Search results for: cluster based

Authors: Talha A. Al-Dubai, Rashad A. Bantan, Ramadan H. Abu-Zied, Brian G. Jones, Aaid G. Al-Zubieri

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Contemporary foraminiferal samples sediments were collected from the intertidal sabkha of Al-Kharrar Lagoon, Saudi Arabia, to study the vertical distribution of Foraminifera and, based on a modern training set, their potential to develop a predictor of former sea-level changes in the area. Based on hierarchical cluster analysis, the intertidal sabkha is divided into three vertical zones (A, B & C) represented by three foraminiferal assemblages, where agglutinated species occupied Zone A and calcareous species occupied the other two zones. In Zone A (high intertidal), Agglutinella compressa, Clavulina angularis and C. multicamerata are dominant species with a minor presence of Peneroplis planatus, Coscinospira hemprichii, Sorites orbiculus, Quinqueloculina lamarckiana, Q. seminula, Ammonia convexa and A. tepida. In contrast, in Zone B (middle intertidal) the most abundant species are P. planatus, C. hemprichii, S. orbiculus, Q. lamarckiana, Q. seminula and Q. laevigata, while Zone C (low intertidal) is characterised by C. hemprichii, Q. costata, S. orbiculus, P. planatus, A. convexa, A. tepida, Spiroloculina communis and S. costigera. A transfer function for sea-level reconstruction was developed using a modern dataset of 75 contemporary sediment samples and 99 species collected from several transects across the sabkha. The model provided an error of 0.12m, suggesting that intertidal foraminifers are able to predict the past sea-level changes with high precision in Al-Kharrar Lagoon, and thus the future prediction of those changes in the area.

Keywords: Lagoonal foraminifers, intertidal sabkha, vertical zonation, transfer function, sea level

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Authors: Abdul Hadi Butt, Asfandyar Arshad

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The purpose of this paper is to study the thrust variation in different configurations of clustered nozzles. It involves the design and analysis of clustered configuration of nozzles using Ansys fluent. Clustered nozzles with different configurations are simulated and compared on basis of effective exhaust thrust. Mixing length for the flow interaction is also calculated. Further clustered configurations are analyzed over different altitudes. An optimum value of the thrust among different configurations is proposed at the end of comparisons.

Keywords: CD nozzle, cluster, thrust, fluent, ANSYS

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Authors: Lijuan Wang, Junsheng Huo, Jing Sun, Wenxian Li, Jian Huang, Lin Ling, Yiping Zhou, Chengyu Huang, Jifang Hu

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Backgrounds and Objective: This study aimed to evaluate the impact of highly nutrient-dense complementary food supplement-Yingyangbao, at the time of 3 months after Wenchuan earthquake, on the anemia of young children in a county in Sichuan province. Methods: The young children aged 6-23 months in the county were fed one sachet Yingyangbao per day. Yingyangbao were distributed for 15 months for free. The children entering 6 months age would be included. The length, weight and hemoglobin of the children aged 6-29 months were assessed at baseline (n=257) and Yingyangbao intervention for 6 (n=218) and 15 months (n=253) by cluster sampling. Growth status has not been described in the paper. The analysis was conducted based on 6-11, 12-17, 18-23 and 24-29 months. Results: It showed that the hemoglobin concentration in each group among the 4 groups increased by 4.9, 6.4, 8.0, 9.5 g/L after 6 months and 12.7, 11.4, 16.7, 15.7 g/L after 15 months compared to the baseline, respectively. The total anemia prevalence in each group was significantly lower after 6 and 15 months than the baseline (P<0.001), except the 6-11 months group after 6 months because of fewer Yingyangbao consumption. Total moderate anemia rate decreased from 18.3% to 5.5% after 6 months, and kept decreasing to 0.8% after another 9 months. The hemoglobin concentration was significantly correlated with the amount of Yingyangbao consumption(P<0.001) The anemia rate was significantly different based on the Yingyangbao compliance (P<0.001). Conclusion: It was concluded that Yingyangbao which contains quality protein, vitamins and micronutrients intervened 15 months could be effective for the improvement of anemia of young children. The study provides the support that the application of the complementary food supplements to reduce the anemia of young children in the emergency of natural disaster.

