Search results for: binary classifier

Authors: Molla Tadesse Lakew

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This study was intended to identify the factors influencing the use of mobile phones in vegetable marketing in Fogera district. The use of mobile phones in vegetable marketing and factors influencing mobile phone use were specific objectives of the study. Three kebeles from the Fogera district were selected purposively based on their vegetable production potential. A simple random sampling technique (lottery method) was used to select 153 vegetable producer farmers. Interview schedule and key informants interviews were used to collect primary data. For analyzing the data, descriptive statistics like frequency and percentage, two independent t-tests, and chi-square were used. Furthermore, econometric analysis (binary logistic model) was used to assess the factors influencing mobile phone use for vegetable market information. Contingency coefficient and variance inflation factor were used to check multicollinearity problems between the independent variables. Of 153 respondents, 82 (61.72%) were mobile phone users, while 71 (38.28 %) were mobile phone nonusers. Moreover, the main use of mobile phones in vegetable marketing includes communicating at a distance to save time and minimizing transport costs, getting vegetable marketing price information, identifying markets and buyers to sell the vegetable, deciding when to sell the vegetable, negotiating with buyers for better vegetable prices and for searching of the fast market to avoid from losing of product through perishing. The model result indicated that the level of education, size of land, income, access to credit, and age were significant variables affecting the use of mobile phones in vegetable marketing. It could be recommended to encourage adult education or give training for farmers on how to operate mobile phones and create awareness for the elderly rural farmers as they are able to use the mobile phone for their vegetable marketing. Moreover, farmers should be aware that mobile phones are very important for those who own very small land to get maximum returns from their production. Lastly, providing access to credit and improving and diversifying income sources for the farmers to have mobile phones were recommended to improve the livelihood of farmers.

Keywords: mobile phone, farmers, vegetable marketing, Fogera District

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Authors: Alaa Hamed Salama, Rehab Nabil Shamma

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Introduction: Polymeric micelles that can deliver drug to intended sites of the eye have attracted much scientific attention recently. The aim of this study was to review the aqueous-based formulation of drug-loaded polymeric micelles that hold significant promise for ophthalmic drug delivery. This study investigated the synergistic performance of mixed polymeric micelles made of linear and branched poly (ethylene oxide)-poly (propylene oxide) for the more effective encapsulation of Lornoxicam (LX) as a hydrophobic model drug. Methods: The co-micellization process of 10% binary systems combining different weight ratios of the highly hydrophilic poloxamers; Synperonic® PE/P84, and Synperonic® PE/F127 and the hydrophobic poloxamine counterpart (Tetronic® T701) was investigated by means of photon correlation spectroscopy and cloud point. The drug-loaded micelles were tested for their solubilizing capacity towards LX. Results: Results showed a sharp solubility increase from 0.46 mg/ml up to more than 4.34 mg/ml, representing about 136-fold increase. Optimized formulation was selected to achieve maximum drug solubilizing power and clarity with lowest possible particle size. The optimized formulation was characterized by 1HNMR analysis which revealed complete encapsulation of the drug within the micelles. Further investigations by histopathological and confocal laser studies revealed the non-irritant nature and good corneal penetrating power of the proposed nano-formulation. Conclusion: LX-loaded polymeric nanomicellar formulation was fabricated allowing easy application of the drug in the form of clear eye drops that do not cause blurred vision or discomfort, thus achieving high patient compliance.

Keywords: confocal laser scanning microscopy, Histopathological studies, Lornoxicam, micellar solubilization

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Authors: Davod Ahmadi, Narges Ebadi, Ethan Wang, Hugo Melgar-Quiñonez

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Compared to the other Least Developed Countries (LDCs), major countries in sub-Saharan Africa (SSA) have limited access to the clean water. People in this region, and more specifically females, suffer from acute water scarcity problems. They are compelled to spend too much of their time bringing water for domestic use like drinking and washing. Apart from domestic use, water through affecting agriculture and livestock contributes to the food security status of people in vulnerable regions like SSA. Livestock needs water to grow, and agriculture requires enormous quantities of water for irrigation. The main objective of this study is to explore the association between access to water and individuals’ food security status. Data from 2017 Gallup World Poll (GWP) for SSA were analyzed (n=35,000). The target population in GWP is the entire civilian, non-institutionalized, aged 15 and older population. All samples selection is probability based and nationally representative. The Gallup surveys an average of 1,000 samples of individuals per country. Three questions related to water (i.e., water quality, availability of water for crops and availability of water for livestock) were used as the exposure variables. Food Insecurity Experience Scale (FIES) was used as the outcome variable. FIES measures individuals’ food security status, and it is composed of eight questions with simple dichotomous responses (1=Yes and 0=No). Different statistical analyses such as descriptive, crosstabs and binary logistic regression, form the basis of this study. Results from descriptive analyses showed that more than 50% of the respondents had no access to enough water for crops and livestock. More than 85% of respondents were categorized as “food insecure”. Findings from cross-tabulation analyses showed that food security status was significantly associated with water quality (0.135; P=0.000), water for crops (0.106; P=0.000) and water for livestock (0.112; P=0.000). In regression analyses, the probability of being food insecure increased among people who expressed no satisfaction with water quality (OR=1.884 (OR=1.768-2.008)), not enough water for crops (OR=1.721 (1.616-1.834)) and not enough water for livestock (OR=1.706 (1.819)). In conclusion, it should note that water access affects food security status in SSA.

