Search results for: hazard identification

Authors: I. Sonia d’Apolito, Bianca Sisinni, Mirko Grimaldi, Barbara Gili Fivela

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The American English contrast /ɑ-ʌ/ (cop-cup) is difficult to be produced by Italian learners since they realize L2-/ɑ-ʌ/ as L1-/ɔ-a/ respectively, due to differences in phonetic-phonological systems and also in grapheme-to-phoneme conversion rules. In this paper, we try to answer the following research questions: Can a short training improve the production of English /ɑ-ʌ/ by Italian learners? Is a perceptual training better than an articulatory (ultrasound - US) training? Thus, we compare a perceptual training with an US articulatory one to observe: 1) the effects of short trainings on L2-/ɑ-ʌ/ productions; 2) if the US articulatory training improves the pronunciation better than the perceptual training. In this pilot study, 9 Salento-Italian monolingual adults participated: 3 subjects performed a 1-hour perceptual training (ES-P); 3 subjects performed a 1-hour US training (ES-US); and 3 control subjects did not receive any training (CS). Verbal instructions about the phonetic properties of L2-/ɑ-ʌ/ and L1-/ɔ-a/ and their differences (representation on F1-F2 plane) were provided during both trainings. After these instructions, the ES-P group performed an identification training based on the High Variability Phonetic Training procedure, while the ES-US group performed the articulatory training, by means of US video of tongue gestures in L2-/ɑ-ʌ/ production and dynamic view of their own tongue movements and position using a probe under their chin. The acoustic data were analyzed and the first three formants were calculated. Independent t-tests were run to compare: 1) /ɑ-ʌ/ in pre- vs. post-test respectively; /ɑ-ʌ/ in pre- and post-test vs. L1-/a-ɔ/ respectively. Results show that in the pre-test all speakers realize L2-/ɑ-ʌ/ as L1-/ɔ-a/ respectively. Contrary to CS and ES-P groups, the ES-US group in the post-test differentiates the L2 vowels from those produced in the pre-test as well as from the L1 vowels, although only one ES-US subject produces both L2 vowels accurately. The articulatory training seems more effective than the perceptual one since it favors the production of vowels in the correct direction of L2 vowels and differently from the similar L1 vowels.

Keywords: L2 vowel production, perceptual training, articulatory training, ultrasound.

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Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: Interactive dashboards, optical fibers, structural health monitoring, visual analytics.

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Authors: Ahmed F. Azmy , Amal E. Saafan, Tamer M. Essam, Magdy A. Amin, Shaban H. Ahmed

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Bacterial strains capable of degradation of malathion from the domestic sewage were isolated by an enrichment culture technique. Three bacterial strains were screened and identified as Acinetobacter baumannii (AFA), Pseudomonas aeruginosa (PS1), and Pseudomonas mendocina (PS2) based on morphological, biochemical identification and 16S rRNA sequence analysis. Acinetobacter baumannii AFA was the most efficient malathion degrading bacterium, so used for further biodegradation study. AFA was able to grow in mineral salt medium (MSM) supplemented with malathion (100 mg/l) as a sole carbon source, and within 14 days, 84% of the initial dose was degraded by the isolate measured by high performance liquid chromatography. Strain AFA could also degrade other organophosphorus compounds including diazinon, chlorpyrifos and fenitrothion. The effect of different culture conditions on the degradation of malathion like inoculum density, other carbon or nitrogen sources, temperature and shaking were examined. Degradation of malathion and bacterial cell growth were accelerated when culture media were supplemented with yeast extract, glucose and citrate. The optimum conditions for malathion degradation by strain AFA were; an inoculum density of 1.5x 10^12CFU/ml at 30°C with shaking. A specific polymerase chain reaction primers were designed manually using multiple sequence alignment of the corresponding carboxylesterase enzymes of Acinetobacter species. Sequencing result of amplified PCR product and phylogenetic analysis showed low degree of homology with the other carboxylesterase enzymes of Acinetobacter strains, so we suggested that this enzyme is a novel esterase enzyme. Isolated bacterial strains may have potential role for use in bioremediation of malathion contaminated.

Keywords: Acinetobacter baumannii, biodegradation, Malathion, organophosphate pesticides.

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Authors: K. Mohammed, M. Agarwal, J. Mewman, Y. Ren

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An optimum technic has been developed for extracting volatile organic compounds which contribute to the aroma of lime fruit (Citrus aurantifolia). The volatile organic compounds of healthy and infested lime fruit with California red scale Aonidiella aurantii were characterized using headspace solid phase microextraction (HS-SPME) combined with gas chromatography (GC) coupled flame ionization detection (FID) and gas chromatography with mass spectrometry (GC-MS) as a very simple, efficient and nondestructive extraction method. A three-phase 50/30 μm PDV/DVB/CAR fibre was used for the extraction process. The optimal sealing and fibre exposure time for volatiles reaching equilibrium from whole lime fruit in the headspace of the chamber was 16 and 4 hours respectively. 5 min was selected as desorption time of the three-phase fibre. Herbivorous activity induces indirect plant defenses, as the emission of herbivorous-induced plant volatiles (HIPVs), which could be used by natural enemies for host location. GC-MS analysis showed qualitative differences among volatiles emitted by infested and healthy lime fruit. The GC-MS analysis allowed the initial identification of 18 compounds, with similarities higher than 85%, in accordance with the NIST mass spectral library. One of these were increased by A. aurantii infestation, D-limonene, and three were decreased, Undecane, α-Farnesene and 7-epi-α-selinene. From an applied point of view, the application of the above-mentioned VOCs may help boost the efficiency of biocontrol programs and natural enemies’ production techniques.

