availability of system would not be compromised. Using this autonomic system, the management cost and time of DBAs can be minimized. In the end, we test our model and present the findings.

Keywords: autonomic computing, self-healing, threat avoidance, security

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Authors: Mohammed R. Elkobaisi, Abdelsalam Maatuk

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The search engines are the large scale information retrieval tools from the Web that are currently freely available to all. This paper explains how to convert the raw resulted number of search engines into useful information. This represents a new method for data gathering comparing with traditional methods. When a query is submitted for a multiple numbers of keywords, this take a long time and effort, hence we develop a user interface program to automatic search by taking multi-keywords at the same time and leave this program to collect wanted data automatically. The collected raw data is processed using mathematical and statistical theories to eliminate unwanted data and converting it to usable data.

Keywords: search engines, information extraction, agent system

Procedia PDF Downloads 430

Authors: Emad Rashwan, M. Mousa, Ayman EL Sabagh, Celaleddin Barutcular

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Flax is a potential winter crop for Egypt that can be grown for both seed and fiber. The study was conducted during two successive winter seasons of 2013/2014, and 2014/2015 in the experimental farm of El-Gemmeiza Agricultural Research Station, Agriculture research Centre, Egypt. The objective of this work was to evaluate the effect of irrigation intervals (25, 35 and 45) on the seed yield and quality of flax cultivars (Sakha1, Giza9 and Giza10). Obtained results indicate that highly significant for all studied traits among irrigation intervals except oil percentage that was not significant in both seasons. Irrigated flax plants every 35 days gave the maximum values for all characters. In contrast, irrigation every 45 days gave the minimum values for all studied characters under this study. In respect to cultivars, significant differences in most yield and quality characters were found. Furthermore, the performance of Sakha1 cultivar was superior in total plant height, main stem diameter, seed index, seed, oil, biological and straw yield /ha as well as fiber length and fiber fineness. Meanwhile, Giza9 and Giza10 cultivars were surpassed in fiber yield/hand fiber percentage, respectively. The interactions between irrigation intervals and flax cultivars were highly significant for total plant height, main stem diameter, seed, oil, biological and straw yields /ha. Based on the results, all flax cultivars recorded the maximum values for major traits were measured under irrigation of flax plants every 35 days.

Keywords: flax, fiber, irrigation intervals, oil, seed yield

Procedia PDF Downloads 254

Authors: S. C. Sharma, Ankit Gambhir, Rajeev Arya

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In today’s era data security is an important concern and most demanding issues because it is essential for people using online banking, e-shopping, reservations etc. The two major techniques that are used for secure communication are Cryptography and Steganography. Cryptographic algorithms scramble the data so that intruder will not able to retrieve it; however steganography covers that data in some cover file so that presence of communication is hidden. This paper presents the implementation of Ron Rivest, Adi Shamir, and Leonard Adleman (RSA) Algorithm with Image and Audio Steganography and Data Encryption Standard (DES) Algorithm with Image and Audio Steganography. The coding for both the algorithms have been done using MATLAB and its observed that these techniques performed better than individual techniques. The risk of unauthorized access is alleviated up to a certain extent by using these techniques. These techniques could be used in Banks, RAW agencies etc, where highly confidential data is transferred. Finally, the comparisons of such two techniques are also given in tabular forms.

Keywords: audio steganography, data security, DES, image steganography, intruder, RSA, steganography

Procedia PDF Downloads 290

Authors: Ozlem Bahadir Acikara, Mert Ilhan, Ekin Kurtul, Karel Smejkal, Esra Kupeli Akkol

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Present study is aimed to investigate in vitro inhibitory effects of the extracts prepared from the aerial parts of Podospermum canum (Asteraceae) on hyaluronidase, collagenase, and elastase enzymes using a bioassay-guided fractionation. Inhibitory effects of the extract, sub-extracts, fractions obtained by column chromatography, and isolated compounds on collagenase, elastase, and hyaluronidase were performed by using in vitro enzyme inhibitory assays based on spectrophotometric evaluation. The ethyl acetate and remaining water extracts prepared from the plant displayed significant inhibitory activities on collagenase and elastase, while petroleum ether and chloroform extracts did not show any inhibitory activity. Eleven known compounds: arbutin, 6'-O-caffeoylarbutin, cichoriin, 3,5-dicaffeoylquinic acid methyl ester, apigenin-7-O-β-glucoside, luteolin-7-O-β-glucoside, apigenin-7-O-β-rutinoside, isoorientin, orientin, vitexin, procatechuic acid, and compound 4-hydroxy-benzoic acid 4-(6-O-α-rhamnopyranosyl-β-glucopyranosyl) benzyl ester have been obtained from ethyl acetate sub-extract of the plant through bioassay-guided fractionation and isolation. Results of the present study have revealed that among the isolated compounds, apigenin-7-O-β-glucoside, luteolin-7-O-β-glucoside, apigenin-7-O-β-rutinoside and isoorientin showed potent enzyme inhibitory activities. However, methanolic extract of P. canum displayed a greater inhibitory activity than fractions and isolated compounds both on collagenase and elastase.

