Search results for: DNA extraction methods

Authors: Haleh Hamidpour

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Since the seismic damageability of structures is controlled by the inelastic deformation capacities of structural elements, seismic design of structure based on force analogy methods is not appropriate. In recent year, the basic approach of design codes have been changed from force-based approach to displacement-based. In this regard, a Direct Displacement-Based Design (DDBD) and a Performance-Based Plastic Design (PBPD) method are proposed. In this study, the efficiency of these two methods on seismic performance of structures is evaluated through a sample 12-story reinforced concrete moment frame. The building is designed separately based on the DDBD and the PBPD methods. Once again the structure is designed by the traditional force analogy method according to the FEMA P695 regulation. Different design method results in different structural elements. Seismic performance of these three structures is evaluated through nonlinear static and nonlinear dynamic analysis. The results show that the displacement-based design methods accommodate the intended performance objectives better than the traditional force analogy method.

Keywords: direct performance-based design, ductility demands, inelastic seismic performance, yield mechanism

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Authors: Nacer Hamza

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Naturally radiation exposure that present due to the cosmic ray or the naturel occurring radioactives materials(NORMs) that originated in the earth's crust and are present everywhere in the environment(1) , a significant concentration of NORMs reported in the produced water which comes out during the oil extraction process, so that the management of this produced water is a challenge for oil and gas companies which include either minimization of produced water which considered as the best way in the term of environment based in the fact that ,the lower water produced the lower cost in treating this water , recycling and reuse by reinjected produced water that fulfills some requirements to enhance oil recovery or disposal in the case that the produced water cannot be minimize or reuse. In the purpose of produced water management, the investigation of NORMs activity concentration present in it considered as the main step for more understanding of the radionuclide’s distribution. Many studies reported the present of NORMs in produced water and investigated the correlation between 〖Ra〗^226and the different metals present in produced water(2) including Cations and anions〖Na〗^+,〖Cl〗^-, 〖Fe〗^(2+), 〖Ca〗^(2+) . and lead, nickel, zinc, cadmium, and copper commonly exist as heavy metal in oil and gas field produced water(3). However, there are no real interesting to investigate the correlation between 〖Rn〗^222and the different metals exist in produced water. methods using, in first to measure the radon concentration activity in produced water samples is a RAD7 .RAD7 is a radiometer instrument based on the solid state detectors(4) which is a type of semi-conductor detector for alpha particles emitting from Rn and their progenies, in second the concentration of different metals presents in produced water measure using an atomic absorption spectrometry AAS. Then to investigate the correlation between the 〖Rn〗^222concentration activity and the metals concentration in produced water a statistical method is Pearson correlation analysis which based in the correlation coefficient obtained between the 〖Rn〗^222 and metals. Such investigation is important to more understanding how the radionuclides act in produced water based on this correlation with metals , in first due to the fact that 〖Rn〗^222decays through the sequence 〖Po〗^218, 〖Pb〗^214, 〖Bi〗^214, 〖Po〗^214, and〖Pb〗^210, those daughters are metals thus they will precipitate with metals present in produced water, secondly the short half-life of 〖Rn〗^222 (3.82 days) lead to faster precipitation of its progenies with metals in produced water.

Keywords: norms, radon concentration, produced water, heavy metals

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Authors: P. van Tonder, U. Bagdadi, B. M. D. Lario, Z. Masina, T. R. Motshwari

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This paper analyses how concrete reinforcing steel bars corrode and how it can be minimised through the use of various protection methods against corrosion, such as metal-based paint, alloying, cathodic protection and electroplating. Samples of carbon steel bars were protected, using these four methods. Tests performed on the samples included durability, electrical resistivity and bond strength. Durability results indicated relatively low corrosion rates for alloying, cathodic protection, electroplating and metal-based paint. The resistivity results indicate all samples experienced a downward trend, despite erratic fluctuations in the data, indicating an inverse relationship between electrical resistivity and corrosion rate. The results indicated lowered bond strengths when the reinforced concrete was cured in seawater compared to being cured in normal water. It also showed that higher design compressive strengths lead to higher bond strengths which can be used to compensate for the loss of bond strength due to corrosion in a real-world application. In terms of implications, all protection methods have the potential to be effective at resisting corrosion in real-world applications, especially the alloying, cathodic protection and electroplating methods. The metal-based paint underperformed by comparison, most likely due to the nature of paint in general which can fade and chip away, revealing the steel samples and exposing them to corrosion. For alloying, stainless steel is the suggested material of choice, where Y-bars are highly recommended as smooth bars have a much-lowered bond strength. Cathodic protection performed the best of all in protecting the sample from corrosion, however, its real-world application would require significant evaluation into the feasibility of such a method.

