Search results for: intraspecific variability

Authors: Sónia C. Andrade, Solange F. Oliveira, Raquel P. F. Guiné, Paula M. R. Correia

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Flours of wheat, chestnut, acorn and lupin were evaluated in relation to phenolic compounds, antioxidant activity, and oxalate content. At the chemical level the results show some variability between samples by type of flour, and the sample of chestnut flour presented the higher value of oxalate (0.00348 mg/100g) when compared to the other samples in the study. Considering the content of phenolic compounds, the sample that stood out was the acorn flour, having a high value of 0.812 g AGE/100 g. All the samples presented intermediate content of antioxidant activity and the sample that showed a slightly higher value was the wheat flour with a value of 0.746 mM TRE/g sample.

Keywords: Wheat, Acorn, Lupin, Chestnut, Flour, Antioxidant properties, Oxalate

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Authors: Monika Soni, Shovonlal Bhowmick, Chandra Bhattacharya, Jitendra Sharma, Prafulla Dutta, Jagadish Mahanta

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Aedes aegypti and Aedes albopictus are considered as two major vectors to transmit dengue virus. In North-east India, two states viz. Assam and Arunachal Pradesh are known to be high endemic zone for dengue and Chikungunya viral infection. The taxonomical classification of medically important vectors are important for mapping of actual evolutionary trends and epidemiological studies. However, misidentification of mosquito species in field-collected mosquito specimens could have a negative impact which may affect vector-borne disease control policy. DNA barcoding is a prominent method to record available species, differentiate from new addition and change of population structure. In this study, a combined approach of a morphological and molecular technique of DNA barcoding was adopted to explore sequence variation in mitochondrial cytochrome c oxidase subunit I (COI) gene within dengue vectors. The study has revealed the map distribution of the dengue vector from two states i.e. Assam and Arunachal Pradesh, India. Approximate five hundred mosquito specimens were collected from different parts of two states, and their morphological features were compared with the taxonomic keys. The analysis of detailed taxonomic study revealed identification of two species Aedes aegypti and Aedes albopictus. The species aegypti comprised of 66.6% of the specimen and represented as dominant dengue vector species. The sequences obtained through standard DNA barcoding protocol were compared with public databases, viz. GenBank and BOLD. The sequences of all Aedes albopictus have shown 100% similarity whereas sequence of Aedes aegypti has shown 99.77 - 100% similarity of COI gene with that of different geographically located same species based on BOLD database search. From dengue prevalent different geographical regions fifty-nine sequences were retrieved from NCBI and BOLD databases of the same and related taxa to determine the evolutionary distance model based on the phylogenetic analysis. Neighbor-Joining (NJ) and Maximum Likelihood (ML) phylogenetic tree was constructed in MEGA6.06 software with 1000 bootstrap replicates using Kimura-2-Parameter model. Data were analyzed for sequence divergence and found that intraspecific divergence ranged from 0.0 to 2.0% and interspecific divergence ranged from 11.0 to 12.0%. The transitional and transversional substitutions were tested individually. The sequences were deposited in NCBI: GenBank database. This observation claimed the first DNA barcoding analysis of Aedes mosquitoes from North-eastern states in India and also confirmed the range expansion of two important mosquito species. Overall, this study insight into the molecular ecology of the dengue vectors from North-eastern India which will enhance the understanding to improve the existing entomological surveillance and vector incrimination program.

Keywords: COI, dengue vectors, DNA barcoding, molecular identification, North-east India, phylogenetics

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Authors: Farah Islam, Md. Monirul Islam, Mosammat Salma Akter, Goutam Kumar Kundu

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The continuous variability of climate and the risk associated with it have a significant impact on the fisheries leading to a global concern for about half a billion fishery-based livelihoods. Though in the context of Bangladesh mounting evidence on the impacts of climate change on fishery-based livelihoods or their socioeconomic conditions are present, the country’s inland fisheries sector remains in a negligible corner as compared to the coastal areas which are spotted on the highlight due to its higher vulnerability to climatic hazards. The available research on inland fisheries, particularly river fisheries, has focussed mainly on fish production, pollution, fishing gear, fish biodiversity and livelihoods of the fishers. This study assesses the impacts of climate variability and changes on the Jamuna (a transboundary river called Brahmaputra in India) River fishing communities and their coping and adaptation strategies. This study has used primary data collected from Kalitola Ghat and Debdanga fishing communities of the Jamuna River during May, August and December 2015 using semi-structured interviews, oral history interviews, key informant interviews, focus group discussions and impact matrix as well as secondary data. This study has found that both communities are exposed to storms, floods and land erosions which impact on fishery-based livelihood assets, strategies, and outcomes. The impact matrix shows that human and physical capitals are more affected by climate hazards which in turn affect financial capital. Both communities have been responding to these exposures through multiple coping and adaptation strategies. The coping strategies include making dam with soil, putting jute sac on the yard, taking shelter on boat or embankment, making raised platform or ‘Kheua’ and involving with temporary jobs. While, adaptation strategies include permanent migration, change of livelihood activities and strategies, changing fishing practices and making robust houses. The study shows that migration is the most common adaptation strategy for the fishers which resulted in mostly positive outcomes for the migrants. However, this migration has impacted negatively on the livelihoods of existing fishers in the communities. In sum, the Jamuna river fishing communities have been impacted by several climatic hazards and they have traditionally coped with or adapted to the impacts which are not sufficient to maintain sustainable livelihoods and fisheries. In coming decades, this situation may become worse as predicted by latest scientific research and an enhanced level of response would be needed.

