Search results for: mixed methods approach

Authors: T. Kuchukhidze, N. Jalagonia, T. Korkia, V. Gabunia, N. Jalabadze, R. Chedia

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In this work, obtaining methods of ultrafine alumina powdery composites and high temperature pressing technology of matrix ceramic composites with different compositions have been discussed. Alumina was obtained by solution combustion synthesis and sol-gel methods. Metal carbides containing powdery composites were obtained by homogenization of finishing powders in nanomills, as well as by their single-step high temperature synthesis .Different types of matrix ceramics composites (α-Al2O3-ZrO2-Y2O3, α-Al2O3- Y2O3-MgO, α-Al2O3-SiC-Y2O3, α-Al2O3-WC-Co-Y2O3, α-Al2O3- B4C-Y2O3, α-Al2O3- B4C-TiB2 etc.) were obtained by using OXYGON furnace. Consolidation of powders were carried out at 1550- 1750°C (hold time - 1 h, pressure - 50 MPa). Corundum ceramics samples have been obtained and characterized by high hardness and fracture toughness, absence of open porosity, high corrosion resistance. Their density reaches 99.5-99.6% TD. During the work, the following devices have been used: High temperature vacuum furnace OXY-GON Industries Inc (USA), Electronic Scanning Microscopes Nikon Eclipse LV 150, Optical Microscope NMM- 800TRF, Planetary mill Pulverisette 7 premium line, Shimadzu Dynamic Ultra Micro Hardness Tester DUH-211S, Analysette 12 Dynasizer.

Keywords: α-alumina, consolidation, phase transformation, powdery composites

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Authors: A. J. Cobley, L. Krishnan

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The demand for multi-functional lightweight materials in sectors such as automotive, aerospace, electronics is growing, and for this reason fibre-reinforced, epoxy polymer composites are being widely utilized. The fibre reinforcing material is mainly responsible for the strength and stiffness of the composites whilst the main role of the epoxy polymer matrix is to enhance the load distribution applied on the fibres as well as to protect the fibres from the effect of harmful environmental conditions. The superior properties of the fibre-reinforced composites are achieved by the best properties of both of the constituents. Although factors such as the chemical nature of the epoxy and how it is cured will have a strong influence on the properties of the epoxy matrix, the method of mixing and degassing of the resin can also have a significant impact. The production of a fibre-reinforced epoxy polymer composite will usually begin with the mixing of the epoxy pre-polymer with a hardener and accelerator. Mechanical methods of mixing are often employed for this stage but such processes naturally introduce air into the mixture, which, if it becomes entrapped, will lead to voids in the subsequent cured polymer. Therefore, degassing is normally utilised after mixing and this is often achieved by placing the epoxy resin mixture in a vacuum chamber. Although this is reasonably effective, it is another process stage and if a method of mixing could be found that, at the same time, degassed the resin mixture this would lead to shorter production times, more effective degassing and less voids in the final polymer. In this study the effect of four different methods for mixing and degassing of the pre-polymer with hardener and accelerator were investigated. The first two methods were manual stirring and magnetic stirring which were both followed by vacuum degassing. The other two techniques were ultrasonic mixing/degassing using a 40 kHz ultrasonic bath and a 20 kHz ultrasonic probe. The cured cast resin samples were examined under scanning electron microscope (SEM), optical microscope, and Image J analysis software to study morphological changes, void content and void distribution. Three point bending test and differential scanning calorimetry (DSC) were also performed to determine the thermal and mechanical properties of the cured resin. It was found that the use of the 20 kHz ultrasonic probe for mixing/degassing gave the lowest percentage voids of all the mixing methods in the study. In addition, the percentage voids found when employing a 40 kHz ultrasonic bath to mix/degas the epoxy polymer mixture was only slightly higher than when magnetic stirrer mixing followed by vacuum degassing was utilized. The effect of ultrasonic mixing/degassing on the thermal and mechanical properties of the cured resin will also be reported. The results suggest that low frequency ultrasound is an effective means of mixing/degassing a pre-polymer mixture and could enable a significant reduction in production times.

Keywords: degassing, low frequency ultrasound, polymer composites, voids

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Authors: Maryam Mousavi Nik, Sara Pasandian