Keywords: water access, agriculture, livestock, FIES

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Authors: Fang Liu, JunShuai Xue, JiaJia Yao, XueYan Yang, ZuMao Li, GuanLin Wu, HePeng Zhang, ZhiPeng Sun

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III-Nitride resonant tunneling diode (RTD) is one of the most promising candidates for multiple-valued logic (MVL) elements. Here, we report a monolithic integration of GaN resonant tunneling diodes to realize multiple negative differential resistance (NDR) regions for MVL application. GaN RTDs, composed of a 2 nm quantum well embedded in two 1 nm quantum barriers, are grown by plasma-assisted molecular beam epitaxy on free-standing c-plane GaN substrates. Negative differential resistance characteristic with a peak current density of 178 kA/cm² in conjunction with a peak-to-valley current ratio (PVCR) of 2.07 is observed. Statistical properties exhibit high consistency showing a peak current density standard deviation of almost 1%, laying the foundation for the monolithic integration. After complete electrical isolation, two diodes of the designed same area are connected in series. By solving the Poisson equation and Schrodinger equation in one dimension, the energy band structure is calculated to explain the transport mechanism of the differential negative resistance phenomenon. Resonant tunneling events in a sequence of the series-connected RTD pair (SCRTD) form multiple NDR regions with nearly equal peak current, obtaining three stable operating states corresponding to ternary logic. A frequency multiplier circuit achieved using this integration is demonstrated, attesting to the robustness of this multiple peaks feature. This article presents a monolithic integration of SCRTD with multiple NDR regions driven by the resonant tunneling mechanism, which can be applied to a multiple-valued logic field, promising a fast operation speed and a great reduction of circuit complexity and demonstrating a new solution for nitride devices to break through the limitations of binary logic.

Keywords: GaN resonant tunneling diode, multiple-valued logic system, frequency multiplier, negative differential resistance, peak-to-valley current ratio

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Authors: Zainab Dahrouch, Beatrix Petrovičová, Claudia Triolo, Fabiola Pantò, Angela Malara, Salvatore Patanè, Maria Allegrini, Saveria Santangelo

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Synthetic dyes dispersed in water cause environmental damage and have harmful effects on human health. Methylene blue (MB) is broadly used as a dye in the textile, pharmaceutical, printing, cosmetics, leather, and food industries. The complete removal of MB is difficult due to the presence of aromatic rings in its structure. The present study is focused on electrospun nanofibers (NFs) with engineered architecture and surface to be used as catalysts for the photodegradation of MB. Ti and/or Zn oxide NFs are produced by electrospinning precursor solutions with different Ti: Zn molar ratios (from 0:1 to 1:0). Subsequent calcination and cooling steps are operated at fast rates to generate porous NFs with capture centers to reduce the recombination rate of the photogenerated charges. The comparative evaluation of the NFs as photocatalysts for the removal of MB from an aqueous solution with a dye concentration of 15 µM under UV irradiation shows that the binary (wurtzite ZnO and anatase TiO₂) oxides exhibit higher catalytic activity compared to ternary (ZnTiO₃ and Zn₂TiO₄) oxides. The higher band gap and lower crystallinity of the ternary oxides are responsible for their lower photocatalytic activity. It has been found that the optimal load for the wurtzite ZnO is 0.66 mg mL⁻¹, obtaining a degradation rate of 7.94.10⁻² min⁻¹. The optimal load for anatase TiO₂ is lower (0.33 mg mL⁻¹) and the corresponding rate constant (1.12×10⁻¹ min⁻¹) is higher. This finding (higher activity with lower load) is of crucial importance for the scaling up of the process on an industrial scale. Indeed, the anatase NFs outperform even the commonly used P25-TiO₂ benchmark. Besides, they can be reused twice without any regeneration treatment, with 5.2% and 18.7% activity decrease after second and third use, respectively. Thanks to the scalability of the electrospinning technique, this laboratory-scale study provides a perspective towards the sustainable large-scale manufacture of photocatalysts for the treatment of industry effluents.

Keywords: anatase, capture centers, methylene blue dye, nanofibers, photodegradation, zinc oxide

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Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

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Authors: Meenakshi

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Background: The complications during pregnancy are the major cause of morbidity and deaths among women in the reproductive age group. Childbearing is the most important phase in women’s lives that occur mainly in the adolescent and adult years. Maternal health, thus is an important issue as this as this is important phase is also productive time for women as they strive fulfill their capabilities as an individual, mothers, family members and also as a citizen. The objective of the study is to document the coverage of ANC and its determinants among domestic workers. Method: A survey of 300 domestic workers were carried in Delhi. Only respondents in the age group (15-49) and whose recent birth was of 5 years preceding the survey were included. Socio-demographic data and information on maternal health was collected from these respondents Information on ANC was collected from total 300 respondents. Standard of living index were composed based on households assists and similarly autonomy index was computed based on women decision making power in the households taking certain key variables. Cross tabulations were performed to obtain frequency and percentages. Potential socio-economic determinants of utilization of ANC among domestic workers were examined using binary logistic regressions. Results: Out of 300 domestic workers survey, only 70.7 per cent per cent received ANC. Domestic workers who married at age 18 years and above are 4 times more likely to utilize antenatal services during their last birth (***p< 0.01). Comparison to domestic workers with number of living children two or less, domestic workers with number of living children more than two are less likely to utilize antenatal care services (**p< 0.05). Domestic workers belonging to Other Backward Castes are more likely to utilize antenatal care services than domestic workers belonging to scheduled tribes ((**p< 0.05). Conclusion: The level of utilization of maternal health services are less among domestic workers is less, as they spend most of their time at the employers household. Though demonstration effect do have impact on their life styles but utilization of maternal health services is poor. Strategies and action are needed to improve the utilization of maternal health services among this section of workers as they are vulnerable because of no proper labour legislations.