Keywords: Lime fruit, Citrus aurantifolia, California red scale, Aonidiella aurantii, VOCs, HS-SPME/GC-FID-MS.

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Authors: S. Looser, W. Wehrmeyer

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Given the limited research on Small and Mediumsized Enterprises’ (SMEs) contribution to Corporate Social Responsibility (CSR) and even scarcer research on Swiss SMEs, this paper helps to fill these gaps by enabling the identification of supranational SME parameters. Thus, the paper investigates the current state of SME practices in Switzerland and across 15 other countries. Combining the degree to which SMEs demonstrate an explicit (or business case) approach or see CSR as an implicit moral activity with the assessment of their attributes for “variety of capitalism” defines the framework of this comparative analysis. To outline Swiss small business CSR patterns in particular, 40 SME owner-managers were interviewed. A secondary data analysis of studies from different countries laid groundwork for this comparative overview of small business CSR. The paper identifies Swiss small business CSR as driven by norms, values, and by the aspiration to contribute to society, thus, as an implicit part of the day-to-day business. Similar to most Central European, Mediterranean, Nordic, and Asian countries, explicit CSR is still very rare in Swiss SMEs. Astonishingly, also British and American SMEs follow this pattern in spite of their strong and distinctly liberal market economies. Though other findings show that nationality matters this research concludes that SME culture and an informal CSR agenda are strongly formative and superseding even forces of market economies, nationally cultural patterns, and language. Hence, classifications of countries by their market system, as found in the comparative capitalism literature, do not match the CSR practices in SMEs as they do not mirror the peculiarities of their business. This raises questions on the universality and generalisability of unmediated, explicit management concepts, especially in the context of small firms.

Keywords: CSR, comparative study, cultures of capitalism, Small and Medium-sized Enterprises.

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Authors: K. Puren, H. Coetzee, V. Roos

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Uniqueness and distinctiveness of localities (referred to as genius loci or sense of place) are important to ensure people-s identification with their locality. Existing frameworks reveals that the affective dimension of environments is rarely mentioned or explored and limited public participation was used in constructing the frameworks. This research argues that the complexity of sense of place would be recognised and appropriate planning guidelines formulated by exploring and integrating the affective dimension of a site. Aims of the research therefore are to (i) explore relational dimensions between people and a natural rural landscape, (ii) to implement a participatory approach to obtain insight into different relational dimensions, and (ii) to concretise socio-affective relational dimensions into site planning guidelines. A qualitative, interdisciplinary research approach was followed and conducted on the farm Kromdraai, Vredefort Dome World Heritage Site. In essence the first phase of the study reveals various affective responses and projections of personal meanings. The findings in phase 1 informed the second phase, to involve people from various disciplines and different involvement with the area to make visual presentations of appropriate planning and design of the site in order to capture meanings of the interactions between people and their environment. Final site planning and design guidelines were formulated, based on these. This research contributed to provide planners with new possibilities of exploring the dimensions between people and places as well as to develop appropriate methods for participation to obtain insight into the underlying meanings of sites.

Keywords: Affective dimension, Sense of place, spatialplanning, Vredefort Dome World Heritage Site.

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Authors: Yepeng Cheng, Yasuhiko Morimoto

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Customer relationship analysis is vital for retail stores, especially for supermarkets. The point of sale (POS) systems make it possible to record the daily purchasing behaviors of customers as an identification point of sale (ID-POS) database, which can be used to analyze customer behaviors of a supermarket. The customer value is an indicator based on ID-POS database for detecting the customer loyalty of a store. In general, there are many supermarkets in a city, and other nearby competitor supermarkets significantly affect the customer value of customers of a supermarket. However, it is impossible to get detailed ID-POS databases of competitor supermarkets. This study firstly focused on the customer value and distance between a customer's home and supermarkets in a city, and then constructed the models based on logistic regression analysis to analyze correlations between distance and purchasing behaviors only from a POS database of a supermarket chain. During the modeling process, there are three primary problems existed, including the incomparable problem of customer values, the multicollinearity problem among customer value and distance data, and the number of valid partial regression coefficients. The improved customer value, Huff’s gravity model, and inverse attractiveness frequency are considered to solve these problems. This paper presents three types of models based on these three methods for loyal customer classification and competitors’ influence analysis. In numerical experiments, all types of models are useful for loyal customer classification. The type of model, including all three methods, is the most superior one for evaluating the influence of the other nearby supermarkets on customers' purchasing of a supermarket chain from the viewpoint of valid partial regression coefficients and accuracy.

