Search results for: middle war and post war architecture

Authors: L. C. Nwosu, C. O. Adedire, M. O. Ashamo, E. O. Ogunwolu

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The maize weevil, Sitophilus zeamais Motschulsky is a notorious pest of stored maize (Zea mays L.). The development of resistant maize varieties to manage weevils is a major breeding objective. The study investigated the parameters and mechanisms that confer resistance on a maize variety to S. zeamais infestation using twenty elite maize varieties. Detailed morphological, physical and chemical studies were conducted on whole-maize grain and the grain pericarp. Resistance was assessed at 33, 56, and 90 days post infestation using weevil mortality rate, weevil survival rate, percent grain damage, percent grain weight loss, weight of grain powder, oviposition rate and index of susceptibility as indices rated on a scale developed by the present study and on Dobie’s modified scale. Linear regression models that can predict maize grain damage in relation to the duration of storage were developed and applied. The resistant varieties identified particularly 2000 SYNEE-WSTR and TZBRELD3C5 with very high degree of resistance should be used singly or best in an integrated pest management system for the control of S. zeamais infestation in stored maize. Though increases in the physical properties of grain hardness, weight, length, and width increased varietal resistance, it was found that the bases of resistance were increased chemical attributes of phenolic acid, trypsin inhibitor and crude fibre while the bases of susceptibility were increased protein, starch, magnesium, calcium, sodium, phosphorus, manganese, iron, cobalt and zinc, the role of potassium requiring further investigation. Characters that conferred resistance on the test varieties were found distributed in the pericarp and the endosperm of the grains. Increases in grain phenolic acid, crude fibre, and trypsin inhibitor adversely and significantly affected the bionomics of the weevil on further assessment. The flat side of a maize grain at the point of penetration was significantly preferred by the weevil. Why the south area of the flattened side of a maize grain was significantly preferred by the weevil is clearly unknown, even though grain-face-type seemed to be a contributor in the study. The preference shown to the south area of the grain flat side has implications for seed viability. The study identified antibiosis, preference, antixenosis, and host evasion as the mechanisms of maize post harvest resistance to Sitophilus zeamais infestation.

Keywords: maize weevil, resistant, parameters, mechanisms, preference

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Authors: Manal E. A Elhalwagy, Nadia Amin Abdulmajeed, Hanan S. Alnahdi, Enas N. Danial

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Baron is herbicide includes (48% glyphosate) widely used in Egypt. The present study assesses the cytotoxic and genotoxic effect of baron on rats liver. Two groups of rats were treated orally with 1/10 LD 50, (275.49 mg kg -1) and 1/40 LD 50, (68.86 mg kg-1) glyphosate for 28 days compared with control group. Serum and liver tissues were taken at 14 and 28 days of treatment. An inhibition in Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities were recorded at both treatment periods and reduction in total serum protein (TP) and albumin (ALB). However, non-significant changes in serum acetylcholinesterase (AChE). Elevation in oxidative stress biomarker malondyaldehyde (MDA) and the decline in detoxification biomarker total reduced glutathione (GSH), Glutathione S-transferase (GST) and superoxide dismutase (SOD) in liver tissues led to increase in percentage of DNA damage. Destruction in liver tissue architecture was observed . Although, Baron was classified in the safe category pesticides repeated exposure to small doses has great danger effect.

Keywords: glyphosate, liver toxicity, oxidative stress, DNA damage, commet assay

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Alexander Hudson, Shaogang Gong

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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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Authors: Azeez Balogun

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Inexperienced building score practices are continually evolving and vary across areas. Yet, a few middle ideas stay steady, such as website selection, design, energy efficiency, water and material conservation, indoor environmental great, operational optimization, and waste discount. The essence of green building lies inside the optimization of 1 or more of those standards. This paper conducts a comparative analysis of 7 extensively recognized sustainable score structures—BREEAM, CASBEE, green GLOBES, inexperienced superstar, HK-BEAM, IGBC green homes, and LEED—based totally on the perceptions and opinions of stakeholders in Nigeria certified in green constructing rating systems. The purpose is to pick out and adopt an appropriate green building rating device for Nigeria. Numerous components of those systems had been tested to determine the high-quality health of the Nigerian built environment. The findings imply that LEED, the important machine within the USA and Canada, is the most suitable for Nigeria due to its sturdy basis, extensive funding, and confirmed blessings. LEED obtained the highest rating of eighty out of one hundred points on this assessment.