Keywords: Asteraceae, collagenase, elastase, hyaluronidase, Podospermum canum

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Authors: Anushtha Saxena

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This paper examines the process of data monetisation bye-commerce companies operating in India. Data monetisation is collecting, storing, and analysing consumers’ data to use further the data that is generated for profits, revenue, etc. Data monetisation enables e-commerce companies to get better businesses opportunities, innovative products and services, a competitive edge over others to the consumers, and generate millions of revenues. This paper analyses the issues and challenges that are faced due to the process of data monetisation. Some of the issues highlighted in the paper pertain to the right to privacy, protection of data of e-commerce consumers. At the same time, data monetisation cannot be prohibited, but it can be regulated and monitored by stringent laws and regulations. The right to privacy isa fundamental right guaranteed to the citizens of India through Article 21 of The Constitution of India. The Supreme Court of India recognized the Right to Privacy as a fundamental right in the landmark judgment of Justice K.S. Puttaswamy (Retd) and Another v. Union of India . This paper highlights the legal issue of how e-commerce businesses violate individuals’ right to privacy by using the data collected, stored by them for economic gains and monetisation and protection of data. The researcher has mainly focused on e-commerce companies like online shopping websitesto analyse the legal issue of data monetisation. In the Internet of Things and the digital age, people have shifted to online shopping as it is convenient, easy, flexible, comfortable, time-consuming, etc. But at the same time, the e-commerce companies store the data of their consumers and use it by selling to the third party or generating more data from the data stored with them. This violatesindividuals’ right to privacy because the consumers do not know anything while giving their data online. Many times, data is collected without the consent of individuals also. Data can be structured, unstructured, etc., that is used by analytics to monetise. The Indian legislation like The Information Technology Act, 2000, etc., does not effectively protect the e-consumers concerning their data and how it is used by e-commerce businesses to monetise and generate revenues from that data. The paper also examines the draft Data Protection Bill, 2021, pending in the Parliament of India, and how this Bill can make a huge impact on data monetisation. This paper also aims to study the European Union General Data Protection Regulation and how this legislation can be helpful in the Indian scenarioconcerning e-commerce businesses with respect to data monetisation.

Keywords: data monetization, e-commerce companies, regulatory framework, GDPR

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Authors: Abejide Dorcas Ropo, , Falusi Olamide Ahmed, Daudu Oladipupo Abdulazeez Yusuf, Salihu Bolaji Zuluquri Neen, Muhammad Liman Muhammad, Gado Aishatu Adamu

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Water stress is a major factor limiting the productivity of crops in the world today. This study evaluated the morpho-agronomic response of twenty-four (24) Nigerian Bambara groundnut landraces to water stress and genetic diversity of some selected accessions using SSR markers. The studies was carried out in the Botanical garden of the Department of Plant Biology, Federal University of Technology, Minna, Niger State, Nigeria in a randomized complete block design using three replicates. Molecular analysis using SSR primers was carried out at the Centre for Bio- Science, International Institute of Tropical Agriculture (IITA) Ibadan, Nigeria in order to characterize ten selected accessions comprising of the seven most drought tolerant and the three most susceptible accessions detected from the morpho-agronomic studies. Results revealed that water stress decreased morpho-agronomic traits such as plant height, leaf area, number of leaves per plant and seed yield etc. A total of 22 alleles were detected by the SSR markers used with a mean number of 4 allelles. Simple Sequence Repeat (SSR) markers MBamCO33, Primer 65 and G358B2-D15 each detected 4 allelles while Primer 3FR and 4FR detected 5 allelles each. The study revealed significantly high polymorphisms in 10 Loci. The mean value of Polymorpic information content was 0.6997 implying the usefulness of the primers used in identifying genetic similarities and differences among the Bambara groundnut genotypes. The SSR analysis revealed a comparable pattern between genetic diversity and drought tolerance of the genotypes. The Unweighted Paired Group Method with Arithmethic Mean (UPGMA) dendrogram showed that at a genetic distance of 0.1, the accessions were grouped into three groups according to their level of tolerance to drought. The two most drought tolerant accessions were grouped together and the 5th and 6th most drought tolerant accession were also grouped together. This suggests that the genotypes grouped together may be genetically close, may possess similar genes or have a common origin. The degree of genetic variants obtained could be useful in bambara groundnut breeding for drought tolerance. The identified drought tolerant bambara groundnut landraces are important genetic resources for drought stress tolerance breeding programme of bambara groundnut. The genotypes are also useful for germplasm conservation and global implications.