Keywords: Customer value, Huff's Gravity Model, POS, retailer.

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Authors: I. Ahmad, A. Hannan, S. Ahmad, M. Asif, M. F. Nawaz, M. A. Tanvir, M. F. Azhar

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During this research, a comprehensive survey of tree growing areas of Faisalabad district of Pakistan was conducted to observe the symptoms, spectrum, occurrence and severity of A. nilotica and E. camaldulensis decline. Objective of current research was to investigate specific fungal pathogens involved in decline of A. nilotica and E. camaldulensis. For this purpose, infected roots, bark, neck portion, stem, branches, leaves and infected soils were collected to identify associated fungi. Potato dextrose agar (PDA) and Czepak dox agar media were used for isolations. Identification of isolated fungi was done microscopically and different fungi were identified. During survey of urban locations of Faisalabad, disease incidence on Kikar and Eucalyptus was recorded as 3.9-7.9% and 2.6-7.1% respectively. Survey of Agroforest zones of Faisalabad revealed decline incidence on kikar 7.5% from Sargodha road while on Satiana and Jhang road it was not planted. In eucalyptus trees, 4%, 8% and 0% disease incidence was observed on Jhang road, Sargodha road and Satiana road respectively. The maximum fungus isolated from the kikar tree was Drechslera australiensis (5.00%) from the stem part. Aspergillus flavus also gave the maximum value of (3.05%) from the bark. Alternaria alternata gave the maximum value of (2.05%) from leaves. Rhizopus and Mucor spp. were recorded minimum as compared to the Drechslera, Alternaria and Aspergillus. The maximum fungus isolated from the Eucalyptus tree was Armillaria luteobubalina (5.00%) from the stem part. The other fungi isolated were Macrophamina phaseolina and A. niger.

Keywords: Decline, frequency of mycoflora, A. nilotica, E. camaldulensis, Drechslera australiensis, Armillaria luteobubalina.

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Authors: V. Churkin, M. Lopatin

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The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.

Keywords: Bass model, generalized Bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States.

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Authors: Omolola A. Tajelawi, Hari L. Garbharran

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Revenue leakages are one of the major challenges manufacturers face in production processes, as most of the input materials that should emanate as products from the lines are lost as waste. Rather than generating income from material input which is meant to end-up as products, losses are further incurred as costs in order to manage waste generated. In addition, due to the lack of a clear view of the flow of resources on the lines from input to output stage, acquiring information on the true cost of waste generated have become a challenge. This has therefore given birth to the conceptualization and implementation of waste minimization strategies by several manufacturing industries. This paper reviews the principles and applications of three environmental management accounting tools namely Activity-based Costing (ABC), Life-Cycle Assessment (LCA) and Material Flow Cost Accounting (MFCA) in the manufacturing industry and their effectiveness in curbing revenue leakages. The paper unveils the strengths and limitations of each of the tools; beaming a searchlight on the tool that could allow for optimal resource utilization, transparency in production process as well as improved cost efficiency. Findings from this review reveal that MFCA may offer superior advantages with regards to the provision of more detailed information (both in physical and monetary terms) on the flow of material inputs throughout the production process compared to the other environmental accounting tools. This paper therefore makes a case for the adoption of MFCA as a viable technique for the identification and reduction of waste in production processes, and also for effective decision making by production managers, financial advisors and other relevant stakeholders.

Keywords: MFCA, environmental management accounting, resource efficiency, waste reduction, revenue losses.

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Authors: Nazli Darkhal

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The use of gems and ornaments has been common in Iran since the beginning of history. The prosperity of the country, the wealth, and the interest of the people of this land in a luxurious and glorious life, combined with beauty, have always attracted the attention of Iranian people to gems and jewelry. Iranians are famous in the world for having a long history of collecting and recognizing precious stones. In this case, we can use the unique treasure of national jewelry. Raman spectroscopy method is one of the oscillating spectroscopy methods that is classified in the group of nondestructive study methods, and like other methods, in addition to several advantages, it also has disadvantages and problems. Micro Raman spectroscopy is one of the different types of Raman spectroscopy in which an optical microscope is combined with a Raman device to provide more capabilities and advantages than its original method. In this way, with the help of Raman spectroscopy and a light microscope, while observing more details from different parts of the historical sample, natural or artificial pigments can be identified in a small part of it. The EDX (Energy Dispersive X ray) electron microscope also functions as the basis for the interaction of the electron beam with the matter. The beams emitted from this interaction can be used to examine samples. In this article, in addition to introducing the micro-Raman spectroscopy method, studies have been conducted on the structure of three samples of existing stones in the historic citadel of Bam. Using this method of study on precious and semi-precious stones, in addition to requiring a short time, can provide us with complete information about the structure and theme of these samples. The results of experiments and gemology of the stones showed that the selected beads are agate and jasper, and they can be placed in the chalcedony group.