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The aim of the current research was to determine the effectiveness of Cognitive-Behavioral Group Therapy (G-CBT) on stress, illness anxiety and obsessions-compulsion caused by the coronavirus crisis in adolescents (14-18-Year-olds) in Tehran, Iran. This research was carried out in the form of a semi-experimental study with a control group and in the framework of a pre-test and post-test design for both experimental and control groups. The statistical population of this research consisted of all high schools in Tehran in 2022. The sample size includes 32 Adolescents (14-18-Year-olds) who were selected using a cluster sampling method, and then they were randomly replaced in two experimental (n=16) and control (n=16) groups. In this research, an adolescent stress questionnaire (ASQ-N) with an emphasis on the impact of Coronavirus, Coronavirus disease anxiety (CDAS) and The Children's Yale-Brown Obsessive Compulsive Symptom Scale (CY-BOCS) emphasis on the Coronavirus were used, and group therapy intervention with The cognitive-behavioral approach was conducted for 8 sessions of 90 minutes in the experimental group. The research data were analyzed by Multivariate analysis of covariance (MANCOVA) and covariance (ANCVA) tests. The results of multivariate covariance analysis showed that group therapy intervention with a cognitive-behavioral approach had a significant effect on at least one of the variables of stress, illness anxiety and obsession-compulsion at the level (P<0.01, F=94.772) in the post-test stage. Also, the results of covariance analysis of one variable showed that group therapy intervention with a cognitive-behavioral approach in the level of (P<0.01, F=106.377) stress, in the level of (P<0.01, F=48.147) disease anxiety and in the level (P>0.01, F=17.033) of obsession-compulsion had a significant effect in the post-test stage. The results showed that The treatment with GCBT can be effective in decreasing stress, illness anxiety and obsessions and compulsion caused by the coronavirus crisis in Adolescents (15-20-Year-olds) and may be considered as an alternative to either individual cognitive-behavioral therapy or medication.

Keywords: stress, disease anxiety, obsession-compulsion, coronavirus (Covid-19) crisis, and cognitive-behavioral therapy

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Authors: Betsy Hannam

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Background: Staff nurses felt overwhelmed to learn new skills or complete competencies during their shift. Med/Surg units need to provide dedicated, uninterrupted time to complete training and mandatory competencies and practice skills. Purpose: To improve nurse satisfaction and competence by creating a Skills Day with uninterrupted time to complete competencies, brush up on skills, and evaluate skills learned through pre- and post-tests. Methods: The USL and CNL interviewed nurses to obtain input regarding skills needing reinforcement and included mandatory competencies relevant to Med/Surg to create the Skills Day agenda. Content experts from multiple disciplines were invited to educate staff to help address knowledge gaps. To increase attendance, multiple class days were offered. Results: 2018 Skills Day was held for an inpatient unit with 95% participation (n=35 out of 37RNs). The average pretest score, comprised of content questions from topics discussed, was 57%, and post test scoresaveraged 80%. 94% of test scores improved or remained the same. RNs were given an evaluation at the end of the day, where100% of staff noted Skills Day as beneficial, and 97% requested to repeat next year. Another Med/Surg unit asked to join Skills Day in 2019. In 2019, with 89% participation (n=57 out 64 RNs), the average pretest score was 68%, and the average post test score was 85%. 97% of scores improved or remained the same. 98% reported the class as beneficial, and 96% requested to repeat next year. Skills Day 2020-2022 on hold due to COVID. Looking forward to Skills Day 2023. Conclusion: Skills Day allows nurses to maintain competencies and improve knowledge in areas of interest without the stress of a patient assignment. Having unit leaders organize Skills Day, with the involvement of content experts from multiple disciplines, showed to be a successful and innovative team approach to support professional development.

Keywords: education, competency, skills day, medical/surgical

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Authors: Meshal Al-Samhan, Abdullah Al-Marshed

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Recently, there has been a tremendous increase in interest in nanotechnology applications and nanomaterials in the oilfield. In the last decade, the global increase in oil production resulted in large amounts of produced water, causing a significant problem for all producing countries and companies. This produced water deserves special attention and a study of its characteristics to understand and determine how it can be treated and later used for suitable applications such as water injection for Enhance Oil Recovery (EOR) without harming the environment. This work aims to investigate the prepared compatible mixed water (seawater and effluent water) response to nanoparticles for EOR water injection. The evaluation of different mix seawater/effluent water ratios (60/40,70/30) for their characteristics prior to nanofluid preparation using Inductive Couple Plasma (ICP) analysis, potential zeta test, and OLI software (the OLI Systems is a recognised leader in aqueous chemistry). This step of the work revealed the suitability of the water mix with a lower effluent-water ratio. Also, OLI predicted that the 60:40 mix needs to be balanced around temperatures of 70 ºC to avoid the mass accumulation of calcium sulfate and strontium sulfate. Later the prepared nanofluid was tested for interfacial tension (IFT) and wettability restoration in the sandstone rock; the Al2O3 nanofluid at 0.06 wt% concentration reduced the IFT by more than 16% with moderate water wet contact angle. The study concluded that the selected nanoparticle Al2O3 had demonstrated excellent performance in decreasing the interfacial tension with respect to the selected water mix type (60/40) at low nanoparticles wt%.

