Search results for: image dataset

Authors: R. Hasterok, A. Betekhtin, N. Borowska, A. Braszewska-Zalewska, E. Breda, K. Chwialkowska, R. Gorkiewicz, D. Idziak, J. Kwasniewska, M. Kwasniewski, D. Siwinska, A. Wiszynska, E. Wolny

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In contrast to animals, the organisation of plant genomes at the cytomolecular level is still relatively poorly studied and understood. However, the Brachypodium genus in general and B. distachyon in particular represent exceptionally good model systems for such study. This is due not only to their highly desirable ‘model’ biological features, such as small nuclear genome, low chromosome number and complex phylogenetic relations, but also to the rapidly and continuously growing repertoire of experimental tools, such as large collections of accessions, WGS information, large insert (BAC) libraries of genomic DNA, etc. Advanced cytomolecular techniques, such as fluorescence in situ hybridisation (FISH) with evermore sophisticated probes, empowered by cutting-edge microscope and digital image acquisition and processing systems, offer unprecedented insight into chromatin organisation at various phases of the cell cycle. A good example is chromosome painting which uses pools of chromosome-specific BAC clones, and enables the tracking of individual chromosomes not only during cell division but also during interphase. This presentation outlines the present status of molecular cytogenetic analyses of plant genome structure, dynamics and evolution using B. distachyon and some of its relatives. The current projects focus on important scientific questions, such as: What mechanisms shape the karyotypes? Is the distribution of individual chromosomes within an interphase nucleus determined? Are there hot spots of structural rearrangement in Brachypodium chromosomes? Which epigenetic processes play a crucial role in B. distachyon embryo development and selective silencing of rRNA genes in Brachypodium allopolyploids? The authors acknowledge financial support from the Polish National Science Centre (grants no. 2012/04/A/NZ3/00572 and 2011/01/B/NZ3/00177)

Keywords: Brachypodium, B. distachyon, chromosome, FISH, molecular cytogenetics, nucleus, plant genome organisation

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Authors: Abdul Rahman Chamseddine

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Tawfiq al-Hakim remains one of the most prominent playwrights in his native in Egypt, and in the broader Arab world. His works, at the time of their release, drew international attention and acclaim. His first 1933 masterpiece Ahl al-Kahf (The People of the Cave) especially, garnered fame and recognition in both Europe and the Arab world. Borrowing its title from the Qur’anic Sura, al-Hakim’s play relays the untold story of the life of those 'three saints' after they wake up from their prolonged sleep. The playwright’s selection of topics upon which to base his works displays a deep appreciation of Arabic and Islamic heritage. Al-Hakim was clearly influenced by Islam, to such a degree that he wrote the biography of the Prophet Muhammad in 1936 very early in his career. Knowing that Al-Hakim was preceded by many poets and creative writers in writing the Prophet Muhammad’s biography. Notably like Al-Barudi, Ahmad Shawqi, Haykal, Al-‘Aqqad, and Taha Husayn who have had their own ways in expressing their views of the Prophet Muhammad. The attempt to understand the concern of all those renaissance men and others in the person of the Prophet would be indispensable in this study. This project will examine the reasons behind al-Hakim’s choice to draw upon these particular texts, embedded as they are in the context of Arabic and Islamic heritage, and how the use of traditional texts serves his contemporary goals. The project will also analyze the image of Islam in al-Hakim’s imagination. Elsewhere, he envisions letters or conversations between God and himself, which offers a window into understanding the powerful impact of the Divine on Tawfiq al-Hakim, one that informs his literature and merits further scholarly attention. His works occupying a major rank in Arabic literature, does not reveal Al-Hakim solely but the unquestioned assumptions operative in the life of his community, its mental make-up and its attitudes. Furthermore, studying the reception of works that touch on sensitive issues, like writing a letter to God, in Al-Hakim’s historical context would be of a great significance in the process of comprehending the mentality of the Muslim community at that time.

Keywords: Arabic language, Arabic literature, Arabic theology, modern Arabic literature

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Authors: Antonio Marques, Graça Guedes

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The Portuguese footwear industry had in the last five years a remarkable performance in the exportation values, the trade balance and others economic indicators. After a long period of difficulties and with a strong reduction of companies and employees since 1994 until 2009, the Portuguese footwear industry changed the strategy and is now a success case between the international players of footwear. Only the Italian industry sells footwear with a higher value than the Portuguese and the distance between them is decreasing year by year. This paper analyses how the Portuguese footwear companies innovate and make innovation, according the classification proposed by the Oslo Manual. Also analyses the strategy follow in the innovation process, as suggested by Freeman and Soete, and shows the linkage between the type of innovation and the strategy of innovation. The research methodology was qualitative and the strategy for data collection was the case study. The qualitative data will be analyzed with the MAXQDA software. The economic results of the footwear companies studied shows differences between all of them and these differences are related with the innovation strategy adopted. The companies focused in product and marketing innovation, oriented to their target market, have higher ratios “turnover per worker” than the companies focused in process innovation. However, all the footwear companies in this “low-tech” industry create value and contribute to a positive foreign trade of 1.310 million euros in 2013. The growth strategies implemented has the participation of the sectorial organizations in several innovative projects. And it’s obvious that cooperation between all of them is a critical element to the performance achieved by the companies and the innovation observed. Can conclude that the Portuguese footwear sector has in the last years an excellent performance (economic results, exportation values, trade balance, brands and international image) and his performance is strongly related with the strategy in innovation followed, the type of innovation and the networks in the cluster. A simplified model, called “Ace of Diamonds”, is proposed by the authors and explains the way how this performance was reached by the seven companies that participate in the study (two of them are the leaders in the setor), and if this model can be used in others traditional and “low-tech” industries.