Keywords: Bam citadel, precious stones, semi-precious stones, Raman spectroscopy, scanning electron microscope.

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Authors: A. Ghanbari Mardasi, N. Wu, C. Wu

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In this study, a spatial wavelet-based crack localization technique for a thick beam is presented. Wavelet scale in spatial wavelet transformation is optimized to enhance crack detection sensitivity. A windowing function is also employed to erase the edge effect of the wavelet transformation, which enables the method to detect and localize cracks near the beam/measurement boundaries. Theoretical model and vibration analysis considering the crack effect are first proposed and performed in MATLAB based on the Timoshenko beam model. Gabor wavelet family is applied to the beam vibration mode shapes derived from the theoretical beam model to magnify the crack effect so as to locate the crack. Relative wavelet coefficient is obtained for sensitivity analysis by comparing the coefficient values at different positions of the beam with the lowest value in the intact area of the beam. Afterward, the optimal wavelet scale corresponding to the highest relative wavelet coefficient at the crack position is obtained for each vibration mode, through numerical simulations. The same procedure is performed for cracks with different sizes and positions in order to find the optimal scale range for the Gabor wavelet family. Finally, Hanning window is applied to different vibration mode shapes in order to overcome the edge effect problem of wavelet transformation and its effect on the localization of crack close to the measurement boundaries. Comparison of the wavelet coefficients distribution of windowed and initial mode shapes demonstrates that window function eases the identification of the cracks close to the boundaries.

Keywords: Edge effect, scale optimization, small crack locating, spatial wavelet.

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Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev

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Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.

Keywords: Lexicon of disasters, modelling, Petri nets, text annotation, social disasters.

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Authors: Lorenzo Casagrande, Antonio Bonati, Ferdinando Auricchio, Antonio Occhiuzzi

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This paper summarizes the results of a survey on smart non-structural element dynamic dissipation when installed in modern high-rise mega-frame prototypes. An innovative glazed curtain wall was designed using Shape Memory Alloy (SMA) joints in order to increase the energy dissipation and enhance the seismic/wind response of the structures. The studied buildings consisted of thirty- and sixty-storey planar frames, extracted from reference three-dimensional steel Moment Resisting Frame (MRF) with outriggers and belt trusses. The internal core was composed of a CBF system, whilst outriggers were placed every fifteen stories to limit second order effects and inter-storey drifts. These structural systems were designed in accordance with European rules and numerical FE models were developed with an open-source code, able to account for geometric and material nonlinearities. With regard to the characterization of non-structural building components, full-scale crescendo tests were performed on aluminium/glass curtain wall units at the laboratory of the Construction Technologies Institute (ITC) of the Italian National Research Council (CNR), deriving force-displacement curves. Three-dimensional brick-based inelastic FE models were calibrated according to experimental results, simulating the fac¸ade response. Since recent seismic events and extreme dynamic wind loads have generated the large occurrence of non-structural components failure, which causes sensitive economic losses and represents a hazard for pedestrians safety, a more dissipative glazed curtain wall was studied. Taking advantage of the mechanical properties of SMA, advanced smart joints were designed with the aim to enhance both the dynamic performance of the single non-structural unit and the global behavior. Thus, three-dimensional brick-based plastic FE models were produced, based on the innovated non-structural system, simulating the evolution of mechanical degradation in aluminium-to-glass and SMA-to-glass connections when high deformations occurred. Consequently, equivalent nonlinear links were calibrated to reproduce the behavior of both tested and smart designed units, and implemented on the thirty- and sixty-storey structural planar frame FE models. Nonlinear time history analyses (NLTHAs) were performed to quantify the potential of the new system, when considered in the lateral resisting frame system (LRFS) of modern high-rise MRFs. Sensitivity to the structure height was explored comparing the responses of the two prototypes. Trends in global and local performance were discussed to show that, if accurately designed, advanced materials in non-structural elements provide new sources of energy dissipation.

Keywords: Advanced technologies, glazed curtain walls, non-structural elements, seismic-action reduction, shape memory alloy.