Keywords: antenatal care, domestic workers, health services, maternal health, women’s health

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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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: Rodrigo Antunes, Olga Borisevich, David Demange

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In future nuclear fusion reactors, tritium self-sufficiency will be ensured by tritium (3H) production via reactions between the fusion neutrons and lithium. To favor tritium breeding, a neutron multiplier must also be used. Both tritium breeder and neutron multiplier will be placed in the so-called Breeding Blanket (BB). For the European Helium-Cooled Pebble Bed (HCPB) BB concept, the tritium production and neutron multiplication will be ensured by neutron bombardment of Li4SiO4 and Be pebbles, respectively. The produced tritium is extracted from the pebbles by purging them with large flows of He (~ 104 Nm3h-1), doped with small amounts of H2 (~ 0.1 vol%) to promote tritium extraction via isotopic exchange (producing HT). Due to the presence of oxygen in the pebbles, production of tritiated water is unavoidable. Therefore, the purging gas downstream of the BB will be composed by Q2/Q2O/He (Q = 1H, 2H, 3H), with Q2/Q2O down to ppm levels, which must be further processed for tritium recovery. A two-stage continuous approach, where zeolite membranes (ZMs) are followed by a catalytic membrane reactor (CMR), has been recently proposed to fulfil this task. The tritium recovery from Q2/Q2O/He is ensured by the CMR, that requires a reduction of the gas flow coming from the BB and a pre-concentration of Q2 and Q2O to be efficient. For this reason, and to keep this stage with reasonable dimensions, ZMs are required upfront to reduce as much as possible the He flows and concentrate the Q2/Q2O species. Therefore, experimental activities have been carried out at the Tritium Laboratory Karlsruhe (TLK) to test the separation performances of different zeolite membranes for H2/H2O/He. First experiments have been performed with binary mixtures of H2/He and H2O/He with commercial MFI-ZSM5 and NaA zeolite-type membranes. Only the MFI-ZSM5 demonstrated selectivity towards H2, with a separation factor around 1.5, and H2 permeances around 0.72 µmolm-2s-1Pa-1, rather independent for feed concentrations in the range 0.1 vol%-10 vol% H2/He. The experiments with H2O/He have demonstrated that the separation factor towards H2O is highly dependent on the feed concentration and temperature. For instance, at 0.2 vol% H2O/He the separation factor with NaA is below 2 and around 1000 at 5 vol% H2O/He, at 30°C. Overall, both membranes demonstrated complementary results at equivalent temperatures. In fact, at low feed concentrations ( ≤ 1 vol% H2O/He) MFI-ZSM5 separates better than NaA, whereas the latter has higher separation factors for higher inlet water content ( ≥ 5 vol% H2O/He). In this contribution, the results obtained with both MFI-ZSM5 and NaA membranes for H2/He and H2O/H2 mixtures at different concentrations and temperatures are compared and discussed.

Keywords: nuclear fusion, gas separation, tritium processes, zeolite membranes

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Authors: Noel Mariam George

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This paper explores the history of Tibetan citizenship, one of the primary non-partition refugee communities, and their negotiation of 'in-betweenness' as a mode of political and legal belonging in India. While South Asian citizenship histories have primarily centered around the 1947 and 1971 Partitions, this paper uncovers an often-overlooked period, spanning the 1950s, 60s, and 70s, when Tibetans began to assert their claims within the Indian state. This paper challenges the conventional teleological narrative of partition by highlighting a distinct period when the Indian state negotiated boundaries of belonging for non-partition refugees differently. It explores how Tibetans occupied an 'in-between' status, existing as both foreigners and potential citizens, thereby complicating the traditional citizen-refugee binary. Moreover, it underscores that citizenship during this era was not solely determined by legal frameworks. Instead, it was a dynamic process shaped by historical contexts, practices, and relationships. Tibetans pursued citizen-like claims through legal battles, lobbying, protests, volunteering, and collective solidarity, revealing citizenship as an 'act' embedded in their daily lives. Tibetan liminality is characterized by their simultaneous maintenance of exile identity and pursuit of citizen-like claims in India. The cautious Indian state, reluctant to label Tibetans as either 'refugees' or 'citizens,' has contributed to this liminal status. This duality has intensified Tibetans' precarity but has also led to creative and transformative practices that have expanded the boundaries of democracy and citizenship in India. Beyond traditional narratives of Indian benevolence, this paper scrutinizes the geopolitical factors driving Indian support for Tibetans. Additionally, it challenges 'common-sensical' narratives by demonstrating how Tibetans strategically navigated Indian citizenship. Using archival sources from the British Library and the National Archives in London and Delhi along with digitized materials, the paper reveals citizenship as a multi-faceted historical process. It examines how Tibetans exercised agency within the Indian state despite their liminal status.