Keywords: protection methods, corrosion, concrete, reinforcing steel bars

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Authors: Erhan Eroğlu

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This paper presents a new method called Mentor and Mentee Based Learning. This new method is becoming more and more common especially at workplaces. This study is significant as it clearly underlines how it works well. Education has always aimed at equipping people with the necessary knowledge and information. For many decades it went on teachers’ talk and chalk methods. In the second half of the nineteenth century educators felt the need for some changes in delivery systems. Some new terms like self- discovery, learner engagement, student centered learning, hands on learning have become more and more popular for such a long time. However, some educators believe that there is much room for better learning methods in many fields as they think the learners still cannot fulfill their potential capacities. Thus, new systems and methods are still being developed and applied at education centers and work places. One of the latest methods is assigning some mentors for the newly recruited employees and training them within a mentor and mentee program which allows both parties to see their strengths and weaknesses and the areas which can be improved. This paper aims at finding out the perceptions of the mentors and mentees on the programs they are offered at their workplaces and suggests some betterment alternatives. The study has been conducted via a qualitative method whereby some interviews have been done with both mentors and mentees separately and together. Results show that it is a great way to train inexperienced one and also to refresh the older ones. Some points to be improved have also been underlined. The paper shows that education is not a one way path to follow.

Keywords: learning, mentor, mentee, training

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Tahra ElObeid, Omnya Ahmed, Reem Al-Sharshani, Doaa Dalloul, Jannat Alnattei

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Background: Camelus dormedarius camels are also called ‘the Arabian camels’ and are present in the desert area of North Africa and the Middle East. Recently, camel’s milk has a great attention globally because of their proteins and peptides that have been reported to be beneficial for the health and in the management of many diseases. Objectives: This study was designed to investigate the antioxidant, antimicrobial activity and to evaluate the total phenolic content of camel’s milk proteins in Qatar. Methods: Fresh two camel’s milk samples from Omani breed and called Muhajer (camel’s milk A and B) were collected on the 1st of the December. Both samples were from the same location Al- Shahaniyah, Doha, Qatar, but from different local private farms and feeding system. Camel’s milk A and B were defatted by centrifugation and their proteins were extracted by acid and thermal precipitation. The antioxidant activity was determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. Total phenolic compound (TPC) was evaluated by Folin-Ciocalteu reagent (FCR). On the other hand, the antimicrobial activity against eight different type of pathogenic bacteria was evaluated by disc diffusion method and the zone of inhibition was measured. Results: The of the total phenolic content of whole milk in both camel’s milk A and B were significantly the highest among the protein extracts. The % of the DPPH radical inhibition of casein protein in both camel’s milk A and B were significantly the highest among the protein extracts. In this study, there were marked changes in the antibacterial activity in the different camel milk protein extracts. All extracts showed bacterial overgrowth. Conclusion: The antioxidant activity of the camel milk protein extracts correlated to their unique phenolic compounds and bioactive protein peptides. The antimicrobial activity was not detected perhaps due to the technique, the quality, or the extraction method. Overall, camel's milk exhibits a high antioxidant activity, which is responsible for many health benefits besides the nutritional values.

Keywords: camels milk, antioxidant content, antimicrobial activity, proteins, Qatar

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Authors: Xue Wang, Li-Wei Fan

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The technology innovation has become the driving force of social and economic development and transformation. The guidance and support of public policies is an important condition to promote the realization of technology innovation goals. Policy effectiveness evaluation is instructive in policy learning and adjustment. This paper reviews existing studies and systematically evaluates the effectiveness of policy-driven technological innovation. We used 167 articles from WOS and CNKI databases as samples to clarify the measurement of technological innovation indicators and analyze the classification and application of policy evaluation methods. In general, technology innovation input and technological output are the two main aspects of technological innovation index design, among which technological patents are the focus of research, the number of patents reflects the scale of technological innovation, and the quality of patents reflects the value of innovation from multiple aspects. As for policy evaluation methods, statistical analysis methods are applied to the formulation, selection and evaluation of the after-effect of policies to analyze the effect of policy implementation qualitatively and quantitatively. The bibliometric methods are mainly based on the public policy texts, discriminating the inter-government relationship and the multi-dimensional value of the policy. Decision analysis focuses on the establishment and measurement of the comprehensive evaluation index system of public policy. The economic analysis methods focus on the performance and output of technological innovation to test the policy effect. Finally, this paper puts forward the prospect of the future research direction.

