Search results for: chemical identification

Authors: Muhammad Sheeraz, Mehwish Ejaz

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This study endeavors to enhance the understanding of the determinants of oppositional brand loyalty, particularly within the context of fans of a sports brand. The primary focus is on investigating how oppositional brand loyalty fosters rivalry among the fans and exploring the interplay between various variables, namely self-congruence, consumer brand identification, consumer brand engagement, and narcissism, in influencing the likelihood of endorsing a rival team. The research adopts a cross-sectional survey methodology, employing a structured questionnaire distributed both online and onsite to gather responses from a representative sample of 460 PSL fans in Pakistan. The data collection process involved obtaining responses from diverse settings, including universities, shopping malls, and other public spaces frequented by PSL enthusiasts. Participants were prompted to indicate their allegiance to a specific PSL team and subsequently respond to the questionnaire based on their preferences. The findings of the study reveal that narcissism, as a moderating factor, exhibits no significant influence on consumer brand identification, consumer brand engagement, and oppositional brand loyalty. However, it does emerge as a significant moderator in the relationship between self-congruence and consumer brand identification. Particularly, consumers express brand identification through self-congruence, elucidating the existence of oppositional sentiments among PSL fans and their counterparts supporting rival teams. The implications of these results underscore the importance for marketers to establish a brand identity that resonates with consumers on a personal level. Such an approach fosters a strong sense of identification with the brand, prompting consumers to vigorously defend and support their favored brands, even in the face of opposition from rival teams. Marketers are encouraged to focus on cultivating long-term consumer loyalty, as it proves pivotal in maintaining a competitive advantage over industry counterparts.

Keywords: oppositional brand loyalty, consumer brand identification, consumer brand engagement, narcissism, self-congruence

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Authors: Sisuwan Kaseamsawat, Sivapan Choo-In

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A study was conducted in May to July 2013 with the aim of determination of heavy metal concentration in orchard area. 60 samples were collected and analyzed for Cadmium (Cd), Copper (Cu), Lead (Pb), and Zinc (Zn) by Atomic Absorption Spectrophotometer (AAS). The heavy metal concentrations in sediment of orchards, that use chemical for Cd (1.13 ± 0.26 mg/l), Cu (8.00 ± 1.05 mg/l), Pb (13.16 ± 2.01) and Zn (37.41 ± 3.20 mg/l). The heavy metal concentrations in sediment of the orchards, that do not use chemical for Cd (1.28 ± 0.50 mg/l), Cu (7.60 ± 1.20 mg/l), Pb (29.87 ± 4.88) and Zn (21.79 ± 2.98 mg/l). Statistical analysis between heavy metal in sediment from the orchard, that use chemical and the orchard, that not use chemical were difference statistic significant of 0.5 level of significant for Cd and Pb while no statistically difference for Cu and Zn.

Keywords: heavy metal, orchard, pollution and monitoring, sediment

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Authors: Neslihan Ozman Say, Jim Gilmour, Pratik Desai, William Zimmerman

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Landfill leachate treatment has been attracting researchers recently for various environmental and economical reasons. Leachate discharge to receiving waterbodies without treatment causes serious detrimental effects including partial oxygen depletion due to high biological oxygen demand (BOD) and chemical oxygen demand (COD) concentrations besides toxicity of heavy metals it contains and high ammonia concentrations. In this study, it is aimed to show microalgal ammonia removal performances of a wild microalgae consortia as an alternative treatment method and determine the dominant leachate tolerant species for this consortia. For the microalgae species identification experiments a microalgal consortium which has been isolated from a local pond in Sheffield inoculated in %5 diluted raw landfill leachate and acclimated to the leachate by batch feeding for a month. In order to determine the most tolerant microalgal consortium, four different untreated landfill leachate samples have been used as diluted in four different ratios as 5%, 10%, 20%, and 40%. Microalgae cell samples have been collected from all experiment sets and have been examined by using 18S rDNA sequencing and specialised gel electrophoresis which are adapted molecular biodiversity methods. The best leachate tolerant algal consortium is being used in order to determine ammonia removal performances of the culture in a microbubble assisted photobioreactor (PBR). A porous microbubble diffuser which is supported by a fluidic oscillator is being used for dosing CO₂ and air mixture in the PBR. It is known that high mass transfer performance of microbubble technology provides a better removal efficiency and a better mixing in the photobioreactor. Ammonia concentrations and microalgal growth are being monitored for PBR currently. It is aimed to present all the results of the study in final paper submission.