Keywords: young children, anemia, nutrition intervention, complementary food supplements, Yingyangbao

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Authors: Giorgio Visentin, Alexei A. Buchachenko

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Recent proposals to use Yb dimer as an optical clock and as a sensor for non-Newtonian gravity imply the knowledge of its interaction potential. Here, the ground-state Born-Oppenheimer Yb₂ potential energy curve is represented by a semi-analytical function, consisting of short- and long-range contributions. For the former, the systematic ab initio all-electron exact 2-component scalar-relativistic CCSD(T) calculations are carried out. Special care is taken to saturate diffuse basis set component with the atom- and bond-centered primitives and reach the complete basis set limit through n = D, T, Q sequence of the correlation-consistent polarized n-zeta basis sets. Similar approaches are used to the long-range dipole and quadrupole dispersion terms by implementing the CCSD(3) polarization propagator method for dynamic polarizabilities. Dispersion coefficients are then computed through Casimir-Polder integration. The semiclassical constraint on the number of the bound vibrational levels known for the ¹⁷⁴Yb isotope is used to scale the potential function. The scaling, based on the most accurate ab initio results, bounds the interaction energy of two Yb atoms within the narrow 734 ± 4 cm⁻¹ range, in reasonable agreement with the previous ab initio-based estimations. The resulting potentials can be used as the reference for more sophisticated models that go beyond the Born-Oppenheimer approximation and provide the means of their uncertainty estimations. The work is supported by Russian Science Foundation grant # 17-13-01466.

Keywords: ab initio coupled cluster methods, interaction potential, semi-analytical function, ytterbium dimer

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Authors: Sohail Ahmed, Ke Xing

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This research theoretically explored the evolution mechanism of enterprise technological innovation capability system (ETICS) from the perspective of complex adaptive systems (CAS). Starting from CAS theory, this study proposed an analytical framework for ETICS, its concepts and theory by integrating CAS methodology into the management of technological innovation capability of enterprises and discusses how to use the principles of complexity to analyze the composition, evolution and realization of the technological innovation capabilities in complex dynamic environment. This paper introduces the concept and interaction of multi-agent, the theoretical background of CAS and summarizes the sources of technological innovation, the elements of each subject and the main clusters of adaptive interactions and innovation activities. The concept of multi-agents is applied through the linkages of enterprises, research institutions and government agencies with the leading enterprises in industrial settings. The study was exploratory based on CAS theory. Theoretical model is built by considering technological and innovation literature from foundational to state of the art projects of technological enterprises. On this basis, the theoretical model is developed to measure the evolution mechanism of enterprise technological innovation capability system. This paper concludes that the main characteristics for evolution in technological systems are based on enterprise’s research and development personal, investments in technological processes and innovation resources are responsible for the evolution of enterprise technological innovation performance. The research specifically enriched the application process of technological innovation in institutional networks related to enterprises.

Keywords: complex adaptive system, echo model, enterprise knowledge system, research institutions, multi-agents.

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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The present study deals with the selection of the most suitable quantitative structure-retention relationship (QSRR) models which should be used in prediction of the retention behavior of basic, neutral, acidic and phenolic pesticides which belong to different classes: fungicides, herbicides, metabolites, insecticides and plant growth regulators. Sum of ranking differences (SRD) approach can give a different point of view on selection of the most consistent QSRR model. SRD approach can be applied not only for ranking of the QSRR models, but also for detection of similarity or dissimilarity among them. Applying the SRD analysis, the most similar models can be found easily. In this study, selection of the best model was carried out on the basis of the reference ranking (“golden standard”) which was defined as the row average values of logarithm of retention time (logtr) defined by high performance liquid chromatography (HPLC). Also, SRD analysis based on experimental logtr values as reference ranking revealed similar grouping of the established QSRR models already obtained by hierarchical cluster analysis (HCA).

Keywords: chemometrics, chromatography, pesticides, sum of ranking differences

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Authors: Laura Piedra-Muñoz, Ángeles Godoy-Durán, Emilio Galdeano-Gómez, Juan C. Pérez-Mesa

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The current agricultural system in some arid and semi-arid areas is not sustainable in the long term. In southeast Spain, groundwater is the main water source and is overexploited, while alternatives like desalination are still limited. The Water Plan for the Mediterranean Basins 2015-2020 indicates a global deficit of 73.42 hm3 and an overexploitation of the aquifers of 205.58hm3. In order to solve this serious problem, two major actions can be taken: increasing available water, and/or improving the efficiency of its use. This study focuses on the latter. The main aim of this study is to present the major factors related to water usage efficiency in farming. It focuses on Almería province, southeast Spain, one of the most arid areas of the country, and in particular on family farms as the main direct managers of water use in this zone. Many of these farms are among the most water efficient in Spanish agriculture, but this efficiency is not generalized throughout the sector. This work conducts a comprehensive assessment of water performance in this area, using on-farm water-use, structural, socio-economic and environmental information. Two statistical techniques are used: descriptive analysis and cluster analysis. Thus, two groups are identified: the least and the most efficient farms regarding water usage. By analyzing both the common characteristics within each group and the differences between the groups with a one-way ANOVA analysis, several conclusions can be reached. The main differences between the two clusters center on the extent to which innovation and new technologies are used in irrigation. The most water efficient farms are characterized by more educated farmers, a greater degree of innovation, new irrigation technology, specialized production and awareness of water issues and environmental sustainability. The research shows that better practices and policies can have a substantial impact on achieving a more sustainable and efficient use of water. The findings of this study can be extended to farms in similar arid and semi-arid areas and contribute to foster appropriate policies to improve the efficiency of water usage in the agricultural sector.

