Search results for: memory isolation

Authors: Rasha Ahmadi

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In December 2019, a coronavirus, currently identified as SARS-CoV-2, produced a series of acute atypical respiratory illnesses in Wuhan, Hubei Province, China. The sickness induced by this virus was named COVID-19. The virus is transmittable between humans and has caused pandemics worldwide. The number of death tolls continues to climb and a huge number of countries have been obliged to perform social isolation and lockdown. Lack of focused therapy continues to be a problem. Epidemiological research showed that senior patients were more susceptible to severe diseases, whereas children tend to have milder symptoms. In this study, we focus on other possible side effects of COVID-19 and more detailed treatment strategies. Using bioinformatics analysis, we first isolated the gene expression profile of patients with severe COVID-19 from the GEO database. Patients' blood samples were used in the GSE183071 dataset. We then categorized the genes with high and low expression. In the next step, we uploaded the genes separately to the Enrichr database and evaluated our data for signs and symptoms as well as related medication regimens. The results showed that 138 genes with high expression and 108 genes with low expression were observed differentially in the severe COVID-19 VS control group. Symptoms and diseases such as embolism and thrombosis of the abdominal aorta, ankylosing spondylitis, suicidal ideation or attempt, regional enteritis were observed in genes with high expression and in genes with low expression of acute and subacute forms of ischemic heart, CNS infection and poliomyelitis, synovitis and tenosynovitis. Following the detection of diseases and possible signs and symptoms, Carmustine, Bithionol, Leflunomide were evaluated more significantly for high-expression genes and Chlorambucil, Ifosfamide, Hydroxyurea, Bisphenol for low-expression genes. In general, examining the different and invisible aspects of COVID-19 and identifying possible treatments can help us significantly in the emergency and hospitalization of patients.

Keywords: phenotypes, drug regimens, gene expression profiles, bioinformatics analysis, severe COVID-19

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Authors: Haftay Abraha Tadesse, Atsebaha Gebrekidan Kahsay, Mahumd Abdulkader

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Background: Salmonella species and Escherichia coli are important foodborne pathogens affecting humans and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. This study was aimed to determine the prevalence, antimicrobial susceptibility patterns and associated risk factors for Salmonella species and E. coli in raw meat from butchery houses of Mekelle, Northern Ethiopia. Methodology: A cross-sectional study was conducted from January to September 2019. Socio-demographic data and risk factors were collected using a predesigned questionnaire. Meat samples were collected aseptically from the butchery houses and transported using icebox to Mekelle University, College of Veterinary Sciences for the isolation and identification of Salmonella species and E. coli, Antimicrobial susceptibility patterns were determined using Kirby disc diffusion method. Data obtained were cleaned and entered into Statistical Package for the Social Sciences version 22 and logistic regression models with odds ratio were calculated. P-value < 0.05 was considered as statistically significant. Results: A total of 153 out of 384 (39.8%) of the meat specimens were found to be contaminated. The contamination of Salmonella species and E. coli were 15.6% (n=60) and 20.8%) (n=80), respectively. Mixed contamination (Salmonella species and E. coli) was observed in 13 (3.4 %) of the analyzed. Poor washing hands regularly (AOR = 8.37; 95% CI: 2.75-25.50) and not using gloves during meat handling (AOR=11. 28; 95% CI: (4.69 27.10) were associated with an overall bacterial contamination.About 95.5% of the tested isolates were sensitive to chloramphenicol and norfloxacin while the resistance of amoxyclav_amoxicillin and erythromycin were both isolated bacteria species. The overall multidrug resistance pattern for Salmonella and E. coli were 51.4% (n=19) and 31.8% (14), respectively. Conclusion: Of the 153 (153/384) contaminated raw meat, 60 (15.6%) and 80 (20.8%) were contaminated by Salmonella species and E. coli, respectively. Poor hand washing practice and not using glove during meat handling showed significant association with bacterial contamination. Multidrug-resistant showed in Salmonella species and E. coli were 19 (51.4%) and 14 (31.8%), respectively.

Keywords: antimicrobial susceptibility test, butchery houses, e. coli, salmonella species

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Authors: César Coelho, Nikolai Wiegand

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The advancement of nanosatellite technology has opened new avenues for cost-effective and faster space missions. The NanoSat MO Framework (NMF) from the European Space Agency (ESA) provides a modular and simpler approach to the development of flight software and operations of small satellites. This paper presents a methodology using the NMF together with Docker for simulating constellations of satellites. By leveraging Docker containers, the software environment of individual satellites can be easily replicated within a simulated constellation. This containerized approach allows for rapid deployment, isolation, and management of satellite instances, facilitating comprehensive testing and development in a controlled setting. By integrating the NMF lightweight simulator in the container, a comprehensive simulation environment was achieved. A significant advantage of using Docker containers is their inherent scalability, enabling the simulation of hundreds or even thousands of satellites with minimal overhead. Docker's lightweight nature ensures efficient resource utilization, allowing for deployment on a single host or across a cluster of hosts. This capability is crucial for large-scale simulations, such as in the case of mega-constellations, where multiple traditional virtual machines would be impractical due to their higher resource demands. This ability for easy horizontal scaling based on the number of simulated satellites provides tremendous flexibility to different mission scenarios. Our results demonstrate that leveraging Docker containers with the NanoSat MO Framework provides a highly efficient and scalable solution for simulating satellite constellations, offering not only significant benefits in terms of resource utilization and operational flexibility but also enabling testing and validation of ground software for constellations. The findings underscore the importance of taking advantage of already existing technologies in computer science to create new solutions for future satellite constellations in space.