Keywords: climatic hazards, impacts and adaptation, fisherfolk, the Jamuna River

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Authors: Yukinori Fuse, Masato Kawaguchi

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A quantitative risk assessment method was developed for fiber emissions from sprayed asbestos-containing materials (ACMs). In Japan, instead of being quantitative, these risk assessments have relied on the subjective judgment of skilled engineers, which may vary from one person to another. Therefore, this closed sampling method aims at avoiding any potential variability between assessments. This method was used to assess emissions from ACM sprayed in eleven buildings and the obtained results were compared with the subjective judgments of a skilled engineer. An approximate correlation tendency was found between both approaches. In spite of existing uncertainties, the closed sampling method is useful for public health protection. We firmly believe that this method may find application in the management and renovation decisions of buildings using friable and sprayed ACM.

Keywords: asbestos, renovation, risk assessment, maintenance

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Authors: A. Alyaaria, b, J. P. Wignerona, A. Ducharneb, Y. Kerrc, P. de Rosnayd, R. de Jeue, A. Govinda, A. Al Bitarc, C. Albergeld, J. Sabaterd, C. Moisya, P. Richaumec, A. Mialonc

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Global Level-3 surface soil moisture (SSM) maps from the passive microwave soil moisture and Ocean Salinity satellite (SMOSL3) have been released. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (referred to here as SMOSL3) is necessary. In this study, a comparative analysis of SMOSL3 with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to here as AMSRM, is presented. The comparison of both products (SMSL3 and AMSRM) were made against SSM products produced by a numerical weather prediction system (SM-DAS-2) at ECMWF (European Centre for Medium-Range Weather Forecasts) for the 03/2010-09/2011 period at global scale. The latter product was considered here a 'reference' product for the inter-comparison of the SMOSL3 and AMSRM products. Three statistical criteria were used for the evaluation, the correlation coefficient (R), the root-mean-squared difference (RMSD), and the bias. Global maps of these criteria were computed, taking into account vegetation information in terms of biome types and Leaf Area Index (LAI). We found that both the SMOSL3 and AMSRM products captured well the spatio-temporal variability of the SM-DAS-2 SSM products in most of the biomes. In general, the AMSRM products overestimated (i.e., wet bias) while the SMOSL3 products underestimated (i.e., dry bias) SSM in comparison to the SM-DAS-2 SSM products. In term of correlation values, the SMOSL3 products were found to better capture the SSM temporal dynamics in highly vegetated biomes ('Tropical humid', 'Temperate Humid', etc.) while best results for AMSRM were obtained over arid and semi-arid biomes ('Desert temperate', 'Desert tropical', etc.). When removing the seasonal cycles in the SSM time variations to compute anomaly values, better correlation with the SM-DAS-2 SSM anomalies were obtained with SMOSL3 than with AMSRM, in most of the biomes with the exception of desert regions. Eventually, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (slightly better) SSM products correlate well with the SM-DAS2 products over regions with sparse vegetation for values of LAI < 1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI>1, SMOSL3 outperformed AMSRM with respect to SM-DAS-2: SMOSL3 had almost consistent performances up to LAI = 6, whereas AMSRM performance deteriorated rapidly with increasing values of LAI.

Keywords: remote sensing, microwave, soil moisture, AMSR-E, SMOS

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Authors: N. Boutra, N. Ravot, J. Benoit, O. Picon

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Submarine power cables used for offshore wind farms electric energy distribution and transmission are subject to numerous threats. Some of the risks are associated with transport, installation and operating in harsh marine environment. This paper describes the feasibility of an electromagnetic low frequency sensing technique for submarine power cable failure prediction. The impact of a structural damage shape and material variability on the induced electric field is evaluated. The analysis is performed by modeling the cable using the finite element method, we use sensitivity analysis in order to identify the main damage characteristics affecting electric field variation. Lastly, we discuss the results obtained.