Keywords: ammonia removal from leachate, landfill leachate treatment, microalgae species identification, microbubble assisted photobioreactors

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Authors: Prashanta Dhoj Adhikari

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We report the introduction of the active surface functionalization group on chemical vapor deposition (CVD) grown graphene film by wet deposition method. The activity of surface functionalized group was tested with surface modified carbon nanotubes (CNTs) and found that both materials were amalgamated by chemical bonding. The introduction of functional group on the graphene film surface and its vigorous role to bind CNTs with the present technique could provide an efficient, novel route to device fabrication.

Keywords: chemical vapor deposition, graphene film, surface functionalization

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Authors: Mohamed Trigui, Fatma Masmoudi, Imen Zouari

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Massive utilizations of chemical fertilizer and chemical pesticides in agriculture sector to improve the farming productivity have created increasing environmental damages. Then, agriculture must become sustainable, focusing on production systems that respect the environment and help to reduce climate change. Isolation and microbial identification of new bacterial strains from naturally saline habitats and compost extracts could be a prominent way in pest management and crop production under saline conditions. In this study, potential mechanisms involved in plant growth promotion and suppressive activity against fungal diseases of a compost extract produced from poultry manure/olive husk compost and halotolerant and halophilic bacterial strains under saline stress were investigated. On the basis of the antimicrobial tests, different strains isolated from Sfax solar saltern (Tunisia) and from compost extracts were selected and tested for their plant growth promoting traits, such as siderophores production, nitrogen fixation, phosphate solubilization and the production of extracellular hydrolytic enzymes (protease and lipase) under in-vitro conditions. Among 450 isolated bacterial strains, 16 isolates showed potent antifungal activity against the tested plant pathogenic fungi. Their identification based on 16S rRNA gene sequence revealed they belonged to different species. Some of these strains were also characterized for their plant growth promoting capacities. Obtained results showed the ability of four strains belonging to Bacillus genesis to ameliorate germination rate and root elongation compared to the untreated positive controls. Combinatorial capacity of halotolerant bacteria with antimicrobial activity and plant growth promoting traits could be promising sources of interesting bioactive substances under saline stress.

Keywords: abiotic stress, biofertilizer, biotic stress, compost extract, halobacteria, plant growth promoting (PGP), soil fertility

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Authors: Sarah Aldhalaan, Tanzila Saba

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Healthcare sectors are increasing rapidly to fulfill patient’s needs across the world. A patient identification is considered as the main aspect for a patient to be served in healthcare institutes. Nowadays, people are presenting their insurance card along with their identification card in order to get the needed treatment in hospitals however, this process lack security preferences. The aim of this research paper is to reveal a solution to introduce and use biometrics in healthcare hospitals. The findings show that the people know biometrics since they are interacting with them through different channels and that the need for biometrics techniques to identify patients is essential. Also, the survey relevant questions are used to analyze and add insights on what is are the suitable biometrics to be used in such cases. Moreover, results are presented to exhibit the effectiveness of the used methodology and in analyzing usage of biometrics in hospitals in an enhancing way. Finally, an interesting conclusion of overall work is presented at the end of paper.

Keywords: biometrics, healthcare, fingerprint, Saudi Arabia

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Authors: Daniel Alfonso Reséndiz-García, Luis Antonio García-Villanueva