Keywords: technology innovation, index, policy effectiveness, evaluation of policy, bibliometric analysis

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Authors: Kizito Ugochukwu Nwajeri

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This paper presents a distinct approach to solving fractional dynamical systems using hybrid block methods (HBMs). Fractional calculus extends the concept of derivatives and integrals to non-integer orders and finds increasing application in fields such as physics, engineering, and finance. However, traditional numerical techniques often struggle to accurately capture the complex behaviors exhibited by these systems. To address this challenge, we develop HBMs that integrate single-step and multi-step methods, enabling the simultaneous computation of multiple solution points while maintaining high accuracy. Our approach employs polynomial interpolation and collocation techniques to derive a system of equations that effectively models the dynamics of fractional systems. We also directly incorporate boundary and initial conditions into the formulation, enhancing the stability and convergence properties of the numerical solution. An adaptive step-size mechanism is introduced to optimize performance based on the local behavior of the solution. Extensive numerical simulations are conducted to evaluate the proposed methods, demonstrating significant improvements in accuracy and efficiency compared to traditional numerical approaches. The results indicate that our hybrid block methods are robust and versatile, making them suitable for a wide range of applications involving fractional dynamical systems. This work contributes to the existing literature by providing an effective numerical framework for analyzing complex behaviors in fractional systems, thereby opening new avenues for research and practical implementation across various disciplines.

Keywords: fractional calculus, numerical simulation, stability and convergence, Adaptive step-size mechanism, collocation methods

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Authors: Deisy Becerra, Nicolas Rios, Miguel Asuaje

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The Electrical Submersible Pump (ESP) is one of the most artificial lifting methods used in the last years, which consists of a serial arrangement of centrifugal pumps. One of the main concerns when handling crude oil is the formation of O/W or W/O (oil/water or water/oil) emulsions inside the pump, due to the shear rate imparted and the presence of high molecular weight substances that act as natural surfactants. Therefore, it is important to perform an analysis of the flow patterns inside the pump to increase the percentage of oil recovered using the centrifugal force and the difference in density between the oil and the water to generate the separation of liquid phases. For this study, a Computational Fluid Dynamic (CFD) model was developed on STAR-CCM+ software based on 3D geometry of a Franklin Electric 4400 4' four-stage ESP. In this case, the modification of the last stage was carried out to improve the centrifugal effect inside the pump, and a perforated double tube was designed with three different holes configurations disposed at the outlet section, through which the cut water flows. The arrangement of holes used has different geometrical configurations such as circles, rectangles, and irregular shapes determined as grating around the tube. The two-phase flow was modeled using an Eulerian approach with the Volume of Fluid (VOF) method, which predicts the distribution and movement of larger interfaces in immiscible phases. Different water-oil compositions were evaluated, such as 70-30% v/v, 80-20% v/v and 90-10% v/v, respectively. Finally, greater recovery of oil was obtained. For the several compositions evaluated, the volumetric oil fraction was greater than 0.55 at the pump outlet. Similarly, it is possible to show an inversely proportional relationship between the Water/Oil rate (WOR) and the volumetric flow. The volumetric fractions evaluated, the oil flow increased approximately between 41%-10% for circular perforations and 49%-19% for rectangular shaped perforations, regarding the inlet flow. Besides, the elimination of the pump diffuser in the last stage of the pump reduced the head by approximately 20%.

Keywords: computational fluid dynamic, CFD, electrical submersible pump, ESP, two phase flow, volume of fluid, VOF, water/oil rate, WOR

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Authors: Shri Krishna Mishra

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In an educational context, technology can prompt interactive plight only when it is used in conjunction with interactive plight methods. This study, therefore, examines the relationships among components that contribute to higher levels of interactive plight and execution, such as interactive Plight methods, technology, intrinsic motivation and deep learning. 526 students participated in this study. With structural equation modelling, the authors test the conceptual model and identify satisfactory model fit. The results indicate that interactive Plight methods, technology and intrinsic motivation have significant relationship with interactive Plight; deep learning mediates the relationships of the other variables with Execution.

Keywords: searching the relationship among components, contribute to interactive plight, educational execution, intrinsic motivation

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Authors: Ramandeep Kaur, Gurjit Singh Bhathal

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Cancer diagnosis is very difficult task. Magnetic resonance imaging (MRI) scan is used to produce image of any part of the body and provides an efficient way for diagnosis of cancer or tumor. In existing method, fuzzy clustering mean (FCM) is used for the diagnosis of the tumor. In the proposed method FCM is used to diagnose the cancer of the foot. FCM finds the centroids of the clusters of the foot cancer obtained from MRI images. FCM thresholding result shows the extract region of the cancer. Morphological operations are applied to get extracted region of cancer.