Keywords: electromagnetism, finite element method, sensitivity analysis, submarine power cables

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Authors: Kostas Philippopoulos, Chris G. Tzanis, Despina Deligiorgi

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Climate change adaptation requires the exploitation of renewable energy sources such as wind. However, climate variability can affect the regional wind energy potential and consequently the available wind power production. The goal of the research project is to examine the impact of atmospheric circulation on wind energy production over Greece. In the context of synoptic climatology, the proposed novel methodology employs Self-Organizing Maps for grouping and classifying the atmospheric circulation and nationally-aggregated capacity factor time series for a 30-year period. The results indicate the critical effect of atmospheric circulation on the national aggregated wind energy production values and therefore address the issue of optimum distribution of wind farms for a specific region.

Keywords: wind energy, atmospheric circulation, capacity factor, self-organizing maps

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Authors: Issam Ben Jami

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Information retrieval in digital libraries is very important because most famous historical documents occupy a significant value. The word spotting in historical documents is a very difficult notion, because automatic recognition of such documents is naturally cursive, it represents a wide variability in the level scale and translation words in the same documents. We first present a system for the automatic recognition, based on the extraction of interest points words from the image model. The extraction phase of the key points is chosen from the representation of the image as a synthetic description of the shape recognition in a multidimensional space. As a result, we use advanced methods that can find and describe interesting points invariant to scale, rotation and lighting which are linked to local configurations of pixels. We test this approach on documents of the 15th century. Our experiments give important results.

Keywords: feature matching, historical documents, pattern recognition, word spotting

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Authors: Yevheniia Varyvoda, Douglas Taren

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At the aggregate level, climate variability, the rising number of active violent conflicts, globalization and industrialization of agriculture, the loss in diversity of crop species, the increase in demand for agricultural production, and the adoption of healthy and sustainable dietary patterns are exacerbating factors of food system destabilization. The importance of pseudocereals to fuel and sustain resilient food systems is recognized by leading organizations working to end hunger, particularly for their critical capability to diversify livelihood portfolios and provide plant-sourced healthy nutrition in the face of systemic shocks and stresses. Amaranth, buckwheat, and quinoa are the most promising and used pseudocereals for ensuring food system resilience in the reality of climate change due to their high nutritional profile, good digestibility, palatability, medicinal value, abiotic stress tolerance, pest and disease resistance, rapid growth rate, adaptability to marginal and degraded lands, high genetic variability, low input requirements, and income generation capacity. The study provides the rationale and examples of advancing local and regional food systems' resilience by scaling up the utilization of amaranth, buckwheat, and quinoa along all components of food systems to architect indirect nutrition interventions and climate-smart approaches. Thus, this study aims to explore the drivers for ancient pseudocereal utilization, the potential resilience benefits that can be derived from using them, and the challenges and opportunities for pseudocereal utilization within the food system components. The PSALSAR framework regarding the method for conducting systematic review and meta-analysis for environmental science research was used to answer these research questions. Nevertheless, the utilization of pseudocereals has been slow for a number of reasons, namely the increased production of commercial and major staples such as maize, rice, wheat, soybean, and potato, the displacement due to pressure from imported crops, lack of knowledge about value-adding practices in food supply chain, limited technical knowledge and awareness about nutritional and health benefits, absence of marketing channels and limited access to extension services and information about resilient crops. The success of climate-resilient pathways based on pseudocereal utilization underlines the importance of co-designed activities that use modern technologies, high-value traditional knowledge of underutilized crops, and a strong acknowledgment of cultural norms to increase community-level economic and food system resilience.

Keywords: resilience, pseudocereals, food system, climate change

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Authors: Z. Jannoo, B. W. Yap, N. Auchoybur, M. A. Lazim

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The two common approaches to Structural Equation Modeling (SEM) are the Covariance-Based SEM (CB-SEM) and Partial Least Squares SEM (PLS-SEM). There is much debate on the performance of CB-SEM and PLS-SEM for small sample size and when distributions are non-normal. This study evaluates the performance of CB-SEM and PLS-SEM under normality and non-normality conditions via a simulation. Monte Carlo Simulation in R programming language was employed to generate data based on the theoretical model with one endogenous and four exogenous variables. Each latent variable has three indicators. For normal distributions, CB-SEM estimates were found to be inaccurate for small sample size while PLS-SEM could produce the path estimates. Meanwhile, for a larger sample size, CB-SEM estimates have lower variability compared to PLS-SEM. Under non-normality, CB-SEM path estimates were inaccurate for small sample size. However, CB-SEM estimates are more accurate than those of PLS-SEM for sample size of 50 and above. The PLS-SEM estimates are not accurate unless sample size is very large.

