Search results for: food composition data

Authors: Ali Aydin, Mert Sudagidan, Aysen Coban, Alparslan Kadir Devrim

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Pseudomonas spp. (specifically, P. fluorescens and P. fragi) are considered the principal spoilage microorganisms of refrigerated poultry meats. The higher the level psychrophilic spoilage Pseudomonas spp. on carcasses at the end of processing lead to decrease the shelf life of the refrigerated product. The aim of the study was the identification of psychrophilic Pseudomonas spp. having proteolytic and lipolytic activities from poultry meats by 16S rRNA and rpoB gene sequencing, investigation of protease and lipase related genes and determination of proteolytic activity of Pseudomonas spp. In the of isolation procedure, collected chicken meat samples from local markets and slaughterhouses were homogenized and the lysates were incubated on Standard method agar and Skim Milk agar for selection of proteolytic bacteria and tributyrin agar for selection of lipolytic bacteria at +4 °C for 7 days. After detection of proteolytic and lipolytic colonies, the isolates were firstly analyzed by biochemical tests such as Gram staining, catalase and oxidase tests. DNA gene sequencing analysis and comparison with GenBank revealed that 126 strong enzyme Pseudomonas spp. were identified as predominantly P. fluorescens (n=55), P. fragi (n=42), Pseudomonas spp. (n=24), P. cedrina (n=2), P. poae (n=1), P. koreensis (n=1), and P. gessardi (n=1). Additionally, protease related aprX gene was screened in the strains and it was detected in 69/126 strains, whereas, lipase related lipA gene was found in 9 Pseudomonas strains. Protease activity was determined using commercially available protease assay kit and 5 strains showed high protease activity. The results showed that psychrophilic Pseudomonas strains were present in chicken meat samples and they can produce important levels of proteases and lipases for food spoilage to decrease food quality and safety.

Keywords: Pseudomonas, chicken meat, protease, lipase

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Authors: S. Adjiri-Bailiche, S. M. Boudia, H. Daaou, S. Hadouche, A. Benzaoui

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In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate.

Keywords: MATLAB, neural network, power low, vertical extrapolation, wind energy, wind speed

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Authors: F. Fernandes, C. Poleto

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This paper aims at assessing the concentrations of heavy metals and the isotopic composition of lead ²¹⁰Pb in different fractions of sediment produced in the watershed that makes up the Mãe d'água dam and thus characterizing the distribution of metals along the sedimentary column and inferencing in the urbanization of the same process. Sample collection was carried out in June 2014; eight sediment cores were sampled in the lake of the dam. For extraction of the sediments core, a core sampler “Piston Core” was used. The trace metal concentrations were determined by conventional atomic absorption spectrophotometric methods. The samples were subjected to radiochemical analysis of ²¹⁰Po. ²¹⁰Pb activity was obtained by measuring ²¹⁰Po activity. The chronology was calculated using the constant rate of supply (CRS). ²¹⁰Pb is used to estimate the sedimentation rate.

Keywords: ²¹⁰Pb dating method, heavy metal, lakes urban, pollution history

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Authors: Ahmad Badawi Saluy, Novawiguna Kemalasari

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This study aims to examine, analyze and explain the impacts of compensation, career development and employee engagement to employee’s performance partially and simultaneously (Case Study at PT Bank XYZ). The research design used is quantitative descriptive research causality involving 30 respondents. Sources of data are from primary and secondary data, primary data obtained from questionnaires distribution and secondary data obtained from journals and books. Data analysis used model test using smart application PLS 3 that consists of test outer model and inner model. The results showed that compensation, career development and employee engagement partially have a positive impact on employee performance, while they have a positive and significant impact on employee performance simultaneously. The independent variable has the greatest impact is the employee engagement.

Keywords: compensation, career development, employee engagement, employee performance

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Authors: A. N. Kurbanova, G. K. Sugurbekova, N. K. Akhmetov