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: O. Grinchuk, E. Motakis, V. Kuznetsov

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Sense-antisense gene pair (SAGP) is a pair of two oppositely transcribed genes sharing a common region on a chromosome. In the mammalian genomes, SAGPs can be organized in more complex sense-antisense gene architectures (CSAGA) in which at least one gene could share loci with two or more antisense partners. Many dozens of CSAGAs can be found in the human genome. However, CSAGAs have not been systematically identified and characterized in context of their role in human diseases including cancers. In this work we characterize the structural-functional properties of a cluster of 5 genes –TMEM97, IFT20, TNFAIP1, POLDIP2 and TMEM199, termed TNFAIP1 / POLDIP2 module. This cluster is organized as CSAGA in cytoband 17q11.2. Affymetrix U133A&B expression data of two large cohorts (410 atients, in total) of breast cancer patients and patient survival data were used. For the both studied cohorts, we demonstrate (i) strong and reproducible transcriptional co-regulatory patterns of genes of TNFAIP1/POLDIP2 module in breast cancer cell subtypes and (ii) significant associations of TNFAIP1/POLDIP2 CSAGA with amplification of the CSAGA region in breast cancer, (ii) cancer aggressiveness (e.g. genetic grades) and (iv) disease free patient-s survival. Moreover, gene pairs of this module demonstrate strong synergetic effect in the prognosis of time of breast cancer relapse. We suggest that TNFAIP1/ POLDIP2 cluster can be considered as a novel type of structural-functional gene modules in the human genome.

Keywords: Sense-antisense gene pair, complex genome architecture, TMEM97, IFT20, TNFAIP1, POLDIP2, TMEM199, 17q11.2, breast cancer, transcription regulation, survival analysis, prognosis.

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Authors: Mustafa Qaseem Hielat, Ahmad Mohammad Al-Shabatat

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Jordan exerts many efforts to nurture their academically gifted students in special schools since 2001. During the past nine years of launching these schools, their learning and excellence environments were believed to be distinguished compared to public schools. This study investigated the environments of gifted students compared with other non-gifted, using a survey instrument that measures the dimensions of family, peers, teachers, school- support, society, and resources –dimensions rooted deeply in supporting gifted education, learning, and achievement. A total number of 109 were selected from excellence schools for academically gifted students, and 119 non-gifted students were selected from public schools. Around 8.3% of the non-gifted students reported that they “Never" received any support from their surrounding environments, 14.9% reported “Seldom" support, 23.7% reported “ Often" support, 26.0% reported “Frequent" support, and 32.8% reported “Very frequent" support. Where the gifted students reported more “Never" support than the non-gifted did with 11.3%, “Seldom" support with 15.4%, “Often" support with 26.6%, “Frequent" support with 29.0%, and reported “Very frequent" support less than the non-gifted students with 23.6%. Unexpectedly, statistical differences were found between the two groups favoring non-gifted students in perception of their surrounding environments in specific dimensions, namely, school- support, teachers, and society. No statistical differences were found in the other dimensions of the survey, namely, family, peers, and resources. As the differences were found in teachers, school- support, and society, the nurturing environments for the excellence schools need to be revised to adopt more creative teaching styles, rich school atmosphere and infrastructures, interactive guiding for the students and their parents, promoting for the excellence environments, and re-build successful identification models. Thus, families, schools, and society should increase their cooperation, communication, and awareness of the gifted supportive environments. However, more studies to investigate other aspects of promoting academic giftedness and excellence are recommended.

Keywords: Academic giftedness, Supportive environment, Excellence schools, Gifted grouping, Gifted nurturing.

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Authors: L. Piñeiro, N. Cobas, L. Gómez-Limia, S. Martínez, I. Franco

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The swordfish (Xiphias gladius) is a large oceanic fish of high commercial value, which is widely distributed in waters of the world’s oceans. They are considered to be an important source of high quality proteins, vitamins and essential fatty acids, although only half of the population follows the recommendation of nutritionists to consume fish at least twice a week. Swordfish is consumed worldwide because of its low fat content and high protein content. It is generally sold as fresh, frozen, and as pieces or slices. The aim of this study was to evaluate the effect of salting and frying on the composition of the water-soluble vitamins (B₂, B₃, B₉ and B₁₂) and fat-soluble vitamins (A, D, and E) of swordfish. Three loins of swordfish from Pacific Ocean were analyzed. All the fishes had a weight between 50 and 70 kg and were transported to the laboratory frozen (-18 ºC). Before the processing, they were defrosted at 4 ºC. Each loin was sliced and salted in brine. After cleaning the slices, they were divided into portions (10×2 cm) and fried in olive oil. The identification and quantification of vitamins were carried out by high-performance liquid chromatography (HPLC), using methanol and 0.010% trifluoroacetic acid as mobile phases at a flow-rate of 0.7 mL min^-1. The UV-Vis detector was used for the detection of the water- and fat-soluble vitamins (A and D), as well as the fluorescence detector for the detection of the vitamin E. During salting, water and fat-soluble vitamin contents remained constant, observing an evident decrease in the values of vitamin B₂. The diffusion of salt into the interior of the pieces and the loss of constitution water that occur during this stage would be related to this significant decrease. In general, after frying water-soluble and fat-soluble vitamins showed a great thermolability with high percentages of retention with values among 50–100%. Vitamin B₃ is the one that exhibited higher percentages of retention with values close to 100%. However, vitamin B₉ presented the highest losses with a percentage of retention of less than 20%.

Keywords: Frying, HPLC, salting, swordfish, vitamins.