Keywords: CB-SEM, Monte Carlo simulation, normality conditions, non-normality, PLS-SEM

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Authors: G. Meccariello, L. Della Ragione

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The exposure to outdoor air pollution causes lung cancer and increases the risk of bladder cancer. Because air pollution in urban areas is mainly caused by transportation, it is necessary to evaluate pollutant exhaust emissions from vehicles during their real-world use. Nevertheless their evaluation and reduction is a key problem, especially in the cities, that account for more than 50% of world population. A particular attention was given to the slope variability along the streets during each journey performed by the instrumented vehicle. In this paper we dealt with the problem of describing a quantitatively approach for the reconstruction of GPS coordinates and altitude, in the context of correlation study between driving cycles / emission / geographical location, during an experimental campaign realized with some instrumented cars. Finally the slope analysis can be correlated to the emission and consumption values in a specific road position, and it could be evaluated its influence on their behaviour.

Keywords: air pollution, driving cycles, GPS signal, slope, emission factor, fuel consumption

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Authors: Asad Abbas, Muhammad Fezan Afzal, Muhammad Latif Anjum, Muhammad Azmat

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The Internet of Things (IoT) is used to link up real objects that use the internet to interact. IoT applications allow handling and operating the equipment in accordance with environmental needs, such as transportation and healthcare. IoT devices are linked together via a number of agents that act as a middleman for communications. The operation of a heat sensor differs indoors and outside because agent applications work with environmental variables. In this article, we suggest using Software Product Line (SPL) to model IoT agents and applications' features on an XML-based basis. The contextual diversity within the same domain of application can be handled, and the reusability of features is increased by XML-based feature modelling. For the purpose of managing contextual variability, we have embraced XML for modelling IoT applications, agents, and internet-connected devices.

Keywords: IoT agents, IoT applications, software product line, feature model, XML

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Authors: Abhishek Mangal, Kunal Tongaria, S. Mandal, Devendra Mohan

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Carbonation of reinforced concrete structures has emerged as one of the major challenges for Civil engineers across the world. With increasing emissions from various activities, carbon dioxide concentration in the atmosphere has been eve rising, enhancing its penetration in porous concrete, reaching steel bars and ultimately leading to premature failure. Several literatures have been published dealing with the various interdependent variables related to carbonation. However, with innumerable variability a generalization of these data proves to be a troublesome task. This paper looks into this carbonation anomaly in concrete structures caused by various external variables such as relative humidity, concentration of CO2, curing period and ambient temperature. Significant discussions and comparisons have been presented on the basis of various studies conducted with an aim to predict the depth of carbonation as a function of these multidimensional parameters using various numerical and statistical modelling techniques.

Keywords: carbonation, curing, exposure conditions, relative humidity

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Authors: Robert Kwame Kpaliba, Dennis Kpakpor Adotey, Yaw Serfor-Armah