Keywords: nano AL2O3, sanstone, nanofluid, IFT, wettability

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Authors: Oladipo Oluwaseun Peter

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Daily consumption of crude oil is alarming as a result of increasing demand for energy. Waste generation tends to rise with the level of economic advancement of a nation. Hence, this project work researches how wastes which could pose toxic if left unattended to can be processed through biodigestion in order to generate biofuel which could serve as a good substitute for petroleum, a non renewable energy source, so as to reduce over-dependence on petroleum and to prevent environmental pollution. Anaerobic digestion was carried out on organic wastes comprising brewery spent grains, rice husks and poultry droppings in a plastic biodigester of 1000 liters volume using the poultry droppings as a natural inoculums source. The feed composition in ratio 5:3:2, spent grain, rice husks and poultry droppings were mixed with water in the ratio 1:6. Thus, 600 Kg of water was used to prepare the slurry with 100 Kg of feed materials. A plastic biodigester was successfully constructed, and the problem of corrosion and rusting were completely overcome as a result of the use of non-corroding materials of construction. A reasonable quantity of biogas, 33.63m3, was generated over a period of 60 days of biodigestion. The bioslurry was processed through two different process routes; evaporation and filteration. Evaporation process of analysis shows high values of 0.64%, 2.11% and 0.034% for nitrogen, phosphorous and potassium respectively, while filteration process gives 00.61%, 1.93% and 0.026% for nitrogen, phosphorous and potassium respectively.

Keywords: biodigestion, biofuel, digestion, slurry, biogas

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Authors: Erina Wulansari, Bambang Soemardiono, Ispurwono Soemarno

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Designing sustainable tourism area is defined as an attempt to design an area, that brings the natural environmental conditions as components are available with a wealth of social conditions and the conservation of natural and cultural heritage. To understanding tourism area in this study is not only focus on the location of the tourist object, but rather to a tourist attraction around the area, tourism objects such as the existence of residential area (settlement), a commercial area, public service area, and the natural environmental area. The principle of success in designing a sustainable tourism area is able to integrate and balance between the limited space and the variety of activities that’s always continuously to growth up. The limited space in this area of tourism needs to be managed properly to minimize the damage of environmental as a result of tourism activities hue. This research aims to identify space in this area of tourism through land suitability approach as an effort to create a sustainable design, especially in terms of ecological. This study will be used several analytical techniques to achieve the research objectives as superimposing analysis with GIS 9.3 software and Analysis Hierarchy Process. Expected outcomes are in the form of classification and criteria of usable space in designing embodiment tourism area. In addition, this study can provide input to the order of settlement patterns as part of the environment in the area of sustainable tourism.

Keywords: sustainable tourism area, land suitability, limited space, environment, criteria

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Authors: Dmitry Yu. Korulkin, Raissa A. Muzychkina

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Currently to treat infectious diseases bioactive substances of plant origin having fewer side effects than synthetic medicines and medicines similar to natural components of a human body by the structure and action, become very important. One of the groups of secondary metabolites of the plants - alkaloids can be related the number of the most promising sources of medicines of plant origin. Currently, the structure of more than 7500 compounds has been identified. Analyzing the scope of research in the field of chemistry, pharmacology and technology of alkaloids, we can make a conclusion about that there is no system approach during the research of relation structure-activity on different groups of these substances. It is connected not only with a complex structure of their molecules, but also with insufficient information on the nature of their effect on organs, tissues and other targets in organism. The purpose of this research was to identify pharmacophore groups in the structure of alkaloids of endemic Polygonum L. plants growing in Kazakhstan responsible for their antiviral action. To isolate alkaloids pharmacopoeian methods were used. Antiviral activity of alkaloids of Polygonum L. plants was researched in the Institute of Microbiology and Virology of the Ministry of Education and Science of the Republic of Kazakhstan. Virus-inhibiting properties of compounds were studies in experiments with ortho- and paramyxoviruses on the model of chick-embryos. Anti-viral properties were determined using ‘screening test’ method designed to neutralization of a virus at the amount of 100EID50 with set concentrations of medicines. The difference of virus titer compared to control group was deemed as the criterion of antiviral action. It has been established that Polygonum L. alkaloids has high antiviral effect to influenza and parainfluenza viruses. The analysis of correlation of the structure and antiviral activity of alkaloids allowed identifying the main pharmacophore groups, among which the most important are glycosidation, the presence of carbonyl and hydroxyl groups, molecular weight and molecular size.

Keywords: alkaloids, antiviral, bioactive substances, isolation, pharmacophore groups, Polygonum L.