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The asphaltenes are heavy fraction of crude oil. Asphaltenes on oilfield is known for its ability to plug wells, surface equipment and pores of the geologic formations. The present research is devoted to the deasphalting of crude oil as the initial stage refining oil. Solvent deasphalting was conducted by extraction with organic solvents (cyclohexane, carbon tetrachloride, chloroform). Analysis of availability of metals was conducted by ICP-MS and spectral feature at deasphalting was achieved by FTIR. High contents of asphaltenes in crude oil reduce the efficiency of refining processes. Moreover, high distribution heteroatoms (e.g., S, N) were also suggested in asphaltenes cause some problems: environmental pollution, corrosion and poisoning of the catalyst. The main objective of this work is to study the effect of deasphalting process crude oil to improve its properties and improving the efficiency of recycling processes. Experiments of solvent extraction are using organic solvents held in the crude oil JSC “Pavlodar Oil Chemistry Refinery. Experimental results show that deasphalting process also leads to decrease Ni, V in the composition of the oil. One solution to the problem of cleaning oils from metals, hydrogen sulfide and mercaptan is absorption with chemical reagents directly in oil residue and production due to the fact that asphalt and resinous substance degrade operational properties of oils and reduce the effectiveness of selective refining of oils. Deasphalting of crude oil is necessary to separate the light fraction from heavy metallic asphaltenes part of crude oil. For this oil is pretreated deasphalting, because asphaltenes tend to form coke or consume large quantities of hydrogen. Removing asphaltenes leads to partly demetallization, i.e. for removal of asphaltenes V/Ni and organic compounds with heteroatoms. Intramolecular complexes are relatively well researched on the example of porphyinous complex (VO2) and nickel (Ni). As a result of studies of V/Ni by ICP MS method were determined the effect of different solvents-deasphalting – on the process of extracting metals on deasphalting stage and select the best organic solvent. Thus, as the best DAO proved cyclohexane (C6H12), which as a result of ICP MS retrieves V-51.2%, Ni-66.4%? Also in this paper presents the results of a study of physical and chemical properties and spectral characteristics of oil on FTIR with a view to establishing its hydrocarbon composition. Obtained by using IR-spectroscopy method information about the specifics of the whole oil give provisional physical, chemical characteristics. They can be useful in the consideration of issues of origin and geochemical conditions of accumulation of oil, as well as some technological challenges. Systematic analysis carried out in this study; improve our understanding of the stability mechanism of asphaltenes. The role of deasphalted crude oil fractions on the stability asphaltene is described.

Keywords: asphaltenes, deasphalting, extraction, vanadium, nickel, metalloporphyrins, ICP-MS, IR spectroscopy

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Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

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Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

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Authors: Rhaed Khiati, Muhammad Hanif

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In the past decade, smart healthcare systems have been on an ascendant drift, especially with the evolution of hospitals and their increasing reliance on bioinformatics and software specializing in healthcare. Doctors have become reliant on technology more than ever, something that in the past would have been looked down upon, as technology has become imperative in reducing overall costs and improving the quality of patient care. With patient-doctor interactions becoming more necessary and more complicated than ever, systems must be developed while taking into account costs, patient comfort, and patient data, among other things. In this work, we proposed a smart hospital bed, which mixes the complexity and big data usage of traditional healthcare systems with the comfort found in soft beds while taking certain concerns like data confidentiality, security, and maintaining SLA agreements, etc. into account. This research work potentially provides users, namely patients and doctors, with a seamless interaction with to their respective nurses, as well as faster access to up-to-date personal data, including prescriptions and severity of the condition in contrast to the previous research in the area where there is lack of consideration of such provisions.

Keywords: big data, smart healthcare, distributed systems, bioinformatics

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Authors: Tero Huhtala, Minna Pikkarainen, Saila Saraniemi

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Information technology has long been used as an enabler of exchange for goods and services. Services are evolving from generic to personalized, and the reverse use of customer data has been discussed in both academia and industry for the past few years. This article presents the results of an empirical case study in the area of preventive health care services. The primary data were gathered in workshops, in which future personal data-based services were conceptualized by analyzing future scenarios from a business perspective. The aim of this study is to understand business model transformation in emerging personal data ecosystems. The work was done as a case study in the context of occupational healthcare. The results have implications to theory and practice, indicating that adopting personal data management principles requires transformation of the business model, which, if successfully managed, may provide access to more resources, potential to offer better value, and additional customer channels. These advantages correlate with the broadening of the business ecosystem. Expanding the scope of this study to include more actors would improve the validity of the research. The results draw from existing literature and are based on findings from a case study and the economic properties of the healthcare industry in Finland.

Keywords: ecosystem, business model, personal data, preventive healthcare

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Authors: C. Panebianco, K. Adamberg, S. Adamberg, C. Saracino, M. Jaagura, K. Kolk, A. Di Chio, P. Graziano, R. Vilu, V. Pazienza

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Background/Aims: Despite recent advances in treatment options, a modest impact on the outcome of the pancreatic cancer (PC) is observed so far. Short-term fasting cycles have the potential to improve the efficacy of chemotherapy against PC. However, diseased people may refuse to follow the fasting regimen and fasting may worsen the weight loss often occurring in cancer patients. Therefore, alternative approaches are needed. The aim of this study was to assess the effect of Engineered Low glycemic food ELGIF mimicking diet on growth of cancer cell lines in vitro and in an in vivo pancreatic cancer mouse xenograft model. Materials and Methods: BxPC-3, MiaPaca-2 and Panc-1 cells were cultured in control and ELGIF mimicking diet culturing condition to evaluate the tumor growth and proliferation pathways. Pancreatic cancer xenograft mice were subjected to ELGIF to assess the tumor volume and weight as compared to mice fed with control diet. Results: Pancreatic cancer cells cultured in ELGIF mimicking medium showed decreased levels of proliferation as compared to those cultured in the standard medium. Consistently, xenograft pancreatic cancer mice subjected to ELGIF diet displayed a significant decrease in tumor growth. Conclusion: A positive effect of ELGIF diet on proliferation in vitro is associated with the decrease of tumor progression in the in vivo PC xenograft mouse model. These results suggest that engineered dietary interventions could be supportive as synergistic approach to enhance the efficacy of existing cancer treatments in pancreatic cancer patients.