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Increase in the oceanic carbon dioxide absorbance from the atmosphere due to climate change has led to appreciable change in the chemistry of the oceans. The change in oceanic pH referred to as ocean acidification poses multiple threats and stresses on marine species, biodiversity, goods and services, and livelihoods. Marine ecosystems are continuously threatened by plethora of natural and anthropogenic stressors including carbon dioxide (CO₂) emissions causing a lot of changes which has not been experienced for approximately 60 years. Little has been done in Africa as a whole and Ghana in particular to improve the understanding of the variations of the carbonate chemistry of seawater and the biophysical impacts of ocean acidification on security of seafood, nutrition, climate and environmental change. There is, therefore, the need for regular monitoring of carbonate chemistry of seawater along Ghana’s coastline to generate reliable data to aid marine policy formulation. Samples of seawater were collected thrice every month for a one-year period from five study sites for the various parameters to be analyzed. Analysis of the measured physico-chemical and the carbonate chemistry parameters was done using simple statistics. Correlation test and ANOVA were run on both of the physico-chemical and carbonate chemistry parameters. The carbonate chemistry parameters were measured using computer software programme (CO₂cal v4.0.9) except total alkalinity and pH. The study assessed the variability of seawater carbonate chemistry in selected portions of the Central Atlantic Coastline of Ghana (Tsokomey/Bortianor, Kokrobitey, Gomoa Nyanyanor, Gomoa Fetteh, and Senya Breku landing beaches) over a 1-year period (June 2016–May 2017). For physico-chemical parameters, there was insignificant variation in nitrate (NO₃⁻) (1.62 - 2.3 mg/L), ammonia (NH₃) (1.52 - 2.05 mg/L), and salinity (sal) (34.50 - 34.74 ppt). Carbonate chemistry parameters for all the five study sites showed significant variation: partial pressure of carbon dioxide (pCO₂) (414.08-715.5 µmol/kg), carbonate ion (CO₃²⁻) (115-157.92 µmol/kg), pH (7.9-8.12), total alkalinity (TA) (1711.8-1986 µmol/kg), total carbon dioxide (TCO₂) (1512.1 - 1792 µmol/kg), dissolved carbon dioxide (CO₂aq) (10.97-18.92 µmol/kg), Revelle Factor (RF) (9.62-11.84), aragonite (ΩAr) (0.75-1.48) and calcite (ΩCa) (1.08-2.14). The study revealed that the partial pressure of carbon dioxide and temperature did not have a significant effect on each other (r² = 0.31) (p-value = 0.0717). There was an appreciable effect of pH on dissolved carbon dioxide (r² = 0.921) (p-value = 0.0000). The variation between total alkalinity and dissolved carbon dioxide was appreciable (r² = 0.731) (p-value = 0.0008). There was a significant correlation between total carbon dioxide and dissolved carbon dioxide (r² = 0.852) (p-value = 0.0000). Revelle factor correlated strongly with dissolved carbon dioxide (r² = 0.982) (p-value = 0.0000). Partial pressure of carbon dioxide corresponds strongly with atmospheric carbon dioxide (r² = 0.9999) (p-value = 0.00000).

Keywords: carbonate chemistry, seawater, central atlantic coastline, Ghana, ocean acidification

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Authors: Abouamama Sidaoui, Noureddine Karkachi, Mebrouk Kihal

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The characteristics of Fusarium oxysporium f.sp. albedinis (Foa) isolates were investigated using electrophoretic studies of isozymes systems (esterase and phosphatase). All the (F.o.a) isolates were pathogenic to the date palm seedlings cultivar Deglet Nour, but they did not induce any disease symptoms on control plants. Fusarium sp. isolated from soil did not show aggression against these seedlings. The isoenzymes profiles revealed polymorphic bands. The data were subjected to analysis with the JMP method. The isolates were delineated into two main groups A and B which were divided into sub-groups. 19 isolates create the group A, and four isolates (E1, E2, E3 and M15A) formed the group B. Analysis of isozyme banding patterns was found to be a reliable marker technology, efficient, and effective tools to find the genetic variability among isolates isolated in different geographical areas.

Keywords: genetic diversity, Fusarium oxysporium f. sp. albedinis, isozyme analysis, pathogenicity

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Authors: Osvaldo Collazo, Cristiano Valerio Dos Santos

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Early maternal separation has been shown to bring about many negative effects on behavior in rats. In the present study, we evaluated the effects of early maternal separation on risky choice in rats. One group of male and female Wistar rats was exposed to an early maternal separation protocol while a control group was left undisturbed. Then both groups were exposed to a series of behavioral tests, including a test of risky choice, where one alternative offered a constant reward while the other offered a variable reward. There was a difference between groups when they chose between a variable and a constant reward delay, but no other difference was significant. These results suggest that early maternal separation may be related to a greater preference for shorter delays, which is characteristic of more impulsive choices.

Keywords: early maternal separation, impulsivity, risky choice, variability

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Authors: Prakash Khatarkar, P. A. Khan, Shweta Mukherjee, Roshni Atulkar, P. K. Purohit, A. K. Gwal

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We have investigated the occurrence characteristics of ionospheric scintillations, using dual frequency GPS, installed and operated at Indian scientific base station Maitri (71.45S and 11.45E), Antarctica, during December 2009 to December 2010. The scintillation morphology is described in terms of S4 Index. The scintillations are classified into four main categories as Weak (0.21.0). From the analysis we found that the percentage of weak, moderate, strong and saturated scintillations were 96%, 80%, 58% and 7%, respectively. The maximum percentage of all types of scintillation was observed in the summer season, followed by equinox and the least in winter season. As the year 2010 was a low solar activity period, consequently the maximum occurrences of scintillations were those of weak and moderate and only four cases of saturated scintillation were observed.