Keywords: structure, built surroundings, inexperienced building score gadget, Nigeria Inexperienced Constructing Council, sustainability

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Authors: Dalia O. Saleha, Gehad A. Abdel Jaleela, Sally W. Al-Awdana

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Diabetes mellitus (DM) is known to exacerbate cerebral ischemic injury. The present study aimed to investigate the anti-oxidant and anti-inflammatory effects of oral supplementation of melatonin (MLN) on cerebral injury caused by middle cerebral artery occlusion and reperfusion (MCAO/Re) in streptozotocin (STZ)-induced hyperglycemic rats. Hyperglycemia was induced by a single injection of STZ (55mg/kg; i.p.), six weeks later the cerebral injury was induced by MCAO/Re. Twenty-four hours after the MCAO/Re the MLN (10 mg/kg) was injected for 14 consecutive days. Results of the present study revealed that MCAO/Re in STZ-induced hyperglycemia in rats causes an increase in the oxidative stress biomarkers; it increased brain lipid peroxidation (measured as malondialdehyde; MDA) and brain level of nitric oxide (NO). Moreover, MCAO/Reproduces a prominent increase in the brain inflammatory markers viz. interleukin-6 (IL-6), interleukin-1β (IL-1β) and tumor necrosis nuclear factor-alpha (TNF-α). Oral treatment of MCAO/Re in STZ-induced hyperglycemic rats with MLN (10 mg/kg) for two weeks restored the brain levels of MDA, GSH, NO, IL-6, IL-1β and the TNF-α. MLN succeeded to suppress the exacerbation of damage in the brain of hyperglycemic rats. These results suggest that daily intake of MLN attenuates the exacerbation of cerebral ischemic injury in a diabetic state, which may be attributed to anti-oxidant and anti-inflammatory effects in the brain.

Keywords: melatonin, brain injury, cerebral ischemia/reperfusion, hyperglycemia, rats

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Authors: Maria Christofi, George Plastiras, Rafaella Elia, Vaggelis Tsiourtis, Theocharis Theocharides, Miltiadis Katsaros

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The rapidly expanding urban areas of the world constitute a challenge of how we need to make the transition to "the next urbanization", which will be defined by new analytical tools and new sources of data. This paper is about the production of a spatial application, the ‘FUMapp’, where space and its initiative will be available literally, in meters, but also abstractly, at a sensed level. While existing spatial applications typically focus on illustrations of the urban infrastructure, the suggested application goes beyond the existing: It investigates how our environment's perception adapts to the alterations of the built environment through a dataset construction of biophysical measurements (eye-tracking, heart beating), and physical metrics (spatial characteristics, size of stimuli, rhythm of mobility). It explores the intersections between architecture, cognition, and computing where future design can be improved and identifies the flexibility and livability of the ‘available space’ of specific examined urban paths.

Keywords: biophysical data, flexibility of urban, livability, next urbanization, spatial application

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Authors: Lei Guo, Xu Zhang, Weigang Hou

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Since the traditional network is closed and it has no architecture to create applications, it has been unable to evolve with changing demands under the rapid innovation in services. Additionally, due to the lack of the whole network profile, the quality of service cannot be well guaranteed in the traditional network. The Software Defined Network (SDN) utilizes global resources to support on-demand applications/services via open, standardized and programmable interfaces. In this paper, we implement the traffic grooming application under a real SDN environment, and the corresponding analysis is made. In our SDN: 1) we use OpenFlow protocol to control the entire network by using software applications running on the network operating system; 2) several virtual switches are combined into the data forwarding plane through Open vSwitch; 3) An OpenFlow controller, NOX, is involved as a logically centralized control plane that dynamically configures the data forwarding plane; 4) The traffic grooming based on SDN is demonstrated through dynamically modifying the idle time of flow entries. The experimental results demonstrate that the SDN-based traffic grooming effectively reduces the end-to-end delay, and the improvement ratio arrives to 99%.