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Authors: B. Sanchez, D. Zambrana-Vasquez, J. Fresner, C. Krenn, F. Morea, L. Mercatelli

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Local administrations are facing established targets on sustainable development from different disciplines at the heart of different city departments. Nevertheless, some of these targets, such as CO₂ reduction, relate to two or more disciplines, as it is the case of sustainable mobility and energy plans (SUMP & SECAP/SEAP). This opens up the possibility to efficiently cooperate among different city departments and to create and develop harmonized spatial plans by using available resources and together achieving more ambitious goals in cities. The steps of the harmonization processes developed result in the identification of areas to achieve common strategic objectives. Harmonization, in other words, helps different departments in local authorities to work together and optimize the use or resources by sharing the same vision, involving key stakeholders, and promoting common data assessment to better optimize the resources. A methodology to promote resilient city planning via the harmonization of sustainable mobility and energy plans is presented in this paper. In order to validate the proposed methodology, a representative city engaged in an innovation process in efficient spatial planning is used as a case study. The harmonization process of sustainable mobility and energy plans covers identifying matching targets between different fields, developing different spatial plans with dual benefit and common indicators guaranteeing the continuous improvement of the harmonized plans. The proposed methodology supports local administrations in consistent spatial planning, considering both energy efficiency and sustainable mobility. Thus, municipalities can use their human and economic resources efficiently. This guarantees an efficient upgrade of land use plans integrating energy and mobility aspects in order to achieve sustainability targets, as well as to improve the wellbeing of its citizens.

Keywords: Harmonized planning, spatial planning, sustainable energy, sustainable mobility, SECAP, SUMP.

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Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

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Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: Modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition.

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Authors: Oluwaseun K. Oyebode, Josiah A. Adeyemo

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Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.

Keywords: Computational modelling, evolutionary algorithms, genetic programming, hydrological modelling.

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Authors: Mariana Lima, Rodrigo Silva, Victor Stange, Teodiano Bastos

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Due to the high reliability reached by DNA tests, since the 1980s this kind of test has allowed the identification of a growing number of criminal cases, including old cases that were unsolved, now having a chance to be solved with this technology. Currently, the use of genetic profiling databases is a typical method to increase the scope of genetic comparison. Forensic laboratories must process, analyze, and generate genetic profiles of a growing number of samples, which require time and great storage capacity. Therefore, it is essential to develop methodologies capable to organize and minimize the spent time for both biological sample processing and analysis of genetic profiles, using software tools. Thus, the present work aims the development of a software system solution for laboratories of forensics genetics, which allows sample, criminal case and local database management, minimizing the time spent in the workflow and helps to compare genetic profiles. For the development of this software system, all data related to the storage and processing of samples, workflows and requirements that incorporate the system have been considered. The system uses the following software languages: HTML, CSS, and JavaScript in Web technology, with NodeJS platform as server, which has great efficiency in the input and output of data. In addition, the data are stored in a relational database (MySQL), which is free, allowing a better acceptance for users. The software system here developed allows more agility to the workflow and analysis of samples, contributing to the rapid insertion of the genetic profiles in the national database and to increase resolution of crimes. The next step of this research is its validation, in order to operate in accordance with current Brazilian national legislation.

Keywords: Database, forensic genetics, genetic analysis, sample management, software solution.

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Authors: A. Abdulkadir, Y. M. Bello, A. A. Okhimamhe, H. Ibrahim, M. B. Matazu, L. S. Barau

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The increasing volume of solid waste generated, collected and disposed daily complicate adequate management of solid waste by relevant agency like Niger State Environmental Protection Agency (NISEPA). In addition, the impacts of solid waste on the natural environment and human livelihood require identification of cost-effective ways for sustainable municipal waste management in Nigeria. These signal the need for identifying environment-friendly initiative and local solution to address the problem of municipal solid waste. A research field was secured at Pago, Minna, Niger State which is located in the guinea savanna belt of Nigeria, within longitude 60 361 4311 - 4511 and latitude 90 291 37.6111 - .6211 N. Poultry droppings, decomposed household waste manure and NPK treatments were used. The experimental field was divided into three replications and four (4) treatments on each replication making a total of twelve (12) plots. The treatments were allotted using Randomized Complete Block Design (RCBD) and Data collected was analyzed using SPSS software and RCBD. The result depicts variation in plant height and number of leaves at 50% flowering; Poultry dropping records the highest height while the number of leaves for waste manure competes fairly well with NPK treatment. Similarly, the varying treatments significantly increase vegetable yield, as the control (non-treatment) records the least yield for the three vegetable samples. Adoption of this organic manure for cultivation does not only enhance environment quality and attainment of food security but will contribute to local economic development, poverty alleviation as well as social inclusion.

Keywords: Environmental issues, food security, NISEPA, solid waste.