Keywords: bambara groundnut, genetic diversity, germplasm, SSR markers, water stress

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Authors: Mounir Soule, Hindatou Saidou, Razafimahefa, Mohamed Thani Ibouroi

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High levels of habitat fragmentation and loss are the main drivers of plant species extinction. They reduce the habitat quality, which is a determining factor for the reproduction of plant species, and generate strong selective pressures for habitat selection, with impacts on the reproduction and survival of individuals. The Comorian’s yam (Dioscorea comorensis) is one of the most threatened plant species of the Comoros archipelago. The species faces one of the highest rates of habitat loss worldwide (9.3 % per year) and is classified as Endangered in the IUCN red list. Despite the nutritional potential of this tuber, the Comorian’s yam cultivation remains neglected by local populations due probably to lack of knowledge on its nutritional importance and the factors driving its spatial distribution and development. In this study, we assessed the nutritional characteristics of Dioscorea comorensis and the drivers of spatial distribution and abundance to propose conservation measures and improve crop yields. To determine the nutritional characteristics, the Kjeldahl method, the Soxhlet method, and Atwater's specific calorific coefficients methods were applied for analyzing proteins, lipids, and caloric energy respectively. In addition, atomic absorption spectrometry was used to measure mineral particles. By combining species occurrences with ecological (habitat types), climatic (temperature, rainfall, etc.), and physicochemical (soil types and quality) variables, we assessed habitat suitability and spatial distribution of the species and the factors explaining the origin, persistence, distribution and competitive capacity of a species using a Species Distribution Modeling (SDM) method. The results showed that the species contains 83.37% carbohydrates, 6.37% protein, and 0.45% lipids. In 100 grams, the quantities of Calcium, Sodium, Zinc, Iron, Copper, Potassium, Phosphorus, Magnesium, and Manganese are respectively 422.70, 599.41, 223.11, 252.32, 332.20, 780.41, 444.17, 287.71 and 220.73 mg. Its PRAL index is negative (- 9.80 mEq/100 g), and its Ca/P (0.95) and Na/K (0.77) ratios are less than 1. This species provides an energy value of 357.46 Kcal per 100 g, thanks to its carbohydrates and minerals and is distinguished from others by its high protein content, offering benefits for cardiovascular health. According to our SDM, the species has a very limited distribution, restricted to forests with higher biomass, humidity, and clay. Our findings highlight how distribution patterns are related to ecological and environmental factors. They also emphasize how the Comoros yam is beneficial in terms of nutritional quality. Our results represent a basic knowledge that will help scientists and decision-makers to develop conservation strategies and to improve crop yields.

Keywords: Dioscorea comorensis, nutritional characteristics, species distribution modeling, conservation strategies, crop yields improvement

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: Thobela Conco, Sheena Kumari, Chika Nnadozie, Mahmoud Nasr, Thor A. Stenström, Mushal Ali, Arshad Ismail, Faizal Bux