Keywords: magnetic resonance imaging (MRI), fuzzy C mean clustering, segmentation, morphological operations

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Authors: David Taillis, Oussama Becissa, Julien Gabaston, Jean-Michel Merillon, Tristan Richard, Stephanie Cluzet

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Nowadays, there is a strong pressure to reduce the phytosanitary inputs of synthetic chemistry in vineyards. It is, therefore, necessary to find viable alternatives in order to protect the vine against its major diseases. For this purpose, we suggest the use of a plant extract enriched in antimicrobial compounds. Being produced from vine trunks and roots, which are co-products of wine production, the extract produced is part of a circular economy. The antimicrobial molecules present in this plant material are polyphenols and, more particularly, stilbenes, which are derived from a common base, the resveratrol unit, and that are well known vine phytoalexins. The stilbenoids were extracted from trunks and roots (30/70, w/w) by a double extraction with ethyl acetate followed by enrichment by liquid-liquid extraction. The produced extract was characterized by UHPLC-MS, then its antimicrobial activities were tested on Plasmopara viticola and Botrytis cinerea in the laboratory and/or in greenhouse and in vineyard. The major compounds were purified, and their antimicrobial activity was evaluated on B. cinerea. Moreover, after its spraying, the effect of the stilbene extract on the plant defence status was evaluated by analysis of defence gene expression. UHPLC-MS analysis revealed that the extract contains 50% stilbenes with resveratrol, ε-viniferin and r-viniferin as major compounds. The extract showed antimicrobial activities on P. viticola with IC₅₀ and IC₁₀₀ respectively of 90 and 300 mg/L in the laboratory. In addition, it inhibited 40% of downy mildew development in greenhouse. However, probably because of the sensitivity of stilbenes to the environment, such as UV degradation, no activity has been observed in vineyard towards P. viticola development. For B. cinerea, the extract IC50 was 123 mg/L, with resveratrol and ε-viniferin being the most active stilbenes (IC₅₀ of 88 and 142 mg/L, respectively). The analysis of the expression of defence genes revealed that the extract can induce the expression of some defence genes 24, 48, and 72 hours after treatment, meaning that the extract has a defence-stimulating effect at least for the first three days after treatment. In conclusion, we produced a plant extract enriched in stilbenes with antimicrobial properties against two major grapevine pathogenic agents P. viticola and B. cinerea. In addition, we showed that this extract displayed eliciting activity of plant defences. This extract can therefore represent, after formulation development, a viable eco-friendly alternative for vineyard protection. Subsequently, the effect of the stilbenoid extract on primary metabolism will be evaluated by quantitative NMR.

Keywords: antimicrobial, bioprotection, grapevine, Plasmopara viticola, stilbene

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Authors: Miklos Taliga

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In the present case study we examined the development and testing methods of systems that contain safety-critical elements in different industrial fields. Consequentially, we observed the classical object-oriented development and testing environment, as both medical technology and automobile industry approaches the development of safety critical elements that way. Subsequently, we examined model-based development. We introduce the quality parameters that define development and testing. While taking modern agile methodology (scrum) into consideration, we examined whether and to what extent the methodologies we found fit into this environment.

Keywords: safety-critical elements, quality managent, unit verification, model base testing, agile methods, scrum, metamodel, object-oriented programming, field specific modelling, sprint, user story, UML Standard

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Authors: Rabia Waseem, Low Kah Hin, Najihah Mohamed Hashim

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The variability in the chemical components of the Syzygium species essential oils has been evaluated. The leaves of Syzygium species have been collected from Perak, Malaysia. The essential oils extracted by using the conventional Hydro-distillation extraction procedure and analyzed by using Gas chromatography System attached with Mass Spectrometry (GCMS). Twenty-seven constituents were found in Syzygium species in which the major constituents include: α-Pinene (3.94%), α-Thujene (2.16%), α-Terpineol (2.95%), g-Elemene (2.89%) and D-Limonene (14.59%). The aim of this study was the comparison between the evaluated data and existing literature to fortify the major variability through statistical analysis.

Keywords: chemotaxonomy, cluster analysis, essential oil, medicinal plants, statistical analysis

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Authors: Sriraman Kothuri, Komal Teja Mattupalli

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In this paper we proposed a novel algorithm for recognizing hulls in a hand written digits. This is an extension to the work on “Digit Recognition Using Freeman Chain code”. In order to find out the hulls in a user given digit it is necessary to follow three steps. Those are pre-processing, Boundary Extraction and at last apply the Hull Detection system in a way to attain the better results. The detection of Hull Regions is mainly intended to increase the machine learning capability in detection of characters or digits. This can also extend this in order to get the hull regions and their intensities in Black Holes in Space Exploration.