Keywords: cluster analysis, family farms, Spain, water-use efficiency

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Authors: Hadri Hussain, M.Nasir Ibrahim, Chee-Ming Ting, Mariani Idroas, Fuad Numan, Alias Mohd Noor

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A biometric security system has become an important application in client identification and verification system. A conventional biometric system is normally based on unimodal biometric that depends on either behavioural or physiological information for authentication purposes. The behavioural biometric depends on human body biometric signal (such as speech) and biosignal biometric (such as electrocardiogram (ECG) and phonocardiogram or heart sound (HS)). The speech signal is commonly used in a recognition system in biometric, while the ECG and the HS have been used to identify a person’s diseases uniquely related to its cluster. However, the conventional biometric system is liable to spoof attack that will affect the performance of the system. Therefore, a multimodal biometric security system is developed, which is based on biometric signal of ECG, HS, and speech. The biosignal data involved in the biometric system is initially segmented, with each segment Mel Frequency Cepstral Coefficients (MFCC) method is exploited for extracting the feature. The Hidden Markov Model (HMM) is used to model the client and to classify the unknown input with respect to the modal. The recognition system involved training and testing session that is known as client identification (CID). In this project, twenty clients are tested with the developed system. The best overall performance at 44 kHz was 93.92% for ECG and the worst overall performance was ECG at 88.47%. The results were compared to the best overall performance at 44 kHz for (20clients) to increment of clients, which was 90.00% for HS and the worst overall performance falls at ECG at 79.91%. It can be concluded that the difference multimodal biometric has a substantial effect on performance of the biometric system and with the increment of data, even with higher frequency sampling, the performance still decreased slightly as predicted.

Keywords: electrocardiogram, phonocardiogram, hidden markov model, mel frequency cepstral coeffiecients, client identification

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Authors: Guilherme Reis Ranieri, Guilherme Leite Gaudereto, Michele Toledo, Luis Fernando Amato-Lourenco, Thais Mauad

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Given the importance to urban sustainability and the growing relevance of the term ‘community garden’, this paper aims to conduct a bibliometric analysis of the term. Using SCOPUS as database, we analyzed 105 articles that contained the keywords ‘community garden’, and conducted a cluster analysis with the associated keywords. As results, we found 205 articles and 404 different keywords. Among the keywords, 334 are not repeated anytime, 44 are repeated 2 times and 9 appear 3 times. The most frequent keywords are: community food systems (74), urban activism (14), Communities of practice (6), food production (6) and public rethoric (5). Within the areas, which contains more articles are: social sciences (74), environmental science (29) and agricultural and biological sciences (24).The three main countries that concentrated the papers are United States (54), Canada (15) and Australia (12). The main journal with these keywords is Local Environment (10). The first publication was in 1999, and by 2010 concentrated 30,5% of the publications. The other 69,5% occurred 2010 to 2015, indicating an increase in frequency. We can conclude that the papers, based on the distribution of the keywords, are still scattered in various research topics and presents high variability between subjects.

Keywords: bibliometrics, community garden, metrics, urban agriculture

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Authors: Maria Anjelica P. Ancheta, Roberto S. Soriano, Erickson L. Llaguno

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The main purpose of this study is to examine whether there is a significant relationship between socio-economic class and household water supply demand, through determining or verifying the factors governing water use consumption patterns of households from a sampling from different socio-economic classes in Metro Manila, the national capital region of the Philippines. This study is also an opportunity to augment the lack of local academic literature due to the very few publications on urban household water demand after 1999. In over 600 Metro Manila households, a rapid survey was conducted on their average monthly water consumption and habits on household water usage. The questions in the rapid survey were based on an extensive review of literature on urban household water demand. Sample households were divided into socio-economic classes A-B and C-D. Cluster analysis, dummy coding and outlier tests were done to prepare the data for regression analysis. Subsequently, backward stepwise regression analysis was used in order to determine different statistical models to describe the determinants of water consumption. The key finding of this study is that the socio-economic class of a household in Metro Manila is a significant factor in water consumption. A-B households consume more water in contrast to C-D families based on the mean average water consumption for A-B and C-D households are 36.75 m3 and 18.92 m3, respectively. The most significant proxy factors of socio-economic class that were related to household water consumption were examined in order to suggest improvements in policy formulation and household water demand management.

Keywords: household water uses, socio-economic classes, urban planning, urban water demand management

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Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

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The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

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Authors: J. A. López, J. E. Olguín, C. W. Camargo, G. A. Quijano, R. Martínez

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This paper presents an anthropometric study conducted to 300 employees in a maquiladora industry that belongs to the cluster of medical products as part of a research project to pretend simulate workplace conditions under which operators conduct their activities. This project is relevant because traditionally performed a study to design ergonomic workspaces according to anthropometric profile of users, however, this paper demonstrates the importance of making decisions when the infrastructure cannot be adapted for economic whichever put emphasis on user activity.