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The discharge of antibiotics and its residues into the wastewater treatment plants (WWTP’s) create a conducive environment for the development of antibiotic resistant pathogens. This presents a risk of potential dissemination of antibiotic resistant pathogens and antibiotic resistance genes into the environment. It is, therefore, necessary to study the level of antibiotic resistance genes (ARG’s) among bacterial pathogens that proliferate in biological wastewater treatment systems. In the current study, metagenomic and meta-transcriptomic sequences of samples collected from the influents, secondary effluents and post chlorinated effluents of three wastewater treatment plants treating domestic and hospital effluents in Durban, South Africa, were analyzed for profiling of ARG’s among bacterial pathogens. Results show that a variety of ARG’s, mostly, aminoglycoside, β-lactamases, tetracycline and sulfonamide resistance genes were harbored by diverse bacterial genera found at different stages of treatment. A significant variation in diversity of pathogen and ARGs between the treatment plant was observed; however, treated final effluent samples from all three plants showed a significant reduction in bacterial pathogens and detected ARG’s. Both pre- and post-chlorinated samples showed the presence of mobile genetic elements (MGE’s), indicating the inefficiency of chlorination to remove of ARG’s integrated with MGE’s. In conclusion, the study showed the wastewater treatment plant efficiently caused the reduction and removal of certain ARG’s, even though the initial focus was the removal of biological nutrients.

Keywords: antibiotic resistance, mobile genetic elements, wastewater, wastewater treatment plants

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Authors: Ronald Villamar-Torres, Michael Staudt, Christopher Viot

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Cotton Gossypium hirsutum L. is one of the most important industrial crops, producing the world leading natural textile fiber, but is very prone to arthropod attacks that reduce crop yield and quality. Cotton cultivation, therefore, makes an outstanding use of chemical pesticides. In reaction to herbivorous arthropods, cotton plants nevertheless show natural defense reactions, in particular through volatile organic compounds (VOCs) emissions. These natural defense mechanisms are nowadays underutilized but have a very high potential for cotton cultivation, and elucidating their genetic bases will help to improve their use. Simulating herbivory attacks by mechanical wounding of cotton plants in greenhouse, we studied by qPCR the changes in gene expression for genes of the terpenoids biosynthesis pathway. Differentially expressed genes corresponded to higher levels of the terpenoids biosynthesis pathway and not to enzymes synthesizing particular terpenoids. The genes were mapped on the G. hirsutum L. reference genome; their global relationships inside the general metabolic pathways and the biosynthesis of secondary metabolites were visualized with iPath2. The chromatographic profiles of VOCs emissions indicated first monoterpenes and sesquiterpenes emissions, dominantly four molecules known to be involved in plant reactions to arthropod attacks. As a result, the study permitted to identify potential key genes for the emission of volatile terpenoids by cotton plants in reaction to an arthropod attack, opening possibilities for molecular-assisted cotton breeding in benefit of smallholder cotton growers.

Keywords: biosynthesis pathways, cotton, mechanisms of plant defense, terpenoids, volatile organic compounds

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Authors: Kenneth Harper

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Blockchain technology presents solutions for managing healthcare data, addressing critical challenges in privacy, integrity, and access. This paper explores how privacy-preserving technologies, such as zero-knowledge proofs (ZKPs) and homomorphic encryption (HE), enhance decentralized healthcare platforms by enabling secure computations and patient data protection. An examination of the mathematical foundations of these methods, their practical applications, and how they meet the evolving demands of healthcare data security is unveiled. Using real-world examples, this research highlights industry-leading implementations and offers a roadmap for future applications in secure, decentralized healthcare ecosystems.

Keywords: blockchain, cryptography, data privacy, decentralized data management, differential privacy, healthcare, healthcare data security, homomorphic encryption, privacy-preserving technologies, secure computations, zero-knowledge proofs

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Authors: Ekramul Hoque, Zinat Ara Eakut Zarin, Ershad Ali

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The growth and development of explants is governed by the effect of nutrient medium. Ammonium nitrate (NH4NO3) as a major salt of stock solution-1 for the preparation of tissue culture medium. But, it has several demerits on human civilization. It is use for the preparation of bomb and other destructive activities. Hence, it is totally ban in our country. A new chemical was identified as a substitute of ammonium nitrate. The concentrations of the other ingredients of major and minor salt were modified from the MS medium. The formulation of new medium is totally different from the MS nutrient composition. The most widely use MS medium composition was used as first check treatment and MS powder (Duchefa Biocheme, The Netherland) was used as second check treatment. The experiments were carried out at the Department of Biotechnology, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh. Two potato varieties viz. Diamant and Asterix were used as experimental materials. The regeneration potentiality of potato onto new medium was best as compare with the two check treatments. The traits -node number, leaf number, shoot length, root lengths were highest in new medium. The plantlets were healthy, robust and strong as compare to plantlets regenerated from check treatments. Three subsequent sub-cultures were made in the new medium to observe the growth pattern of plantlet. It was also showed the best performance in all the parameter under studied. The regenerated plantlet produced good quality minituber under field condition. Hence, it is concluded that, a new plant tissue culture medium as discovered from the Department of Biotechnology, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh under the leadership of Professor Dr. Md. Ekramul Hoque.