Keywords: chain code, machine learning, hull regions, hull recognition system, SASK algorithm

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Authors: Ravneil Nand

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Cooperative coevolution uses problem decomposition methods to solve a larger problem. The problem decomposition deals with breaking down the larger problem into a number of smaller sub-problems depending on their method. Different problem decomposition methods have their own strengths and limitations depending on the neural network used and application problem. In this paper we are introducing a new problem decomposition method known as Hidden-Neuron Level Decomposition (HNL). The HNL method is competing with established problem decomposition method in time series prediction. The results show that the proposed approach has improved the results in some benchmark data sets when compared to the standalone method and has competitive results when compared to methods from literature.

Keywords: cooperative coevaluation, feed forward network, problem decomposition, neuron, synapse

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Authors: Clairecynth Yu, Geminne Manzano

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The mariculture potential of the Philippine blue sponge, Xestospongia sp. was assessed through the pilot sponge culture in the open-sea at two different biogeographic regions in the Philippines. Thirty explants were randomly allocated for the Puerto Galera, Oriental Mindoro culture setup and the other nine were transported to Lucero, Bolinao, Pangasinan. Two different sponge culture methods of the sponge explants- the lantern and the wall method, were employed to assess the production of the Renieramycin M. Both methods have shown to be effective in growing the sponge explants and that the Thin Layer Chromatography (TLC) results have shown that Renieramycin M is present on the sponges. The effect of partial harvesting in the growth and survival rates of the blue sponge in the Puerto Galera setup was also determined. Results showed that a higher growth rate was observed on the partially harvested explants on both culture methods as compared to the unharvested explants.

Keywords: chemical ecology, porifera, sponge, Xestospongia sp.

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Authors: Nikita Valluri, Vatcharaporn Esichaikul

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With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.

Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data

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Authors: Van Truong Pham

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Background: Self-management was described as a potential strategy for blood pressure control in patients with hypertension. However, the effects of self-management interventions on blood pressure, self-efficacy, medication adherence, and body mass index (BMI) in older adults with hypertension have not been systematically evaluated. We evaluated the effects of self-management interventions on systolic blood pressure (SBP) and diastolic blood pressure (DBP), self-efficacy, medication adherence, and BMI in hypertensive older adults. Methods: We followed the recommended guidelines of preferred reporting items for systematic reviews and meta-analyses. Searches in electronic databases including CINAHL, Cochrane Library, Embase, Ovid-Medline, PubMed, Scopus, Web of Science, and other sources were performed to include all relevant studies up to April 2019. Studies selection, data extraction, and quality assessment were performed by two reviewers independently. We summarized intervention effects as Hedges' g values and 95% confidence intervals (CI) using a random-effects model. Data were analyzed using Comprehensive Meta-Analysis software 2.0. Results: Twelve randomized controlled trials met our inclusion criteria. The results revealed that self-management interventions significantly improved blood pressure control, self-efficacy, medication adherence, whereas the effect of self-management on BMI was not significant in older adult patients with hypertension. The following Hedges' g (effect size) values were obtained: SBP, -0.34 (95% CI, -0.51 to -0.17, p < 0.001); DBP, -0.18 (95% CI, -0.30 to -0.05, p < 0.001); self-efficacy, 0.93 (95%CI, 0.50 to 1.36, p < 0.001); medication adherence, 1.72 (95%CI, 0.44 to 3.00, p=0.008); and BMI, -0.57 (95%CI, -1.62 to 0.48, p = 0.286). Conclusions: Self-management interventions significantly improved blood pressure control, self-efficacy, and medication adherence. However, the effects of self-management on obesity control were not supported by the evidence. Healthcare providers should implement self-management interventions to strengthen patients' role in managing their health care.

Keywords: self-management, meta-analysis, blood pressure control, self-efficacy, medication adherence, body mass index

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Authors: Iyabode A. Kehinde, Temitope A. Oyedele, Clement G. Afolabi

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One of the limitations of African yam bean (AYB) (Sphenostylis sternocarpa) is poor storage ability due to the adverse effect of seed-borne fungi. This study was conducted to examine the effects of storage methods on the nutritive composition of AYB seeds stored in three types of storage materials viz; Jute bags, Polypropylene bags, and Plastic Bowls. Freshly harvested seeds of AYB seeds were stored in all the storage materials for 6 months using 2 × 3 factorial (2 AYB cultivars and 3 storage methods) in 3 replicates. The proximate analysis of the stored AYB seeds was carried out at 3 and 6 months after storage using standard methods. The temperature and relative humidity of the storeroom was recorded monthly with Kestrel pocket weather tracker 4000. Seeds stored in jute bags gave the best values for crude protein (24.87%), ash (5.69%) and fat content (6.64%) but recorded least values for crude fibre (2.55%), carbohydrate (50.86%) and moisture content (12.68%) at the 6th month of storage. The temperature of the storeroom decreased from 32.9ºC - 28.3ºC, while the relative humidity increased from 78% - 86%. Decreased incidence of field fungi namely: Rhizopus oryzae, Aspergillus flavus, Geotricum candidum, Aspergillus fumigatus and Mucor meihei was accompanied by the increase in storage fungi viz: Apergillus niger, Mucor hiemalis, Penicillium espansum and Penicillium atrovenetum with prolonged storage. The study showed that of the three storage materials jute bag was more effective at preserving AYB seeds.