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As a result of the high industrial activity, which arises from the search to satisfy the needs of products and services for society, several chemical accidents have occurred, causing serious damage to different sectors: human, economic, infrastructure and environmental losses. Historically, with the study of this chemical accidents, it has been determined that the causes are mainly due to human errors (inexperienced personnel, negligence, lack of maintenance and deficient risk analysis). The industries have the aim to increase production and reduce costs. However, it should be kept in mind that the costs involved in risk studies, implementation of barriers and safety systems is much cheaper than paying for the possible damages that could occur in the event of an accident, without forgetting that there are things that cannot be replaced, such as human lives.Therefore, it is of utmost importance to implement risk studies in all industries, which provide information for prevention and planning. The aim of this study is to compare risk methodologies by identifying the consequences of accidents related to the storage of flammable, dangerous goods for decision making and emergency response.The methodologies considered in this study are qualitative and quantitative risk analysis and consequence analysis. The latter, by means of modeling software, which provides radius of affectation and the possible scope and magnitude of damages.By using risk analysis, possible scenarios of occurrence of chemical accidents in the storage of flammable substances are identified. Once the possible risk scenarios have been identified, the characteristics of the substances, their storage and atmospheric conditions are entered into the software.The results provide information that allows the implementation of prevention, detection, control, and combat elements for emergency response, thus having the necessary tools to avoid the occurrence of accidents and, if they do occur, to significantly reduce the magnitude of the damage.This study highlights the importance of risk studies applying tools that best suited to each case study. It also proves the importance of knowing the risk exposure of industrial activities for a better prevention, planning and emergency response.

Keywords: chemical accidents, emergency response, flammable substances, risk analysis, modeling

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Authors: Sundus Mona, Atif Adnan, Babar Ali, Fareeha Arshad, Allah Rakha

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Molecular diversity is the variation in the abundance of species. Forensic entomology is a neglected field in Pakistan. Insects collected from the crime scene should be handled by forensic entomologists who are currently virtually non-existent in Pakistan. Correct identification of insect specimen along with knowledge of their biodiversity can aid in solving many problems related to complicated forensic cases. Inadequate morphological identification and insufficient thermal biological studies limit the entomological utility in Forensic Medicine. Recently molecular identification of entomological evidence has gained attention globally. DNA barcoding is the latest and established method for species identification. Only proper identification can provide a precise estimation of postmortem intervals. Arthropods are known to be the first tourists scavenging on decomposing dead matter. The objective of the proposed study was to identify species by molecular techniques and analyze their phylogenetic importance with barcoded necrophagous insect species of early succession on human cadavers. Based upon this identification, the study outcomes will be the utilization of established DNA bar codes to identify carrion feeding insect species for concordant estimation of post mortem interval. A molecular identification method involving sequencing of a 658bp ‘barcode’ fragment of the mitochondrial cytochrome oxidase subunit 1 (CO1) gene from collected specimens of unknown dipteral species from cadavers of Lahore was evaluated. Nucleotide sequence divergences were calculated using MEGA 7 and Arlequin, and a neighbor-joining phylogenetic tree was generated. Three species were identified, Chrysomya megacephala, Chrysomya saffranea, and Chrysomya rufifacies with low genetic diversity. The fixation index was 0.83992 that suggests a need for further studies to identify and classify forensically relevant insects in Pakistan. There is an exigency demand for further research especially when immature forms of arthropods are recovered from the crime scene.

Keywords: molecular diversity, DNA barcoding, species identification, forensically relevant

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Authors: Sadia Ameen, M. Nazim, Hyumg-Kee Seo, Hyung-Shik Shin

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TiO2 nanotube (NT) arrays were grown on titanium (Ti) foil substrate by electrochemical anodic oxidation and utilized as working electrode to fabricate a highly sensitive and reproducible chemical sensor for the detection of harmful phenyl hydrazine chemical. The fabricated chemical sensor based on TiO2 NT arrays electrode exhibited high sensitivity of ~40.9 µA.mM-1.cm-2 and detection limit of ~0.22 µM with short response time (10s).

Keywords: TiO2 NT, phenyl hydrazine, chemical sensor, sensitivity, electrocatalytic properties

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Authors: Nitin Shravan, Sudarsun Santhiappan, B. Sivaselvan

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Subsection identification, in the context of Electronic Health Records (EHRs), is identifying the important sections for down-stream tasks like auto-coding. In this work, we classify the text present in EHRs according to their information, using machine learning and deep learning techniques. We initially describe briefly about the problem and formulate it as a text classification problem. Then, we discuss upon the methods from the literature. We try two approaches - traditional feature extraction based machine learning methods and deep learning methods. Through experiments on a private dataset, we establish that the deep learning methods perform better than the feature extraction based Machine Learning Models.