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Authors: Bandar Alahmadi, Lethia Jackson

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Machine Learning model is used today in many real-life applications. The safety and security of such model is important, so the results of the model are as accurate as possible. One challenge of machine learning model security is the adversarial examples attack. Adversarial examples are designed by the attacker to cause the machine learning model to misclassify the input. We propose a method to generate adversarial examples to attack image classifiers. We are modifying the successfully classified images, so a classifier misclassifies them after the modification. In our method, we do not update the whole image, but instead we detect the important region, modify it, place it back to the original image, and then run it through a classifier. The algorithm modifies the detected region using two methods. First, it will add abstract image matrix on back of the detected image matrix. Then, it will perform a rotation attack to rotate the detected region around its axes, and embed the trace of image in image background. Finally, the attacked region is placed in its original position, from where it was removed, and a smoothing filter is applied to smooth the background with foreground. We test our method in cascade classifier, and the algorithm is efficient, the classifier confident has dropped to almost zero. We also try it in CNN (Convolutional neural network) with higher setting and the algorithm was successfully worked.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Jan Van Uden

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The paper reviews classical agency-theory and its contributions to the analysis of complex business negotiations and gives an approach for the modification of the basic agency-model in order to examine the negotiation specific dimensions of agency-problems. By illustrating fundamental potentials for the modification of agency-theory in context of business negotiations the paper highlights recent empirical research that investigates agent-based negotiations and inter-team constellations. A general theoretical analysis of complex negotiation would be based on a two-level approach. First, the modification of the basic agency-model in order to illustrate the organizational context of business negotiations (i.e., multi-agent issues, common-agencies, multi-period models and the concept of bounded rationality). Second, the application of the modified agency-model on complex business negotiations to identify agency-problems and relating areas of risk in the negotiation process. The paper is placed on the first level of analysis – the modification. The method builds on the one hand on insights from behavior decision research (BRD) and on the other hand on findings from agency-theory as normative directives to the modification of the basic model. Through neoclassical assumptions concerning the fundamental aspects of agency-relationships in business negotiations (i.e., asymmetric information, self-interest, risk preferences and conflict of interests), agency-theory helps to draw solutions on stated worst-case-scenarios taken from the daily negotiation routine. As agency-theory is the only universal approach able to identify trade-offs between certain aspects of economic cooperation, insights obtained provide a deeper understanding of the forces that shape business negotiation complexity. The need for a modification of the basic model is illustrated by highlighting selected issues of business negotiations from agency-theory perspective: Negotiation Teams require a multi-agent approach under the condition that often decision-makers as superior-agents are part of the team. The diversity of competences and decision-making authority is a phenomenon that overrides the assumptions of classical agency-theory and varies greatly in context of certain forms of business negotiations. Further, the basic model is bound to dyadic relationships preceded by the delegation of decision-making authority and builds on a contractual created (vertical) hierarchy. As a result, horizontal dynamics within the negotiation team playing an important role for negotiation success are therefore not considered in the investigation of agency-problems. Also, the trade-off between short-term relationships within the negotiation sphere and the long-term relationships of the corporate sphere calls for a multi-period perspective taking into account the sphere-specific governance-mechanisms already established (i.e., reward and monitoring systems). Within the analysis, the implementation of bounded rationality is closely related to findings from BRD to assess the impact of negotiation behavior on underlying principal-agent-relationships. As empirical findings show, the disclosure and reservation of information to the agent affect his negotiation behavior as well as final negotiation outcomes. Last, in context of business negotiations, asymmetric information is often intended by decision-makers acting as superior-agents or principals which calls for a bilateral risk-approach to agency-relations.

Keywords: business negotiations, agency-theory, negotiation analysis, interteam negotiations

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Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean

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The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.

Keywords: pan evaporation, intelligent methods, shahroud, mayamey

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Authors: Eakarat Boonreang

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The past two decades, Thailand faced the natural disasters, for instance, Gay typhoon in 1989, tsunami in 2004, and huge flood in 2011. The disaster management in Thailand was improved both structure and mechanism for cope with the natural disaster since 2007. However, the natural disaster management in Thailand has various problems, for examples, cooperation between related an organizations have not unity, inadequate resources, the natural disaster management of public sectors not proactive, people has not awareness the risk of the natural disaster, and communities did not participate in the natural disaster management. Objective of this study is to find the methods for capacity building in the natural disaster management of Thailand. The concept and information about the capacity building and the natural disaster management of Thailand were reviewed and analyzed by classifying and organizing data. The result found that the methods for capacity building in the natural disaster management of Thailand should be consist of 1)link operation and information in the natural disaster management between nation, province, local and community levels, 2)enhance competency and resources of public sectors which relate to the natural disaster management, 3)establish proactive natural disaster management both planning and implementation, 4)decentralize the natural disaster management to local government organizations, 5)construct public awareness in the natural disaster management to community, 6)support Community Based Disaster Risk Management (CBDRM) seriously, and 7)emphasis on participation in the natural disaster management of all stakeholders.