Keywords: storage methods, proximate composition, African Yam Bean, fungi

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Authors: Ahmed Abdullah Ahmed

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The task of recognizing the writer of a handwritten text has been an attractive research problem in the document analysis and recognition community with applications in handwriting forensics, paleography, document examination and handwriting recognition. This research presents an automatic method for writer recognition from digitized images of unconstrained writings. Although a great effort has been made by previous studies to come out with various methods, their performances, especially in terms of accuracy, are fallen short, and room for improvements is still wide open. The proposed technique employs optimal codebook based writer characterization where each writing sample is represented by a set of features computed from two codebooks, beginning and ending. Unlike most of the classical codebook based approaches which segment the writing into graphemes, this study is based on fragmenting a particular area of writing which are beginning and ending strokes. The proposed method starting with contour detection to extract significant information from the handwriting and the curve fragmentation is then employed to categorize the handwriting into Beginning and Ending zones into small fragments. The similar fragments of beginning strokes are grouped together to create Beginning cluster, and similarly, the ending strokes are grouped to create the ending cluster. These two clusters lead to the development of two codebooks (beginning and ending) by choosing the center of every similar fragments group. Writings under study are then represented by computing the probability of occurrence of codebook patterns. The probability distribution is used to characterize each writer. Two writings are then compared by computing distances between their respective probability distribution. The evaluations carried out on ICFHR standard dataset of 206 writers using Beginning and Ending codebooks separately. Finally, the Ending codebook achieved the highest identification rate of 98.23%, which is the best result so far on ICFHR dataset.

Keywords: off-line text-independent writer identification, feature extraction, codebook, fragments

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Authors: Scott Nielsen, Luca Longanesi, Chris Chuck

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Palm oil is obtained from the flesh and kernel of the fruit of oil palms and is the most productive and inexpensive oil crop. The global demand for palm oil is approximately 75 million metric tonnes, a 29% increase in global production of palm oil since 2016. This expansion of oil palm cultivation has resulted in mass deforestation, vast biodiversity destruction and increasing net greenhouse gas emissions. One possible alternative is to produce a saturated oil, similar to palm, from microbes such as oleaginous yeast. The yeasts can be cultured on sugars derived from second-generation sources and do not compete with tropical forests for land. One highly promising oleaginous yeast for this application is Metschnikowia pulcherrima. However, recent techno-economic modeling has shown that cell lysis and standard lipid extraction are major contributors to the cost of the oil. Typical cell disruption techniques to extract either single cell oils or proteins have been based around bead-beating, homogenization and acid lysis. However, these can have a detrimental effect on lipid quality and are energy-intensive. In this study, a vortex separator, which produces high sheer with minimal energy input, was investigated as a potential low energy method of lysing cells. This was compared to four more traditional methods (thermal lysis, acid lysis, alkaline lysis, and osmotic lysis). For each method, the yeast loading was also examined at 1 g/L, 10 g/L and 100 g/L. The quality of the cell disruption was measured by optical cell density, cell counting and the particle size distribution profile comparison over a 2-hour period. This study demonstrates that the vortex separator is highly effective at lysing the cells and could potentially be used as a simple apparatus for lipid recovery in an oleaginous yeast process. The further development of this technology could potentially reduce the overall cost of microbial lipids in the future.

Keywords: palm oil substitute, metschnikowia pulcherrima, cell disruption, cell lysis

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Authors: Hyun-Woo Cho

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For ensuring the safety of a manufacturing process one should quickly identify an assignable cause of a fault in an on-line basis. To this end, many statistical techniques including linear and nonlinear methods have been frequently utilized. However, such methods possessed a major problem of small sample size, which is mostly attributed to the characteristics of empirical models used for reference models. This work presents a new method to overcome the insufficiency of measurement data in the monitoring and diagnosis tasks. Some quasi-measurement data are generated from existing data based on the two indices of similarity and importance. The performance of the method is demonstrated using a real data set. The results turn out that the presented methods are able to handle the insufficiency problem successfully. In addition, it is shown to be quite efficient in terms of computational speed and memory usage, and thus on-line implementation of the method is straightforward for monitoring and diagnosis purposes.