Keywords: new medium, potato, regeneration, ammonium nitrate

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Authors: Dražen Cvitanić, Biljana Maljković

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This paper presents models for predicting operating speeds on tangent sections of two-lane rural roads developed on continuous speed data. The data corresponds to 20 drivers of different ages and driving experiences, driving their own cars along an 18 km long section of a state road. The data were first used for determination of maximum operating speeds on tangents and their comparison with speeds in the middle of tangents i.e. speed data used in most of operating speed studies. Analysis of continuous speed data indicated that the spot speed data are not reliable indicators of relevant speeds. After that, operating speed models for tangent sections were developed. There was no significant difference between models developed using speed data in the middle of tangent sections and models developed using maximum operating speeds on tangent sections. All developed models have higher coefficient of determination then models developed on spot speed data. Thus, it can be concluded that the method of measuring has more significant impact on the quality of operating speed model than the location of measurement.

Keywords: operating speed, continuous speed data, tangent sections, spot speed, consistency

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Ruixia Liu

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Qinghai-Tibet Plateau has an important influence on the precipitation of its lower reaches. Data from remote sensing has itself advantage and numerical prediction model which assimilates RS data will be better than other. We got the assimilation data of MHS and terrestrial and sounding from GSI, and introduced the result into WRF, then got the result of RH and precipitation forecast. We found that assimilating MHS and terrestrial and sounding made the forecast on precipitation, area and the center of the precipitation more accurate by comparing the result of 1h,6h,12h, and 24h. Analyzing the difference of the initial field, we knew that the data assimilating about Qinghai-Tibet Plateau influence its lower reaches forecast by affecting on initial temperature and RH.

Keywords: Qinghai-Tibet Plateau, precipitation, data assimilation, GSI

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Authors: Rian O. Miranda, Lidia V. de Sa, Julio C. Suita

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The Brazilian Nuclear Energy Commission (CNEN) is the main manufacturer of radiopharmaceuticals in Brazil. The Nuclear Engineering Institute (IEN), located at Rio de Janeiro, is one of its main centers of research and production, attending public and private hospitals in the state. This radiopharmaceutical production is used in diagnostic and therapy procedures and allows one and a half million nuclear medicine procedures annually. Despite this, the country is not self-sufficient to meet national demand, creating the need for importation and consequent dependence on other countries. However, IEN facilities were designed in the 60's, and today its structure is inadequate in relation to the good manufacturing practices established by sanitary regulator (ANVISA) and radiological protection leading to the need for a new project. In order to adapt and increase production in the country, a new plant will be built and integrated to the existing facilities with a new 30 MeV Cyclotron that is actually in project detailing process. Thus, it is proposed to survey current CNEN and ANVISA standards for radiopharmaceutical production facilities, as well as the radiological protection analysis of each area of the plant, following good manufacturing practices recommendations adopted nationally besides licensing exigencies for radioactive facilities. In this way, the main requirements for proper operation, equipment location, building materials, area classification, and maintenance program have been implemented. The access controls, interlocks, segregation zones and pass-through boxes integrated into the project were also analyzed. As a result, IEN will in future have the flexibility to produce all necessary radioisotopes for nuclear medicine application, more efficiently by simultaneously bombarding two targets, allowing the simultaneous production of two different radioisotopes, minimizing radiation exposure and saving operating costs.

Keywords: cyclotron, legislation, norms, production, radiopharmaceuticals

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Authors: Sook Ching Yee, Angela Siew Hoong Lee

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Big data technologies have become a trend to exploit business opportunities and provide valuable business insights through the analysis of big data. However, there are still many organizations that have yet to adopt big data technologies especially small and medium organizations (SME). This study uses the technology acceptance model (TAM) to look into several constructs in the TAM and other additional constructs which are positive affect, negative affect, organizational factor and motivational factor. The conceptual model proposed in the study will be tested on the relationship and influence of positive affect, negative affect, organizational factor and motivational factor towards the intention to use big data technologies to produce an outcome. Empirical research is used in this study by conducting a survey to collect data.