Keywords: capacity building, Community Based Disaster Risk Management (CBDRM), Natural Disaster Management, Thailand

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Authors: Cristian Crespo

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Conditional cash transfers (CCTs) have been targeted towards the poor. Thus, their targeting assessments check whether these schemes have been allocated to low-income households or individuals. However, CCTs have more than one goal and target group. An additional goal of CCTs is to increase school enrolment. Hence, students at risk of dropping out of school also are a target group. This paper analyses whether one of the most common targeting mechanisms of CCTs, a proxy means test (PMT), is suitable to identify the poor and future school dropouts. The PMT is compared with alternative approaches that use the outputs of a predictive model of school dropout. This model was built using machine learning algorithms and rich administrative datasets from Chile. The paper shows that using machine learning outputs in conjunction with the PMT increases targeting effectiveness by identifying more students who are either poor or future dropouts. This joint targeting approach increases effectiveness in different scenarios except when the social valuation of the two target groups largely differs. In these cases, the most likely optimal approach is to solely adopt the targeting mechanism designed to find the highly valued group.

Keywords: conditional cash transfers, machine learning, poverty, proxy means tests, school dropout prediction, targeting

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Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

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Authors: Blerim Olluri

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A forensic science laboratory in Kosovo has never been organized at the level of most modern forensic science laboratories. This was made possible after the war of 1999 with the help and support from the United States. The United States Government/ICITAP provided 9.5 million dollars to support this project, this support have greatly benefitted law enforcement in Kosovo. With the establishment of Operative Procedures of Work and the law for Kosovo Agency of Forensic, the accreditation with ISO/IEC 17025 of the KAF labs it becomes mandatory. Since 2012 Laboratory’s DNA/Serology and Narcotics has begun reviewing and harmonizing their procedures according to ISO/IEC 17025. The focus of this work was to create quality manuals, procedures, work instructions, quality documentation and quality records. Furthermore, during this time is done the validation of work methods from scientific qualified personnel of KAF, without any help from other foreign agencies or accreditation body.In October 2014 we had the first evaluation based on ISO 17025 standards. According to the initial report of this assessment we have non conformity in test and Calibration methods method’s, and accommodation and environmental conditions. We identified several issues that are of extreme importance to KAF. One the most important issue is to create a professional group with experts of KAF, which will work in all the obligations, requested from ISO/IEC 17025. As conclusions that we earn in this path of accreditation, are that laboratory’s need to take corrective action, and all nonconformance’s must be addressed and corrective action taken before accreditation can be granted.

Keywords: accreditation, assessment, narcotics, DNA

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Authors: Amna Batool

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Agile methodology is the current most popular technique in software development projects. Agile methods in software development bring optimistic impact on software performances, quality and customer satisfaction. There are some organizations and small-medium enterprises adopting agile into their local software development projects as well as in distributed software development projects. Adopting agile methods in local software development projects is valuable. However, agile global software deployment needs an attention. There are different key challenges in agile global software development that need to resolve and enhance the global software development cycles. The proposed systematic literature review investigates all key challenges of agile in global software development. Moreover, a quantitative methodology (an actual survey) targeted to present a real case scenario of these particular key challenges faced by one of the software houses that is BestWeb Malaysia. The outcomes of systematic literature and the results of quantitative methodology are compared with each other to evaluate if the key challenges pointed out in systematic review still exist. The proposed research and its exploratory results can assist small medium enterprises to avoid these challenges by adopting the best practices in their global software development projects. Moreover, it is helpful for novice researchers to get valuable information altogether.

Keywords: agile software development, ASD challenges, agile global software development, challenges in agile global software development

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Authors: Shima Hashemi, Firoozeh Ghazanfari

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Introduction: Eating disorder is a psychiatric disorder that is increasingly growing. This study aimed to determine the relationship between eating disorders (anorexia and bulimia nervosa) with some of the demographic factors among Lorestan University of Medical Sciences students. Materials and Methods: This study is a cross-sectional and descriptive study that was done at Lorestan University of Medical Sciences in 2019. Four hundred fifty students were studied by stratified and cluster sampling methods. For gathering data, we use the standard questionnaire Eating Attitudes Test EAT (26). Data were analyzed using statistical software SPSS. Results: According to the results, 144 (32%) males and 305 (67.8%) females were studied. 88.7% were single, and 8.9% were married. In the anorexia nervosa group, the results showed that there was a significant meaning between demographic information, and the number of family members, marital status, BMI, level of education, family income, father and mother education, as well as in the bulimia nervosa group, there was no significant meaning with any demographic information (p>0.05). Conclusion: Anorexia and bulimia nervosa are two known types of eating disorders, and some demographic factors can be effective in causing or aggravating these disorders.