Keywords: data analysis, diagnosis, monitoring, process data, quality control

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Authors: Janet C. Read

Abstract:

UClan set collaboration with Lingokids to assess the Lingokids learning app's impact on learning outcomes in classrooms in the UK for children with ages ranging from 3 to 5 years. Data gathered during the controlled study with 69 children includes attitudinal data, engagement, and learning scores. Data shows that children enjoyment while learning was higher among those children using the game-based app compared to those children using other traditional methods. It’s worth pointing out that engagement when using the learning app was significantly higher than other traditional methods among older children. According to existing literature, there is a direct correlation between engagement, motivation, and learning. Therefore, this study provides relevant data points to conclude that Lingokids learning app serves its purpose of encouraging learning through playful and interactive content. That being said, we believe that learning outcomes should be assessed with a wider range of methods in further studies. Likewise, it would be beneficial to assess the level of usability and playability of the app in order to evaluate the learning app from other angles.

Keywords: learning app, learning outcomes, rapid test activity, Smileyometer, early childhood education, innovative pedagogy

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Authors: Magdy Danial Riad

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Introduction: The ability of our world to support the expanding population after 2050 is at risk due to the food system's global role in poor health, climate change, and resource depletion. Healthy, equitable, and sustainable food systems must be achieved from the point of production through consumption in order to meet several of the sustainable development goals (SDG) targets. There is evidence that changing the local food environment can effectively change dietary habits in a community. The purpose of this article is to outline the policy initiatives taken by local governments to support environmentally friendly eating habits. Methods: Five databases were searched for peer-reviewed articles that described local government authorities' implementation of environmentally sustainable eating habits, were located in cities that had signed the Milan Urban Food Policy Pact, were published after 2015, were available in English, and described policy interventions. Data extraction was a two-step approach that started with extracting information from the included study and ended with locating information unique to policies in the grey literature. Results: 45 papers that described a variety of policy initiatives from low-, middle-, and high-income countries met the inclusion criteria. A variety of desired dietary behaviors were the focus of policy action, including reducing food waste, procuring food locally and in season, boosting breastfeeding, avoiding overconsumption, and consuming more plant-based meals and fewer items derived from animals. Conclusions: In order to achieve SDG targets, local governments are under pressure to implement evidence-based interventions. This study can help direct local governments toward evidence-based policy measures to improve regional food systems and support ecologically friendly eating habits.

Keywords: meals, planet, poor health, eating habits

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Authors: William Brasier, Nicolas Rabin, Celeste Joly

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Japanese knotweed (Fallopia japonica) is very present on the banks of the Rhone, colonizing more and more areas along the river. The Compagnie Nationale du Rhone (C.N.R.), which manages the river, has experimented with several control techniques in recent years. Since 2015, 15 experimental plots have been monitored on the banks of a restored river appendix to measure the effect of three control methods: confinement by felt, repeated mowing and the planting of competing species and/or species with allelopathic power: Viburnum opulus, Rhamnus frangula, Sambucus ebulus and Juglans regia. Each year, the number of stems, the number of elderberry plants, the height of the plants and photographs were collected. After six years of monitoring, the results showed that the density of knotweed stems decreased by 50 to 90% on all plots. The control methods are sustainable and are gradually gaining in efficiency. The establishment of native plants coupled with regular manual maintenance can reduce the development of Japanese knotweed. Continued monitoring over the next few years will determine the kinetics of the total eradication (i.e. 0 stem/plot) of the Japanese knotweed by these methods.

Keywords: fallopia japonica, interspecific plant competition , Rhone river, riparian trees

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Authors: H. Imad, Y. Cheah, O. Aamera

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The aims of this research are to study the mitochondrial non-coding region by using the Sanger sequencing technique and establish the degree of variation characteristics of a fragment. FTA® Technology (FTA™ paper DNA extraction) utilized to extract DNA. A portion of a non-coding region encompassing positions 37 to 340 amplified in accordance with the Anderson reference sequence. PCR products purified by EZ-10 spin column then sequenced and detected by using the ABI 3730xL DNA Analyzer. New polymorphic positions 57, 63, and 101 are described may in future be suitable sources for identification purpose. The data obtained can be used to identify variable nucleotide positions characterized by frequent occurrence most promising for identification variants.