Keywords: footwear, innovation, “low-tech” industry, Oslo manual

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Authors: KuiDong Kang, Hye Bin Yim, Su Ah Kim

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Purpose: Tectorigenin is an isoflavone derived from the rhizome of Belamacanda chinensis. In this study, oxygen-induced retinopathy was used to characterize the anti-angiogenic properties of tectorigenin in mice. Methods: ICR neonatal mice were exposed to 75% oxygen from postnatal day P7 until P12 and returned to room air (21% oxygen) for five days (P12 to P17). Mice were subjected to daily intraperitoneal injection of tectorigenin (1 mg/kg, 10 mg/kg) and vehicle from P12 to P17. Retro-orbital injection of FITC-dextran was performed and retinal flat mounts were viewed by fluorescence microscopy. The Central avascular area was quantified from the digital images in a masked fashion using image analysis software (NIH ImageJ). Neovascular tufts were quantified by using SWIFT_NV and neovascular lumens were quantified from a histologic section in a masked fashion. Immunohistochemistry and Western blot analysis were also performed to demonstrate the anti-angiogenic activity of this compound in vivo. Results: In the retina of tectorigenin injected mouse (10mg/kg), the central non-perfusion area was significantly decreased compared to the vehicle injected group (1.76±0.5 mm2 vs 2.85±0.6 mm2, P<0.05). In vehicle-injected group, 33.45 ± 5.51% of the total retinal area was avascular, whereas the retinas of pups treated with high-dose (10 mg/kg) tectorigenin showed avascular retinal areas of 21.25 ±4.34% (P<0.05). High dose of tectorigenin also significantly reduced the number of vascular lumens in the histologic section. Tectorigenin (10 mg/kg) significantly reduced the expression of vascular endothelial growth factor (VEGF), matrix metalloproteinase-2 (MMP-2), MMP-9, and angiotensin II compared to the vehicle injected group. Tectorigenin did not affect CD31 abundance at any tested dose. Conclusions: Our results show that tectorigenin possesses powerful anti-angiogenic properties and can attenuate new vessel formation in the retina after systemic administration. These results imply that this compound can be considered as a candidate substance for therapeutic inhibition of retinal angiogenesis.

Keywords: tectorigenin, anti-angiogenic, retinopathy, Belamacanda chinensis

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Warnakulasuriya Arachichige Malisha Ann Rosary Fernando, Udalamatta Gamage Omila Chalanka Jinadasa, Bihini Pabasara Amandi Amarasinghe, Manul Thisuraka Mandalawatta, Uthpala Samarakoon, Manori Gamage

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The surge in sexually transmitted diseases (STDs) has become a critical public health crisis demanding urgent attention and action. Like many other nations, Sri Lanka is grappling with a significant increase in STDs due to a lack of education and awareness regarding their dangers. Presently, the available applications for tracking and managing STDs cover only a limited number of easily detectable infections, resulting in a significant gap in effectively controlling their spread. To address this gap and combat the rising STD rates, it is essential to leverage technology and data. Employing technology to enhance the tracking and management of STDs is vital to prevent their further propagation and to enable early intervention and treatment. This requires adopting a comprehensive approach that involves raising public awareness about the perils of STDs, improving access to affordable healthcare services for early detection and treatment, and utilizing advanced technology and data analysis. The proposed mobile application aims to cater to a broad range of users, including STD patients, recovered individuals, and those unaware of their STD status. By harnessing cutting-edge technologies like image detection, symptom-based identification, prevention methods, doctor and clinic recommendations, and virtual counselor chat, the application offers a holistic approach to STD management. In conclusion, the escalating STD rates in Sri Lanka and across the globe require immediate action. The integration of technology-driven solutions, along with comprehensive education and healthcare accessibility, is the key to curbing the spread of STDs and promoting better overall public health.

Keywords: STD, machine learning, NLP, artificial intelligence

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Authors: Shagufta Tazin Shathy, Mohammad Imam Hasan Reza

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Fragmentation due to urbanization and agricultural expansion has become the main reason for destruction of forest area and loss of biodiversity particularly in the developing world. At present, the world is experiencing the largest wave of urban growth in human history, and it is estimated that this influx will be mainly taking place in developing world. Therefore, study on urban fragmentation is vital for a sustainable urban development. Landscape fragmentation is one of the most important conservation issues in the last few decades. Habitat fragmentation due to landscape alteration has caused habitat isolation, destruction in ecosystem pattern and processes. Thus, this research analyses the spatial and temporal extent of urban fragmentation using landscape indices in the Kuala Lumpur (KL) – the capital and most populous city in Malaysia. The objective of this study is to examine the urban fragmentation index in KL city. Fragmentation metrics used in the study are: a) Urban landscape ratio (the ratio of urban landscape area and build up area), b) Infill (development that occurred within urbanized open space), and c) Extension (development of exterior open space). After analyzing all three metrics, these are calculated for the combined urban fragmentation index (UFI). In this combined index, all three metrics are given an equal weight. Land cover/ land use maps of the year 1996 and 2005 have been developed from the Landsat TM 30 m resolution satellite image. The year 1996 is taken as a reference year to analyze the changes. The UFI calculated for the year of 1996 and2005 found that the KL city has undergone rapid landscape changes destructing forest ecosystem adversely. Increasing UFI for the year of 1996 compared to 2005 indicates that the developmental activities have been occupying open spaces and fragmenting natural lands and forest. This index can be implemented in other unplanned and rapidly urbanizing Asian cities for example Dhaka and Delhi to calculate the urban fragmentation rate. The findings from the study will help the stakeholders and urban planners for a sustainable urban management planning in this region.

Keywords: GIS, index, sustainable urban management, urbanization

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Authors: Hasan Ziari, Hassan Fazaeli, Seyed Javad Vaziri Kang Olyaei, Asma Sadat Dabiri

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The presence of cracks in concrete pavements is a place for the ingression of corrosive substances, acids, oils, and water into the pavement and reduces its long-term durability and level of service. One of the causes of early cracks in concrete pavements is the plastic shrinkage. This shrinkage occurs due to the formation of negative capillary pressures after the equilibrium of the bleeding and evaporation rates at the pavement surface. These cracks form if the tensile stresses caused by the restrained shrinkage exceed the tensile strength of the concrete. Different climate conditions change the rate of evaporation and thus change the balance time of the bleeding and evaporation, which changes the severity of cracking in concrete. The present study examined the relationship between the balance time of bleeding and evaporation and the area of cracking in the concrete slabs using the standard method ASTM C1579 in 27 different environmental conditions by using continuous video recording and digital image analyzing. The results showed that as the evaporation rate increased and the balance time decreased, the crack severity significantly increased so that by reducing the balance time from the maximum value to its minimum value, the cracking area increased more than four times. It was also observed that the cracking area- balance time curve could be interpreted in three sections. An examination of these three parts showed that the combination of climate conditions has a significant effect on increasing or decreasing these two variables. The criticality of a single factor cannot cause the critical conditions of plastic cracking. By combining two mild environmental factors with a severe climate factor (in terms of surface evaporation rate), a considerable reduction in balance time and a sharp increase in cracking severity can be prevented. The results of this study showed that balance time could be an essential factor in controlling and predicting plastic shrinkage cracking in concrete pavements. It is necessary to control this factor in the case of constructing concrete pavements in different climate conditions.