Keywords: citizenship, borderlands, forced displacement, refugees in India

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Saeed Saffar-Heidari

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This article aims to study the recent Iranian national uprising of “Women, Life, Freedom” as a site of memory which renders the political possibility of imagining the post-Islamic futures in Iran. “Women, Life, Freedom” movement in Iran has been arguably the most pervasive social movement since the Islamic Revolution (1979) as it has posed serious issues and conflicts for the present Islamic state in Iran. The core argument of this article, however, is oriented toward the critical role of collective memory as a means of political transition and revolutionary mobilization. “Women, Life, Freedom” movement, among other things, has revitalized the popular binary opposition of pre-1979 and post-1979 Iran through which the Ancien Régime or the pre-1979 era is likely to be interpreted, read, and remembered in terms of present post-1979 cultural and political demands. As remembering involves everyday participation in shaping and reshaping the past through new codes, criteria, and values, it is argued that the presentist refashioning and remembering of the pre-1979 monarchical era has been one of the major facilitatory forces for the on-going revolutionary mobilization in Iran. The construction of the pre-1979 memory and the return of the dynastic specter has played a significant role in revolutionary mobilization as it has provided the protesters with the possible perspectives of post-Islamic regime in Iran. Additionally, the question of compulsory “Hijab” (veiling) as the prime mover of "Women, Life, Freedom” movement in Iran has strongly contributed to the everyday comparative discourse of pre/post 1979 memory. According to this presentist remembering of pre-1979, the Pahlavi dynasty would be conceived as a symbol of modernization, westernization, secularization, and non-compulsory Hijab. While the memory of the pre-revolutionary Iran is genuinely an imaginative as well as a constructed entity that finally culminates in the public condemnation of the very Islamic revolution (1979), it serves the enrichment of the Iranian political imagination as it paves the ways for the revolutionary mobilization and then the overthrowing of the Islamic regime in Iran. This article makes a case for the ways that the public narrative and discourse around the Islamic regime (especially the Islamic Hijab) led to the refashioning of the memory of pre-1979 era and inspired he revolutionary mobilization in Iran.

Keywords: post-islamic, utopias, memory, revolutionary, mobilization, Iran

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Authors: Anteneh Wodaje Bayeh, Daniel Manaye Kabtamu, Chen-Hao Wang

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As one of the most promising electrochemical energy storage systems, vanadium redox flow batteries (VRFBs) have received increasing attention owing to their attractive features for largescale storage applications. However, their high production cost and relatively low energy efficiency still limit their feasibility. For practical implementation, it is of great interest to improve their efficiency and reduce their cost. One of the key components of VRFBs that can greatly influence the efficiency and final cost is the electrode, which provide the reactions sites for redox couples (VO²⁺/VO₂ + and V²⁺/V³⁺). Carbon-based materials are considered to be the most feasible electrode materials in the VRFB because of their excellent potential in terms of operation range, good permeability, large surface area, and reasonable cost. However, owing to limited electrochemical activity and reversibility and poor wettability due to its hydrophobic properties, the performance of the cell employing carbon-based electrodes remained limited. To address the challenges, we synthesized heteroatom-doped bimetallic oxide grown on the surface of carbon through the one-step approach. When applied to VRFBs, the prepared electrode exhibits significant electrocatalytic effect toward the VO²⁺/VO₂ + and V³⁺/V²⁺ redox reaction compared with that of pristine carbon. It is found that the presence of heteroatom on metal oxide promotes the absorption of vanadium ions. The controlled morphology of bimetallic metal oxide also exposes more active sites for the redox reaction of vanadium ions. Hence, the prepared electrode displays the best electrochemical performance with energy and voltage efficiencies of 74.8% and 78.9%, respectively, which is much higher than those of 59.8% and 63.2% obtained from the pristine carbon at high current density. Moreover, the electrode exhibit durability and stability in an acidic electrolyte during long-term operation for 1000 cycles at the higher current density.

Keywords: VRFB, VO²⁺/VO₂ + and V³⁺/V²⁺ redox couples, graphite felt, heteroatom-doping

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Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

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Authors: Anil Kumar, Diwakar Aggarwal, M. Sudhakara Reddy

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The wood of Eucalyptus, Populus and bamboos are some important species used as raw material for the manufacture of pulp. However, higher levels of lignin pose a problem during Kraft pulping and yield of pulp is also lower. In order to increase the yield of pulp per unit wood and reduce the use of chemicals during kraft pulping it is important to reduce the lignin content and/or increase cellulose content in wood. Cellulose biosynthesis in wood takes place by the coordinated action of many enzymes. The two important enzymes are KORRIGAN and SUCROSE SYNTHASE. KORRIGAN (Endo-1,4--glucanase) is implicated in the process of editing growing cellulose chains and improvement of the crystallinity of produced cellulose, whereas SUCROSE SYNTHASE is involved in providing substrate (UDP-glucose) for growing cellulose chains. The present study was aimed at the cloning, characterization and overexpression of these genes in Eucalyptus and Populus. An efficient shoot organogenesis protocol from leaf explants taken from micro shoots of the species has been developed. Agrobacterium mediated genetic transformation using Agrobacterium tumefaciens strain EHA105 and LBA4404 harboring binary vector pBI121 was achieved. Both the genes were cloned from cDNA library of Populus deltoides. These were subsequently characterized using various bioinformatics tools. The cloned genes were then inserted into pBI121 under the CaMV35S promotors replacing GUS gene. The constructs were then mobilized into above strains of Agrobacterium and used for the transformation work. Subsequently, genetic transformation of these clones with target genes following already developed protocol is in progress. Four transgenic lines of Eucalyptus tereticornis overexpressing Korrigan gene under the strong constitutive promoters CaMV35S have been developed, which are being further evaluated. Work on development of more transgenic lines overexpressing these genes in Populus and Eucalyptus is also in progress. This presentation will focus on important developments in this direction.