Keywords: L-band scintillation, GPS, auroral region, low solar activity

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

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

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

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Authors: M. Eickermann, M. K. Class, J. Junk

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Winter oilseed rape, Brassica napus L., is characterized by a high number of herbicide applications. Therefore, its cultivation can lead to massive contamination of ground water and soil by herbicide and their metabolites. A multi-side long-term field experiment (EFFO, Efficient crop rotation) was set-up in Luxembourg to quantify these effects. Based on soil sampling and laboratory analysis, preliminary results showed reduced dehydrogenase activities of several soil organisms due to herbicide treatments. This effect is highly depending on the soil type. Relation between the dehydrogenase activity and the amount of microbial carbon showed higher variability on the test side with loamy Brown Earth, based on Bunter than on those with sandy-loamy Brown Earth, based on calciferous Sandstone.

Keywords: cropping system, dehydrogenase activity, herbicides, mechanical weed control, oilseed rape

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Authors: Baeza S. Roberto

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The knitted fabric suffers a deformation in its dimensions due to stretching and tension factors, transverse and longitudinal respectively, during the process in rectilinear knitting machines so it performs a dry relaxation shrinkage procedure and thermal action of prefixed to obtain stable conditions in the knitting. This paper presents a dry relaxation shrinkage prediction of Bordeaux fiber using a feed forward neural network and linear regression models. Six operational alternatives of shrinkage were predicted. A comparison of the results was performed finding neural network models with higher levels of explanation of the variability and prediction. The presence of different reposes are included. The models were obtained through a neural toolbox of Matlab and Minitab software with real data in a knitting company of Southern Guanajuato. The results allow predicting dry relaxation shrinkage of each alternative operation.

Keywords: neural network, dry relaxation, knitting, linear regression

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Authors: Pulkeria Pascoe, Hawa P. Tundui, Marcia Dutra de Barcellos, Hans de Steur, Xavier Gellynck

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A majority of Micro and Small Enterprises (MSEs) experience low or no growth. Understanding their performance remains unfinished and disjointed as there is no consensus on the factors influencing it, especially in developing countries. Using a Resource-Based View (RBV) as the theoretical background, this cross-sectional study employed four regression models to examine the influence of firm-level factors (firm-specific characteristics, firm resources, manager socio-demographic characteristics, and selected management practices) on the overall performance variations among 442 Tanzanian micro and small agri-food processing firms. Study results confirmed the RBV argument that intangible resources make a larger contribution to overall performance variations among firms than that tangible resources. Firms' tangible and intangible resources explained 34.5% of overall performance variations (intangible resources explained the overall performance variability by 19.4% compared to tangible resources, which accounted for 15.1%), ranking first in explaining the overall performance variance. Firm-specific characteristics ranked second by influencing variations in overall performance by 29.0%. Selected management practices ranked third (6.3%), while the manager's socio-demographic factors were last on the list, as they influenced the overall performance variability among firms by only 5.1%. The study also found that firms that focus on proper utilization of tangible resources (financial and physical), set targets, and undertake better working capital management practices performed higher than their counterparts (low and average performers). Furthermore, accumulation and proper utilization of intangible resources (relational, organizational, and reputational), undertaking performance monitoring practices, age of the manager, and the choice of the firm location and activity were the dominant significant factors influencing the variations among average and high performers, relative to low performers. The entrepreneurial background was a significant factor influencing variations in average and low-performing firms, indicating that entrepreneurial skills are crucial to achieving average levels of performance. Firm age, size, legal status, source of start-up capital, gender, education level, and total business experience of the manager were not statistically significant variables influencing the overall performance variations among the agri-food processors under the study. The study has identified both significant and non-significant factors influencing performance variations among low, average, and high-performing micro and small agri-food processing firms in Tanzania. Therefore, results from this study will help managers, policymakers and researchers to identify areas where more attention should be placed in order to improve overall performance of MSEs in agri-food industry.

Keywords: firm-level factors, micro and small enterprises, performance, regression analysis, resource-based-view

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Authors: Priyashri Kamlesh Sridhar, Suranga Nanayakkara

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Current frameworks in assessment follow lesson delivery and rely heavily on test performance or teacher’s observations. This, however, neglects the underlying cognitive load during the learning process. Identifying the pivotal points when the load occurs helps design effective pedagogies and tools that respond to learners’ cognitive state. There has been limited research on quantifying cognitive load in preschoolers, real-time. In this study, we recorded electrodermal activity and heart rate variability (HRV) from 10 kindergarteners performing executive function tasks and Johnson Woodcock test of cognitive abilities. Preliminary findings suggest that there are indeed sensitive task-dependent markers in skin conductance (number of SCRs and average amplitude of SCRs) and HRV (mean heart rate and low frequency component) captured during the learning process.