Keywords: functional food, microbiota, mouse model, pancreatic cancer

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Authors: Syed Nauman Bin Asghar Bukhari, Mohtashim Mansoor, Mohammad Nouman

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Engine test-Bed system is a fundamental tool to measure dynamic parameters, economic performance, and reliability of an aircraft Engine, and its automation and accuracy directly influences the precision of acquired and analysed data. In this paper, we present the design of digital Data Acquisition (DAQ) system for a vintage aircraft engine test bed that lacks the capability of displaying all the analyzed parameters at one convenient location (one panel-one screen). Recording such measurements in the vintage test bed is not only time consuming but also prone to human errors. Digitizing such measurement system requires a Data Acquisition (DAQ) system capable of recording these parameters and displaying them on one screen-one panel monitor. The challenge in designing upgrade to the vintage systems arises with a need to build and integrate digital measurement system from scratch with a minimal budget and modifications to the existing vintage system. The proposed design not only displays all the key performance / maintenance parameters of the gas turbine engines for operator as well as quality inspector on separate screens but also records the data for further processing / archiving.

Keywords: Gas turbine engine, engine test cell, data acquisition, instrumentation

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Authors: Agboka Komi Mensah, John Odindi, Elfatih M. Abdel-Rahman, Onisimo Mutanga, Henri Ez Tonnang

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Ecosystems are networks of organisms and populations that form a community of various species interacting within their habitats. Such habitats are defined by abiotic and biotic conditions that establish the initial limits to a population's growth, development, and reproduction. The habitat’s conditions explain the context in which species interact to access resources such as food, water, space, shelter, and mates, allowing for feeding, dispersal, and reproduction. Dispersal is an essential life-history strategy that affects gene flow, resource competition, population dynamics, and species distributions. Despite the importance of dispersal in population dynamics and survival, understanding the mechanism underpinning the dispersal of organisms remains challenging. For instance, when an organism moves into an ecosystem for survival and resource competition, its progression is highly influenced by extrinsic factors such as its physiological state, climatic variables and ability to evade predation. Therefore, greater spatial detail is necessary to understand organism dispersal dynamics. Understanding organisms dispersal can be addressed using empirical and mechanistic modelling approaches, with the adopted approach depending on the study's purpose Cellular automata (CA) is an example of these approaches that have been successfully used in biological studies to analyze the dispersal of living organisms. Cellular automata can be briefly described as occupied cells by an individual that evolves based on proper decisions based on a set of neighbours' rules. However, in the ambit of modelling individual organisms dispersal at the landscape scale, we lack user friendly tools that do not require expertise in mathematical models and computing ability; such as a visual analytics framework for tracking and forecasting the dispersal behaviour of organisms. The term "visual analytics" (VA) describes a semiautomated approach to electronic data processing that is guided by users who can interact with data via an interface. Essentially, VA converts large amounts of quantitative or qualitative data into graphical formats that can be customized based on the operator's needs. Additionally, this approach can be used to enhance the ability of users from various backgrounds to understand data, communicate results, and disseminate information across a wide range of disciplines. To support effective analysis of the dispersal of organisms at the landscape scale, we therefore designed Pydisp which is a free visual data analytics tool for spatiotemporal dispersal modeling built in Python. Its user interface allows users to perform a quick and interactive spatiotemporal analysis of species dispersal using bioecological and climatic data. Pydisp enables reuse and upgrade through the use of simple principles such as Fuzzy cellular automata algorithms. The potential of dispersal modeling is demonstrated in a case study by predicting the dispersal of Fopius arisanus (Sonan), endoparasitoids to control Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) in Kenya. The results obtained from our example clearly illustrate the parasitoid's dispersal process at the landscape level and confirm that dynamic processes in an agroecosystem are better understood when designed using mechanistic modelling approaches. Furthermore, as demonstrated in the example, the built software is highly effective in portraying the dispersal of organisms despite the unavailability of detailed data on the species dispersal mechanisms.