Keywords: NOX, OpenFlow, Software Defined Network (SDN), traffic grooming

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Authors: Arun Sanjel, Greg Speegle

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Every second, massive amounts of data are generated, and Data Intensive Scalable Computing (DISC) frameworks have evolved into effective tools for analyzing such massive amounts of data. Since the underlying architecture of these distributed computing platforms is often new to users, building a DISC application can often be time-consuming and prone to errors. The automated conversion of a sequential program to a DISC program will consequently significantly improve productivity. However, synthesizing a user’s intended program from an input specification is complex, with several important applications, such as distributed program synthesizing and code refactoring. Existing works such as Tyro and Casper rely entirely on deductive synthesis techniques or similar program synthesis approaches. Our approach is to develop a data-driven synthesis technique to identify sequential components and translate them to equivalent distributed operations. We emphasize using reinforcement learning and unit testing as feedback mechanisms to achieve our objectives.

Keywords: program synthesis, distributed computing, reinforcement learning, unit testing, DISC

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Authors: Juan Manuel Real-Espinosa

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This paper addresses the first step to evaluate language learning apps: what theoretical framework to adopt when designing the app evaluation framework. The answer is not just one since there are several options that could be proposed. However, the question to be clarified is to what extent the learning design of apps is based on a specific learning approach, or on the contrary, on a fusion of elements from several theoretical proposals and paradigms, such as m-learning, mobile assisted language learning, and a number of theories about language acquisition. The present study suggests that the reality is closer to the second assumption. This implies that the theoretical framework against which the learning design of the apps should be evaluated must also be a hybrid theoretical framework, which integrates evaluation criteria from the different theories involved in language learning through mobile applications.

Keywords: mobile-assisted language learning, action-oriented approach, apps evaluation, post-method pedagogy, second language acquisition

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Authors: Fernanda T. Orsati, Julie Causton

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Discursive practices enacted by educators in kindergarten create a blueprint for how the educational trajectories of students with disabilities are constructed. This two-year ethnographic case study critically examine educators’ relationships with students considered to present challenging behaviors in one kindergarten classroom located in a predominantly White middle-class school district in the Northeast of the United States. Focusing on the language and practices used by one special education teacher and three teaching assistants, this paper analyzes how teacher responses to students’ behaviors constructs and positions students over one year of kindergarten education. Using a critical discourse analysis, it shows that educators understand students’ behaviors as a deficit and needing consequences. This study highlights how educators’ responses reflect students' individual characteristics including family background, socioeconomics and ability status. This paper offers in-depth analysis of two students’ stories, which evidenced that the language used by educators amplifies the social positioning of students within the classroom and creates a foundation for who they are constructed to be. Through exploring routine language and practices, this paper demonstrates that educators outlined a blueprint of kindergartners, which positioned students as learners in ways that became the ground for either a limited or a promising educational pathway for them.

Keywords: behavior, early education, special education, critical discourse analysis

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Benguerine Zohra, Merzak Siham, Bouziane Cheimaa, Si Tayeb Fatima, Jou Siham, Belkessam

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Introduction: Antibiotics, widely produced and consumed in large quantities, have proven problematic due to various types of side effects. The development of bacterial resistance to currently available antibiotics has made the search for new antibacterial agents necessary. One alternative strategy to combat antibiotic-resistant bacteria is the use of natural antimicrobial substances such as plant extracts. The objective of this study is to provide an overview of the antibacterial effects of a plant native to the Middle East and Mediterranean regions, Salvia officinalis (sage). Materials and Methods: This review article was conducted by searching studies in the PubMed, Scopus, JSTOR, and SpringerLink databases. The search terms were "Salvia officinalis L." and "antibacterial effects." Only studies that met our inclusion criteria (in English, antibacterial effects of Salvia officinalis L., and primarily dating from 2012 to 2023) were accepted for further review. Results and Discussion: The initial search strategy identified approximately 78 references, with only 13 articles included in this review. The synthesis of the articles revealed that several data sources confirm the antimicrobial effects of S. officinalis. Its essential oil and alcoholic extract exhibit strong bactericidal and bacteriostatic effects against both Gram-positive and Gram-negative bacteria. Conclusion: The significant value of the extract, oil, and leaves of S. officinalis calls for further studies on the other useful and unknown properties of this multi-purpose plant.