Keywords: containerization, docker containers, NanoSat MO framework, satellite constellation simulation, scalability, small satellites

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Authors: Kumudini Apsara Munasinghe, Devin Gregory Lissau, Ryan Thomas Wade

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Fresh fruits and vegetables are rich in vitamins, minerals, and fibers and help maintain a healthy weight over high-calorie food. Eating fruits and vegetables protects us from free radicals produced by metabolic reactions and safeguards us from cardiovascular disease and cancer. However, there has been an increased concern about foodborne diseases tied to contaminated farmers’ market produce. In addition, very little information is available about the contribution of eating raw fruits and vegetables to human exposure to antibiotic-resistant bacteria. This research aims to identify bacteria isolated from farmers’ market fruits and vegetables and understand their antibiotic resistance. Vegetables and fruits were collected from farmers’ markets around Frostburg and Cumberland areas in Maryland and transported to the microbiology lab at Frostburg State University for the isolation of bacteria. Bacteria were extracted from tomatoes, cucumber, strawberry, and lettuce using Tryptic soy broth overnight at 37°C, and Tryptic Soy agar was used for the streak plate technique to isolate bacteria. Pure cultures were used to identify bacteria using biochemical reactions after conducting Gram staining technique. The research used many biochemical reactions, including Mannitol Salt agar, MacConkey agar, and Eosin Methylene blue agar, for identification. Antibiotic sensitivity was tested for many different types of antibiotics, including amoxicillin, penicillin, tetracycline, ampicillin, and erythromycin. Most prevalent bacteria in the isolates were Staphylococcus, Bacillus, Micrococcus, Enterococcus, Enterobacter, Citrobacter, and other bacteria from the family Enterobacteriaceae. The data obtained from this research will be useful to educate and train farmers and individuals involved in post-harvest processes such as transportation and selling in farmers’ markets. Further results for bacterial antibiotic resistance will be obtained, and unculturable bacteria will be identified by next-generation DNA sequencing.

Keywords: antibiotic resistance, farmers markets, fruits, bacteria, vegetables

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Authors: Małgorzata Tomczyńska, Joanna Saluk-Bijak

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Background: Graves’ disease is a frequent organ-specific autoimmune thyroid disease, which characterized by the presence of different kind autoantibodies, that, in most cases, act as agonists of the thyrotropin receptor, leading to hyperthyroidism. Role of platelets and lymphocytes can be modulated in the pathophysiology of thyroid autoimmune diseases. Interference in the physiology of platelets can lead to enhanced activity of these cells. Activated platelets can bind to circulating lymphocytes and to affect lymphocyte adhesion. Platelets and lymphocytes can regulate mutual functions. Therefore, the activation of T lymphocytes, as well as blood platelets, is associated with the development of inflammation and oxidative stress within the target tissue. The present study was performed to investigate a platelet-lymphocyte relation by assessing the degree of their mutual aggregation in whole blood of patients with Graves’ disease. Also, the purpose of this study was to examine the impact of platelet interaction on lymphocyte migration capacity. Methods: 30 patients with Graves’ disease were recruited in the study. The matched 30 healthy subjects were served as the control group. Immunophenotyping of lymphocytes was carried out by flow cytometry method. A CytoSelect™ Cell Migration Assay Kit was used to evaluate lymphocyte migration and adhesion to blood platelets. Visual assessment of lymphocyte-platelet aggregate morphology was done using confocal microscope after magnetic cell isolation by Miltenyi Biotec. Results: The migration and functional responses of lymphocytes to blood platelets were greater in the group of Graves’ disease patients compared with healthy controls. The group of Graves’ disease patients exhibited a reduced T lymphocyte and a higher B cell count compared with controls. Based on microscopic analysis, more platelet-lymphocyte aggregates were found in patients than in control. Conclusions: Studies have shown that in Graves' disease, lymphocytes show increased platelet affinity, more strongly migrating toward them, and forming mutual cellular conglomerates. This may be due to the increased activation of blood platelets in this disease.