Keywords: deep learning, machine learning, semantic clinical classification, subsection identification, text classification

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Authors: Zellagui Rahima, Chaumont Denis, Boughelout Abderrahman, Adnane Mohamed

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Thin films of CdxZn1-xS were deposed by chemical bath deposition on glass substrates for photovoltaic applications. The thin films CdZnS were synthesized by chemical bath (CBD) with different deposition protocols for optimized the parameter of deposition as the temperature, time of deposition, concentrations of ion and pH. Surface morphology, optical and chemical composition properties of thin film CdZnS were investigated by SEM, EDAX, spectrophotometer. The transmittance is 80% in visible region 300 nm – 1000 nm; it has been observed in that films the grain size is between 50nm and 100nm measured by SEM image and we also note that the shape of particle is changing with the change in concentration. This result favors of application these films in solar cells; the chemical analysis with EDAX gives information about the presence of Cd, Zn and S elements and investigates the stoichiometry.

Keywords: thin film, solar cells, transmition, cdzns

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Authors: Fuad M. Alkoot

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DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

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Authors: Aouiche Abdelaziz, Soudani Mouhamed Salah, Aouiche El Moundhe

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The present paper addresses the utilization of Artificial Neural Networks (ANNs) and Fuzzy Inference Systems (FISs) for the identification and control of dynamical systems with some degree of uncertainty. Because ANNs and FISs have an inherent ability to approximate functions and to adapt to changes in input and parameters, they can be used to control systems too complex for linear controllers. In this work, we show how ANNs and FISs can be put in order to form nets that can learn from external data. In sequence, it is presented structures of inputs that can be used along with ANNs and FISs to model non-linear systems. Four systems were used to test the identification and control of the structures proposed. The results show the ANNs and FISs (Back Propagation Algorithm) used were efficient in modeling and controlling the non-linear plants.

Keywords: non-linear systems, fuzzy set Models, neural network, control law

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Authors: Di Yao, Gunther Prokop, Kay Buttner

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Dynamic parameters, including the center of gravity, mass and inertia moments of vehicle, play an essential role in vehicle simulation, collision test and real-time control of vehicle active systems. To identify the important vehicle dynamic parameters, a systematic parameter identification procedure is studied in this work. In the first step of the procedure, a conceptual parallel manipulator (virtual test rig), which possesses three rotational degrees-of-freedom, is firstly proposed. To realize kinematic characteristics of the conceptual parallel manipulator, the kinematic analysis consists of inverse kinematic and singularity architecture is carried out. Based on the Euler's rotation equations for rigid body dynamics, the dynamic model of parallel manipulator and derivation of measurement matrix for parameter identification are presented subsequently. In order to reduce the sensitivity of parameter identification to measurement noise and other unexpected disturbances, a parameter optimization process of searching for optimal exciting trajectory of parallel manipulator is conducted in the following section. For this purpose, the 321-Euler-angles defined by parameterized finite-Fourier-series are primarily used to describe the general exciting trajectory of parallel manipulator. To minimize the condition number of measurement matrix for achieving better parameter identification accuracy, the unknown coefficients of parameterized finite-Fourier-series are estimated by employing an iterative algorithm based on MATLAB®. Meanwhile, the iterative algorithm will ensure the parallel manipulator still keeps in an achievable working status during the execution of optimal exciting trajectory. It is showed that the proposed procedure and methods in this work can effectively identify the vehicle dynamic parameters and could be an important application of parallel manipulator in the fields of parameter identification and test rig development.

Keywords: parameter identification, parallel manipulator, singularity architecture, dynamic modelling, exciting trajectory

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Authors: Felora Rafiei, Shahram Shoaei

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The aim of this studies was to evaluate effect of nitroxin, super nitro plus and biophosphorus on yield and yield components of maize (Zea mays) under different levels of chemical fertilizers in the condition of normal and difficiet irrigation. Experiment laid out as split plot factorial based on randomized complete block design with three replications. Main plots includes two irrigation treatments of 70 (I1), 120(I2) mm evaporation from class A pan. Sub plots were biological fertilizer and chemical fertilizer as factorial biological fertilizer consisting of nitroxin: Azospirillium lipoferum, Azospirillium brasilens, Azotobacter chroococcum Azotobacter agilis (108 CFU ml-1) (B1), super nitro plus (Azospirillium spp, + Pseudomonas fluorescence + Bacillus subtilis (108 CFU ml-1) + biological fungicide) (B2), biophosphorus (Pseudomonas spp + Bacillus spp (107 CFU ml-1) (B3), and chemical fertilizer consisting of NPK (C1), N5oP5oK5o (C2) and NoPoKo (C3).The results showed that usage of biological fertilizer have positive effects on chemical fertilizers use efficiency and tolerance to drought stress in maize. Also with use of biological fertilizer can decrease usage of chemical fertilizers.