Keywords: salvia officinalis, literature review, antibacterial, effects

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Authors: Sareh Rajabi, Salwa Bheiry

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In general, Covid-19 created many financial and non-financial damages to the economy and community. Level and severity of covid-19 as pandemic case varies over the region and due to different types of the projects. Covid-19 virus emerged as one of the most imperative risk management factors word-wide recently. Therefore, as part of portfolio management assessment, it is essential to evaluate severity of such risk on the project and program in portfolio management level to avoid any risky portfolio. Covid-19 appeared very effectively in South America, part of Europe and Middle East. Such pandemic infection affected the whole universe, due to lock down, interruption in supply chain management, health and safety requirements, transportations and commercial impacts. Therefore, this research proposes Analytical Hierarchy Process (AHP) to analyze and assess such pandemic case like Covid-19 and its impacts on the construction projects. The AHP technique uses four sub-criteria: Health and safety, commercial risk, completion risk and contractual risk to evaluate the project and program. The result will provide the decision makers with information which project has higher or lower risk in case of Covid-19 and pandemic scenario. Therefore, the decision makers can have most feasible solution based on effective weighted criteria for project selection within their portfolio to match with the organization’s strategies.

Keywords: portfolio management, risk management, COVID-19, analytical hierarchy process technique

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Authors: Kuniko Muramoto, Tadashi Nakamura, Shiro Dan

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On March 11, 2011 the Great East Japan Disaster caused widespread damage. In the aftermath, we searched for ways to provide long-term support and enhanced resilience to affected areas, arriving at the Family Manga Exhibition: an art collection portraying family life. It became a tool for community outreach and intervention, and we implemented support programs by collaborating with local support agencies. This 10-year project has been touring through four prefectures in Tohoku since the disaster struck, bearing witness to the effects of disaster and recovery alike. At this five-year mark, we use a narrative perspective to present our findings and reflect on post-disaster community support. It is important to note that the exhibition’s art does not directly depict the disaster; it portrays stories of anonymous families instead. They stimulate viewers’ memories and remind them of their own family stories. We analyzed viewers' oral and written responses to the exhibition and discovered that family manga as an art form enhances the viewer’s sense of connection to people close to them. We also discovered that the viewers gained more universal perspective on their own situations by viewing the exhibition. Manga, we found, offered a certain safety by enabling the viewers to control how they would interact with the exhibition's content and themes. In addition, the purpose of the project was for us to become witnesses of the disaster and recovery. Supporters of the project became active listeners, functioning as interactive agents who helped forming stories. Voices of the story tellers and the listeners layered upon each other and, as a result, converged into brand new narratives. The essence of traumatic experience is ‘the sense of overwhelming powerlessness and isolation’. When we redefine trauma as ‘broken relationships’, we can say that ‘enhancing relationships’ and ‘weaving relationships’ are what strengthen our resilience. This project used narrative as a modality to fortify the resilience of people involved by enhancing the social capital of bonding, bridging, and linking. The manga exhibition functioned as a tool to achieve this end, suggesting that similar applications are possible. Programs we held in-between manga exhibitions also served to enhance narratives of resiliency in the regions. However, we will save that story for another time. We hope to continue collecting the precious and polyphonic voices of people to present as stories born out of the Great East Japan Disaster. This effort extends beyond the immediately affected area by helping us prepare our resilience for future disasters.

Keywords: community, manga, narrative, resilience

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Authors: Sean Paulsen, Michael Casey

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In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

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Authors: Aulia Dwi Nastiti

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A number of studies and reports on terrorism have continuously addressed the role of internet and online activism to support terrorist and extremist groups. In particular, they stress on social media’s usage that generally serves for the terrorist’s propaganda as well as justification of their causes. While those analyses are important to understand how social media is a vital tool for global network terrorism, they are inadequate to explain the online communication patterns that enable terrorism acts. Beyond apparent online narratives, there is a deep cyber sphere where the very vein of terrorism movement lies. That is a hidden space in the internet called ‘darknet’. Recent investigations, particularly in Middle Eastern context, have shed some lights that this invisible space in the internet is fundamental to maintain the terrorist activities. Despite that, limited number of research examines darknet within the issue of terrorist movements in Indonesian context—where the country is considered quite a hotbed for extremist groups. Therefore, this paper attempts to provide an insight of darknet operation in Indonesian cases. By exploring how the darknet is used by the Indonesian-based extremist groups, this paper maps out communication patterns of terrorist groups on the internet which appear as an intermingled network. It shows the usage of internet is differentiated in different level of anonymity for distinctive purposes. This paper further argues that the emerging terrorist communication network calls for a more comprehensive counterterrorism strategy on the Internet.