Keywords: bleeding and cracking severity, concrete pavements, climate conditions, plastic shrinkage

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Authors: Antoifi Abdoulhalik, Ashraf Ahmed

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The ever growing threat of saltwater intrusion has prompted the need to further advance the understanding of underlying processes related to SWI for effective water resource management. While research efforts have mainly been focused on steady state analysis, studies on the transience of saltwater intrusion mechanism remain very scarce and studies considering transient SWI in heterogeneous medium are, as per our knowledge, simply inexistent. This study provides for the first time a quantitative analysis of the effect of both inland and coastal water level changes on the transition zone under transient conditions in layered coastal aquifer. In all, two sets of four experiments were completed, including a homogeneous case, and four layered cases: case LH and case HL presented were two bi-layered scenarios where a low K layer was set at the top and the bottom, respectively; case HLH and case LHL presented two stratified aquifers with High K–Low K–High K and Low K–High K– Low K pattern, respectively. Experimental automated image analysis technique was used here to quantify the main SWI parameters under high spatial and temporal resolution. The findings of this study provide an invaluable insight on the underlying processes responsible of transition zone dynamics in coastal aquifers. The results show that in all the investigated cases, the width of the transition zone remains almost unchanged throughout the saltwater intrusion process regardless of where the boundary change occurs. However, the results demonstrate that the width of the transition zone considerably increases during the retreat, with largest amplitude observed in cases LH and LHL, where a low K was set at the top of the system. In all the scenarios, the amplitude of widening was slightly smaller when the retreat was prompted by instantaneous drop of the saltwater level than when caused by inland freshwater rise, despite equivalent absolute head change magnitude. The magnitude of head change significantly caused larger widening during the saltwater wedge retreat, while having no impact during the intrusion phase.

Keywords: freshwater-saltwater transition-zone dynamics, heterogeneous coastal aquifers, laboratory experiments, transience seawater intrusion

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Authors: Evangelia-Matroni Tomara

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This thesis answers the question whether the media representations and reporting in 2015-2016 - especially, after the image of the drowned three-year-old Syrian boy in the Mediterranean Sea which made global headlines in the beginning of September 2015 -, the European Commission regulatory sources material and related reporting, have the power to challenge the conceptualization of humanitarianism or even redefine it. The theoretical foundations of the thesis are based on humanitarianism and its core definitions, the power of media representations and the relative portrayal of migrants, refugees and/or asylum seekers, as well as the dominant migration discourse and EU migration governance. Using content analysis for the media portrayal of migrants (436 newspaper articles) and qualitative content analysis for the European Commission Communication documents from May 2015 until June 2016 that required various depths of interpretation, this thesis allowed us to revise the concept of humanitarianism, realizing that the current crisis may seem to be a turning point for Europe but is not enough to overcome the past hostile media discourses and suppress the historical perspective of security and control-oriented EU migration policies. In particular, the crisis helped to shift the intensity of hostility and the persistence in the state-centric, border-oriented securitization in Europe into a narration of victimization rather than threat where mercy and charity dynamics are dominated and into operational mechanisms, noting the emergency of immediate management of the massive migrations flows, respectively. Although, the understanding of a rights-based response to the ongoing migration crisis, is being followed discursively in both political and media stage, the nexus described, points out that the binary between ‘us’ and ‘them’ still exists, with only difference that the ‘invaders’ are now ‘pathetic’ but still ‘invaders’. In this context, the migration crisis challenges the concept of humanitarianism because rights dignify migrants as individuals only in a discursive or secondary level while the humanitarian work is mostly related with the geopolitical and economic interests of the ‘savior’ states.

Keywords: European Union politics, humanitarianism, immigration, media representation, policy-making, refugees, security studies

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Authors: Panatda Intanin, Sangutid Thongsawad, Chirapha Tannanonta, Todsaporn Fuangrod

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Stereotactic radiosurgery (SRS) is a highly precision delivery technique that requires comprehensive quality assurance (QA) tests prior to treatment delivery. An isocenter of delivery beam plays a critical role that affect the treatment accuracy. The uncertainty of isocenter is traditionally accessed using circular cone equipment, Winston-Lutz (WL) phantom and film. This technique is considered time consuming and highly dependent on the observer. In this work, the development of multileaf collimator (MLC)-based isocenter verification tool using electronic portal imaging device (EPID) was proposed and evaluated. A mechanical isocenter alignment with ball bearing diameter 5 mm and circular cone diameter 10 mm fixed to gantry head defines the radiation field was set as the conventional WL test method. The conventional setup was to compare to the proposed setup; using MLC (10 x 10 mm) to define the radiation filed instead of cone. This represents more realistic delivery field than using circular cone equipment. The acquisition from electronic portal imaging device (EPID) and radiographic film were performed in both experiments. The gantry angles were set as following: 0°, 90°, 180° and 270°. A software tool was in-house developed using MATLAB/SIMULINK programming to determine the centroid of radiation field and shadow of WL phantom automatically. This presents higher accuracy than manual measurement. The deviation between centroid of both cone-based and MLC-based WL tests were quantified. To compare between film and EPID image, the deviation for all gantry angle was 0.26±0.19mm and 0.43±0.30 for cone-based and MLC-based WL tests. For the absolute deviation calculation on EPID images between cone and MLC-based WL test was 0.59±0.28 mm and the absolute deviation on film images was 0.14±0.13 mm. Therefore, the MLC-based isocenter verification using EPID present high sensitivity tool for SRS QA.