Keywords: big data technologies, motivational factor, negative affect, organizational factor, positive affect, technology acceptance model (TAM)

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Authors: Byung Ho Jung, Ji Eun Shin, Dong Hoon Lim

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Rhipe that integrates R and Hadoop environment made it possible to process and analyze massive amounts of data using a distributed processing environment. In this paper, we implemented multiple regression analysis using Rhipe with various data sizes of actual data. Experimental results for comparing the performance of our Rhipe with stats and biglm packages available on bigmemory, showed that our Rhipe was more fast than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases. We also compared the computing speeds of pseudo-distributed and fully-distributed modes for configuring Hadoop cluster. The results showed that fully-distributed mode was faster than pseudo-distributed mode, and computing speeds of fully-distributed mode were faster as the number of data nodes increases.

Keywords: big data, Hadoop, Parallel regression analysis, R, Rhipe

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Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

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Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios.

Keywords: hybrid MAC protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node dataprocessing, Z-MAC

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Authors: Mthokozisi Simelane

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Background: Malaria remains a life-threatening disease in tropical regions despite the advances in the treatment of this disease, it still remains a significant burden as some parasites have become resistant to the currently available drugs. This has created a necessity for the development of alternative, more efficient antimalarial drugs. Warburgia salutaris is a traditional medicinal plant used in malaria treatment by Zulu traditional healers. Materials and methods: The W. salutaris stem-bark was extracted with dichloromethane and the compound was isolated through column chromatography. The compound was identified and characterized by spectroscopic analysis (1H NMR, 13C NMR, IR and MS) and the structure was also confirmed by x-ray crystallography. The anti-plasmodial activity (in vitro) was studied on NF54 Plasmodium falciparum strain (CQS). Cytotoxicity was measured using the MTT assay on HEK239 and HEPG2 cell lines. Docking of Mukaadial acetate was conducted in AutoDock Vina. Structural modifications were conducted in UCSF Chimera and molecular interactions examined in LigPlot. Results: The compound, Mukaadial Acetate showed appreciable inhibition (IC50 0.44±0.10 µg/ml) of the parasite growth and cytotoxicity activity of 0.124±0.109 and 0.199±0.083 (µg/ml) on HEK293 and HEPG2 cells respectively. Molecular docking revealed that Mukaadial Acetate binds to the purine, pyrophosphate and ribose binding sites of the PfHGXPRT with an optimum binding conformation and forms hydrogen bond, steric and hydrophobic interactions with the residues inhabiting the respective binding sites. Conclusion: It is apparent that W. salutaris contains components (including Mukaadial Acetate) that exhibit antimalarial activity. This study scientifically validates the use of this plant in folk medicine.

Keywords: plasmodium falciparum, molecular docking, antimalarial activity, PfHGXPRT, Warburgia salutaris, mukaadial acetate

Procedia PDF Downloads 199

Authors: Hiba T. Allah ALtieb Gusm ALsied, Amna Beshir Medani Ahmed, Ikram Mohamed ELtayeb, Saad Mohamed Hussein Ayoub

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This study was carried out to determine the hepatoactivity and the antioxidant activity of Coiradrum sativum L. aerial part and fruit extracts against CCL4 induced acute liver damages in Wistar rats. The aerial parts and fruits part of the plant were extracted 96% ethanol with soxhlet apparatus. Hepatic injury was achieved by subcutaneous injection of 3 ml/kg of CCL4 diluted with olive oil with ratio 1:1. The extracts were mixed together 1:1 ratio and given in different doses 100,200,400 mg/kg/day for 5 days under CCL4 induction at 3rd day. The significance of differences between means by using T-test was compared among the groups. The mixture of the two extracts didn’t show any significant result in protecting liver injury (antagonistic effects), it shows high level of liver enzyme like alkaline phosphatase (ALP), glutamate oxaloacetate transaminase (SGOT) and glutamate pyruvate transaminase (SGPT). Serological studies further confirmed the results. The results obtained were compared with silymarin (70 mg/kg/day) orally, the standard drug for hepatoprotection which show recovery close to normalization almost like that of silymarin; therefore, further studies on this plant with different ratios especially in isolated tissue to spot more light on antagonistic effects of the two extracts. Antioxidant activity of the extracts was determined by the DPPH method. The results obtained show high anti-oxidant activity for fruits extract while slight or moderate antioxidant activity to aerial extracts.