Keywords: Eucalyptus tereticornis, genetic transformation, Kraft pulping Populus deltoides

Procedia PDF Downloads 111

Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Rohit Shrivastava, Stefan Luding

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A mechanical wave is propagation of vibration with transfer of energy and momentum. Studying the energy as well as spectral energy characteristics of a propagating wave through disordered granular media can assist in understanding the overall properties of wave propagation through inhomogeneous materials like soil. The study of these properties is aimed at modeling wave propagation for oil, mineral or gas exploration (seismic prospecting) or non-destructive testing for the study of internal structure of solids. The study of Energy content (Kinetic, Potential and Total Energy) of a pulse propagating through an idealized one-dimensional discrete particle system like a mass disordered granular chain can assist in understanding the energy attenuation due to disorder as a function of propagation distance. The spectral analysis of the energy signal can assist in understanding dispersion as well as attenuation due to scattering in different frequencies (scattering attenuation). The selection of one-dimensional granular chain also helps in studying only the P-wave attributes of the wave and removing the influence of shear or rotational waves. Granular chains with different mass distributions have been studied, by randomly selecting masses from normal, binary and uniform distributions and the standard deviation of the distribution is considered as the disorder parameter, higher standard deviation means higher disorder and lower standard deviation means lower disorder. For obtaining macroscopic/continuum properties, ensemble averaging has been used. Interpreting information from a Total Energy signal turned out to be much easier in comparison to displacement, velocity or acceleration signals of the wave, hence, indicating a better analysis method for wave propagation through granular materials. Increasing disorder leads to faster attenuation of the signal and decreases the Energy of higher frequency signals transmitted, but at the same time the energy of spatially localized high frequencies also increases. An ordered granular chain exhibits ballistic propagation of energy whereas, a disordered granular chain exhibits diffusive like propagation, which eventually becomes localized at long periods of time.

Keywords: discrete elements, energy attenuation, mass disorder, granular chain, spectral energy, wave propagation

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Authors: Julie Lucille H. Del Valle

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To improve its public school education, the Philippines took a radical curriculum reform in 2012, by launching the K-to-12 program which not only added two years to its basic education but also mandated for a replacement of traditional teaching with learner-centered pedagogy, an instruction whose western underpinnings suggest improving student achievement, thus, making pedagogies in the country more or less similar with those in Europe and USA. This policy, however, placed learner-centered pedagogy in a binary opposition against teacher-centered instruction, creating a simplistic dichotomy between good and bad teaching. It is in this dichotomy that this study seeks to explore, using Critical Pedagogy of the Place as the lens, in understanding what constitutes good teaching across a range of learner-centered and teacher-centered pedagogies in the context of public schools in disadvantaged communities. Furthermore, this paper examines how pedagogical homogeneity, arguably influenced by dominant global imperatives with economic agenda – often referred as economisation of education – not only thins out local identities as structures of global schooling become increasingly similar but also limits the concept of good teaching to student outcomes and corporate employability. This paper draws from qualitative research on students, thus addressing the gap created by studies on good teaching which looked mainly into the perceptions of teachers and administrators, while overlooking those of students whose voices must be considered in the formulation of inclusive policies that advocate for true education reform. Using ethnographic methods including student focus groups, classroom observations, and teacher interviews, responses from students of disadvantaged schools reveal that good teaching includes both learner-centered and teacher-centered practices that incorporate ‘academic caring’ which sustains their motivation to achieve in school despite the challenging learning environments. The combination of these two pedagogies equips students with life-long skills necessary to gain equal access to sustainable economic opportunities in their local communities.

Keywords: critical pedagogy of the place, good teaching, learner-centered pedagogy, placed-based instruction

Procedia PDF Downloads 231

Authors: Henok Yebyo Henok, Araya Abrha Araya, Alemayehu Bayray Alemayehu, Gelila Goba Gelila

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Background: Every year, an estimated 19–20 million unsafe abortions take place, almost all in developing countries, leading to 68,000 deaths and millions more injured many permanently. Many women throughout the world, experience more than one abortion in their lifetimes. Repeat abortion is an indicator of the larger problem of unintended pregnancy. This study aimed to identify determinants of repeat abortion in Tigray Region, Ethiopia. Methods: Unmatched case-control study was conducted in hospitals in Tigray Region, Northern Ethiopia, from November 2014 to June 2015. The sample included 105 cases and 204 controls, recruited from among women seeking abortion care at public hospitals. Clients having two or more abortions (“repeat abortion”) were taken as cases, and those who had a total of one abortion were taken as controls (“single abortion”). Cases were selected consecutive based on proportional to size allocation while systematic sampling was employed for controls. Data were analyzed using SPSS version 20.0. Binary and multiple variable logistic regression analyses were calculated with 95% CI. Results: Mean age of cases was 24 years (±6.85) and 22 years (±6.25) for controls. 79.0% of cases had their sexual debut in less than 18 years of age compared to 57% of controls. 42.2% of controls and 23.8% of cases cited rape as the reason for having an abortion. Study participants who did not understand their fertility cycle and when they were most likely to conceive after menstruation (adjusted odds ratio [AOR]=2.0, 95% confidence interval [CI]: 1.1-3.7), having a previous abortion using medication(AOR=3.3, CI: 1.83, 6.11), having multiple sexual partners in the preceding 12 months (AOR=4.4, CI: 2.39,8.45), perceiving that the abortion procedure is not painful (AOR=2.3, CI: 1.31,4.26), initiating sexual intercourse before the age of 18 years (AOR=2.7, CI: 1.49, 5.23) and disclosure to a third-party about terminating the pregnancy (AOR=2.1, CI: 1.2,3.83) were independent predictors of repeat abortion. Conclusion: This study identified several factors correlated with women having repeat abortions. It may be helpful for the Government of Ethiopia to encourage women to delay sexual debut and decrease their number of sexual partners, including by promoting discussion within families about sexuality, to decrease the occurrence of repeated abortion.