Keywords: isocenter verification, quality assurance, EPID, SRS

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Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

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Authors: Masayuki Mori

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This study investigates the relationship between teachers’ perceptions of the usability of classroom space and various elements, including both physical and non-physical, of classroom environments. With the introduction of the GIGA School funding program in Japan in 2019, understanding its impact on learning in classroom space is crucial. The program enabled local educational authorities (LEA) to make it possible to provide one PC/tablet for each student of both elementary and junior high schools. Moreover, at the same time, the program also supported LEA to purchase other electronic devices for educational purposes such as electronic whiteboards, large displays, and real image projectors. A nationwide survey was conducted using random sampling methodology among 100 junior high schools to collect data on classroom space. Of those, 60 schools responded to the survey. The survey covered approximately fifty items, including classroom space size, class size, and educational electronic devices owned. After the data compilation, statistical analysis was used to identify correlations between the variables and to explore the extent to which classroom environment elements influenced teachers’ perceptions. Furthermore, decision tree analysis was applied to visualize the causal relationships between the variables. The findings indicate a significant negative correlation between class size and teachers’ evaluation of usability. In addition to the class size, the way students stored their belongings also influenced teachers’ perceptions. As for the placement of educational electronic devices, the installation of a projector produced a small negative correlation with teachers’ perceptions. The study suggests that while the GIGA School funding program is not significantly influential, traditional educational conditions such as class size have a greater impact on teachers’ perceptions of the usability of classroom space. These results highlight the need for awareness and strategies to integrate various elements in designing the learning environment of the classroom for teachers and students to improve their learning experience.

Keywords: classroom space, GIGA School, questionnaire survey, teachers’ perceptions

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Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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Authors: Daan F. Oostveen

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‘Religion’ as a term is not native to the Global East. The concept ‘religion’ is both understood in its meaning of ‘religious traditions’, commonly referring to the ‘World Religions’ and in its adjective meaning ‘the religious’ or ‘religiosity’ as a separate domain of human culture, commonly contrasted to the secular. Though neither of these understandings are native to the historical worldviews of East Asia, their development in modern Western scholarship has had an enormous impact on the self-understanding of cultural diversity in the Global East as well. One example is the identification and therefore elevation to the status of World Religion of ‘Buddhism’ which connected formerly dispersed religious practices throughout the Global East and subsumed them under this powerful label. On the other hand, we see how popular religiosity, shamanism and hybrid cultural expressions have become excluded from genuine religion; this had an immense impact on the sense of legitimacy of these practices, which became sometimes labeled as superstition are rejected as magic. Our theoretical frameworks on religion in the Global East do not always consider the complex power dynamics between religious actors, both elites and lay expressions of religion in everyday life, governments and religious studies scholars. In order to get a clear image of how religiosity functions in the context of the Global East, we have to take into account these power dynamics. What is important in particular is the issue of religious identity or absence of religious identity. The self-understanding of religious actors in the Global East is often very different from what scholars of religion observe. Religious practice, from an etic perspective, is often unrelated to religious identification from an emic perspective. But we also witness the rise of Christian churches in the Global East, in which religious identity and belonging does play a pivotal role. Finally, religion in the Global East has since the beginning of the 20th Century been conceptualized as the ‘other’ or republicanism or Marxist-Maoist ideology. It is important not to deny the key role of colonial thinking in the process of religion formation in the Global East. In this paper, it is argued that religious realities constituted emerging as a result from our theory of religion, and that these religious realities in turn inform our theory. Therefore, the relationship between phenomenology of religion and theory of religion can never be disentangled. In fact, we have to acknowledge that our conceptualizations of religious diversity are always already influenced by our valuation of those cultural expressions that we have come to call ‘religious’.

Keywords: global east, religion, religious belonging, secularity

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Authors: Sudeshna Sengupta

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Women’s work lives weave a complex fabric of myriad work relations and complex structures. Lives, when seen from the lens of work, is a saga of conjugated oppression by intertwined structures that are vertically and horizontally interwoven in a very complex manner. Women interact with multiple institutions through their work. The interactions and interplay of institutions shape their organization of work. They intersperse productive work with reproductive work, unpaid economic activities with unpaid care work, and all kinds of activities with leisure and self-care. The proposed paper intends to understand how women working as home-based workers in the National Capital Region (NCR) of India are organizing their everyday work, and how the organization of work is influenced by the interplay of structures. Situating itself in a multidisciplinary theoretical framework, this paper brings out how the gendering of work is playing out in the political, economic and social domain and shaping the work-life within the family, and in the paid workspace. The paper will use a primary data source, which is qualitative in nature. It will comprise 15 qualitative interviews of women home-based workers from the National Capital Region. The research uses a life history approach. The sampling was purposive using snowballing as a method. The dataset is part of the primary data (qualitative) collected for the ongoing Ph.D. work in Gender Studies at Ambedkar University Delhi. The home-based workers interviewed were in “non-factory” wage relations based on piece rates with flexible working hours. Their workplaces were their own homes with no spatial divide between living spaces and workspaces. Home-based workers were recognized as a group in the domain of labor economics in the 1980s. When menial work was cheaper than machine work, the capital owners preferred to outsource work as home-based work to women. These production spaces are fragmented and the identity of gender is created within labor processes to favor material accumulation. Both the employers and employees acknowledged the material gain of the capital owner when work was subcontracted to women at home. Simultaneously the market reinforced women’s reproductive role by conforming to patriarchal ideology. The contractors played an important role in implementing localized control on workers and also in finding workers for fragmented, gendered production processes. Their presence helped the employers in bringing together multiple forms of oppression that ranged from creating a structure to flout laws by creating shadow employers. It created an intertwined social and economic structure as well as a workspace where the line between productive and reproductive work gets blurred. The state invisibilized itself either by keeping the sector out of the domain of laws or by not implementing its own laws regulating working conditions or social security. It allowed the local hierarchy to function and define localized working conditions. The productive reproductive continuum reveals a labor control that influenced both the productive and reproductive work of women.