Keywords: anthropometry, biomechanics, design, ergonomics, productivity

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Authors: Carolina S. Correia, Thalita V. Thomé, Andersen Boniolo, Dhayana I. Veiga

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Evidence-based practices (EBP) in education is a set of principles and practices used to raise educational policy, it involves the integration of professional expertise in education with the best empirical evidence in making decisions about how to deliver instruction. The purpose of this presentation is to describe and characterize studies about EBP in education in elementary classroom setting. Data here presented is part of an ongoing systematic review research. Articles were searched and selected from four academic databases: ProQuest, Scielo, Science Direct and Capes. The search terms were evidence-based practices or program effectiveness, and education or teaching or teaching practices or teaching methods. Articles were included according to the following criteria: The studies were explicitly described as evidence-based or discussed the most effective practices in education, they discussed teaching practices in classroom context in elementary school level. Document excerpts were extracted and recorded in Excel, organized by reference, descriptors, abstract, purpose, setting, participants, type of teaching practice, study design and main results. The total amount of articles selected were 1.185, 569 articles from Proquest Research Library; 216 from CAPES; 251 from ScienceDirect and 149 from Scielo Library. The potentially relevant references were 178, from which duplicates were removed. The final number of articles analyzed was 140. From 140 articles, are 47 theoretical studies and 93 empirical articles. The following research design methods were identified: longitudinal intervention study, cluster-randomized trial, meta-analysis and pretest-posttest studies. From 140 articles, 103 studies were about regular school teaching and 37 were on special education teaching practices. In several studies, used as teaching method: active learning, content acquisition podcast (CAP), precision teaching (PT), mediated reading practice, speech therapist programs and peer-assisted learning strategies (PALS). The countries of origin of the studies were United States of America, United Kingdom, Panama, Sweden, Scotland, South Korea, Argentina, Chile, New Zealand and Brunei. The present study in is an ongoing project, so some representative findings will be discussed, providing further acknowledgment on the best teaching practices in elementary classroom setting.

Keywords: best practices, children, evidence-based education, elementary school, teaching methods

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Authors: Alina Goldberg Cavalleri, Sara Franco Ortega, Nawaporn Onkokesung, Richard Dale, Melissa Brazier-Hicks, Robert Edwards

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Non-target site based resistance (NTSR) to herbicides in weeds is a polygenic trait associated with the upregulation of proteins involved in xenobiotic detoxification and translocation we have termed the xenome. Among the xenome proteins, ABC transporters play a key role in enhancing herbicide metabolism by effluxing conjugated xenobiotics from the cytoplasm into the vacuole. The importance of ABC transporters is emphasized by the fact that they often contribute to multidrug resistance in human cells and antibiotic resistance in bacteria. They also play a key role in insecticide resistance in major vectors of human diseases and crop pests. By surveying available databases, transcripts encoding ABCs have been identified as being enhanced in populations exhibiting NTSR in several weed species. Based on a transcriptomics data in black grass (Alopecurus myosuroides, Am), we have identified three proteins from the ABC-C subfamily that are upregulated in NTSR populations. ABC-C transporters are poorly characterized proteins in plants, but in Arabidopsis localize to the vacuolar membrane and have functional roles in transporting glutathionylated (GSH)-xenobiotic conjugates. We found that the up-regulation of AmABCs strongly correlates with the up-regulation of a glutathione transferase termed AmGSTU2, which can conjugate GSH to herbicides. The expression profile of the ABC transcripts was profiled in populations of black grass showing different degree of resistance to herbicides. This, together with a phylogenetic analysis, revealed that AmABCs cluster in different groups which might indicate different substrate and roles in the herbicide resistance phenotype in the different populations

Keywords: black grass, herbicide, resistance, transporters

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Authors: M. Benhaliliba, A. Ben Ahmed, C.E. Benouis, A.Ayeshamariam

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The properties of nonlinear optical NLOs are examined, and the results confirm the 2.19 eV HOMO-LUMO mismatch. In the Al-Pc cluster, certain functional bond lengths and bond angles have been observed. The Quantum chemical method (DFT and TD-DFT) and Vibrational spectra properties of AlPc are studied. X-ray pattern reveals the crystalline structure along with the (242) orientation of the AlPc organic thin layer. UV-Vis shows the frequency selective behavior of the device. The absorbance of such layer exhibits a high value within the UV range and two consecutive peaks within visible range. Spin coating is used to make an organic diode based on the Aluminium-phthalocynanine (AlPc-Cl) molecule. Under dark and light conditions, electrical characterization of Ag/AlPc/Si/Au is obtained. The diode's high rectifying capability (about 1x104) is subsequently discovered. While the height barrier is constant and saturation current is greatly reliant on light, the ideality factor of such a diode increases to 6.9 which confirms the non-ideality of such a device. The Cheung-Cheung technique is employed to further the investigation and gain additional data such as series resistance and barrier height.