Keywords: antioxidant, aerial part, Coriadrum sativum L., fruity, hepatoprotection, Silymarin, phytochemical screening

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Authors: Madaki Umar Yusuf, Mohd Rizam B. Abubakar

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The survival censored data with incomplete covariate data is a common occurrence in many studies in which the outcome is survival time. With model when the missing covariates are categorical, a useful technique for obtaining parameter estimates is the EM by the method of weights. The survival outcome for the class of generalized linear model is applied and this method requires the estimation of the parameters of the distribution of the covariates. In this paper, we propose some clinical trials with ve covariates, four of which have some missing values which clearly show that they were fully censored data.

Keywords: EM algorithm, incomplete categorical covariates, ignorable missing data, missing at random (MAR), Weibull Distribution

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Authors: Abdeljalil Beniiche

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The limitation with smart contracts is that they cannot access external data that might be required to control the execution of business logic. Oracles can be used to provide external data to smart contracts. An oracle is an interface that delivers data from external data outside the blockchain to a smart contract to consume. Oracle can deliver different types of data depending on the industry and requirements. In this paper, we study and describe the widely used blockchain oracles. Then, we elaborate on his potential role, technical architecture, and design patterns. Finally, we discuss the human oracle and its key role in solving the truth problem by reaching a consensus about a certain inquiry and tasks.

Keywords: blockchain, oracles, oracles design, human oracles

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Authors: Paul Rowley, Adam Thirkill, Nick Doylend, Philip Leicester, Becky Gough

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The dynamic performance of all energy generation technologies is impacted to varying degrees by the stochastic properties of the wider system within which the generation technology is located. This stochasticity can include the varying nature of ambient renewable energy resources such as wind or solar radiation, or unpredicted changes in energy demand which impact upon the operational behaviour of thermal generation technologies. An understanding of these stochastic impacts are especially important in contexts such as highly distributed (or embedded) generation, where an understanding of issues affecting the individual or aggregated performance of high numbers of relatively small generators is especially important, such as in ESCO projects. Probabilistic evaluation of monitored or simulated performance data is one technique which can provide an insight into the dynamic performance characteristics of generating systems, both in a prognostic sense (such as the prediction of future performance at the project’s design stage) as well as in a diagnostic sense (such as in the real-time analysis of underperforming systems). In this work, we describe the development, application and outcomes of a new approach to the acquisition of datasets suitable for use in the subsequent performance and impact analysis (including the use of Bayesian approaches) for a number of distributed generation technologies. The application of the approach is illustrated using a number of case studies involving domestic and small commercial scale photovoltaic, solar thermal and natural gas boiler installations, and the results as presented show that the methodology offers significant advantages in terms of plant efficiency prediction or diagnosis, along with allied environmental and social impacts such as greenhouse gas emission reduction or fuel affordability.

Keywords: renewable energy, dynamic performance simulation, Bayesian analysis, distributed generation

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Authors: Yahia Massinissa, Benhouda Afaf, Benbia Souhila, Meddour Noura, Takellalet Karima, Zeroual Amina

Abstract:

Introduction: chenopodiaceae family species are known for their important biological activity, in which Atriplex halimus belongs . However, the inflammatory effect of this plant leaves has not been studied. This work aimed at assessing the anti- inflammatory and hemostatic activities of the methanolic extract AHMeOH of Atriplex halimus’s leaves. Methods: The extract was obtained using sonication of leaves powder in 80 % methanol. The analysis of phenolic compounds was carried out using thin-layer chromatography (TLC).The anti-inflammatory activity was determined by studying the plasmical membrane stabilization and albumin denaturation inhibition, the hemostatic activity was evaluated by measuring the plasma in the blood. Results: Quantitative determination of total flavonoids reveals that AHMeOH is rich in flavonoids (16 ± 0.88 μg Q / mg extract) and polyphenols (20 ± 0.20 μg AG / mg extract). about anti-inflammatory activity, the tests show that AHMeOH has a significant effect (P≤0.05) of inhibiting hypotonic-induced hemolysis with concentrations (100 and 200 μg / ml) with 77.55 and 90% respectively, and heat-induced hemolysis with percentages 81.75% and 87.44% respectively with significant difference (P ≤0.05). The obtained results with this plant reveal that the inhibition of denaturation of albumin is dose dependent. The concentration of 400 μg / ml gives denaturation inhibition of 81.00 ± 17.70% and the concentration 600 μg / ml gives an effect of 82.95 ± 17.40%. Regarding the haemostatic activity our extract with the doses 10 mg / ml, 20 mg / ml and 30 mg / ml confer a decrease of the plasma recalcification time in the tube, these concentrations could prolong the time of coagulation significantly compared to the control (P≤0.001). This result is an interesting indication in favor of haemostatic activity of AHMeOH. Conclusion: Atriplex Halimus has a strong anti-inflammatory activity and constitutes a potential source for the development of new treatments.