Keywords: abortion, Ethiopia, repeated abortion, single abortion

Procedia PDF Downloads 247

Authors: Ayesha Sanjana Kawser Parsha

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S-acylation is an irreversible bond in which cysteine residues are linked to fatty acids palmitate (74%) or stearate (22%), either at the COOH or NH2 terminal, via a thioester linkage. There are several experimental methods that can be used to identify the S-palmitoylation site; however, since they require a lot of time, computational methods are becoming increasingly necessary. There aren't many predictors, however, that can locate S- palmitoylation sites in Arabidopsis Thaliana with sufficient accuracy. This research is based on the importance of building a better prediction tool. To identify the type of machine learning algorithm that predicts this site more accurately for the experimental dataset, several prediction tools were examined in this research, including the GPS PALM 6.0, pCysMod, GPS LIPID 1.0, CSS PALM 4.0, and NBA PALM. These analyses were conducted by constructing the receiver operating characteristics plot and the area under the curve score. An AI-driven deep learning-based prediction tool has been developed utilizing the analysis and three sequence-based input data, such as the amino acid composition, binary encoding profile, and autocorrelation features. The model was developed using five layers, two activation functions, associated parameters, and hyperparameters. The model was built using various combinations of features, and after training and validation, it performed better when all the features were present while using the experimental dataset for 8 and 10-fold cross-validations. While testing the model with unseen and new data, such as the GPS PALM 6.0 plant and pCysMod mouse, the model performed better, and the area under the curve score was near 1. It can be demonstrated that this model outperforms the prior tools in predicting the S- palmitoylation site in the experimental data set by comparing the area under curve score of 10-fold cross-validation of the new model with the established tools' area under curve score with their respective training sets. The objective of this study is to develop a prediction tool for Arabidopsis Thaliana that is more accurate than current tools, as measured by the area under the curve score. Plant food production and immunological treatment targets can both be managed by utilizing this method to forecast S- palmitoylation sites.

Keywords: S- palmitoylation, ROC PLOT, area under the curve, cross- validation score

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Authors: Temitope L. Baiyegunhi, Kuiwu Liu, Oswald Gwavava, Christopher Baiyegunhi

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Shale gas has recently been the exploration focus for future energy resource in South Africa. Specifically, the black shales of the lower Ecca Group in the study area are considered to be one of the most prospective targets for shale gas exploration. Evaluation of this potential resource has been restricted due to the lack of exploration and scarcity of existing drill core data. Thus, only limited previous geochemical data exist for these formations. In this study, outcrop and core samples of the Ecca Group were analysed to assess their total organic carbon (TOC), organic matter type, thermal maturity and hydrocarbon generation potential (SP). The results show that these rocks have TOC ranging from 0.11 to 7.35 wt.%. The SP values vary from 0.09 to 0.53 mg HC/g, suggesting poor hydrocarbon generative potential. The plot of S1 versus TOC shows that the source rocks were characterized by autochthonous hydrocarbons. S2/S3 values range between 0.40 and 7.5, indicating Type- II/III, III, and IV kerogen. With the exception of one sample from the collingham formation which has HI value of 53 mg HC/g TOC, all other samples have HI values of less than 50 mg HC/g TOC, thus suggesting Type-IV kerogen, which is mostly derived from reworked organic matter (mainly dead carbon) with little or no potential for hydrocarbon generation. Tmax values range from 318 to 601℃, indicating immature to over-maturity of hydrocarbon. The vitrinite reflectance values range from 2.22 to 3.93%, indicating over-maturity of the kerogen. Binary plots of HI against OI and HI versus Tmax show that the shales are of Type II and mixed Type II-III kerogen, which are capable of generating both natural gas and minor oil at suitable burial depth. Based on the geochemical data, it can be inferred that the source rocks are immature to over-matured variable from localities and have potential of producing wet to dry gas at present-stage. Generally, the Whitehill formation of the Ecca Group is comparable to the Marcellus and Barnett Shales. This further supports the assumption that the Whitehill Formation has a high probability of being a profitable shale gas play, but only when explored in dolerite-free area and away from the Cape Fold Belt.

Keywords: source rock, organic matter type, thermal maturity, hydrocarbon generation potential, Ecca Group

Procedia PDF Downloads 117

Authors: Mohsen Bahrami, Banafsheh Nikmehr, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Tamer M. Yalcinkaya