Keywords: AlPc-Cl organic material, nonlinear optic, optical filter, diode

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Authors: Rouhollah Radjabi, Mojtaba Zarei, Elham Sanatgar, Hossein Shouhani

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RAPD molecular markers in order to discrimination of the Iranian native Bombyx mori silkworm breeds were used. DNA extraction using phenol - chloroform was and the qualitative and quantitative measurements of extracted DNA and its dilution, the obtained bands on agarose gel 1.5 percent were marked and analyzed. Results showed that the bands are observed between 250-2500 bp and most bands have been observed as Gilani-orange, the lowest bands observed are Khorasani-lemon. Primer 3 with 100% polymorphism with the highest polymorphism and primer 2 with 61.5 polymorphism had the lowest percentage of polymorphism. Cluster analysis of races and placed them in three main groups, races Gilani - orange, Baghdad and Khorasani -pink if the first group, camel's thorn, Herati - yellow race was alone in the second group and Khorasani – lemon was alone in the third group. The greatest similarity between the races, between Khorasani- pink and Baghdad (0.64). RAPD markers have been determined different silkworm races based on various morphological or economic characteristics except geographic origin.

Keywords: silkworm, molecular marker, RAPD, Iran

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Authors: Sohan Sengupta, Arnab Pramanik, Abhrajyoti Ghosh, Maitree Bhattacharyya

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Newly emerged phyto-pathogens and multi drug resistance have been threating the world for last few decades. Actinomycetes, the most endowed group of microorganisms isolated from unexplored regions of the world may be the ultimate solution to these problems. Thus the aim of this study was to isolate several bioactive actinomycetes strains capable of producing antimicrobial secondary metabolite from Sundarbans, the only mangrove tiger land of the world. Fifty four actinomycetes were isolated and analyzed for antimicrobial activity against fifteen test organisms including three phytopathogens. Nine morphologically distinct and biologically active isolates were subjected to polyphasic identification study. 16s rDNA sequencing indicated eight isolates to reveal maximum similarity to the genus streptomyces, whereas one isolate presented only 93.57% similarity with Streptomyces albogriseolus NRRL B-1305T. Seventy-one carbon sources and twenty-three chemical sources utilization assay revealed their metabolic relatedness. Among these nine isolates three specific strains were found to have notably higher degree of antimicrobial potential effective in a broader range including phyto-pathogenic fungus. PCR base whole genome screen for PKS and NRPS genes, confirmed the occurrence of bio-synthetic gene cluster in some of the isolates for novel antibiotic production. Finally the strain SMS_SU21, which showed antimicrobial activity with MIC value of 0.05 mg ml-1and antioxidant activity with IC50 value of 0.242±0.33 mg ml-1 was detected to be the most potential one. True prospective of this strain was evaluated utilizing GC-MS and the bioactive compound responsible for antimicrobial activity was purified and characterized. Rare bioactive actinomycetes were isolated from unexplored heritage site. Diversity of the biosynthetic gene cluster for antimicrobial compound production has also been evaluated. Antimicrobial compound SU21-C has been identified and purified which is active against a broad range of pathogens.

Keywords: actinomycetes, sundarbans, antimicrobial, pks nrps, phyto-pathogens, GC-MS

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Authors: Yun Zhang

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Urban housing in China is typified by residential districts that occupy 25 to 40 percentage of the urban land. In residential districts, squares, roads, and building facades, as well as plants, usually form a four-grade spatial structure: district entrances, central landscapes, housing cluster entrances, green spaces between dwellings. This spatial structure and its elements not only compose the visible residential landscape but also play a major role of carrying rain water. These elements, therefore, imply ecological significance to urban fitness. Based upon theories of landscape ecology, residential landscape can be understood as a pattern typified by minor soft patch of planted area and major hard patch of buildings and squares, as well as hard corridors of roads. Use five landscape districts in Hangzhou as examples; this paper finds that the size, shape and slope direction of soft patch, the bend of roads, and the form of the four-grade spatial structure are influential for adapting to natural rainwater circulation.

Keywords: Hangzhou China, rainwater, residential landscape, spatial character, urban housing

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Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

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Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: pollen recognition, logistic model tree, expectation-maximization, local binary pattern

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Authors: Mitra Sadoughi

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This study presents the knowledge-sharing model based on individual and organizational factors related to faculty members. To achieve this goal, individual and organizational factors were presented through qualitative research in the form of open codes, axial, and selective observations; then, the final model was obtained using structural equation model. Participants included 1,719 faculty members of the Azad Universities, Mazandaran Province, Region 3. The samples related to the qualitative survey included 25 faculty members experienced at teaching and the samples related to the quantitative survey included 326 faculty members selected by multistage cluster sampling. A 72-item questionnaire was used to measure the quantitative variables. The reliability of the questionnaire was 0.93. Its content and face validity was determined with the help of faculty members, consultants, and other experts. For the analysis of quantitative data obtained from structural model and regression, SPSS and LISREL were used. The results showed that the status of knowledge sharing is moderate in the universities. Individual factors influencing knowledge sharing included the sharing of educational materials, perception, confidence and knowledge self-efficiency, and organizational factors influencing knowledge sharing included structural social capital, cognitive social capital, social capital relations, organizational communication, organizational structure, organizational culture, IT infrastructure and systems of rewards. Finally, it was found that the contribution of individual factors on knowledge sharing was more than organizational factors; therefore, a model was presented in which contribution of individual and organizational factors were determined.