Keywords: communication pattern, counterterrorism, darknet, extremist groups, terrorism

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Authors: Hakim Derradji, Abdelkader Yahi, Abdelmalek Sabrou, Nacer Tabet

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Introduction: Cystic lesions located in the sellar and suprasellar region cause a diagnostic and therapeutic problem, given their location and their impact on neighboring structures. The patient's symptomatology varies from a simple headache to serious visual and endocrine disorders, involving the functional prognosis, sometimes even the vital prognosis. Surgery in this region remains a therapeutic challenge, and several surgical techniques have been described and used. Material and Methods: We treated 15 patients during the period from 2015 to 2022, whose clinical, biological, radiological, and therapeutic characteristics will be presented in detail in this work, and in whom the surgical technique differs from one case to another. Conclusion: We will discuss in this work the different techniques used to treat these lesions and the different objectives to be achieved for each case, as well as the complications and our conduct to be taken per and post-operative.

Keywords: cystic lesions, adenomas, sellar and suprasellar region, neuroendoscopy

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Authors: Mahvish Anjum

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India is a land of craftsmen and a hub of many popular embroidery clusters. Chikankari is the name given to the delicate art of hand embroidery, traditionally practiced in the city of Lucknow and its environs. Chikankari not only provide employment to 250,000 artisans of different crafts but people from non-craft base also earn their livelihood by associating themselves with this craft. People working in this sector are exploited in term of working hours, low and irregular income, unsatisfactory work conditions, no legal protection and exposed to occupational health hazards. The present paper is an attempt to analyse occupational profile of workers engaged in Chikan embroidery industry. Being an empirical study, the entire work is based upon primary sources of data which have collected through field survey. Purposive random sampling has used for selection of data. Total 150 workers have surveyed through questionnaire technique in Lucknow city during October-November, 2017. For analysis of data Z-score, ANOVA, and Pearson correlation techniques are used. The result of present study indicates that artisans are exploited by the middle man and face the problem of late payment and long working hours because they are not directly associated with the manufacturers. Work conditions of the workers are quite poor such as improper ventilation, poor light and unhygienic conditions that adversely affect the health of workers.

Keywords: artisans, socio-economic status, unorganized industry, work condition

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Authors: Kristina Zuzek, Xuan Xu, Awais Ikram, Richard Sheridan, Allan Walton, Saso Sturm

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Recycling of end-of-life REEs based Nd-Fe-B magnets is an important strategy for reducing the environmental dangers associated with rare-earth mining and overcoming the well-documented supply risks related to the REEs. However, challenges on their reprocessing still remain. We report on the possibility of direct electrochemical recycling and reprocessing of Nd-Fe(B)-based magnets. In this investigation, we were able first to electrochemically leach the end-of-life NdFeB magnet and to electrodeposit Nd–Fe using a 1-ethyl-3-methyl imidazolium dicyanamide ([EMIM][DCA]) ionic liquid-based electrolyte. We observed that Nd(III) could not be reduced independently. However, it can be co-deposited on a substrate with the addition of Fe(II). Using advanced TEM techniques of electron-energy-loss spectroscopy (EELS) it was shown that Nd(III) is reduced to Nd(0) during the electrodeposition process. This gave a new insight into determining the Nd oxidation state, as X-ray photoelectron spectroscopy (XPS) has certain limitations. This is because the binding energies of metallic Nd (Nd0) and neodymium oxide (Nd₂O₃) are very close, i. e., 980.5-981.5 eV and 981.7-982.3 eV, respectively, making it almost impossible to differentiate between the two states. These new insights into the electrodeposition process represent an important step closer to efficient recycling of rare piles of earth in metallic form at mild temperatures, thus providing an alternative to high-temperature molten-salt electrolysis and a step closer to deposit Nd-Fe-based magnetic materials. Further, we propose a new concept of recycling the sintered Nd-Fe-B magnets by direct recovering the 2:14:1 matrix phase. Via an electrochemical etching method, we are able to recover pure individual 2:14:1 grains that can be re-used for new types of magnet production. In the frame of physical reprocessing, we have successfully synthesized new magnets out of hydrogen (HDDR)-recycled stocks with a contemporary technique of pulsed electric current sintering (PECS). The optimal PECS conditions yielded fully dense Nd-Fe-B magnets with the coercivity Hc = 1060 kA/m, which was boosted to 1160 kA/m after the post-PECS thermal treatment. The Br and Hc were tackled further and increased applied pressures of 100 – 150 MPa resulted in Br = 1.01 T. We showed that with a fine tune of the PECS and post-annealing it is possible to revitalize the Nd-Fe-B end-of-life magnets. By applying advanced TEM, i.e. atomic-scale Z-contrast STEM combined with EDXS and EELS, the resulting magnetic properties were critically assessed against various types of structural and compositional discontinuities down to atomic-scale, which we believe control the microstructure evolution during the PECS processing route.