Keywords: eating disorder, anorexia nervosa, bulimia nervosa, students

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Authors: Sara Mahesar, Saleem M. Chandio, Hira Soomro

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Nonlinear system of equations in two variables is a system which contains variables of degree greater or equal to two or that comprises of the transcendental functions. Mathematical modeling of numerous physical problems occurs as a system of nonlinear equations. In applied and pure mathematics it is the main dispute to solve a system of nonlinear equations. Numerical techniques mainly used for finding the solution to problems where analytical methods are failed, which leads to the inexact solutions. To find the exact roots or solutions in case of the system of non-linear equations there does not exist any analytical technique. Various methods have been proposed to solve such systems with an improved rate of convergence and accuracy. In this paper, a new scheme is developed for solving system of non-linear equation in two variables. The iterative scheme proposed here is modified form of the conventional Newton’s Method (CN) whose order of convergence is two whereas the order of convergence of the devised technique is three. Furthermore, the detailed error and convergence analysis of the proposed method is also examined. Additionally, various numerical test problems are compared with the results of its counterpart conventional Newton’s Method (CN) which confirms the theoretic consequences of the proposed method.

Keywords: conventional Newton’s method, modified Newton’s method, order of convergence, system of nonlinear equations

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Authors: Yoftahe Nigussie Worku

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This report unveils a meticulous project focused on the design intricacies of a Fire Tube Boiler tailored for the efficient generation of saturated steam. The overarching objective is to produce 2000kg/h of saturated steam at 12-bar design pressure, achieved through the development of an advanced fire tube boiler. This design is meticulously crafted to harmonize cost-effectiveness and parameter refinement, with a keen emphasis on material selection for component parts, construction materials, and production methods throughout the analytical phases. The analytical process involves iterative calculations, utilizing pertinent formulas to optimize design parameters, including the selection of tube diameters and overall heat transfer coefficients. The boiler configuration incorporates two passes, a strategic choice influenced by tube and shell size considerations. The utilization of heavy oil fuel no. 6, with a higher heating value of 44000kJ/kg and a lower heating value of 41300kJ/kg, results in a fuel consumption of 140.37kg/hr. The boiler achieves an impressive heat output of 1610kW with an efficiency rating of 85.25%. The fluid flow pattern within the boiler adopts a cross-flow arrangement strategically chosen for inherent advantages. Internally, the welding of the tube sheet to the shell, secured by gaskets and welds, ensures structural integrity. The shell design adheres to European Standard code sections for pressure vessels, encompassing considerations for weight, supplementary accessories (lifting lugs, openings, ends, manhole), and detailed assembly drawings. This research represents a significant stride in optimizing fire tube boiler technology, balancing efficiency and safety considerations in the pursuit of enhanced saturated steam production.

Keywords: fire tube, saturated steam, material selection, efficiency

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Authors: Pratima Kumari, Sukha Ranjan Samadder

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This research aims to contribute to the sustainable production of graphene materials by exploring the extraction of graphite from spent primary and secondary batteries. The increasing demand for graphene materials, a versatile and high-performance material, necessitates environmentally friendly methods for its synthesis. The process involves a well-planned methodology, beginning with the gathering and categorization of batteries, followed by the disassembly and careful removal of graphite from anode structures. The use of environmentally friendly solvents and mechanical techniques ensures an efficient and eco-friendly extraction of graphite. Advanced approaches such as the modified Hummers' method and chemical reduction process are utilized for the synthesis of graphene materials, with a focus on optimizing parameters. Various analytical techniques such as Fourier-transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy, thermogravimetric analysis, and Raman spectroscopy were employed to validate the quality and structure of the produced graphene materials. The major findings of this study reveal the successful implementation of the methodology, leading to the production of high-quality graphene materials suitable for advanced material applications. Thorough characterization using various advanced techniques validates the structural integrity and purity of the graphene. The economic viability of the process is demonstrated through a comprehensive economic analysis, highlighting the potential for large-scale production. This research contributes to the field of sustainable production of graphene materials by offering a systematic methodology that efficiently transforms spent batteries into valuable graphene resources. Furthermore, the findings not only showcase the potential for upcycling electronic waste but also address the pressing need for environmentally conscious processes in advanced material synthesis.

Keywords: spent primary batteries, spent secondary batteries, graphite extraction, advanced material synthesis, circular economy approach

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Authors: L. Abdou, O. Taibaoui, A. Moumen, A. Talib Ahmed

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This paper proposes an application of the simulated annealing to optimize the detection threshold in an ordered statistics constant false alarm rate (OS-CFAR) system. Using conventional optimization methods, such as the conjugate gradient, can lead to a local optimum and lose the global optimum. Also for a system with a number of sensors that is greater than or equal to three, it is difficult or impossible to find this optimum; Hence, the need to use other methods, such as meta-heuristics. From a variety of meta-heuristic techniques, we can find the simulated annealing (SA) method, inspired from a process used in metallurgy. This technique is based on the selection of an initial solution and the generation of a near solution randomly, in order to improve the criterion to optimize. In this work, two parameters will be subject to such optimisation and which are the statistical order (k) and the scaling factor (T). Two fusion rules; “AND” and “OR” were considered in the case where the signals are independent from sensor to sensor. The results showed that the application of the proposed method to the problem of optimisation in a distributed system is efficiency to resolve such problems. The advantage of this method is that it allows to browse the entire solutions space and to avoid theoretically the stagnation of the optimization process in an area of local minimum.