Keywords: encompassing nucleotide positions 37 to 340, HVII, Iraq, mitochondrial DNA, polymorphism, frequency

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Authors: Mehmood Ali, Attaullah Khan, Md. Abul Kalam

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Petroleum crude oil reserves are going to deplete in future due to the consumption of fossil fuels in transportation and energy generating sector. Thus, increasing the fossil fuel prices and also causing environmental degradation issues such as climate change and global warming due to air pollution. Therefore, to tackle these issues the environmentally friendly fuels are the potential substitute with lower emissions of toxic gases. A non-edible vegetable oilseed crop, Jatropha curcas, from different origins such as Malaysia, Thailand and India were cultivated in Pakistan. The harvested seeds physical, chemical and mechanical properties were measured, having an influence on the post-harvesting machines design parameters for dehulling, storing bins, drying, oil extraction from seeds with a screw expeller and in-situ transesterification reaction to produce biodiesel fuel. The seed variety from Thailand was found better in comparison of its properties with other varieties from Malaysia and India. The seed yield from these three varieties i.e. Malaysia, Thailand and India were 829, 943 and 735 kg/ acre/ year respectively. While the oil extraction yield from Thailand variety seed was found higher (i.e. 32.61 % by wt.) as compared to other two varieties from Malaysia and India were 27.96 and 24.96 % by wt respectively. The physical properties investigated showed the geometric mean diameter of seeds from three varieties Malaysia, Thailand and India were 11.350, 10.505 and 11.324 mm, while the sphericity of seeds were found 0.656, 0.664 and 0.655. The bulk densities of the powdered seeds from three varieties Malaysia, Thailand and India, were found as 0.9697, 0.9932 and 0.9601 g/cm³ and % passing was obtained with sieve test were 78.7, 87.1 and 79.3 respectively. The densities of the extracted oil from three varieties Malaysia, Thailand and India were found 0.902, 0.898 and 0.902 g/ mL with corresponding kinematic viscosities 54.50, 49.18 and 48.16 mm2/sec respectively. The higher heating values (HHV) of extracted oil from Malaysia, Thailand and India seed varieties were measured as 40.29, 36.41 and 34.27 MJ/ kg, while the HHV of de-oiled cake from these varieties were 21.23, 20.78 and 17.31 MJ/kg respectively. The de-oiled cake can be used as compost with nutrients and carbon content to enhance soil fertility to grow future Jatropha curcas oil seed crops and also can be used as a fuel for heating and cooking purpose. Moreover, the mechanical parameter micro Vickers hardness of Malaysia seed was found lowest 16.30 HV measured with seed in a horizontal position to the loading in comparison to other two varieties as 25.2 and 18.7 HV from Thailand and India respectively. The fatty acid composition of three varieties of seed oil showed the presence of C8-C22, required to produce good quality biodiesel fuel. In terms of physicochemical properties of seeds and its extracted oil, the variety from Thailand was found better as compared to the other two varieties.

Keywords: biodiesel, Jatropha curcas, mechanical property, physico-chemical properties

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Authors: Kunal Shah, Swati Patel

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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

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Authors: V. D. Povolockiy, V. E. Roshchin, Y. Kapelyushin

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Smelting of copper matte is followed by production of a large amount of slag. This slag mostly contains silicates and can be utilized in a construction industry. In addition to silicates it also contains Fe; if the Fe content is high, the density of the silicate phases increases and such a slag cannot be used as an additive for the concrete. Furthermore, slags obtained during copper matte production contain copper, sulphur, zinc and some other elements. Fe is the element with the highest price in these slags. An extraction of Fe is possible even using the conventional methods, e.g., the addition of slag to the charge materials during production of sinter for the blast furnace smelting. However, in this case, the blast furnace hot metal would accumulate sulphur and copper which is very harmful impurity for the steelmaking. An accumulation of copper by the blast furnace hot metal is unacceptable, as copper cannot be removed during further steelmaking operations having a critical effect on the properties of steel. In present work, the technological scheme for non-waste utilization of the copper smelting slags has been suggested and experimentally confirmed. This scheme includes a solid state reduction of Fe and smelting for the separation of cast iron and slag. During solid state reduction, the zinc vapor was trapped. After the reduction and smelting operations, the cast iron containing copper was used for the production of metal balls with increased mechanical properties allowing their utilization for milling of ore minerals. Such a cast iron could also be applied in the production of special types of steel with copper. The silicate slag freed from Fe might be used as a propping agent in the oil industry, or granulated for application as an additive for concrete in a construction industry. Thereby, the suggested products for a Mini Mill plant with non-waste utilization of the copper smelting slags are cast iron grinding balls for the ore minerals, special types of steel with copper, silicate slag utilized as an additive for the concrete and propping agents for the oil industry.

Keywords: utilization of copper slag, cast iron, grinding balls, propping agents

Procedia PDF Downloads 157