Keywords: cellular automata, fuzzy logic, landscape, spatiotemporal

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Authors: Kanwal Javid, Shazia Pervaiz, Maria Mumtaz, Muhammad Ameer Nawaz Akram

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Forests and grasslands ecosystems play an important role in the global carbon cycle. Land management activities influence both ecosystems and enable them to absorb and sequester carbon dioxide (CO2). Similarly, in Pakistan, these terrestrial ecosystems are well known to mitigate carbon emissions and have a great source to supply a variety of services such as clean air and water, biodiversity, wood products, wildlife habitat, food, recreation and carbon sequestration. Carbon sequestration is the main agenda of developed and developing nations to reduce the impacts of global warming. But the amount of carbon storage within these ecosystems can be affected by many factors related to air quality such as land management, land-use change, deforestation, over grazing and natural calamities. Moreover, the long-term capacity of forests and grasslands to absorb and sequester CO2 depends on their health, productivity, resilience and ability to adapt to changing conditions. Thus, the main rationale of this study is to monitor the difference in carbon amount of forests and grasslands of Northern Pakistan using MODIS data sets and map results using Geographic Information System. Results of the study conclude that forests ecosystems are more effective in reducing the CO2 level and play a key role in improving the quality of air.

Keywords: carbon sequestration, grasslands, global warming, climate change.

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Authors: Hashem Dadashpoor, Sadegh Saeidi Shirvan

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While with the evolution of the economy towards a knowledge-based economy, innovation is a requirement for metropolitan regions, the adoption of an open innovation strategy is an option and a requirement for many industrial firms in these regions. Studies show that investing in research and development units cannot alone increase innovation. Within the framework of the theory of learning regions, this gap, which scholars call it the ‘innovation gap’, is filled with regional features of firms. This paper attempts to investigate the factors affecting the open innovation of firms in metropolitan regions, and it searches for these in territorial innovation models and, in particular, the theory of learning regions. In the next step, the effect of identified factors which is considered as regional learning factors in this research is analyzed on the innovation of sample firms by SPSS software using multiple linear regression. The case study of this research is constituted of industrial enterprises from two groups of food industry and auto parts in Toos industrial town in Mashhad metropolitan region. For data gathering of this research, interviews were conducted with managers of industrial firms using structured questionnaires. Based on this study, the effect of factors such as size of firms, inter-firm competition, the use of local labor force and institutional infrastructures were significant in the innovation of the firms studied, and 44% of the changes in the firms’ innovation occurred as a result of the change in these factors.

Keywords: regional knowledge networks, learning regions, interactive learning, innovation

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Authors: Almontas Vilutis, Vytenis Jankauskas

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The paper presents the results of the investigation of the dry sliding friction of wood-plastic composites (WPCs) against WC-Co cemented carbide. The dependence of the dynamic coefficient of friction on the main influencing factors (vertical load, temperature, and sliding distance) was investigated by evaluating their mutual interaction. Multiple regression analysis showed a high polynomial dependence (adjusted R2 > 0.98). The resistance of the composite to thermo-mechanical effects determines how temperature and force factors affect the magnitude of the coefficient of friction. WPC-B composite has the lowest friction and highest resistance compared to WPC-A, while composite and cemented carbide materials wear the least. Energy dispersive spectroscopy (EDS), based on elemental composition, provided important insights into the friction process.

Keywords: friction, composite, carbide, factors

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Authors: Mariana Stuparu-Cretu, Doina-Carina Voinescu, Rodica-Mihaela Dinica, Daniela Borda, Camelia Vizireanu, Gabriela Iordachescu, Camelia Busila

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Obesity is involved in the etiology or acceleration of progression of important non-communicable diseases, such as: metabolic, cardiovascular, rheumatological, oncological and depression. It is a need to prevent the obesity occurrence, like a key link in disease management. From this point of view, the best approach is to early educate youngsters upon the need for a healthy nutrition lifestyle associated with constant physical activities. The objective of the study was to assess correlations between weight condition, physical activities and food preferences of students from South East Romania. Questionnaires were applied on high school students in Galati: 1006 girls and 880 boys, aged between 14 and 19 years (being approved by Local School Inspectorate and the Ethics Committee of the 'Dunarea de Jos' University of Galati). The collected answers have been statistically processed by using the multivariate regression method (PLS2) by Unscramble X program (Camo, Norway). Multiple variables such as age group, body mass index, nutritional habits and physical activities were separately analysed, depending on gender and general mathematical models were proposed to explain the obesity trend at an early age. The study results show that overweight and obesity are present in less than a fifth of the adolescents who were surveyed. With a very small variation and a strong correlation of over 86% for 99% of the cases, a general preference for sweet foods, nocturnal eating associated with computer work and a reduced period of physical activity is noticed for girls. In addition, the overweight girls consume sweet juices and alcohol, although a percentage of them also practice the gym. There is also a percentage of the normoponderal girls that consume high caloric foods which predispose this group to turn into overweight cases in time. Within the studied group, statistics for the boys show a positive correlation of almost 87% for over 96% of cases. They prefer high calories foods, fast food, and sweet juices, and perform medium physical activities. Both overweight and underweight boys are more sedentary. Over 15% of girls and over a quarter of boys consume alcohol. All these bad eating habits seem to increase with age, for both sexes. To conclude, obesity and overweight assessed in adolescents in S-E Romania reveal nonsignificant percentage differences between boys and girls. However, young people in this area of the country are sedentary in general; a significant percentage prefers sweets / sweet juices / fast-food and practice computer nourishing. The authors consider that at this age, it is very useful to adapt nutritional education by new methods of food processing and market supply. This would require an early understanding of the difference among foods and nutrients and the benefits of physical activities integrated into the healthy current lifestyle, as a measure for preventing and managing non-communicable chronic diseases related to nutritional errors and sedentarism. Acknowledgment— This study has been partial founded by the Francophone University Agency, Project Réseau régional dans le domaine de la santé, la nutrition et la sécurité alimentaire (SaIN), no.21899/ 06.09.2017.