Keywords: informal sector, paid work, women workers, labor processes

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Authors: Pulari C. Milu Maria Anto

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Background: Cognitive Rehabilitation/Retraining has been variously used in the research literature to represent non-pharmacological interventions that target the cognitive impairments with the goal of ameliorating cognitive function and functional behaviors to optimize the quality of life. Along with adult’s cognitive impairments, the need to address acquired cognitive impairments (due to any chronic illnesses like CHD - congenital heart diseases or ALL - Acute Lymphoblastic Leukemia) among child populations is inevitable. Also, it has to be emphasized as same we consider the cognitive impairments seen in the children having neurodevelopmental disorders. Methods: All published brain image studies (Hermann, B. et al,2002, Khalil, A. et al., 2004, Follin, C. et al, 2016, etc.) and studies emphasizing cognitive impairments in attention, memory, and/or executive function and behavioral aspects (Henkin, Y. et al,2007, Bellinger, D. C., & Newburger, J. W. (2010), Cheung, Y. T., et al,2016, that could be identified were reviewed. Based on a systematic review of the literature from (2000 -2021) different brain imaging studies, increased risk of neuropsychological and psychosocial impairments are briefly described. Clinical and research gap in the area is discussed. Results:30 papers, both Indian studies and foreign publications (Sage journals, Delhi psychiatry journal, Wiley Online Library, APA PsyNet, Springer, Elsevier, Developmental medicine, and child neurology), were identified. Conclusions: In India, a very limited number of brain imaging studies and neuropsychological studies have done by indicating the cognitive deficits of a child having or undergone chronic illness. None of the studies have emphasized the relevance nor the need of implementingCR among such children, even though its high time to address but still not established yet. The review of the current evidence is to bring out an insight among rehabilitation professionals in establishing a child specific CR and to publish new findings regarding the implementation of CR among such children. Also, this study will be an awareness on considering cognitive aspects of a child having acquired cognitive deficit (due to chronic illness), especially during their critical developmental period.

Keywords: cognitive rehabilitation, neuropsychological impairments, congenital heart diseases, acute lymphoblastic leukemia, epilepsy, and neuroplasticity

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Authors: Elmira Solati, Atousa Mehrani, Davoud Dorranian

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Generation of ZnO-Au nanocomposite under laser irradiation of a mixture of the ZnO and Au colloidal suspensions are experimentally investigated. In this work, firstly ZnO and Au nanoparticles are prepared by pulsed laser ablation of the corresponding metals in water using the 1064 nm wavelength of Nd:YAG laser. In a second step, the produced ZnO and Au colloidal suspensions were mixed in different volumetric ratio and irradiated using the second harmonic of a Nd:YAG laser operating at 532 nm wavelength. The changes in the size of the nanostructure and optical properties of the ZnO-Au nanocomposite are studied as a function of the volumetric ratio of ZnO and Au colloidal suspensions. The crystalline structure of the ZnO-Au nanocomposites was analyzed by X-ray diffraction (XRD). The optical properties of the samples were examined at room temperature by a UV-Vis-NIR absorption spectrophotometer. Transmission electron microscopy (TEM) was done by placing a drop of the concentrated suspension on a carbon-coated copper grid. To further confirm the morphology of ZnO-Au nanocomposites, we performed Scanning electron microscopy (SEM) analysis. Room temperature photoluminescence (PL) of the ZnO-Au nanocomposites was measured to characterize the luminescence properties of the ZnO-Au nanocomposites. The ZnO-Au nanocomposites were characterized by Fourier transform infrared (FTIR) spectroscopy. The X-ray diffraction pattern shows that the ZnO-Au nanocomposites had the polycrystalline structure of Au. The behavior observed by images of transmission electron microscope reveals that soldering of Au and ZnO nanoparticles include their adhesion. The plasmon peak in ZnO-Au nanocomposites was red-shifted and broadened in comparison with pure Au nanoparticles. By using the Tauc’s equation, the band gap energy for ZnO-Au nanocomposites is calculated to be 3.15–3.27 eV. In this work, the formation of ZnO-Au nanocomposites shifts the FTIR peak of metal oxide bands to higher wavenumbers. PL spectra of the ZnO-Au nanocomposites show that several weak peaks in the ultraviolet region and several relatively strong peaks in the visible region. SEM image indicates that the morphology of ZnO-Au nanocomposites produced in water was spherical. The TEM images of ZnO-Au nanocomposites demonstrate that with increasing the volumetric ratio of Au colloidal suspension the adhesion increased. According to the size distribution graphs of ZnO-Au nanocomposites with increasing the volumetric ratio of Au colloidal suspension the amount of ZnO-Au nanocomposites with the smaller size is further.

Keywords: Au nanoparticles, pulsed laser ablation, ZnO-Au nanocomposites, ZnO nanoparticles

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Authors: S. V. Ukwungwu, A. J. Abbas, G. G. Nasr

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The increasing high price of natural gas and oil with attendant increase in energy demand on world markets in recent years has stimulated interest in recovering residual oil saturation across the globe. In order to meet the energy security, efforts have been made in developing new technologies of enhancing the recovery of oil and gas, utilizing techniques like CO2 flooding, water injection, hydraulic fracturing, surfactant flooding etc. Surfactant flooding however optimizes production but poses risk to the environment due to their toxic nature. Amongst proven records that have utilized other type of bacterial in producing biosurfactants for enhancing oil recovery, this research uses a technique to combine biosurfactants that will achieve a scale of EOR through lowering interfacial tension/contact angle. In this study, three biosurfactants were produced from three Bacillus species from freeze dried cultures using sucrose 3 % (w/v) as their carbon source. Two of these produced biosurfactants were screened with the TEMCO Pendant Drop Image Analysis for reduction in IFT and contact angle. Interfacial tension was greatly reduced from 56.95 mN.m-1 to 1.41 mN.m-1 when biosurfactants in cell-free culture (Bacillus licheniformis) were used compared to 4. 83mN.m-1 cell-free culture of Bacillus subtilis. As a result, cell-free culture of (Bacillus licheniformis) changes the wettability of the biosurfactant treatment for contact angle measurement to more water-wet as the angle decreased from 130.75o to 65.17o. The influence of microbial treatment on crushed rock samples was also observed by qualitative wettability experiments. Treated samples with biosurfactants remained in the aqueous phase, indicating a water-wet system. These results could prove that biosurfactants can effectively change the chemistry of the wetting conditions against diverse surfaces, providing a desirable condition for efficient oil transport in this way serving as a mechanism for EOR. The environmental friendly effect of biosurfactants applications for industrial purposes play important advantages over chemically synthesized surfactants, with various possible structures, low toxicity, eco-friendly and biodegradability.