Keywords: distributed system, OS-CFAR system, independent sensors, simulating annealing

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Authors: Lina M. Vidal

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This paper discusses yoga practices involvement in both self-transformation and social transformations by means of an embodied ethnographic approach to different initiatives for social change in Medellín. In the context of gradual popularization of embodied spiritualities, yoga practices have opened their way in calls for social change in a performative perspective which involves collective experiences, reflections and production of embodied knowledge. Through the reflection on bodily dimension and corporal experience, this ethnographic approach acknowledges inter-corporality and somatic modes of attention during observations and personal experiences. In social change initiatives that include yoga practices were identified transformations of common understanding on social issues such as it is produced by institutionalized education, health system and other fields of knowledge. This is clearly visible in yoga projects for children in vulnerable conditions, homeless people, prisoners, and young people recovering from drug addiction. These projects are often promoted by organizations and networks, which incorporate individual life stories into collective experiences. Dissemination of yoga is heading to a broad institutional and cultural legitimation of yoga and of spirituality that impact different fields of social work and everyday life in general. This way, yoga is becoming an embodied activist way of life and a legitimate field for social work.

Keywords: embodied ethnography, Medellin, social transformation, embodied spiritualities, yoga practices

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Authors: Aly Kassem, Eman Sapet, Eman Abdelbaset, Hosam Mahmoud

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Objective: Hypertension is an important public health challenge being one of the most common worldwide disease-affecting human. Our aim is to study the clinical characteristics, therapeutic regimens, treatment compliance, and risk factors in a sector of of hypertensive patients at Sohag City. Subject and Methods: A cross sectional study; conducted in Sohag city; it involved 520 patients; males (45.7 %) and females (54.3 %). Their ages ranged between 35-85 years. BP measurements, BMI, blood glucose, Serum creatinine, urine analysis, serum Lipids, blood picture and ECG were done all the studied patients. Results: Hypertension presented more between non-smokers (72.55%), females (54.3%), educated patients (50.99%) and patients with low SES (54.9%). CAD presented in (51.63%) of patients, while laboratory investigations showed hyperglycaemia in (28.7%), anemia in (18.3%), high serum creatinine level in (8.49%) and proteinuria in (10.45%) of patient. Adequate BP control was achieved in (49.67%); older patients had lower adequacy of BP control in spite of the extensive use of multiple-drug therapy. Most hypertensive patients had more than one coexistent CV risk factor. Aging, being a female (54.3%), DM (32.3%), family history of hypertension (28.7%), family history of CAD (25.4%), and obesity (10%) were the common contributing risk factors. ACE-inhibitors were prescribed in (58.16%), Beta-blockers in (34.64%) of the patients. Monotherapy was prescribed for (41.17%) of the patients. (75.81%) of patients had regular use of their drug regimens. (49.67%) only of patients had their condition under control, the number of drugs was inversely related to BP control. Conclusion: Hypertensive patients in Sohag city had a profile of high CV risks, and poor blood pressure control particularly in the elderly. A multidisciplinary approach for routine clinical check-up, follow-up, physicians and patients training, prescribing simple once-daily regimens and encouraging life style modifications are recommended. Anti hypertensives, hypertension, elderly patients, risk factors, treatment compliance.

Keywords: anti hypertensives, hypertension, elderly patients, risk factors, treatment compliance

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Authors: Kritika Kulhari, Aparna Sahu

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Test anxiety results from concerns about failure in examinations or evaluative situations. Attentional biases are known to pronounce the symptomatic expression of test anxiety. In recent times, the inattentional blindness (IB) paradigm has shown promise as an attention bias modification treatment (ABMT) for anxiety by overcoming practice and expectancy effects which preexisting paradigms fail to counter. The IB paradigm assesses the inability of an individual to attend to a stimulus that appears suddenly while indulging in a perceptual discrimination task. The present study incorporated an IB task with three critical items (book, face, and triangle) appearing randomly in the perceptual discrimination task. Attentional biases were assessed as detection and identification of the critical item. The sample (N = 50) consisted of low test anxiety (LTA) and high test anxiety (HTA) groups based on the reactions to tests scale scores. Test threat manipulation was done with pre- and post-test assessment of test anxiety using the State Test Anxiety Inventory. A mixed factorial design with gender, test anxiety, presence or absence of test threat, and critical items was conducted to assess their effects on attentional biases. Results showed only a significant main effect for test anxiety on detection with higher accuracy of detection of the critical item for the LTA group. The study presents promising results in the realm of ABMT for test anxiety.