Keywords: early childhood, learning, methodologies, pedagogies

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Authors: Sheeraz Memon, Namunu C. Maddage, Margaret Lech, Nicholas Allen

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The effect of a clinical environment on the accuracy of the speaker verification was tested. The speaker verification tests were performed within homogeneous environments containing clinically depressed speakers only, and non-depresses speakers only, as well as within mixed environments containing different mixtures of both climatically depressed and non-depressed speakers. The speaker verification framework included the MFCCs features and the GMM modeling and classification method. The speaker verification experiments within homogeneous environments showed 5.1% increase of the EER within the clinically depressed environment when compared to the non-depressed environment. It indicated that the clinical depression increases the intra-speaker variability and makes the speaker verification task more challenging. Experiments with mixed environments indicated that the increase of the percentage of the depressed individuals within a mixed environment increases the speaker verification equal error rates.

Keywords: speaker verification, GMM, EM, clinical environment, clinical depression

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Authors: Charline David, Alexandre Blondin Massé, Arnaud Zinflou

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In 2016, Clements, Hurn, and Li proposed a multiple equation time series approach for the short-term load forecasting, reporting an average mean absolute percentage error (MAPE) of 1.36% on an 11-years dataset for the Queensland region in Australia. We present an adaptation of their model to the electrical power load consumption for the whole Quebec province in Canada. More precisely, we take into account two additional meteorological variables — cloudiness and wind speed — on top of temperature, as well as the use of multiple meteorological measurements taken at different locations on the territory. We also consider other minor improvements. Our final model shows an average MAPE score of 1:79% over an 8-years dataset.

Keywords: short-term load forecasting, special days, time series, multiple equations, parallelization, clustering

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Authors: Luke Onyekakeyah, Cynthia Onyekakeyah

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The conflict in Northeastern Nigeria could mar local and international efforts to salvage the drying Lake Chad, which at present is merely 20 per cent of its original size. The conflict which began in 2009, assumed a monstrous dimension to the extent that any prospects of a redeeming action on the Lake is bleak. The concern of the authorities in the basin countries is how to bring the conflict to an end in the interest of the ecologically-dependent riparian population. Lake Chad is Africa’s fourth largest lake. From a previous 388,500 km2 some 600, 000 years ago, the Lake has shrunk to a maximum length of 25,000 km2. During the last four decades, the Lake has been susceptible to increasing variability and irregular rainfall. Dry spell, excessive evaporation and sandstorm have adversely affected the Lake, such that a 2001 estimate put the Lake to a meager 19,000 km2. Given the critical importance of the Lake as a source of livelihood for over 20 million people, there is mounting concern that an unprecedented human and ecological catastrophe is unfolding, should the Lake eventually dries up. The study evaluates the Lake Chad and how the conflict has adversely impacted it.

Keywords: lake chad, conflict, salvage, Nigeria

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Authors: Bhojan Dhakal, Naba Raj Devkota, Chet Raj Upreti, Maheshwar Sapkota

Abstract:

A study was conducted to find out the production potential, nutrient composition, and the variability of the most commonly available fodder trees along with the varying altitude to help optimize the dry matter requirement during winter lean period. The study was carried out from March to June, 2012 in Lho and Prok Village Development Committee of Manaslu Conservation Area (MCA), located in Gorkha district of Nepal. The other objective of the research was to learn the impact of climate change on livestock production linking it with feed availability. The study was conducted in two parts: social and biological. Accordingly, a households (HHs) survey was conducted to collect primary data from 70 HHs, focusing on the perception of respondents on impacts of climatic variability on the feeding management. The next part consisted of understanding yield potential and nutrient composition of the four most commonly available fodder trees (M. azedirach, M. alba, F. roxburghii, F. nemoralis), within two altitudes range: (1500-2000 masl and 2000-2500 masl) by using a RCB design in 2*4 factorial combination of treatments, each replicated four times. Results revealed that majority of the farmers perceived the change in climatic phenomenon more severely within the past five years. Farmers were using different adaptation technologies such as collection of forage from jungle, reducing unproductive animals, fodder trees utilization, and crop by product feeding at feed scarcity period. Ranking of the different fodder trees on the basis of indigenous knowledge and experiences revealed that F. roxburghii was the best-preferred fodder tree species (index value 0.72) in terms overall preferability whereas M. azedirach had highest growth and productivity (index value 0.77), F. roxburghii had highest adoptability (index value 0.69) and palatability (index value 0.69) as well. Similarly, fresh yield and dry matter yield of the each fodder trees was significant (P < 0.01) between the altitude and within species. Fodder trees yield analysis revealed that the highest dry matter (DM) yield (28 kg/tree) was obtained for F. roxburghii but that remained statistically similar (P > 0.05) to the other treatment. On the other hand, most of the parameters: ether extract (EE), acid detergent lignin (ADL), acid detergent fibre (ADF), cell wall digestibility (CWD), relative digestibility (RD), digestible nutrient (TDN), and Calcium (Ca) among the treatments were highly significant (P < 0.01). This indicates the scope of introducing productive and nutritive fodder trees species even at the high altitude to help reduce fodder scarcity problem during winter. The finding also revealed the scope of promoting all available local fodder trees species as crude protein content of these species were similar.