Keywords: bacillus, biosurfactant, enhanced oil recovery, residual oil, wettability

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Authors: Rotem Mashkov, Noam Shoval

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In an age when a tourist’s gaze is more focused on the daily lives of locals, it is evident that local food markets are being rediscovered. Traditional urban markets succeed in reinventing themselves as a space for consumption, recreation, and culture, enabling authentic experiences and interpersonal interactions with the local culture. Alongside this, the pressure of tourism development may result in commercialization and retail gentrification to the point of losing the sense of local identity. The issue of finding a balance between tourism development and the preservation of unique local features is at the heart of this study and is being tested using the case of the Mahane Yehuda market in Jerusalem. The research question—how merchants respond to tourism development in the Mahane Yehuda food market— focuses on local traders, a group of players who are usually absent from the research arenas, although they influence tourism development as well as influenced by it. Three main research methods were integrated into this study. The first two methods, a survey of articles survey and comparative mapping of the business mix, were used to characterize the changes in the Mahane Yehuda market both consciously and physically. The third research method, involving in-depth interviews with merchants, was used to examine the traders' attitudes and responses to tourism development. The findings indicate that there has been a turnaround in the market image over the past decade and a half. Additionally, there has been a significant physical change in the business mix, reflected by a decline of 15% in the number of stalls selling food products and delicacies. The data from the interviews on the traders’ attitudes towards tourism development were inconclusive; there were disagreements among the traders about the economic contribution of tourism development in relation to their dependence on the tourism industry. However, there was a consensus on the need for authentic elements in the marketplace. The findings of the study also indicate a strong link between the merchants’ response to tourism development and their stall ownership status as the merchant could exercise their position in various ways depending on the possession type.

Keywords: business mix, Jerusalem, local food markets, Mahane Yehuda market, merchants’ attitude, ownership status, retail gentrification, tourism development, traditional urban markets

Procedia PDF Downloads 139

Authors: Thilina Ranaweera, Enes Makalic, John L. Hopper, Adrian Bickerstaffe

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Data are the primary asset of biomedical researchers, and the engine for both discovery and research translation. As the volume and complexity of research datasets increase, especially with new technologies such as large single nucleotide polymorphism (SNP) chips, so too does the requirement for software to manage, process and analyze the data. Researchers often need to execute complicated queries and conduct complex analyzes of large-scale datasets. Existing tools to analyze such data, and other types of high-dimensional data, unfortunately suffer from one or more major problems. They typically require a high level of computing expertise, are too simplistic (i.e., do not fit realistic models that allow for complex interactions), are limited by computing power, do not exploit the computing power of large-scale parallel architectures (e.g. supercomputers, GPU clusters etc.), or are limited in the types of analysis available, compounded by the fact that integrating new analysis methods is not straightforward. Solutions to these problems, such as those developed and implemented on parallel architectures, are currently available to only a relatively small portion of medical researchers with access and know-how. The past decade has seen a rapid expansion of data management systems for the medical domain. Much attention has been given to systems that manage phenotype datasets generated by medical studies. The introduction of heterogeneous genomic data for research subjects that reside in these systems has highlighted the need for substantial improvements in software architecture. To address this problem, we have developed SPARK, an enabling and translational system for medical research, leveraging existing high performance computing resources, and analysis techniques currently available or being developed. It builds these into The Ark, an open-source web-based system designed to manage medical data. SPARK provides a next-generation biomedical data management solution that is based upon a novel Micro-Service architecture and Big Data technologies. The system serves to demonstrate the applicability of Micro-Service architectures for the development of high performance computing applications. When applied to high-dimensional medical datasets such as genomic data, relational data management approaches with normalized data structures suffer from unfeasibly high execution times for basic operations such as insert (i.e. importing a GWAS dataset) and the queries that are typical of the genomics research domain. SPARK resolves these problems by incorporating non-relational NoSQL databases that have been driven by the emergence of Big Data. SPARK provides researchers across the world with user-friendly access to state-of-the-art data management and analysis tools while eliminating the need for high-level informatics and programming skills. The system will benefit health and medical research by eliminating the burden of large-scale data management, querying, cleaning, and analysis. SPARK represents a major advancement in genome research technologies, vastly reducing the burden of working with genomic datasets, and enabling cutting edge analysis approaches that have previously been out of reach for many medical researchers.

Keywords: biomedical research, genomics, information systems, software

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Authors: M. S. Nikitenko, S. A. Kizilov, D. Y. Khudonogov

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The paper considers an approach to a machine vision operating system combined with using a grid of light markers. This approach is used to solve several scientific and technical problems, such as measuring the capability of an apron feeder delivering coal from a lining return port to a conveyor in the technology of mining high coal releasing to a conveyor and prototyping an autonomous vehicle obstacle detection system. Primary verification of a method of calculating bulk material volume using three-dimensional modeling and validation in laboratory conditions with relative errors calculation were carried out. A method of calculating the capability of an apron feeder based on a machine vision system and a simplifying technology of a three-dimensional modelled examined measuring area with machine vision was offered. The proposed method allows measuring the volume of rock mass moved by an apron feeder using machine vision. This approach solves the volume control issue of coal produced by a feeder while working off high coal by lava complexes with release to a conveyor with accuracy applied for practical application. The developed mathematical apparatus for measuring feeder productivity in kg/s uses only basic mathematical functions such as addition, subtraction, multiplication, and division. Thus, this fact simplifies software development, and this fact expands the variety of microcontrollers and microcomputers suitable for performing tasks of calculating feeder capability. A feature of an obstacle detection issue is to correct distortions of the laser grid, which simplifies their detection. The paper presents algorithms for video camera image processing and autonomous vehicle model control based on obstacle detection machine vision systems. A sample fragment of obstacle detection at the moment of distortion with the laser grid is demonstrated.

Keywords: machine vision, machine vision operating system, light markers, measuring capability, obstacle detection system, autonomous transport

Procedia PDF Downloads 117

Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

Procedia PDF Downloads 179

Authors: J. Ticona Chambi, E. A. De Almeida, C. A. Andrade Raymundo Gaiotto, A. M. Do Espírito Santo, L. Infantes, S. L. Cuffini