Keywords: electrochemistry, Nd-Fe-B, pulsed electric current sintering, recycling, reprocessing

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Authors: Matthias Haenisch, Katharina Hermann, Marc Godau, Verena Weidner

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Over the past two decades, international music education has been characterized by a growing interest in informal learning for formal contexts and a "compositional turn" that has moved from closed to open forms of composing. This change occurs under social and technological conditions that permeate 21st-century musical practices. This forms the background of Musical Communities in the (Post)Digital Age (MusCoDA), a four-year joint research project of the University of Erfurt (UE) and the University of Education Karlsruhe (PHK), funded by the German Federal Ministry of Education and Research (BMBF). Both explore songwriting processes as an example of collective creativity in (post)digital communities, one in formal and the other in informal learning contexts. Collective songwriting will be studied from a network perspective, that will allow us to view boundaries between both online and offline as well as formal and informal or hybrid contexts as permeable and to reconstruct musical learning practices. By comparing these songwriting processes, possibilities for a pedagogical-didactic interweaving of different educational worlds are highlighted. Therefore, the subproject of the University of Erfurt investigates school music lessons with the help of interviews, videography, and network maps by analyzing new digital pedagogical and didactic possibilities. In the first step, the international literature on songwriting in the music classroom was examined for design development. The analysis focused on the question of which methods and practices are circulating in the current literature. Results from this stage of the project form the basis for the first instructional design that will help teachers in planning regular music classes and subsequently reconstruct musical learning practices under these conditions. In analyzing the literature, we noticed certain structural methods and concepts that recur, such as the Building Blocks method and the pre-structuring of the songwriting process. From these findings, we developed a deck of cards that both captures the current state of research and serves as a method for design development. With this deck of cards, both teachers and students themselves can plan their individual songwriting lessons by independently selecting and arranging topic, structure, and action cards. In terms of science communication, music educators' interactions with the card game provide us with essential insights for developing the first design. The overall goal of MusCoDA is to develop an empirical model of collective musical creativity and learning and an instructional design for teaching music in the postdigital age.

Keywords: card game, collective songwriting, community of practice, network, postdigital

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Authors: Hyunho Shin, Jaekwang Jung, Jeongho Park, Sungwon Hwang

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For the application of graphene quantum dots (GQDs) to optoelectronic nanodevices, it is of critical importance to understand the mechanisms which result in novel phenomena of their light absorption/emission. The optical transitions are known to be available up to ~6 eV in GQDs, especially useful for ultraviolet (UV) photodetectors (PDs). Here, we present size-dependent shape/edge-state variations of GQDs and visible photoluminescence (PL) showing anomalous size dependencies. With varying the average size (da) of GQDs from 5 to 35 nm, the peak energy of the absorption spectra monotonically decreases, while that of the visible PL spectra unusually shows nonmonotonic behaviors having a minimum at diameter ∼17 nm. The PL behaviors can be attributed to the novel feature of GQDs, that is, the circular-to-polygonal-shape and corresponding edge-state variations of GQDs at diameter ∼17 nm as the GQD size increases, as demonstrated by high resolution transmission electron microscopy. We believe that such a comprehensive scheme in designing device architecture and the structural formulation of GQDs provides a device for practical realization of environmentally benign, high performance flexible devices in the future.