Keywords: fodder trees, yield potential, climate change, nutrient composition

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Authors: Mohamad H. Atyeh, Wael Alrashed, Steven Telford

Abstract:

The main objective of this research is to measure if there have been any notable changes in the trading actives of the Kuwait stock Exchange (KSE) after the privatization process that took place on the 25th of April 2016. The data that are used to test if there is any change in the KSE market performance are the daily indices for the period from the 25th of April 2016 till the 24th of October 2016 (after privatization) and a similar six months period before the date of the privatization from the 24th of October 2015 till the 24th of April 2016. In addition, as a control, the study included a period that is a period parallel to the six months period after the privatization. The results indicate that privatization is associated with lower variability for the majority of variables, but that the observed switch in slope direction is not actually a product of privatization, but rather one of serial correlation.

Keywords: privatization, Kuwait stock exchange (KSE), market capitalization (MCAP), capital markets authority (CMA), Boursa Kuwait securities company (BKSC)

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Authors: Mohammad Moezzibadi, Isabelle Charpentier, Adrien Wanko, Robert Mosé

Abstract:

The calibration of hydrodynamic parameters for subsurface constructed wetlands (CWs) is a sensitive process since highly non-linear equations are involved in unsaturated flow modeling. CW systems are engineered systems designed to favour natural treatment processes involving wetland vegetation, soil, and their microbial flora. Their significant efficiency at reducing the ecological impact of urban runoff has been recently proved in the field. Numerical flow modeling in a vertical variably saturated CW is here carried out by implementing the Richards model by means of a mixed hybrid finite element method (MHFEM), particularly well adapted to the simulation of heterogeneous media, and the van Genuchten-Mualem parametrization. For validation purposes, MHFEM results were compared to those of HYDRUS (a software based on a finite element discretization). As van Genuchten-Mualem soil hydrodynamic parameters depend on water content, their estimation is subject to considerable experimental and numerical studies. In particular, the sensitivity analysis performed with respect to the van Genuchten-Mualem parameters reveals a predominant influence of the shape parameters α, n and the saturated conductivity of the filter on the piezometric heads, during saturation and desaturation. Modeling issues arise when the soil reaches oven-dry conditions. A particular attention should also be brought to boundary condition modeling (surface ponding or evaporation) to be able to tackle different sequences of rainfall-runoff events. For proper parameter identification, large field datasets would be needed. As these are usually not available, notably due to the randomness of the storm events, we thus propose a simple, robust and low-cost numerical method for the inverse modeling of the soil hydrodynamic properties. Among the methods, the variational data assimilation technique introduced by Le Dimet and Talagrand is applied. To that end, a variational data assimilation technique is implemented by applying automatic differentiation (AD) to augment computer codes with derivative computations. Note that very little effort is needed to obtain the differentiated code using the on-line Tapenade AD engine. Field data are collected for a three-layered CW located in Strasbourg (Alsace, France) at the water edge of the urban water stream Ostwaldergraben, during several months. Identification experiments are conducted by comparing measured and computed piezometric head by means of the least square objective function. The temporal variability of hydrodynamic parameter is then assessed and analyzed.

Keywords: automatic differentiation, constructed wetland, inverse method, mixed hybrid FEM, sensitivity analysis

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Authors: Tiee-Jian Wu, Chih-Yuan Hsu

Abstract:

Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.

Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method

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Authors: Phuong Nguyen, Trung Tran

Abstract:

Along with the global ongoing energy transition, Vietnam has indicated a strong commitment in the last COP events on the zero-carbon emission target. However, it is a real challenge for the nation to replace fossil-fired power plants by a significant amount of renewable energy sources (RES) while maintaining security of supply. The unpredictability and variability of RES would cause technical issues for supply-demand balancing, network congestions, system balancing, among others. It is crucial to take these into account while planning the future grid infrastructure. This study will address both generation and transmission adequacy and reveal a comprehensive analysis about the impact of ongoing energy transition on the development of Vietnam power system in 2030. This will provide insight for creating an secure, stable, and affordable pathway for the country in upcoming years.

Keywords: generation adequacy, transmission adequacy, security of supply, energy transition

Procedia PDF Downloads 50