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The solubility of active pharmaceutical ingredients (APIs) is challenging for the pharmaceutical industry. The new multicomponent crystalline forms as cocrystal and solvates present an opportunity to improve the solubility of APIs. Commonly, the procedure to obtain multicomponent crystalline forms of a drug starts by screening the drug molecule with the different coformers/solvents. However, it is necessary to develop methods to obtain multicomponent forms in an efficient way and with the least possible environmental impact. The Hansen Solubility Parameters (HSPs) is considered a tool to obtain theoretical knowledge of the solubility of the target compound in the chosen solvent. H-Bond Propensity (HBP), Molecular Complementarity (MC), Coordination Values (CV) are tools used for statistical prediction of cocrystals developed by the Cambridge Crystallographic Data Center (CCDC). The HSPs and the CCDC tools are based on inter- and intra-molecular interactions. The curcumin (Cur), target molecule, is commonly used as an anti‐inflammatory. The demethoxycurcumin (Demcur) and bisdemethoxycurcumin (Bisdcur) are natural analogues of Cur from turmeric. Those target molecules have differences in their solubilities. In this way, the work aimed to analyze and compare different tools for multicomponent forms prediction (solvates) of Cur, Demcur and Biscur. The HSP values were calculated for Cur, Demcur, and Biscur using the chemical group contribution methods and the statistical optimization from experimental data. The HSPmol software was used. From the HSPs of the target molecules and fifty solvents (listed in the HSP books), the relative energy difference (RED) was determined. The probability of the target molecules would be interacting with the solvent molecule was determined using the CCDC tools. A dataset of fifty molecules of different organic solvents was ranked for each prediction method and by a consensus ranking of different combinations: HSP, CV, HBP and MC values. Based on the prediction, 15 solvents were selected as Dimethyl Sulfoxide (DMSO), Tetrahydrofuran (THF), Acetonitrile (ACN), 1,4-Dioxane (DOX) and others. In a starting analysis, the slow evaporation technique from 50°C at room temperature and 4°C was used to obtain solvates. The single crystals were collected by using a Bruker D8 Venture diffractometer, detector Photon100. The data processing and crystal structure determination were performed using APEX3 and Olex2-1.5 software. According to the results, the HSPs (theoretical and optimized) and the Hansen solubility sphere for Cur, Demcur and Biscur were obtained. With respect to prediction analyses, a way to evaluate the predicting method was through the ranking and the consensus ranking position of solvates already reported in the literature. It was observed that the combination of HSP-CV obtained the best results when compared to the other methods. Furthermore, as a result of solvent selected, six new solvates, Cur-DOX, Cur-DMSO, Bicur-DOX, Bircur-THF, Demcur-DOX, Demcur-ACN and a new Biscur hydrate, were obtained. Crystal structures were determined for Cur-DOX, Biscur-DOX, Demcur-DOX and Bicur-Water. Moreover, the unit-cell parameter information for Cur-DMSO, Biscur-THF and Demcur-ACN were obtained. The preliminary results showed that the prediction method is showing a promising strategy to evaluate the possibility of forming multicomponent. It is currently working on obtaining multicomponent single crystals.

Keywords: curcumin, HSPs, prediction, solvates, solubility

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Authors: Francesca Alemanno

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As a complex socio-spatial phenomenon, migration is a practice that also contains a strong imaginative component with respect to the place that, through displacement, one person wants to reach. Every migrant has undertaken his journey having in his mind an image of the displacement he was about to make, of its implications and finally, of the place or city in which he was or would have liked to land. Often, however, the imaginary that has come to build before departure does not fully correspond to the reality of landing; this discrepancy, which can be more or less wide, plays an important role in the relationship that is established with the territory and in the evolution, therefore, of the city itself. In this sense, therefore, the clash that occurs between the imagined and the real is one of the factors that can contribute to making the entry of a migrant into new territory as critical as it can be. Starting from this perspective, the experiences of people who derive from a migratory context and who, over time, manage to create a bond with the land of reception, are taken into account as stories of resistance as they are necessarily charged with a force that is capable of driving difficult and articulated processes of change. The phenomenon of migrant entrepreneurship that is taken into consideration by this abstract plays a very important role because it highlights the story of many people who have managed to build such a close bond with the new territory of arrival that they can imagine and then realize the construction of their own personal business. The margin of contrast between the imagined city and the one that will be inhabited will be observed through the narratives of those who, through the realization of his business project has acted directly on the reality in which he landed. The margin of contrast that exists between the imagined city and the one actually inhabited, together with the implications that this may have on real life, has been observed and analyzed through a period of fieldwork, practicing ethnography, through the narratives of people who find themselves living in a new city as a result of a migration path, and has been contextualized with the support of semi-structured interviews and field notes. At the theoretical level, the research is inserted into a constructionist framework, particularly suited to detect and analyze processes of change, construction of the imaginary and its own modification, being able to capture the consequent repercussions of this process on the conceptual, emotional and practical level.

Keywords: entrepreneurship, imagination, migration, resistance

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Authors: Antoifi Abdoulhalik, Ashraf Ahmed

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Saltwater intrusion (SWI) in coastal aquifers has become a growing threat for many countries around the world. While various control measures have been suggested to mitigate SWI, the construction of subsurface physical barriers remains one of the most effective solutions for this problem. In this work, we used laboratory experiments and numerical simulations to investigate the effectiveness of subsurface dams in heterogeneous layered coastal aquifer with different layering patterns. Four different cases were investigated, including a homogeneous (case H), and three heterogeneous cases in which a low permeability (K) layer was set in the top part of the system (case LH), in the middle part of the system (case HLH) and the bottom part of the system (case HL). Automated image analysis technique was implemented to quantify the main SWI parameters under high spatial and temporal resolution. The method also provides transient salt concentration maps, allowing for the first time clear visualization of the spillage of saline water over the dam (advancing wedge condition) as well as the flushing of residual saline water from the freshwater area (receding wedge condition). The SEAWAT code was adopted for the numerical simulations. The results show that the presence of an overlying layer of low permeability enhanced the ability of the dam to retain the saline water. In such conditions, the rate of saline water spillage and inland extension may considerably be reduced. Conversely, the presence of an underlying low K layer led to a faster increase of saltwater volume on the seaward side of the wall, therefore considerably facilitating the spillage. The results showed that a complete removal of the residual saline water eventually occurred in all the investigated scenarios, with a rate of removal strongly affected by the hydraulic conductivity of the lower part of the aquifer. The data showed that the addition of the underlying low K layer in case HL caused the complete flushing to be almost twice longer than in the homogeneous scenario.