Keywords: attentional bias, attentional bias modification treatment, inattentional blindness, test anxiety

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Authors: Jill Steel

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Introduction: Animal-assisted learning (AAL) interventions are increasing exponentially, yet a paucity of quality research in the field exists. The aim of this study was to evaluate how the promotion of emotional wellbeing, through AAL, in this case, a dog, may support children’s engagement with reading in a Primary 1 classroom. Research indicates that dogs can provide emotional support to children; by forming a trusting attachment with a non-critical ‘friend’ who confers unconditional positive regard on the child, confidence may be boosted and anxiety reduced. By promoting emotional wellbeing through interactions with the dog, it is hoped that children begin to associate reading with feelings of wellbeing, which then results in increased engagement with reading. Methodology: A review of the literature was conducted. The relationship between emotional wellbeing and learning was explored, followed by an examination of the literature relating to Animal-Assisted Therapy and AAL. Scottish educational policy and legislation were analysed to establish the extent to which AAL might be suitable for the Scottish pedagogical context. An empirical study was conducted in a mainstream Primary 1 classroom over a four-week period. An inclusive approach was adopted whereby all children that wanted to interact with the dog were given the opportunity to do so, and all 25 children subsequently chose to participate. Children were not withdrawn from the classroom. Primary methods included interviews, observations, and questionnaires. Three focus children were selected for closer study. Main Results: Results were remarkably close to previous research and literature. Children’s emotional wellbeing was boosted, and engagement in reading improved. Principal Conclusions and Implications for Field: It was concluded that AAL could support emotional wellbeing and, in turn, promote children’s engagement with reading. The main limitation of the study was its short-term nature, and a longer randomised controlled trial with a larger sample, currently being undertaken by the author, would provide a fuller answer to the research question. Barriers to AAL include health and safety concerns and steps to ensure the welfare of the dog.

Keywords: animal-assisted learning, emotional wellbeing, reading, reading to dogs

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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Authors: Rama Shanker, Anil Kumar Sachan

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Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.

Keywords: aggregate proportions, artificial neural network, concrete grade, concrete mix design

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Authors: Xinyuan Y. Song, Kai Kang

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Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

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Authors: Rims Janeliukstis, Deniss Mironovs, Andrejs Kovalovs

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Operational Modal Analysis (OMA) is widely applied as a method for Structural Health Monitoring for structural damage identification and assessment by tracking the changes of the identified modal parameters over time. Unfortunately, modal parameters also depend on such external factors as temperature and loads. Any structural condition assessment using modal parameters should be done taking into consideration those external factors, otherwise there is a high chance of false positives. A method of structural reliability assessment based on anomaly detection technique called Machalanobis Squared Distance (MSD) is proposed. It requires a set of reference conditions to learn healthy state of a structure, which all future parameters are compared to. In this study, structural modal parameters (natural frequency and mode shape), as well as ambient temperature and loads acting on the structure are used as features. Numerical tests were performed on a finite element model of a carbon fibre reinforced polymer composite beam with delamination damage at various locations and of various severities. The advantages of the demonstrated approach include relatively few computational steps, ability to distinguish between healthy and damaged conditions and discriminate between different damage severities. It is anticipated to be promising in reliability assessment of massively produced structural parts.

Keywords: operational modal analysis, reliability assessment, anomaly detection, damage, mahalanobis squared distance

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Authors: Hannah S. Elizabeth, D. Gnanasekaran, M. R. Manju Gowda, Antony George

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Phytoremediation a new technology of remediating the contaminated soil, water and air using plants and serves as a green technology with environmental friendly approach. The main aim of this technique is cleansing and detoxifying of organic compounds, organo-phosphorous pesticides, heavy metals like arsenic, iron, cadmium, gold, radioactive elements which cause teratogenic and life threatening diseases to mankind and animal kingdom when consume the food crops, vegetables, fruits, cerals, and millets obtained from the contaminated soil. Also, directly they may damage the genetic materials thereby alters the biosynthetic pathways of secondary metabolites and other phytoconstituents which may have different pharmacological activities which lead to lost their efficacy and potency as well. It would reflect in mutagenicity, drug resistance and affect other antagonistic properties of normal metabolism. Is the technology for real clean-up of contaminated soils and the contaminants which are potentially toxic. It reduces the risks produced by a contaminated soil by decreasing contaminants using plants as a source. The advantages are cost-effectiveness and less ecosystem disruption. Plants may also help to stabilize contaminants by accumulating and precipitating toxic trace elements in the roots. Organic pollutants can potentially be chemically degraded and ultimately mineralized into harmless biological compounds. Hence, the use of plants to revitalize contaminated sites is gaining more attention and preferred for its cost-effective when compared to other chemical methods. The introduction of harmful substances into the environment has been shown to have many adverse effects on human health, agricultural productivity, and natural ecosystems. Because the costs of growing a crop are minimal compared to those of soil removal and replacement, the use of plants to remediate hazardous soils is seen as having great promise.

Keywords: cost effective, eco-friendly, phytoremediation, secondary metabolites

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