Keywords: graphene, quantum dot, size, photoluminescence

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Authors: Rajashekhar K. Patil, Martin J. Babu

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Weaver ants-Oecophylla smaragdina live in colonies that have polymorphic castes. The females which include the queen, major and minor workers are haploid. The individuals of castes are dependent on olfactory cues for carrying out caste-specific behaviour. In an effort to understand whether organizational differences exist to support these behavioural differences, we studied the olfactory system at the level of the sensilla on the antennae, olfactory glomeruli and the Kenyon cells in the mushroom bodies (MB). The MB differ in major and minor workers in terms of their size, with the major workers having relatively larger calyces and peduncle. The morphology of different types of Kenyon cells as revealed by Golgi-rapid staining was studied and the major workers had more dendritic arbors than minor workers. This suggests a greater degree of olfactory processing in major workers. Differences in caste-specific arrangement of sensilla, olfactory glomeruli and celluar architecture of MB indicate a developmental programme that forms basis of differential behaviour.

Keywords: ant, oecophylla, caste, mushroom body

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Authors: Amin Ebrahimi Ghadi, Morteza Moalagh

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This research is carried out to find how a perfect combination of IoT architecture (Internet of Things) and ERP system can strengthen environmental accounting to incorporate both economic and environmental information. IoT (e.g., sensors, software, and other technologies) can be used in the company’s value chain from raw material extraction through materials processing, manufacturing products, distribution, use, repair, maintenance, and disposal or recycling products (Cradle to Grave model). The desired ERP software then will have the capability to track both midpoint and endpoint environmental impacts on a green supply chain system for the whole life cycle of a product. All these enable environmental accounting to calculate, and real-time analyze the operation environmental impacts, control costs, prepare for environmental legislation and enhance the decision-making process. In this study, we have developed a model on how to use IoT devices in life cycle assessment (LCA) to gather emissions, energy consumption, hazards, and wastes information to be processed in different modules of ERP systems in an integrated way for using in environmental accounting to achieve sustainability.

Keywords: ERP, environmental accounting, green supply chain, IOT, life cycle assessment, sustainability

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Authors: Lena Murawski

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Currently, researchers and experts from the business world recognize entrepreneurial behaviors as a decisive factor for economic success, allowing firms to adapt to changing internal and external needs. The purpose of this study is to explore how gamification can enhance entrepreneurial behaviors, reporting on a gamification project in a new venture operating in the IT sector in Germany. This article is based on data gathered from observations of pre‐ and post‐implementation in the case company. Results have indicated that the use of gamification encourages entrepreneurial behaviors, especially relating to seeking ways on how to integrate new employees, improve teamwork and communication, and to adapt existing processes to increase productivity. The interdisciplinary dialogue furthers our understanding of factors that foster entrepreneurial behaviors. The matter is of practical relevance, guiding practitioners on how to exploit the potentials of gamification to exhibit an entrepreneurial orientation in organizations.

Keywords: case study, entrepreneurial behaviors, gamification, new venture

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Authors: Refilwe Moeletsi

Abstract:

Dimension stone quarrying around Brits and Belfast areas started in the early 1930s and has been growing rapidly since then. Environmental impacts associated with these quarries have not been documented, and hence this study aims at detecting any change in the environment that might have been caused by these activities. Landsat images that were used to assess land use/land cover changes in Brits quarries from 1998 - 2015. A supervised classification using maximum likelihood classifier was applied to classify each image into different land use/land cover types. Classification accuracy was assessed using Google Earth™ as a source of reference data. Post-classification change detection method was used to determine changes. The results revealed significant increase in granite quarries and corresponding decrease in vegetation cover within the study region.