Keywords: biological fertilizer, chemical fertilizer, yield component, yield, corn

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Authors: Yu Qin

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In order to tackle the ever-growing problem of the lack of parking space, this paper presents the design and implementation of a smart unmanned parking system that is based on RFID (radio frequency identification) technology and Wireless communication technology. This system uses RFID technology to achieve the identification function (transmitted by 2.4 G wireless module) and is equipped with an STM32L053 micro controller as the main control chip of the smart vehicle. This chip can accomplish automatic parking (in/out), charging and other functions. On this basis, it can also help users easily query the information that is stored in the database through the Internet. Experimental tests have shown that the system has the features of low power consumption and stable operation, among others. It can effectively improve the level of automation control of the parking lot management system and has enormous application prospects.

Keywords: RFID, embedded system, unmanned, parking management

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Chih Hung Shih

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Eyewitness identification is one of the efficient information to identify suspects during criminal investigation. However eyewitness identification is improved frequently, inaccurate and plays vital roles in wrongful convictions. Most eyewitness misidentifications are made during police criminal investigation stage and then accepted by juries. Four failure investigation case studies in Taiwan are conduct to demonstrate how misidentifications are caused during the police investigation context. The result shows that there are several common grounds among these cases: (1) investigators lacked for knowledge about eyewitness memory so that they couldn’t evaluate the validity of the eyewitnesses’ accounts and identifications, (2) eyewitnesses were always asked to filter out several suspects during the investigation, and received investigation information which contaminated the eyewitnesses’ memory, (3) one to one live individual identifications were made in most of cases, (4) eyewitness identifications were always used to support the hypotheses of investigators, and exaggerated theirs powers when conform with the investigation lines, (5) the eyewitnesses’ confidence didn’t t reflect the validity of their identifications , but always influence the investigators’ beliefs for the identifications, (6) the investigators overestimated the power of the eyewitness identifications and ignore the inconsistency with other evidence. Recommendations have been proposed for future academic research and police practice of eyewitness identification in Taiwan.

Keywords: criminal investigation, eyewitness identification, investigative bias, investigative failures

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Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: deep-learning, image classification, image identification, industrial engineering.

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Authors: Adejo Andrew Ojonugwa, Jomboh Jeff Kator, Garkida Adele Dzikwi

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This study investigates the behaviour of textured glass coat to chemical reactions upon application. Samples of textured glass coat developed from mixed post consumer glass were subjected to pH test (ASTM D5464), Chemical resistance test (ASTM D3260 and D1308), Adhesion test (ASTM D3359), and Abrasion test (ASTM D4060). Results shows a pH of 8.50, Chemical resistance of 5% flick rate when reacted with Sodium hydroxide (NaOH), a 3%, 5%, 10%, and 15% discolouration when reacted with Magnesium hydroxide (Mg(OH)2), Hydrogen fluoride (HF), Potassium hydroxide (KOH) and NaOH respectively, an adhesion of 4A and abrasion of 0.2g. The results confirm that the developed textured glass coat is in line with the standard pH range of 8-9, resistant to acid and base except for HF, NaOH, and Mg(OH)₂, good adhesion and abrasion properties, thereby making the coat resistant to chemical degradation and a good engineering material.