Keywords: adolescents, body mass index, nutritional habits, obesity, physical activity

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Authors: Yue Feng, Chun-jiang Wang, Zhi-long Huang

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The study of the sedimentary environment of Mesoproterozoic marine deposits in North China has attracted special attention in recent years. It is not clear that the sedimentary environment and the cause of formation of the sandstone strip and its internal carbonate cements and pyrite in the Mesoproterozoic Chuanlinggou Formation in North China. In this study, drilling core samples in North China were identified by microscopy, and their petrological characteristics such as mineral composition and structure were identified. The geochemical data of carbon and oxygen isotopes, total organic carbon (TOC) contents and total sulfur (TS) contents were obtained by processing and analyzing the samples. The samples are mainly quartz particles with low compositional maturity, combined with low value of TOC, it shows that the sedimentary environment of the sandy clastic is a sandy littoral sedimentary environment with relative strong hydrodynamic force, and then the sandstone strip in black shale are formed by the deposition of gravity flow. Analysis of TS values reflect sandstone bands formed in hypoxic environments. The carbonate cements and the pyrite in the sandstone belt are authigenic. The carbon isotope values of authigenic carbonate cements are negatively biased in comparison with the carbonate isotope of carbonate rocks in the same period, but it is more biased than the carbon isotopic values of anaerobic oxidation of methane (AOM) genetic carbonate rocks. Authigenic pyrite may be mainly due to the formation of HS- by the action of bacterial sulfate reduction (BSR) and Fe²⁺, their causes are in contact. This indicates that authigenic carbonate cements are mainly carbonate precipitates formed but are significantly affected by the effects of AOM. Summary, the sedimentary environment of the sandstone zone in the Chuanlinggou Formation in the North China is a shallow sea facies with iron rich and anoxic.

Keywords: sandstone strip, sedimentary environment, authigenic carbonate cements, authigenic pyrite, The Chuanlinggou group, North China

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Authors: T. M. L. Hoang, G. Tan, S. D. Bhowmik, B. Williams, A. Johnson, M. R. Karbaschi, Y. Cheng, H. Long, S. G. Mundree

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Iron deficiency is a worldwide problem affecting both developed and developing countries. Currently, two major approaches namely iron supplementation and food fortification have been used to combat this issue. These measures, however, are limited by the economic status of the targeted demographics. Iron biofortification through genetic modification to enhance the inherent iron content and bioavailability of crops has been employed recently. Several important crops such as rice, wheat, and banana were reported successfully improved iron content via this method, but there is no known study in legumes. Chickpea (Cicer arietinum) is an important leguminous crop that is widely consumed, particularly in India where iron deficiency anaemia is prevalent. Chickpea is also an ideal pulse in the formulation of complementary food between pulses and cereals to improve micronutrient contents. This project aims at generating enhanced ion accumulation and bioavailability chickpea through the exogenous expression of genes related to iron transport and iron homeostasis in chickpea plants. Iron-Regulated Transport (IRT) and Ferritin genes in combination were transformed into chickpea half-embryonic axis by agrobacterium–mediated transformation. Transgenic independent event was confirmed by Southern Blot analysis. T3 leaves and seeds of transgenic chickpea were assessed for iron contents using LA-ICP-MS (Laser Ablation – Inductively Coupled Plasma Mass Spectrometry) and ICP-OES (Inductively Coupled Plasma Optical Emission Spectrometry). The correlation between transgene expression levels and iron content in T3 plants and seeds was assessed using qPCR. Results show that iron content in transgenic chickpea expressing the above genes significantly increased compared to that in non-transgenic controls.