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Authors: Giulio Nisoli, Jonas Brüngger, Karin Hostettler, Nicole Stoller, Katrin Fischer

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Technical operators in the railway domain are experts responsible for the supervisory control of the railway power grid as well as of the railway tunnels. The technical systems used to master these demanding tasks are constantly increasing in their degree of automation. It becomes therefore difficult for technical operators to maintain the control over the technical systems and the processes of their job. In particular, the operators must have the necessary experience and knowledge in dealing with a malfunction situation or unexpected event. For this reason, it is of growing importance that the skills relevant for the execution of the job are maintained and further developed beyond the basic training they receive, where they are educated in respect of technical knowledge and the work with guidelines. Training methods aimed at improving the cognitive skills needed by technical operators are still missing and must be developed. Goals of the present study were to identify which are the relevant cognitive skills of technical operators in the railway domain and to define which topics should be addressed by the training of these skills. Observational interviews were conducted in order to identify the main tasks and the organization of the work of technical operators as well as the technical systems used for the execution of their job. Based on this analysis, the most demanding tasks of technical operators could be identified and described. The cognitive skills involved in the execution of these tasks are those, which need to be trained. In order to identify and analyze these cognitive skills a cognitive task analysis (CTA) was developed. CTA specifically aims at identifying the cognitive skills that employees implement when performing their own tasks. The identified cognitive skills of technical operators were summarized and grouped in training topics. For every training topic, specific goals were defined. The goals regard the three main categories; knowledge, skills and attitude to be trained in every training topic. Based on the results of this study, it is possible to develop specific training methods to train the relevant cognitive skills of the technical operators.

Keywords: Cognitive skills, cognitive task analysis, technical operators in the railway domain, training topics.

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Authors: N. Umasuthan, S. D. N. K. Bathige, W. S. Thulasitha, I. Whang, J. Lee

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The MyD88 is an evolutionarily conserved host-expressed adaptor protein that is essential for proper TLR/ IL1R immune-response signaling. A previously identified complete cDNA (1626 bp) of OfMyD88 comprised an ORF of 867 bp encoding a protein of 288 amino acids (32.9 kDa). The gDNA (3761 bp) of OfMyD88 revealed a quinquepartite genome organization composed of 5 exons (with the sizes of 310, 132, 178, 92 and 155 bp) separated by 4 introns. All the introns displayed splice signals consistent with the consensus GT/AG rule. A bipartite domain structure with two domains namely death domain (24-103) coded by 1^st exon, and TIR domain (151-288) coded by last 3 exons were identified through in silico analysis. Moreover, homology modeling of these two domains revealed a similar quaternary folding nature between human and rock bream homologs. A comprehensive comparison of vertebrate MyD88 genes showed that they possess a 5-exonic structure.In this structure, the last three exons were strongly conserved, and this suggests that a rigid structure has been maintained during vertebrate evolution.A cluster of TATA box-like sequences were found 0.25 kb upstream of cDNA starting position. In addition, putative 5'-flanking region of OfMyD88 was predicted to have TFBS implicated with TLR signaling, including copies of NFkB1, APRF/ STAT3, Sp1, IRF1 and 2 and Stat1/2. Using qPCR technique, a ubiquitous mRNA expression was detected in liver and blood. Furthermore, a significantly up-regulated transcriptional expression of OfMyD88 was detected in head kidney (12-24 h; >2-fold), spleen (6 h; 1.5-fold), liver (3 h; 1.9-fold) and intestine (24 h; ~2-fold) post-Fla challenge. These data suggest a crucial role for MyD88 in antibacterial immunity of teleosts.

Keywords: MyD88, Innate immunity, Flagellin, Genomic analysis.

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

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The automatic extraction of shipping routes is advantageous for intelligent traffic management systems to identify events and support decision-making in maritime surveillance. At present, there is a high demand for the extraction of maritime traffic networks that resemble the real traffic of vessels accurately, which is valuable for further analytical processing tasks for vessels trajectories (e.g., naval routing and voyage planning, anomaly detection, destination prediction, time of arrival estimation). With the help of big data and processing huge amounts of vessels’ trajectory data, it is possible to learn these shipping routes from the navigation history of past behaviour of other, similar ships that were travelling in a given area. In this paper, we propose a spatial clustering model of vessels’ trajectories (SPTCLUST) to extract spatial representations of sailing routes from historical Automatic Identification System (AIS) data. The whole model consists of three main parts: data preprocessing, path finding, and route extraction, which consists of clustering and representative trajectory extraction. The proposed clustering method provides techniques to overcome the problems of: (i) optimal input parameters selection; (ii) the high complexity of processing a huge volume of multidimensional data; (iii) and the spatial representation of complete representative trajectory detection in the context of trajectory clustering algorithms. The experimental evaluation showed the effectiveness of the proposed model by using a real-world AIS dataset from the Port of Halifax. The results contribute to further understanding of shipping route patterns. This could aid surveillance authorities in stable and sustainable vessel traffic management.

Keywords: Vessel trajectory clustering, trajectory mining, Spatial Clustering, marine intelligent navigation, maritime traffic network extraction, sdailing routes extraction.