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In recent years, we have witnessed an explosion of studies aimed at using a combination of artificial intelligence (AI) and time-lapse imaging data on embryos to improve IVF outcomes. However, despite promising results, no study has used a matched cohort of transferred embryos which only differ in pregnancy outcome, i.e., embryos from a single clinic which are similar in parameters, such as: morphokinetic condition, patient age, and overall clinic and lab performance. Here, we used time-lapse data on embryos with known pregnancy outcomes to see if the rich spatiotemporal information embedded in this data would allow the prediction of the pregnancy outcome regardless of such critical parameters. Methodology—We did a retrospective analysis of time-lapse data from our IVF clinic utilizing Embryoscope 100% of the time for embryo culture to blastocyst stage with known clinical outcomes, including live birth vs nonpregnant (embryos with spontaneous abortion outcomes were excluded). We used time-lapse data from 200 elective single transfer embryos randomly selected from January 2019 to June 2021. Our sample included 100 embryos in each group with no significant difference in patient age (P=0.9550) and morphokinetic scores (P=0.4032). Data from all patients were combined to make a 4th order tensor, and feature extraction were subsequently carried out by a tensor decomposition methodology. The features were then used in a machine learning classifier to classify the two groups. Major Findings—The performance of the model was evaluated using 100 random subsampling cross validation (train (80%) - test (20%)). The prediction accuracy, averaged across 100 permutations, exceeded 80%. We also did a random grouping analysis, in which labels (live birth, nonpregnant) were randomly assigned to embryos, which yielded 50% accuracy. Conclusion—The high accuracy in the main analysis and the low accuracy in random grouping analysis suggest a consistent spatiotemporal pattern which is associated with pregnancy outcomes, regardless of patient age and embryo morphokinetic condition, and beyond already known parameters, such as: early cleavage or early blastulation. Despite small samples size, this ongoing analysis is the first to show the potential of AI methods in capturing the complex morphokinetic changes embedded in embryo time-lapse data, which contribute to successful pregnancy outcomes, regardless of already known parameters. The results on a larger sample size with complementary analysis on prediction of other key outcomes, such as: euploidy and aneuploidy of embryos will be presented at the meeting.

Keywords: IVF, embryo, machine learning, time-lapse imaging data

Procedia PDF Downloads 69

Authors: Martial Amou

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This study was carried out to assess the situation of households’ livelihood under a changing climate pattern in the Zio district of Togo, West Africa. The study examined three important aspects: (i) assessment of households’ livelihood situation under a changing climate pattern, (ii) farmers’ perception and understanding of local climate change, (iii) determinants of adaptation strategies undertaken in cropping pattern to climate change. To this end, secondary sources of data, and survey data collected from 235 farmers in four villages in the study area were used. Adapted conceptual framework from Sustainable Livelihood Framework of DFID, two steps Binary Logistic Regression Model and descriptive statistics were used in this study as methodological approaches. Based on Sustainable Livelihood Approach (SLA), various factors revolving around the livelihoods of the rural community were grouped into social, natural, physical, human, and financial capital. Thus, the study came up that households’ livelihood situation represented by the overall livelihood index in the study area (34%) is below the standard average households’ livelihood security index (50%). The natural capital was found as the poorest asset (13%) and this will severely affect the sustainability of livelihood in the long run. The result from descriptive statistics and the first step regression (selection model) indicated that most of the farmers in the study area have clear understanding of climate change even though they do not have any idea about greenhouse gases as the main cause behind the issue. From the second step regression (output model) result, education, farming experience, access to credit, access to extension services, cropland size, membership of a social group, distance to the nearest input market, were found to be the significant determinants of adaptation measures undertaken in cropping pattern by farmers in the study area. Based on the result of this study, recommendations are made to farmers, policy makers, institutions, and development service providers in order to better target interventions which build, promote or facilitate the adoption of adaptation measures with potential to build resilience to climate change and then improve rural livelihood.

Keywords: climate change, rural livelihood, cropping pattern, adaptation, Zio District

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Authors: Adebisi David Alade

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In pre-colonial West Africa, the deadliness of the climate vis-a- vis malaria and other tropical diseases to Europeans turned the region into the “white man’s grave.” Thus, immediately after the partition of Africa in 1885, civilisatrice and mise en valeur not only became a pretext for the establishment of colonial rule; from a medical point of view, the control and possible eradication of disease in the continent emerged as one of the first concerns of the European colonizers. Though geared toward making Africa exploitable, historical evidence suggests that some colonial Water, Sanitation and Hygiene (WASH) policies and projects reduced certain tropical diseases in some West African communities. Exploring some of these disease control interventions by way of historical revisionism, this paper challenges the orthodox interpretation of colonial sanitation and public health measures in West Africa. This paper critiques the deployment of race and class as analytical tools for the study of colonial WASH projects, an exercise which often reduces the complexity and ambiguity of colonialism to the binary of colonizer and the colonized. Since West Africa presently ranks high among regions with Neglected Tropical Diseases (NTDs), it is imperative to decentre colonial racism and economic exploitation in African history in order to give room for Africans to see themselves in other ways. Far from resolving the problem of NTDs by fiat in the region, this study seeks to highlight important blind spots in African colonial history in an attempt to prevent post-colonial African leaders from throwing away the baby with the bath water. As scholars researching colonial sanitation and public health in the continent rarely examine its complex meaning and content, this paper submits that the outright demonization of colonial rule across space and time continues to build ideological wall between the present and the past which not only inhibit fruitful borrowing from colonial administration of West Africa, but also prevents a wide understanding of the challenges of WASH policies and projects in most West African states.

Keywords: colonial rule, disease control, neglected tropical diseases, WASH

Procedia PDF Downloads 158

Authors: Thomas Suarez, Anne-Sophie Grenouilleau, Erwan Autin, Alexandre Biosse-Duplan, Emmanuelle Blondet, Laurence Chazalette, Marie Coniel, Agnes Dessaigne, Sylvie Lascols, Andrea Lasserre, Candice Legris, Pierre Liot, Aline Metais, Karine Petitprez, Christophe Varlet, Christian Saout