Keywords: iron biofortification, chickpea, IRT, ferritin, Agrobacterium-mediated transformation, LA-ICP-MS, ICP-OES

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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Authors: Jacob T. Liberty, Wilfred I. Okonkwo

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The present study designed and constructed a post-harvest passive solar tomato dryer of dimension 176 x 152 x 54cm for drying tomato. Quality of the dried crop was evaluated and compared with the fresh ones. The solar dryer consist of solar collector (air heater), 110 x 61 x 10 x 10cm, the drying chamber, 102 x54cm, removal heat storage unit, 40 x 35 x 13cm and drying trays, 43 x 42cm. The physicochemical properties of this crop were evaluated before and after drying. Physicochemical properties evaluated includes moisture, protein, fat, fibre, ash, carbohydrate and vitamin C, contents. The fresh, open and solar dried samples were analysed for their proximate composition using the recommended method of AOAC. Also, statistical analysis of the data was conducted using analysis of variance (ANOVA) using completely Randomize Design (CRD) and means were separated by Duncan’s New Multiple Range test (DNMRT). Proximate analysis showed that solar dried tomato had significantly (P < 0.05) higher protein, fibre, ash, carbohydrate and vitamin C except for the fat content that was significantly (P < 0.05) higher for all the open sun dried samples than the solar dried and fresh product. The nutrient which is highly affected by sun drying is vitamin C. Result indicates that moisture loss in solar dried tomato was faster and lower than the open dried samples and as such makes the solar dried products of lesser tendency to mould and bacterial growth. Also, the open sun dried samples had to be carried into the sheltered place each time it rained. The solar dried produce is of high quality. Further processing of the dried crops will involve packaging for commercial purposes. This will also help in making these agricultural product available in a relatively cheap price in off season and also avert micronutrient deficiencies in diet especially among the low-income groups in Nigeria.

Keywords: tomato, passive solar dryer, physicochemical properties, removal heat storage

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Authors: Ilknur Kahriman, Hacer Kobya Bulut, Birsel C. Demirbag

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Introduction and Aim: One of the most challenging aspects of being parents of a child diagnosed with cancer is to balance their normal family life with the child's health needs and treatment requirements. Cancer covers an important part of family life and gets ahead of other matters. Families mostly feel that everything has changed in their lives with the cancer diagnosis and are obliged to make a number of adjustments in their lives. Their normal family life suddenly begins to include treatments, hospital appointments and hospitalizations. This study is a descriptive research conducted to determine the changes in the lives of families who had a child with cancer. Methods: This study was carried out with 65 families having children diagnosed with cancer in 0-17 age group at outpatient pediatric oncology clinic and polyclinic of a university hospital in Trabzon. Data were collected through survey method from August to November, 2015. In the analysis of the data, numbers, percentage and chi-square test were used. Findings: It was found out that the average age of mothers was 35.33 years, most of them were primary school graduates (44.6%) and housewives (89.2%) and the average age of fathers was 39.30 years, most of them were high school graduates (29.2%) and self-employed (43.8% ). The majority of their children were boys and their average age was 7.74 years and 77% had Acute lymphocytic leukemia (ALL) diagnosis. 87.5% of the mothers who had a child with cancer had increased fears in their lives, 84.4% had increased workload at home, 82.8% had more stressful life and 82.8% felt themselves physically tired. The mothers indicated that their healthy children could not do the social activities they had used to do before (56.5%), they no longer fed their healthy children with the food they loved eating so that the sick child did not aspire (52.3%) and their healthy children were more furious than before (53.2%). As for the fathers, the fundamental change they had was increased workload at home (82.3%), had more stressful life (80.6%) and could no longer allocate time to the activities they had been interested in and done before (77.8%). There was not a significant difference between the sick children gender and the changes in their parents lives. The communication between the mothers and their healthy children were determined to be positively affected in the families in which the sick child's disease duration was under 12 months (X2 = 6.452, p = 0.011). Conclusion: This study showed that parents having a child with cancer had more workload at home, had more stressful lives, could not allocate time to social activities, had increased fears, felt themselves tired and their healthy children became more furious and their social activities reduced.

Keywords: child, cancer, changes in lives, family

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Authors: Mengxiao Li, Johnson Zhang

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Currently, topology optimization technique is widely used to define the layout design of structures that are presented as truss-like topologies. However, due to the difficulty in combining optimization technique with more realistic material models where their nonlinear properties should be considered, the achieved optimized topologies are commonly unable to apply straight towards the practical design problems. This study presented an optimization procedure of composite structures where different elastic stiffness, yield criteria, and hardening models are assumed for the candidate materials. From the results, it can be concluded that a more explicit modeling has the significant influence on the resulting topologies. Also, the isotropic or kinematic hardening is important for elastoplastic structural optimization design. The capability of the proposed optimization procedure is shown through several cases.

Keywords: topology optimization, material composition, nonlinear modeling, hardening rules

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Authors: Aminah Muchdar, Nuraeni, Eddy

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The aims of the research are: (1) to verify the cropsyst plant model of experimental data in the field of soybean plants and (2) to predict planting time and potential yield soybean plant with the use of cropsyst model. This research is divided into several stages: (1) first calibration stage which conducted in the field from June until September 2015.(2) application models stage, where the data obtained from calibration in the field will be included in cropsyst models. The required data models are climate data, ground data/soil data,also crop genetic data. The relationship between the obtained result in field with simulation cropsyst model indicated by Efficiency Index (EF) which the value is 0,939.That is showing that cropsyst model is well used. From the calculation result RRMSE which the value is 1,922%.That is showing that comparative fault prediction results from simulation with result obtained in the field is 1,92%. The conclusion has obtained that the prediction of soybean planting time cropsyst based models that have been made valid for use. and the appropriate planting time for planting soybeans mainly on rain-fed land is at the end of the rainy season, in which the above study first planting time (June 2, 2015) which gives the highest production, because at that time there was still some rain. Tanggamus varieties more resistant to slow planting time cause the percentage decrease in the yield of each decade is lower than the average of all varieties.