Keywords: knowledge sharing, social capital, organizational communication, knowledge self-efficiency, perception, trust, organizational culture

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Authors: Ali Rahnamoun, Adri van Duin

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The concept of high velocity particle impact on the spacecraft surface materials has been one of the important issues in the design of such materials. Among these particles, water clusters might be the most abundant and the most important particles to be studied. The importance of water clusters is that upon impact on the surface of the materials, they can cause damage to the material and also if they are sub-cooled water clusters, they can attach to the surface of the materials and cause ice accumulation on the surface which is very problematic in spacecraft and also aircraft operations. The dynamics of the collisions between amorphous silica structures and water clusters with impact velocities of 1 km/s to 10 km/s are studied using the ReaxFF reactive molecular dynamics simulation method. The initial water clusters include 150 water molecules and the water clusters are collided on the surface of amorphous fully oxidized and suboxide silica structures. These simulations show that the most abundant molecules observed on the silica surfaces, other than reflecting water molecules, are H3O+ and OH- for the water cluster impacts on suboxide and fully oxidized silica structures, respectively. The effect of impact velocity on the change of silica mass is studied. At high impact velocities the water molecules attach to the silica surface through a chemisorption process meaning that water molecule dissociates through the interaction with silica surface. However, at low impact velocities, physisorbed water molecules are also observed, which means water molecule attaches and accumulates on the silica surface. The amount of physisorbed waters molecules at low velocities is higher on the suboxide silica surfaces. The evolution of the temperatures of the water clusters during the collisions indicates that the possibility of electron excitement at impact velocities less than 10 km/s is minimal and ReaxFF reactive molecular dynamics simulation can predict the chemistry of these hypervelocity impacts. However, at impact velocities close to 10 km/s the average temperature of the impacting water clusters increase to about 2000K, with individual molecules oocasionally reaching temperatures of over 8000K and thus will be prudent to consider the concept of electron excitation at these higher impact velocities which goes beyond the current ReaxFF ability.

Keywords: spacecraft materials, hypervelocity impact, reactive molecular dynamics simulation, amorphous silica

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Authors: Hamed Hossein Afshari, Shahrzad Jalali, Amir Hossein Ghods, Bijan Raahemi

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This paper introduces an automated clustering solution that applies to WiFi/Bluetooth sensing data and is later used for traffic management applications. The paper initially summarizes a number of clustering approaches and thereafter shows their performance for noise removal. In this context, clustering is used to recognize WiFi and Bluetooth MAC addresses that belong to passengers traveling by a public urban transit bus. The main objective is to build an intelligent system that automatically filters out MAC addresses that belong to persons located outside the bus for different routes in the city of Ottawa. The proposed intelligent system alleviates the need for defining restrictive thresholds that however reduces the accuracy as well as the range of applicability of the solution for different routes. This paper moreover discusses the performance benefits of the presented clustering approaches in terms of the accuracy, time and space complexity, and the ease of use. Note that results of clustering can further be used for the purpose of the origin-destination estimation of individual passengers, predicting the traffic load, and intelligent management of urban bus schedules.

Keywords: WiFi-Bluetooth sensing, cluster analysis, artificial intelligence, traffic management

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Authors: Dilani Wimalasiri, Robert Brkljaca, Sylvia Urban, Terrence Piva, Tien Huynh

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Momordica cochinchinensis (Cucurbitaceae) is used as food and traditional medicine in South East Asia and is commonly known as Red Gac. The fruit aril consists 70 times higher lycopene and 10 times higher β-carotene than all known fruits and vegetables. Despite its nutritional value there is little information available on its genetic variation and its influence on nutritional value. In this study; genetic and nutritional variation (lycopene and β-carotene) was investigated among 47 M. cochinchinensis samples collected from Australia, Thailand and Vietnam using molecular markers (RAPD and ISSR) and HPLC, respectively. UPGMA based cluster analysis of genetic data grouped Northern and Central Vietnam samples together but were separated from Australia, Thailand and Southern Vietnam samples. The concentration of lycopene was significantly higher among the samples collected from Central Vietnam (p<0.05) and the concentration of β-carotene was significantly higher among the samples collected from Northern Vietnam (p<0.05) indicating the existence of best varieties. This study provides vital information in genetic diversity and facilitates the selection and breeding for nutritious M. cochinchinensis varieties.