Keywords: chemical durability, glass-coat, building, recycling

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Authors: M. Chňapek, M. Tomka, R. Peroutková, Z. Gálová

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Processes of plant breeding, testing and licensing of new varieties, patent protection in seed production, relations in trade and protection of copyright are dependent on identification, differentiation and characterization of plant genotypes. Therefore, we focused our research on utilization of wheat storage proteins as genetic markers suitable not only for differentiation of individual genotypes, but also for identification and characterization of their considerable properties. We analyzed a collection of 102 genotypes of bread wheat (Triticum aestivum L.), 41 genotypes of spelt wheat (Triticum spelta L.), and 35 genotypes of durum wheat (Triticum durum Desf.), in this study. Our results show, that genotypes of bread wheat and durum wheat were homogenous and single line, but spelt wheat genotypes were heterogenous. We observed variability of HMW-GS composition according to environmental factors and level of breeding and predict technological quality on the basis of Glu-score calculation.

Keywords: genotype identification, HMW-GS, wheat quality, polymorphism

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Authors: Shokofeh Ebrtahimi

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Let G be the chemical graph of a molecule. The matrix D = [dij ] is called the detour matrix of G, if dij is the length of longest path between atoms i and j. The sum of all entries above the main diagonal of D is called the detour index of G.Chemical graph theory is the topology branch of mathematical chemistry which applies graph theory to mathematical modelling of chemical phenomena.[1] The pioneers of the chemical graph theory are Alexandru Balaban, Ante Graovac, Ivan Gutman, Haruo Hosoya, Milan Randić and Nenad TrinajstićLet G be the chemical graph of a molecule. The matrix D = [dij ] is called the detour matrix of G, if dij is the length of longest path between atoms i and j. The sum of all entries above the main diagonal of D is called the detour index of G. In this paper, a new program for computing the detour index of molecular graphs of nanotubes by heptagons is determineded. Some Conjectures about detour index of Molecular graphs of nanotubes is included.

Keywords: chemical graph, detour matrix, Detour index, carbon nanotube

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Authors: Ernesto Linan, Linda Cruz, Lucero Becerra

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In this paper, a new hybridized algorithm based on Chemical Reaction Optimization and Simulated Annealing is proposed to solve the alignment sequence Problem. The Chemical Reaction Optimization is a population-based meta-heuristic algorithm based on the principles of a chemical reaction. Simulated Annealing is applied to solve a large number of combinatorial optimization problems of general-purpose. In this paper, we propose hybridization between Chemical Reaction Optimization algorithm and Simulated Annealing in order to solve the Sequence Alignment Problem. An initial population of molecules is defined at beginning of the proposed algorithm, where each molecule represents a sequence alignment problem. In order to simulate inter-molecule collisions, the process of Chemical Reaction is placed inside the Metropolis Cycle at certain values of temperature. Inside this cycle, change of molecules is done due to collisions; some molecules are accepted by applying Boltzmann probability. The results with the hybrid scheme are better than the results obtained separately.

Keywords: chemical reaction optimization, sequence alignment problem, simulated annealing algorithm, metaheuristics

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Authors: Anahita Yarahmadi, Nazanin Mahboobi, Nahid Sadat Rahmatpour Nori, Mohammad Hossein Bijeh Keshavarzi, Mohammad Javad Shakori

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This research aimed at considering biological fertilizer effect and chemical fertilizer on the quantitative characteristics of Sweet wormwood (Artemisia annua L.), an experiment was carried out in factorial design in completely randomized design with 4 replications in an experimental greenhouse which was located in Tehran. Experimental treatment involved chemical fertilizers (Nitrogen, Phosphorus) in4 levels and biological fertilizers in 4 levels (control, Nitroxin, Bio-phosphorus and Vemricompost). Results showed that using biological fertilizers and increasing different levels of chemical fertilizers (N, P) had significant effects on all the characteristics. Considering means comparison showed that biological fertilizers lead to significant enhancement on all the characteristics and among biological fertilizers, Vermicompost treatment has the most effect. Considering means comparison tables of different levels of chemical fertilizer have been found that (N80P80) had the most increase on characteristics.

Keywords: Artemisia annua L, bio-fertilizer, chemical fertilizer, vermicompost

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Authors: Sergey Sorokin, Irina Sorokina, Alexander Yazenin

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We present a solution to the Maxmin u/E parameters estimation problem of possibility distributions in m-dimensional case. Our method is based on geometrical approach, where minimal area enclosing ellipsoid is constructed around the sample. Also we demonstrate that one can improve results of well-known algorithms in fuzzy model identification task using Maxmin u/E parameters estimation.