Keywords: soybean, Cropsyst, calibration, efficiency Index, RRMSE

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Authors: Vladimir Kulyukin, Tanwir Zaman, Sarat Kiran Andhavarapu

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Research on nutrition label use identifies four factors that impede comprehension and retention of nutrition information by consumers: label’s location on the package, presentation of information within the label, label’s surface size, and surrounding visual clutter. In this paper, a system is presented that makes nutrition label use more effective for nutrition information comprehension and retention. The system’s front end is a smartphone application. The system’s back end is a four node Linux cluster for image recognition and data storage. Image frames captured on the smartphone are sent to the back end for skewed or aligned barcode recognition. When barcodes are recognized, corresponding nutrition labels are retrieved from a cloud database and presented to the user on the smartphone’s touchscreen. Each displayed nutrition label is positioned centrally on the touchscreen with no surrounding visual clutter. Wikipedia links to important nutrition terms are embedded to improve comprehension and retention of nutrition information. Standard touch gestures (e.g., zoom in/out) available on mainstream smartphones are used to manipulate the label’s surface size. The nutrition label database currently includes 200,000 nutrition labels compiled from public web sites by a custom crawler. Stress test experiments with the node cluster are presented. Implications for proactive nutrition management and food policy are discussed.

Keywords: mobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: Jakub Berčík, Elena Horská, Ľudmila Nagyová

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Nowadays, the point of sale remains one of the few channels of communication which is not oversaturated yet and has great potential for the future. The fact that purchasing decisions are significantly affected by emotions, while up to 75 % of them are implemented at the point of sale, only demonstrates its importance. The share of impulsive purchases is about 60-75 %, depending on the particular product category. Nevertheless, habits predetermine the content of the shopping cart above all and hence in this regard the role of in-store communication is to disrupt the routine and compel the customer to try something new. This is the reason why it is essential to know how to work with this relatively young branch of marketing communication as efficiently as possible. New global trend in this discipline is evaluating the effectiveness of particular tools in the in-store communication. To increase the efficiency it is necessary to become familiar with the factors affecting the customer both consciously and unconsciously, and that is a task for neuromarketing and sensory marketing. It is generally known that the customer remembers the negative experience much longer and more intensely than the positive ones, therefore it is essential for marketers to avoid this negative experience. The final effect of POP (Point of Purchase) or POS (Point of Sale) tools is conditional not only on their quality and design, but also on the location at the point of sale which contributes to the overall positive atmosphere in the store. Therefore, in-store advertising is increasingly in the center of attention and companies are willing to spend even a third of their marketing communication budget on it. The paper deals with a comprehensive, interdisciplinary research of the impact of traditional as well as innovative tools of in-store communication on the attention and emotional state (valence and arousal) of consumers on the food market. The research integrates measurements with eye camera (Eye tracker) and electroencephalograph (EEG) in real grocery stores as well as in laboratory conditions with the purpose of recognizing attention and emotional response among respondents under the influence of selected tools of in-store communication. The object of the research includes traditional (e.g. wobblers, stoppers, floor graphics) and innovative (e.g. displays, wobblers with LED elements, interactive floor graphics) tools of in-store communication in the fresh unpackaged food segment. By using a mobile 16-channel electroencephalograph (EEG equipment) from the company EPOC, a mobile eye camera (Eye tracker) from the company Tobii and a stationary eye camera (Eye tracker) from the company Gazepoint, we observe the attention and emotional state (valence and arousal) to reveal true consumer preferences using traditional and new unusual communication tools at the point of sale of the selected foodstuffs. The paper concludes with suggesting possibilities for rational, effective and energy-efficient combination of in-store communication tools, by which the retailer can accomplish not only captivating and attractive presentation of displayed goods, but ultimately also an increase in retail sales of the store.