Keywords: albumin, atriplex halimus, hemostatic activity, methanolic extract

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Authors: Yasir Ali, Farhatullah

Abstract:

The present study was conducted to estimate the genetic variability, heritability and genetic advance in six parental lines and their 56 genotypes derived from five introgressed brassica populations on the basis of morphological and biochemical traits. The experiment was laid out in a randomized complete block design with two replications at The University of Agriculture Peshawar-Pakistan during growing season of 2015-2016. The ANOVA of all traits of F5:6 populations showed highly significant differences (P ≤ 0.01) for all morphological and biochemical traits. Among F5:6 populations, the genotype 2(526) was earlier in flowering (108.65 days), and genotype 14(485) was earlier in maturity (170 days). Tallest plants (182.5 cm), largest main raceme (91.5 cm) and maximum number of pods (80.5) on main raceme were recorded for genotype 17(34). Maximum primary branches plant-1(6.2) and longest pods (10.26 cm) were recorded for genotype 15, while genotype 16(171) had more seeds pod⁻¹ (22) and gave maximum yield plant-1 (30.22 g). The maximum 100-seed weight (0.60 g) was observed for genotype 10(506) while high protein content (22.61%) was recorded for genotype 4(99). Maximum oil content (54.08 %) and low linoleic acid (7.07 %) were produced by genotype (12(138) and low glucosinolate (59.01 µMg⁻¹) was recorded for genotype 21(113). The genotype 27(303) having high oleic acid content (51.73 %) and genotype 1(209) gave low erucic acid (35.97 %). Among the F5:6 populations moderate to high heritability observed for all morphological and biochemical traits coupled with high genetic advance. Cluster analysis grouped the 56 F5:6 populations along their parental lines into seven different groups. Each group was different from the other group on the basis of morphological and biochemical traits. Moreover all the F5:6 populations showed sufficient variability. Genotypes 10(506) and 16(171) were superior for high seed yield⁻¹, 100-seeds weight, and seed pod⁻¹ and are recommended for future breeding program.

Keywords: Brassicaceae, biochemical characterization, introgression, morphological characterization

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Authors: Abdoullah Nyassi, Golam Sarwar, Sarra Baldeh, Mamadou S. K. Jallow, Bai Lamin Dondeh, Isaac Osei, Grant A. Mackenzie

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A randomized controlled trial is the "gold standard" for evaluating the efficacy of an intervention. Large-scale, cluster-randomized trials are expensive and difficult to conduct, though. To guarantee the validity and generalizability of findings, high-quality, dependable, and accurate data management systems are necessary. Robust data management systems are crucial for optimizing and validating the quality, accuracy, and dependability of trial data. Regarding the difficulties of data gathering in clinical trials in low-resource areas, there is a scarcity of literature on this subject, which may raise concerns. Effective data management systems and implementation goals should be part of trial procedures. Publicizing the creative clinical data management techniques used in clinical trials should boost public confidence in the study's conclusions and encourage further replication. In the ongoing pneumococcal vaccine schedule study in rural Gambia, this report details the development and deployment of multi-data management systems and methodologies. We implemented six different data management, synchronization, and reporting systems using Microsoft Access, RedCap, SQL, Visual Basic, Ruby, and ASP.NET. Additionally, data synchronization tools were developed to integrate data from these systems into the central server for reporting systems. Clinician, lab, and field data validation systems and methodologies are the main topics of this report. Our process development efforts across all domains were driven by the complexity of research project data collected in real-time data, online reporting, data synchronization, and ways for cleaning and verifying data. Consequently, we effectively used multi-data management systems, demonstrating the value of creative approaches in enhancing the consistency, accuracy, and reporting of trial data in a poor resource setting.

Keywords: data management, data collection, data cleaning, cluster-randomized trial

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