Keywords: momordica cochinchinensis, lycopene, beta carotene, genetic diversity

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Authors: N. Taghinejad, F. Dortaj, N. Khodabandeh

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This research aimed at comparing resilience among male and female children with and without parental supervision in Bandar Abbas. The sample consists of 200 subjects selected through cluster sampling. The research method was comparative causal and Conner and Davidson’s questionnaire form resilience was used for data collection. Results indicated that there is no difference between children with and without parental supervision regarding their resilience capacity. These findings may be challenging and useful for psychologists, officials of children’s affairs and legislators.

Keywords: resilience, children , children with parental supervision, children without parental supervision

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Authors: Chung-Ming Lo, Chung-Chien Lee

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In many countries, the lifetime prevalence of shoulder pain is up to 70%. In America, the health care system spends 7 billion per year about the healthy issues of shoulder pain. With respect to the origin, up to 70% of shoulder pain is attributed to rotator cuff lesions This study proposed a computer-aided diagnosis (CAD) system to assist radiologists classifying rotator cuff lesions with less operator dependence. Quantitative features were extracted from the shoulder ultrasound images acquired using an ALOKA alpha-6 US scanner (Hitachi-Aloka Medical, Tokyo, Japan) with linear array probe (scan width: 36mm) ranging from 5 to 13 MHz. During examination, the postures of the examined patients are standard sitting position and are followed by the regular routine. After acquisition, the shoulder US images were drawn out from the scanner and stored as 8-bit images with pixel value ranging from 0 to 255. Upon the sonographic appearance, the boundary of each lesion was delineated by a physician to indicate the specific pattern for analysis. The three lesion categories for classification were composed of 20 cases of tendon inflammation, 18 cases of calcific tendonitis, and 18 cases of supraspinatus tear. For each lesion, second-order statistics were quantified in the feature extraction. The second-order statistics were the texture features describing the correlations between adjacent pixels in a lesion. Because echogenicity patterns were expressed via grey-scale. The grey-scale co-occurrence matrixes with four angles of adjacent pixels were used. The texture metrics included the mean and standard deviation of energy, entropy, correlation, inverse different moment, inertia, cluster shade, cluster prominence, and Haralick correlation. Then, the quantitative features were combined in a multinomial logistic regression classifier to generate a prediction model of rotator cuff lesions. Multinomial logistic regression classifier is widely used in the classification of more than two categories such as the three lesion types used in this study. In the classifier, backward elimination was used to select a feature subset which is the most relevant. They were selected from the trained classifier with the lowest error rate. Leave-one-out cross-validation was used to evaluate the performance of the classifier. Each case was left out of the total cases and used to test the trained result by the remaining cases. According to the physician’s assessment, the performance of the proposed CAD system was shown by the accuracy. As a result, the proposed system achieved an accuracy of 86%. A CAD system based on the statistical texture features to interpret echogenicity values in shoulder musculoskeletal ultrasound was established to generate a prediction model for rotator cuff lesions. Clinically, it is difficult to distinguish some kinds of rotator cuff lesions, especially partial-thickness tear of rotator cuff. The shoulder orthopaedic surgeon and musculoskeletal radiologist reported greater diagnostic test accuracy than general radiologist or ultrasonographers based on the available literature. Consequently, the proposed CAD system which was developed according to the experiment of the shoulder orthopaedic surgeon can provide reliable suggestions to general radiologists or ultrasonographers. More quantitative features related to the specific patterns of different lesion types would be investigated in the further study to improve the prediction.

Keywords: shoulder ultrasound, rotator cuff lesions, texture, computer-aided diagnosis

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Authors: Rosely Sichieri, Bruna K. Hassan, Michele Sgambato, Barbara S. N. Souza, Rosangela A. Pereira, Edna M. Yokoo, Diana B. Cunha

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Obesity is increasing at a fast rate in low and middle-income countries where few school-based obesity interventions have been conducted. Results of obesity prevention studies are still inconclusive mainly due to underestimation of sample size in cluster-randomized trials and overestimation of changes in body mass index (BMI). The pooled analysis in the present study overcomes these design problems by analyzing 4,448 students (mean age 11.7 years) from three randomized behavioral school-based interventions, conducted in public schools of the metropolitan area of Rio de Janeiro, Brazil. The three studies focused on encouraging students to change their drinking and eating habits over one school year, with monthly 1-h sessions in the classroom. Folders explaining the intervention program and suggesting the participation of the family, such as reducing the purchase of sodas were sent home. Classroom activities were delivered by research assistants in the first two interventions and by the regular teachers in the third one, except for culinary class aimed at developing cooking skills to increase healthy eating choices. The first intervention was conducted in 2005 with 1,140 fourth graders from 22 public schools; the second, with 644 fifth graders from 20 public schools in 2010; and the last one, with 2,743 fifth and sixth graders from 18 public schools in 2016. The result was a non-significant change in BMI after one school year of positive changes in dietary behaviors associated with obesity. Pooled intention-to-treat analysis using linear mixed models was used for the overall and subgroup analysis by BMI status, sex, and race. The estimated mean BMI changes were from 18.93 to 19.22 in the control group and from 18.89 to 19.19 in the intervention group; with a p-value of change over time of 0.94. Control and intervention groups were balanced at baseline. Subgroup analyses were statistically and clinically non-significant, except for the non-overweight/obese group with a 0.05 reduction of BMI comparing the intervention with control. In conclusion, this large pooled analysis showed a very small effect on BMI only in the normal weight students. The results are in line with many of the school-based initiatives that have been promising in relation to modifying behaviors associated with obesity but of no impact on excessive weight gain. Changes in BMI may require great changes in energy balance that are hard to achieve in primary prevention at school level.