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Background: The role of biological sex and gender identity -whether assigned or chosen- as health determinants are far from a recent discovery: several reports have stressed out how being a woman or a man could affect health on various scales. However, taking it into consideration beyond stereotypes and rigid binary assumptions still seems to be a work in progress. Method: The report is a synthesis on a variety of specific topics, each of which was studied by a specialist from the French National Authority for Health (HAS), through an analysis of existing literature on both healthcare policy construction process and instruments (norms, data analysis, clinical trials, guidelines, and professional practices). This work also implied a policy analysis of French recent public health laws and a retrospective study of guidelines with a gender mainstreaming approach. Results: The analysis showed that though sex and gender were well-known determinants of health, their consideration by both public policy and health operators was often incomplete, as it does not incorporate how sex and gender interact, as well as how they interact with other factors. As a result, the health and social care systems and their professionals tend to reproduce some stereotypical and inadequate habits. Though the data available often allows to take sex and gender into consideration, such data is often underused in practice guidelines and policy formulation. Another consequence is a lack of inclusiveness towards transgender or intersex persons. Conclusions: This report first urges for raising awareness of all the actors of health, in its broadest definition, that sex and gender matter beyond first-look conclusions. It makes a series of recommendations in order to reshape policy construction in the health sector on the one hand and to design public health instruments to make them more inclusive regarding sex and gender on the other hand. The HAS finally committed to integrate sex and gender preoccupations in its workings methods, to be a driving force in the spread of these concerns.

Keywords: biological sex, determinants of health, gender, healthcare policy instruments, social accompaniment

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Authors: Fakhreldin O. Suliman, Alia H. Al-Battashi

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This work explored the interaction of three different imidazoline drugs, naphazoline nitrate (NPH), oxymetazoline hydrochloride (OXY) and xylometazoline hydrochloride (XYL) with two different synthesized cucurbit[n]urils CB[n], cucurbit[7]uril (CB[7]) and cucuribit[8]uril (CB[8]). Three binary inclusion complexes have been investigated in solution and in the solid state. The solid complexes were obtained by lyophilization, whereas the physical mixtures of guests and hosts at a stoichiometric ratio of 1:1 were obtained for each drug. 1HNMR, electrospray ionization mass spectrometry (ESI-MS), and matrix-assisted laser desorption-ionization time-of-flight (MALDI-TOF) mass spectrometry was used to study the complexes prepared in aqueous media. The lyophilized solid complexes were characterized by Fourier transform-infrared spectroscopy (FT-IR), powder X-ray diffractometry (PXRD), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). MS, FT-IR and PXRD experimental results established in this work reveal that NPH, OXY and XYL molecules form stable inclusion complexes with the two hosts. The TGA and DSC confirmed the enhancement of the thermal stability of each drug and the production of a thermally stable solid complex. The 1HNMR has shown that the protons of the guests faced shifting in ppm and broadening of their peaks upon the formation of inclusion complexes with the selected CB[n]. The aromatic protons of the guest exhibited the highest changes in the chemical shifts and shape of the NMR peaks, suggesting their inclusion into the cavity of the CB[n]. The diffusion coefficients (D), developed from the diffusion-controlled NMR Spectroscopy (DOSY) measurements, for the complexation of the selected imidazoline drugs with CB[7] and CB[8], were decreased in the presence of hosts compared to the free guests indicating the formation of the guest-host adduct. Furthermore, we conducted molecular dynamic simulations and quantum mechanics calculations on these complexes. The results of the theoretical study corroborate the experimental findings and have also shed light on the mechanism of inclusion of the guests into the two hosts. This study generates initial data for potential drug delivery or drug formulation systems for these three selected imidazoline drug compounds based on their inclusion into the CB[n] cavities.

Keywords: cucurbit[n]urils, imidazoline, inclusion complexes, molecular dynamics, DFT calculations, mass spectrometry

Procedia PDF Downloads 37

Authors: Tigist Mekonnen Melesse

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Since rural households are basically entitled to food through own production, improving productivity might lead to enhance the welfare of rural population through higher food availability at the household level and lowering the price of agricultural products. Increasing agricultural productivity through the use of improved technology is one of the desired outcomes from sensible food security and agricultural policy. The ultimate objective of this study was to evaluate the potential impact of improved agricultural technology adoption on smallholders’ crop productivity and welfare. The study is conducted in Ethiopia covering 1500 rural households drawn from four regions and 15 rural villages based on data collected by Ethiopian Rural Household Survey. Endogenous treatment effect model is employed in order to account for the selection bias on adoption decision that is expected from the self-selection of households in technology adoption. The treatment indicator, technology adoption is a binary variable indicating whether the household used improved seeds and chemical fertilizer or not. The outcome variables were cereal crop productivity, measured in real value of production and welfare of households, measured in real per capita consumption expenditure. Results of the analysis indicate that there is positive and significant effect of improved technology use on rural households’ crop productivity and welfare in Ethiopia. Adoption of improved seeds and chemical fertilizer alone will increase the crop productivity by 7.38 and 6.32 percent per year of each. Adoption of such technologies is also found to improve households’ welfare by 1.17 and 0.25 percent per month of each. The combined effect of both technologies when adopted jointly is increasing crop productivity by 5.82 percent and improving welfare by 0.42 percent. Besides, educational level of household head, farm size, labor use, participation in extension program, expenditure for input and number of oxen positively affect crop productivity and household welfare, while large household size negatively affect welfare of households. In our estimation, the average treatment effect of technology adoption (average treatment effect on the treated, ATET) is the same as the average treatment effect (ATE). This implies that the average predicted outcome for the treatment group is similar to the average predicted outcome for the whole population.

Keywords: Endogenous treatment effect, technologies, productivity, welfare, Ethiopia

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Authors: T. Thein, S. Kalyar Myo

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Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

Procedia PDF Downloads 263