Keywords: possibility distribution, parameters estimation, Maxmin u\E estimator, fuzzy model identification

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Authors: Arun Kharate, Sarata Kumar Sahu, Susen Kumar Panda, Niranjan Sahoo, H. K. Panda

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In the present study, an attempt has been made for isolation and identification of feline panleukopaenia virus (FPLV) from wild felids of Nandankanan zoo, Odisha, India, along with prevalence study of FPLV. Fecal samples collected from wild felids (26 tigers, 22 lions, 5 leopards, 3 hyenas, 1 jaguar, 2 foxes and 1 wild cat) were subjected to hemagglutinnation test and fluorescent antibody test. In hemagglutinnation test 13 (50%) samples from tiger, 14 (63.63%) samples from lions, 1 (20%) sample from leopards, 1 (50%) from fox, 3 (100%) samples from hyenas and 1 (100%) sample from wild cat were positive. On fluorescent antibody test (FAT), 15 (57.69%) samples from tiger, 18 (81.81%) from lions, 2 (40%) from leopards, 1 (50%) from fox, 3 (100%) from hyenas and 1 (100%) from wild cat were positive. FPLV was isolated using MDBK cell line and preliminary characterization was done on the basis of characteristic cytopathic effect. The virus samples were quantified through titration in MDBK cells. Serological confirmation of FPLV isolates was carried out by HI test, micro-SNT and indirect-ELISA. Physico-chemical characters like pH and temperature resistance along molecular identification using specific FPLV primers was carried out. Seroprevalence study of 36 serum samples employing HI test, micro SNT and indirect-ELISA revealed prevalence of 38.8, 44.4 and 72.2% respectively. During study period an adult tigress and a tiger cub died suspected of feline panleukopenia. The necropsy findings in both animals showed hemorrhagic gastroenteritis. The cytological examination revealed presence of intranuclear inclusion bodies in the intestinal epithelial cells. Spleen, mesenteric lymph node and intestine were positive for feline panleukopenia by FAT. The investigation revealed that feline panleukopenia was prevalent in wild felines of Nandankanan zoo.

Keywords: Feline panleukopenia, fluorescent antibody test, hemagglutination test, indirect-ELISA, Nandankanan zoo

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Authors: Guohua Cao, Xu Dong

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X-ray Fluorescence Molecular Imaging (XFMI) holds great promise as a low-cost molecular imaging modality for biomedical applications with high chemical sensitivity. However, for in vivo biomedical applications, a key technical bottleneck is the relatively low chemical sensitivity of XFMI, especially at a reasonably low radiation dose. In laboratory x-ray source based XFMI, one of the main factors that limits the chemical sensitivity of XFMI is the scattered x-rays. We will present our latest findings on improving the chemical sensitivity of XFMI using excitation beam spectrum optimization. XFMI imaging experiments on two mouse-sized phantoms were conducted at three different excitation beam spectra. Our results show that the minimum detectable concentration (MDC) of iodine can be readily increased by five times via excitation spectrum optimization. Findings from this investigation could find use for in vivo pre-clinical small-animal XFMI in the future.

Keywords: molecular imaging, X-ray fluorescence, chemical sensitivity, X-ray scattering

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Authors: Reda Abdel-Aziz

Abstract:

Agricultural activities in Egypt generate annually around 35 million tons of waste. Composting is one of the most promising technologies to turnover waste in a more economical way, for many centuries. Composting has been used as a mean of recycling organic matter back into the soil to improve soil structure and fertility. Field experiments were conducted in two governorates, Giza and Al-Monofia, to find out the effect of compost with different rates of chemical fertilizers on growth and yield of corn (Zea mays L.) during two constitutive seasons of 2012 and 2013. The experiment, laid out in a randomized complete block design (RCBD), was carried out on five farmers’ fields in each governorate. The treatments were: unfertilized control, full dose of NPK (120, 30, and 50 kg/acre, respectively), compost at rate of 20 ton/acre, compost at rate of 10 ton/acre + 25% of chemical fertilizer, compost at rate of 10 ton/acre + 50% of chemical fertilizer and compost at rate of 10 ton/acre + 75% of chemical fertilizer. Results revealed a superiority of the treatment of compost at rate of 10 ton/acre + 50% of NPK that caused significant improvement in growth, yield and nutrient uptakes of corn in the two governorates during the two constitutive seasons. Results showed that agricultural waste could be composted into value added soil amendment to enhance efficiency of chemical fertilizer. Composting of agricultural waste could also reduce the chemical fertilizers potential hazard to the environment.