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Authors: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

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In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: Early stage prediction, heart rate variability, linear and non linear analysis, sudden cardiac death.

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Authors: Mohamed K. Shahin, Ahmed M. Badawi, Mohamed E. M. Rasmy

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Prior research evidenced that unimodal biometric systems have several tradeoffs like noisy data, intra-class variations, restricted degrees of freedom, non-universality, spoof attacks, and unacceptable error rates. In order for the biometric system to be more secure and to provide high performance accuracy, more than one form of biometrics are required. Hence, the need arise for multimodal biometrics using combinations of different biometric modalities. This paper introduces a multimodal biometric system (MMBS) based on fusion of whole dorsal hand geometry and fingerprints that acquires right and left (Rt/Lt) near-infra-red (NIR) dorsal hand geometry (HG) shape and (Rt/Lt) index and ring fingerprints (FP). Database of 100 volunteers were acquired using the designed prototype. The acquired images were found to have good quality for all features and patterns extraction to all modalities. HG features based on the hand shape anatomical landmarks were extracted. Robust and fast algorithms for FP minutia points feature extraction and matching were used. Feature vectors that belong to similar biometric traits were fused using feature fusion methodologies. Scores obtained from different biometric trait matchers were fused using the Min-Max transformation-based score fusion technique. Final normalized scores were merged using the sum of scores method to obtain a single decision about the personal identity based on multiple independent sources. High individuality of the fused traits and user acceptability of the designed system along with its experimental high performance biometric measures showed that this MMBS can be considered for med-high security levels biometric identification purposes.

Keywords: Unimodal, Multi-Modal, Biometric System, NIR Imaging, Dorsal Hand Geometry, Fingerprint, Whole Hands, Feature Extraction, Feature Fusion, Score Fusion

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Authors: Bibiana Hlebova

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The Slovak Republic is a democratic and plural society consisting of people differing in language and culture, and its citizens should already be well prepared for the coexistence of multiple nations, nationalities or ethnic groups. Reflection on culture, art and literature of the Roma minority has taken on a new dimension in Slovakia in the past two decades when it comes to social, cultural and arts integration of this ethnic group with the plural society. Non-Roma view Roma as a specific ethnic group with their own culture, language, customs and traditions, social norms and coexistence that has retained archetypal qualities of Roma identity (romipen) in their real lives as well as in the literary world. Roma characters in works of art are specific and distinguishable from other literary characters simply by being Roma, that is, of a different origin and social status, they represent a different way of life, a distinctive hierarchy of values. The portrayal of Roma and the life of Roma ethnic group in the most dominant genre of Roma literature for children and youth, a Roma fairy tale (paramisi), can work as a suitable means to learn about, accept and tolerate the otherness of Roma in the conditions of school inclusion of students coming from the Roma ethnic group, and to support their identification with their own ethnic group and its cultural traditions. The paper aims to point out not only the specific nature of Roma identity (romipen) through the selected Roma fairy tale (paramisa) – Children of the Sun, but also the diversity of its uses in the educational process within primary education of pupils at elementary schools, advocating the philosophy of inclusive education. Through the suggestions of multi-cultural, emotional, and language and communication education of pupils through the work with the selected Roma fairy tale (paramisa), the author is exploring ways to overcome the issues stemming from the coexistence of Roma and Non-Roma pupils, which are burdened with prejudice, intolerance, aggression and racism on both sides, in the education process.

Keywords: Inclusive education, otherness, Roma Pupils, Roma identity, Roma fairy tale.

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Authors: Aurelija Burinskienė, Dalė Dzemydienė, Arūnas Miliauskas

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This research aims at developing the approach for more effective freight delivery and transportation process management. The road congestions and the identification of causes are important, as well as the context information recognition and management. The measure of many parameters during the transportation period and proper control of driver work became the problem. The number of vehicles per time unit passing at a given time and point for drivers can be evaluated in some situations. The collection of data is mainly used to establish new trips. The flow of the data is more complex in urban areas. Herein, the movement of freight is reported in detail, including the information on street level. When traffic density is extremely high in congestion cases, and the traffic speed is incredibly low, data transmission reaches the peak. Different data sets are generated, which depend on the type of freight delivery network. There are three types of networks: long-distance delivery networks, last-mile delivery networks and mode-based delivery networks; the last one includes different modes, in particular, railways and other networks. When freight delivery is switched from one type of the above-stated network to another, more data could be included for reporting purposes and vice versa. In this case, a significant amount of these data is used for control operations, and the problem requires an integrated methodological approach. The paper presents an approach for providing e-services for drivers by including the assessment of the multi-component infrastructure needed for delivery of freights following the network type. The construction of such a methodology is required to evaluate data flow conditions and overloads, and to minimize the time gaps in data reporting. The results obtained show the possibilities of the proposing methodological approach to support the management and decision-making processes with functionality of incorporating networking specifics, by helping to minimize the overloads in data reporting.

Keywords: Transportation networks, freight delivery, data flow, monitoring, e-services.

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