Keywords: remote sensing, GIS, change detection, granite quarries

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Authors: Muhammad Ali Sarwar, Muhammad Farooq, Nayab Hassan, Hammad Hassan

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Pakistan is highly recognized for its agriculture and is well known for producing substantial amounts of wheat, cotton, and sugarcane. However, some factors contribute to a decline in crop quality and a reduction in overall output. One of the main factors contributing to this decline is the presence of weed and its late detection. This process of detection is manual and demands a detailed inspection to be done by the farmer itself. But by the time detection of weed, the farmer will be able to save its cost and can increase the overall production. The focus of this research is to identify and classify the four main types of weeds (Small-Flowered Cranesbill, Chick Weed, Prickly Acacia, and Black-Grass) that are prevalent in our region’s major crops. In this work, we implemented three different deep learning techniques: YOLO-v5, Inception-v3, and Deep CNN on the same Dataset, and have concluded that deep convolutions neural network performed better with an accuracy of 97.45% for such classification. In relative to the state of the art, our proposed approach yields 2% better results. We devised the architecture in an efficient way such that it can be used in real-time.

Keywords: deep convolution networks, Yolo, machine learning, agriculture

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Authors: Shiksha Jain, Ramesh Mishra

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One of the most widely used complex signals processing operation is filtering. The most important FIR digital filter are widely used in DSP for filtering to alter the spectrum according to some given specifications. Power consumption and Area complexity in the algorithm of Finite Impulse Response (FIR) filter is mainly caused by multipliers. So we present a multiplier less technique (DA technique). In this technique, precomputed value of inner product is stored in LUT. Which are further added and shifted with number of iterations equal to the precision of input sample. But the exponential growth of LUT with the order of FIR filter, in this basic structure, makes it prohibitive for many applications. The significant area and power reduction over traditional Distributed Arithmetic (DA) structure is presented in this paper, by the use of slicing of LUT to the desired length. An architecture of 16 tap FIR filter is presented, with different length of slice of LUT. The result of FIR Filter implementation on Xilinx ISE synthesis tool (XST) vertex-4 FPGA Tool by using proposed method shows the increase of the maximum frequency, the decrease of the resources as usage saving in area with more number of slices and the reduction dynamic power.

Keywords: multiplier less technique, linear phase symmetric FIR filter, FPGA tool, look up table

Procedia PDF Downloads 390

Authors: Diego Roberto Goncalves De Pontes, Sergio Donizetti Zorzo

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Studies show that most users do not read privacy policies from the online services they use. Some authors claim that one of the main causes of this is that policies are long and usually hard to understand, which make users lose interest in reading them. In this scenario, users may agree with terms without knowing what kind of data is being collected and why. Given that, we aimed to develop a model that would present the privacy policies contents in an easy and graphical way for the user to understand. We call it the Privacy Label. Using information recovery techniques, we propose an architecture that is able to extract information about what kind of data is being collected and to what end in the policies and show it to the user in an automated way. To assess our model, we calculated the precision, recall and f-measure metrics on the information extracted by our technique. The results for each metric were 68.53%, 85.61% e 76,13%, respectively, making it possible for the final user to understand which data was being collected without reading the whole policy. Also, our proposal can facilitate the notice-and-choice by presenting privacy policy information in an alternative way for online users.

Keywords: privacy, policies, user behavior, computer human interaction

Procedia PDF Downloads 307

Authors: Poteet Frances, Glovinski Ira

Abstract:

INTRODUCTION: The interoceptive nervous system continuously senses chemical and anatomical changes and helps you recognize, understand, and feel what’s going on inside your body so it is important for energy regulation, memory, affect, and sense of self. A newborn needs predictable routines rather than confusion/chaos to make connections between internal experiences and emotions. AIM: Current legal protocols of removing babies from drug-addicted mothers impact the critical window of bonding. The newborn’s brain is social and the attachment process influences a child’s development which begins immediately after birth through nourishment, comfort, and protection. DESCRIPTION: Our project aims to educate drug-addicted mothers, and medical, nursing, and social work professionals on interoceptive concepts and practices to sustain the mother/newborn relationship. A mother’s interoceptive knowledge predicts children’s emotion regulation and social skills in middle childhood. CONCLUSION: When mothers develop an awareness of their inner bodily sensations, they can self-regulate and be emotionally available to co-regulate (support their newborn during distressing emotions and sensations). Our project has enhanced relationship preservation (mothers understand how their presence matters) and the overall mother/newborn connection.

Keywords: drug-addiction, interoception, legal, mothers, newborn, self-regulation

Procedia PDF Downloads 61