Keywords: agricultural waste, compost, chemical fertilizers, corn production, environment

Procedia PDF Downloads 296

Authors: Merih Şimşek, Recep Keşli, Özgül Çetinkaya, Cengiz Demir, Adem Aslan

Abstract:

Bacteremia is a clinical entity with high morbidity and mortality rates when immediate diagnose, or treatment cannot be achieved. Microorganisms which can cause sepsis or bacteremia are easily isolated from blood cultures. Fifty-five positive blood cultures were included in this study. Microorganisms in 55 blood cultures were isolated by conventional microbiological methods; afterwards, microorganisms were defined in terms of the phenotypic aspects by the Vitek-2 system. The same microorganisms in all blood culture samples were defined in terms of genotypic aspects again by Multiplex-PCR DNA Low-Density Microarray System. At the end of the identification process, the DNA microarray system’s success in identification was evaluated based on the Vitek-2 system. The Vitek-2 system and DNA Microarray system were able to identify the same microorganisms in 53 samples; on the other hand, different microorganisms were identified in the 2 blood cultures by DNA Microarray system. The microorganisms identified by Vitek-2 system were found to be identical to 96.4 % of microorganisms identified by DNA Microarrays system. In addition to bacteria identified by Vitek-2, the presence of a second bacterium has been detected in 5 blood cultures by the DNA Microarray system. It was identified 18 of 55 positive blood culture as E.coli strains with both Vitek 2 and DNA microarray systems. The same identification numbers were found 6 and 8 for Acinetobacter baumanii, 10 and 10 for K.pneumoniae, 5 and 5 for S.aureus, 7 and 11 for Enterococcus spp, 5 and 5 for P.aeruginosa, 2 and 2 for C.albicans respectively. According to these results, DNA Microarray system requires both a technical device and experienced staff support; besides, it requires more expensive kits than Vitek-2. However, this method should be used in conjunction with conventional microbiological methods. Thus, large microbiology laboratories will produce faster, more sensitive and more successful results in the identification of cultured microorganisms.

Keywords: microarray, Vitek-2, blood culture, bacteremia

Procedia PDF Downloads 315

Authors: Sami Ayad, Mengshan Lee

Abstract:

The Sustainable Development Goals (SDGs) were designed to be the best possible blueprint to achieve peace, prosperity, and overall, a better and more sustainable future for the Earth and all its people, and such a blueprint is needed more than ever. The SDGs face many hurdles that will prevent them from becoming a reality, one of such hurdles, arguably, is the chemical pollution and unintended chemical impacts generated through the production of various goods and resources that we consume. Chemical Alternatives Assessment has proven to be a viable solution for chemical pollution management in terms of filtering out hazardous chemicals for a greener alternative. However, the current substitution practice lacks crucial quantitative datasets (exposures and life cycle impacts) to ensure no unintended trade-offs occur in the substitution process. A Chemical Life Cycle Alternative Assessment (CLiCAA) framework is proposed as a reliable and replicable alternative to Life Cycle Based Alternative Assessment (LCAA) as it integrates chemical molecular structure analysis and Chemical Life Cycle Collaborative (CLiCC) web-based tool to fill in data gaps that the former frameworks suffer from. The CLiCAA framework consists of a four filtering layers, the first two being mandatory, with the final two being optional assessment and data extrapolation steps. Each layer includes relevant impact categories of each chemical, ranging from human to environmental impacts, that will be assessed and aggregated into unique scores for overall comparable results, with little to no data. A feasibility study will demonstrate the efficiency and accuracy of CLiCAA whilst bridging both cancer potency and exposure limit data, hoping to provide the necessary categorical impact information for every firm possible, especially those disadvantaged in terms of research and resource management.

Keywords: chemical alternative assessment, LCA, LCAA, CLiCC, CLiCAA, chemical substitution framework, cancer potency data, chemical molecular structure analysis

Procedia PDF Downloads 57