Keywords: heterogeneous coastal aquifers, laboratory experiments, physical barriers, seawater intrusion control

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

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Authors: Nguyen-Thanh Son

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Flood is among the most frequent and costliest natural hazards. The flood disasters especially affect the poor people in rural areas, who are heavily dependent on agriculture and have lower incomes. Cambodia is identified as one of the most climate-vulnerable countries in the world, ranked 13th out of 181 countries most affected by the impacts of climate change. Flood monitoring is thus a strategic priority at national and regional levels because policymakers need reliable spatial and temporal information on flood-prone areas to form successful monitoring programs to reduce possible impacts on the country’s economy and people’s likelihood. This study aims to develop methods for flood mapping and assessment from MODIS data in Cambodia. We processed the data for the period from 2000 to 2017, following three main steps: (1) data pre-processing to construct smooth time-series vegetation and water surface indices, (2) delineation of flood-prone areas, and (3) accuracy assessment. The results of flood mapping were verified with the ground reference data, indicating the overall accuracy of 88.7% and a Kappa coefficient of 0.77, respectively. These results were reaffirmed by close agreement between the flood-mapping area and ground reference data, with the correlation coefficient of determination (R²) of 0.94. The seasonally flooded areas observed for 2010, 2015, and 2016 were remarkably smaller than other years, mainly attributed to the El Niño weather phenomenon exacerbated by impacts of climate change. Eventually, although several sources potentially lowered the mapping accuracy of flood-prone areas, including image cloud contamination, mixed-pixel issues, and low-resolution bias between the mapping results and ground reference data, our methods indicated the satisfactory results for delineating spatiotemporal evolutions of floods. The results in the form of quantitative information on spatiotemporal flood distributions could be beneficial to policymakers in evaluating their management strategies for mitigating the negative effects of floods on agriculture and people’s likelihood in the country.

Keywords: MODIS, flood, mapping, Cambodia

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Authors: Syed Jamil H. Kazmi, Faiza Sarwar

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The Indus delta of Sindh Province forms the largest creeks zone of Pakistan. The Sindh coast starts from the mouth of Hab River and terminates at Sir Creek area. In this paper, we have considered the major creeks from the site of Bin Qasim Port in Karachi to Jetty of Keti Bunder in Thatta District. A general decline in the mangrove forest has been observed that within a span of last 25 years. The unprecedented human interventions damage the creeks habitat badly which includes haphazard urban development, industrial and sewage disposal, illegal cutting of mangroves forest, reduced and inconsistent fresh water flow mainly from Jhang and Indus rivers. These activities not only harm the creeks habitat but affected the fish stock substantially. Fishing is the main livelihood of coastal people but with the above-mentioned threats, it is also under enormous pressure by fish catches resulted in unchecked overutilization of the fish resources. This pressure is almost unbearable when it joins with deleterious fishing methods, uncontrolled fleet size, increase trash and by-catch of juvenile and illegal mesh size. Along with these anthropogenic interventions study area is under the red zone of tropical cyclones and active seismicity causing floods, sea intrusion, damage mangroves forests and devastation of fish stock. In order to sustain the natural resources of the Indus Creeks, this study was initiated with the support of FAO, WWF and NIO, the main purpose was to develop a Geo-Spatial dataset for fish stock assessment. The study has been spread over a year (2013-14) on monthly basis which mainly includes detailed fish stock survey, water analysis and few other environmental analyses. Environmental analysis also includes the habitat classification of study area which has done through remote sensing techniques for 22 years’ time series (1992-2014). Furthermore, out of 252 species collected, fifteen species from estuarine and marine groups were short-listed to measure the weight, health and growth of fish species at each creek under GIS data through SPSS system. Furthermore, habitat suitability analysis has been conducted by assessing the surface topographic and aspect derivation through different GIS techniques. The output variables then overlaid in GIS system to measure the creeks productivity. Which provided the results in terms of subsequent classes: extremely productive, highly productive, productive, moderately productive and less productive. This study has revealed the Geospatial tools utilization along with the evaluation of the fisheries resources and creeks habitat risk zone mapping. It has also been identified that the geo-spatial technologies are highly beneficial to identify the areas of high environmental risk in Sindh Creeks. This has been clearly discovered from this study that creeks with high rugosity are more productive than the creeks with low levels of rugosity. The study area has the immense potential to boost the economy of Pakistan in terms of fish export, if geo-spatial techniques are implemented instead of conventional techniques.

Keywords: fish stock, geo-spatial, productivity analysis, risk

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Authors: Fariha Asif

Abstract:

The Saudi EFL learners face a number of problems in EFL learning, anxiety is the most potent one among those. It means that its resolution can lead to better language skills in Saudi students. That’s why, the study is carried out and is considered to be of interest to the Saudi language learners, educators and the policy makers because of the potentially negative impact that anxiety has on English language learning. The purpose of the study is to explore the factors that cause language anxiety in the Saudi EFL learners while learning speaking skills and the influence it casts on communication in the target language. The investigation of the anxiety-producing factors that arise while learning to communicate in the target language will hopefully broaden the insight into the issue of language anxiety and will help language teachers in making the classroom environment less stressful. The study seeks to answer the questions such as what are the psycholinguistic factors that cause language anxiety among ESL/EFL learners in learning and speaking English Language, especially in the context of the Saudi students. What are the socio-cultural factors that cause language anxiety among Saudi EFL learners in learning and speaking English Language? How is anxiety manifested in the language learning of the Saudi EFL learners? And which strategies can be used to successfully cope with language anxiety? The scope of the study is limited to the college and university English Teachers and subject specialists (males and females) in public sectors colleges and universities in Saudi Arabia. Some of the key findings of the study are:, Anxiety plays an important role in English as foreign language learning for the Saudi EFL learners. Some teachers believe that anxiety bears negatives effects for the learners, while some others think that anxiety serves a positive outcome for the learners by giving them an extra bit of motivation to do their best in English language learning. Language teachers seem to have consensus that L1 interference is one of the major factors that cause anxiety among the Saudi EFL learners. Most of the Saudi EFL learners are found to have fear of making mistakes. They don’t take initiative and opt to keep quiet and don’t respond fearing that they would make mistakes and this would ruin their image in front of their peers. Discouraging classroom environment is also counted as one of the major anxiety causing factors. The teachers, who don’t encourage learners positively, make them anxious and they start avoiding class participation. It is also found that English language teachers have their important role to minimize the negative effects of anxiety in the classes. The teachers’ positive encouragement can do wonders in this regard. A positive, motivating and encouraging class environment is essential to produce desired results in English language learning for the Saudi EFL learners.

Keywords: factors, psychology, speaking, EFL

Procedia PDF Downloads 467