Keywords: adolescents, obesity prevention, randomized controlled trials, school-based study

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Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

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Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

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Authors: Xu Yifei, Le Yining, Yang Qingluan, Tu Yanjie

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Objective: This study aims to investigate the distribution features of Traditional Chinese Medicine (TCM) syndromes and syndrome elements in Epstein-Barr virus-associated diseases and then explores the relations between TCM syndromes or syndrome elements and laboratory indicators of Epstein-Barr virus-associated diseases. Methods: A cross-sectional study of 70 patients with EBV infection was described. We assessed the diagnostic information and laboratory indicators of these patients from Huashan Hospital Affiliated to Fudan University between November 2017 and July 2019. The disease diagnosis and syndrome differentiation were based on the diagnostic criteria of EBV-associated diseases and the theory of TCM respectively. Confidence correlation analysis, logistic regression analysis, cluster analysis, and the Sankey diagram were used to analyze the correlation between the data. Results: The differentiation of the 4 primary TCM syndromes in the collected patients was correlated with the indexes of immune function, liver function, inflammation, and anemia, especially the relationship between Qifen syndrome and high lactic acid dehydrogenase level. The common 11 TCM syndrome elements were associated with the increased CD3+ T cell rate, low hemoglobin level, high procalcitonin level, high lactic acid dehydrogenase level, and low albumin level. Conclusion: The changes in immune function indexes, procalcitonin, and liver function-related indexes in patients with EBV-associated diseases were consistent with the evolution law of TCM syndromes. This study provides a reference for judging the pathological stages of these kinds of diseases, predicting their prognosis, and guiding subsequent treatment strategies based on TCM syndrome type.

Keywords: EBV-associated diseases, traditional Chinese medicine syndrome, syndrome element, diagnostics

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Authors: Saeid Motevalli, Siti Fatimah Azzahrah Binti Abd Mutalib, Mohd Sahandri Ghani Hamzah, Hazalizah Hamzah

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The main purpose of the present study was to investigate the relationship between body esteem and self-esteem with sport-confidence among university students. This study was conducted by using the descriptive and correlational study design. Meanwhile, the method involved in this study was the online survey method. The population of the sample are mainly Universiti Pendidikan Sultan Idris (UPSI) students only which 120 participants were selected by cluster sampling method from two faculties named Fakulti Pembangunan Manusia (FPM) and Fakulti Sains Sukan dan Kejurulatihan (FSSKJ). The instrument used in this study was The Body-Esteem Scale (BES) by Franzoi and Shields (1984), Rosenberg Self-Esteem Scale (RSES) by Rosenberg (1965) and the Vealey’s Trait Sport-Confidence Inventory (TSCI) by (Vealey, 1986). The results of the Pearson product-moment correlation coefficient showed that there was a positive and moderate correlation between students’ body-esteem and sport-confidence and a negative and low correlation between students’ self-esteem and sport-confidence. Likewise, based on the entry method used all two predictor variables were significant in explaining sport confidence among UPSI students. In conclusion, it can be said that students’ sport-confidence affected by students’ self-esteem and body-esteem.

Keywords: body esteem, self-esteem, sport-confidence, students

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Authors: Ana Paula Lisboa Sohn, Filipa Dionísio Vieria, Nelson Casarotto, Idaulo José Cunha

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This paper aims at identifying and analyzing the knowledge transmission channels in textile and clothing clusters located in Brazil and in Europe. Primary data was obtained through interviews with key individuals. The collection of primary data was carried out based on a questionnaire with ten categories of indicators of knowledge transmission. Secondary data was also collected through a literature review and through international organizations sites. Similarities related to the use of the main transmission channels of knowledge are observed in all cases. The main similarities are: influence of suppliers of machinery, equipment and raw materials; imitation of products and best practices; training promoted by technical institutions and businesses; and cluster companies being open to acquire new knowledge. The main differences lie in the relationship between companies, where in Europe the intensity of this relationship is bigger when compared to Brazil. The differences also occur in importance and frequency of the relationship with the government, with the cultural environment, and with the activities of research and development. It is also found factors that reduce the importance of geographical proximity in transmission of knowledge, and in generating trust and the establishment of collaborative behavior.

Keywords: industrial clusters, interorganizational learning, knowledge transmission channels, textile and clothing industry

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