Keywords: electroencephalograph (EEG), emotion, eye tracker, in-store communication

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Authors: Harinder Singh

Abstract:

The paper sheds light on the perceptions of the uninsured workers employed in the urban informal sector of India, towards the health insurance. In addition to this, it also explores the association of the identified perceptions with household decisions to enroll for health insurance schemes in India. Firstly the data taken from the primary survey of the uninsured workers employed in the urban informal sector was analyzed using exploratory factor analysis to evaluate the perceptions. Thereafter, logistic regression was employed to determine the association of the identified perceptions regarding the enrollment. Our study identifies twelve perceptions related to the health insurance enrollment of the uninsured workers employed in the urban informal sector of India. The study demonstrates that perceptions have the strongest association with the voluntary enrollment. These specifically relate to the lack of awareness about the need to buy health insurance; comprehensive coverage; income constraint; future contingencies and social obligations; lack of information; availability of subsidized government health care; linkage with government hospitals and preference for government schemes. Conclusions: Along with the food security, health security has become a crying need of the workers employed in the informal sector and the time has come to scale up the health insurance schemes for them in the country. Policy makers or marketers of health insurance policies should recognize the household perceptions as a potential barrier and try to develop a health insurance package as per the actual needs of the informal sector (low income) in India.

Keywords: association, enrollment, health insurance, informal sector, perceptions, uninsured

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: Marcin Debowski, Marcin Zielinski, Magdalena Zielinska, Paulina Rusanowska

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The problem with digestate management is one of the most important factors influencing on the development and operation of biogas plant. Turbidity and bacterial contamination negatively affect the growth of algae, which can limit the use of the effluent in the production of algae biomass on a large scale. These problems can be overcome by cultivating of algae species resistant to environmental factors, such as Chlorella sp., Scenedesmus sp., or reducing load of organic compounds to prevent bacterial contamination. The effluent requires dilution and/or purification. One of the methods of effluent treatment is the use of a membrane technology such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF) and reverse osmosis (RO), depending on the membrane pore size and the cut off point. Membranes are a physical barrier to solids and particles larger than the size of the pores. MF membranes have the largest pores and are used to remove turbidity, suspensions, bacteria and some viruses. UF membranes remove also color, odor and organic compounds with high molecular weight. In treatment of wastewater or other waste streams, MF and UF can provide a sufficient degree of purification. NF membranes are used to remove natural organic matter from waters, water disinfection products and sulfates. RO membranes are applied to remove monovalent ions such as Na⁺ or K⁺. The effluent was used in UF for medium to cultivation of two microalgae: Chlorella sp. and Phaeodactylum tricornutum. Growth rates of Chlorella sp. and P. tricornutum were similar: 0.216 d⁻¹ and 0.200 d⁻¹ (Chlorella sp.); 0.128 d⁻¹ and 0.126 d⁻¹ (P. tricornutum), on synthetic medium and permeate from UF, respectively. The final biomass composition was also similar, regardless of the medium. Removal of nitrogen was 92% and 71% by Chlorella sp. and P. tricornutum, respectively. The fermentation effluents after UF and dilution were also used for cultivation of algae Scenedesmus sp. that is resistant to environmental conditions. The authors recommended the development of biorafinery based on the production of algae for the biogas production. There are examples of using a multi-stage membrane system to purify the liquid fraction from digestate. After the initial UF, RO is used to remove ammonium nitrogen and COD. To obtain a permeate with a concentration of ammonium nitrogen allowing to discharge it into the environment, it was necessary to apply three-stage RO. The composition of the permeate after two-stage RO was: COD 50–60 mg/dm³, dry solids 0 mg/dm³, ammonium nitrogen 300–320 mg/dm³, total nitrogen 320–340 mg/dm³, total phosphorus 53 mg/dm³. However compostion of permeate after three-stage RO was: COD < 5 mg/dm³, dry solids 0 mg/dm³, ammonium nitrogen 0 mg/dm³, total nitrogen 3.5 mg/dm³, total phosphorus < 0,05 mg/dm³. Last stage of RO might be replaced by ion exchange process. The negative aspect of membrane filtration systems is the fact that the permeate is about 50% of the introduced volume, the remainder is the retentate. The management of a retentate might involve recirculation to a biogas plant.

Keywords: digestate, membrane filtration, microalgae cultivation, Chlorella sp.

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Authors: Qiuxiao Chen, Yan Hou, Ning Wu

Abstract:

As there are deficiencies of the classic Douglas-Peucker Algorithm (DPA), such as high risks of deleting key nodes by mistake, high complexity, time consumption and relatively slow execution speed, a new Deletion-Cost Based Compression Algorithm (DCA) for linear vector data was proposed. For each curve — the basic element of linear vector data, all the deletion costs of its middle nodes were calculated, and the minimum deletion cost was compared with the pre-defined threshold. If the former was greater than or equal to the latter, all remaining nodes were reserved and the curve’s compression process was finished. Otherwise, the node with the minimal deletion cost was deleted, its two neighbors' deletion costs were updated, and the same loop on the compressed curve was repeated till the termination. By several comparative experiments using different types of linear vector data, the comparison between DPA and DCA was performed from the aspects of compression quality and computing efficiency. Experiment results showed that DCA outperformed DPA in compression accuracy and execution efficiency as well.

Keywords: Douglas-Peucker algorithm, linear vector data, compression, deletion cost

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Authors: Janusz Bobulski, Mariusz Kubanek

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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

Procedia PDF Downloads 208