Keywords: blood platelets, cell migration, Graves’ disease, lymphocytes, lymphocyte-platelet aggregates

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Authors: Hongbo Zhang, Xinlu Tang, Jiangwei Li, Chi Yan

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Home zone parking pilot (HPP) is a fast-growing segment in low-speed autonomous driving applications. It requires the car automatically cruise around a parking lot and park itself in a range of up to 100 meters inside a recurrent home/office parking lot, which requires precise parking lot mapping and localization solution. Although Lidar is ideal for SLAM, the car OEMs favor a low-cost fish-eye camera based visual SLAM approach. Recent approaches have employed segmentation models to extract semantic features and improve mapping accuracy, but these AI models are memory unfriendly and computationally expensive, making deploying on embedded ADAS systems difficult. To address this issue, we proposed a new method that utilizes object detection models to extract robust and accurate parking lot features. The proposed method could reduce computational costs while maintaining high accuracy. Once combined with vehicles’ wheel-pulse information, the system could construct maps and locate the vehicle in real-time. This article will discuss in detail (1) the fish-eye based Around View Monitoring (AVM) with transparent chassis images as the inputs, (2) an Object Detection (OD) based feature point extraction algorithm to generate point cloud, (3) a low computational parking lot mapping algorithm and (4) the real-time localization algorithm. At last, we will demonstrate the experiment results with an embedded ADAS system installed on a real car in the underground parking lot.

Keywords: ADAS, home zone parking pilot, object detection, visual SLAM

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Authors: Sandhya Rao

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Kevin Lynch’s Theory on Imeageability, let on explore a city in terms of five elements, Nodes, Paths, Edges, landmarks and Districts. What happens when we try to record the same data in an Indian context? What happens when we apply the same theory of Imageability to a complex shifting urban pattern of the Indian cities and how can we as Urban Designers demonstrate our role in the image building ordeal of these cities? The organizational patterns formed through mental images, of an Indian city is often diverse and intangible. It is also multi layered and temporary in terms of the spirit of the place. The pattern of images formed is loaded with associative meaning and intrinsically linked with the history and socio-cultural dominance of the place. The embedded memory of a place in one’s mind often plays an even more important role while formulating these images. Thus while deriving an image of a city one is often confused or finds the result chaotic. The images formed due to its complexity are further difficult to represent using a single medium. Under such a scenario it’s difficult to derive an output of an image constructed as well as make design interventions to enhance the legibility of a place. However, there can be a combination of tools and methods that allows one to record the key elements of a place through time, space and one’s user interface with the place. There has to be a clear understanding of the participant groups of a place and their time and period of engagement with the place as well. How we can translate the result obtained into a design intervention at the end, is the main of the research. Could a multi-faceted cognitive mapping be an answer to this or could it be a very transient mapping method which can change over time, place and person. How does the context influence the process of image building in one’s mind? These are the key questions that this research will aim to answer.

Keywords: imageability, organizational patterns, legibility, cognitive mapping

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Authors: Prathama Guha Chaudhuri, Arunima Datta, Ashis Mukhopadhyay

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Background: Visualization (guided imagery) is a set of techniques which induce relaxation and help people create positive mental images in order to reduce stress.It is relatively inexpensive and can even be practised by bed bound people. Studies have shown visualization to be an effective tool to improve cancer patients’ anxiety, depression and quality of life. The common images used with cancer patients in the developed world are those involving the individual’s body and its strengths. Since breast cancer patients in India are more family oriented and often their main concerns are the stigma of having cancer and subsequent isolation of their families, including their children, we figured that positive images involving acceptance and integration within family and society would be more effective for them. Method: Data was collected from 119 breast cancer patients on chemotherapy willing to undergo psychotherapy, with no history of past psychiatric illness. Their baseline stress, anxiety, depression and quality of life were assessed using validated tools. The participants were then randomly divided into three groups: a) those who received visualization therapy with standard imageries involving the body and its strengths (sVT), b) those who received visualization therapy using indigenous family oriented imageries (mVT) and c) a control group who received supportive therapy. There were six sessions spread over two months for each group. The psychological outcome variables were measured post intervention. Appropriate statistical analyses were done. Results:Both forms of visualization therapy were more effective than supportive therapy alone in reducing patients’ depression, anxiety and quality of life.Modified VT proved to be significantly more effective in improving patients’ anxiety and quality of life. Conclusion: Visualization is a valuable therapeutic option for reduction of psychological distress and improving quality of life of breast cancer patients.In order to be more effective, the images used need to be modified according to the sociocultural background and individual needs of the patients.

Keywords: breast cancer, visualization therapy, quality of life, anxiety, depression

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Authors: Chrysovalanto Sofia Karatosidi, Dimitra Iordanoglou

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The overlap of leadership skills with personality traits, beliefs, values, and the integration of cognitive abilities, analytical and critical thinking skills into leadership competencies raises the need to segregate further and investigate them. Hence, the domains of cognitive functions that contribute to leadership effectiveness should also be identified. Organizational cognitive neuroscience and neuroleadership can shed light on the study of these critical leadership skills. As the first part of our research, this pilot study aims to explore the relationships between higher-order cognitive functions (executive functions), trait emotional intelligence (EI), personality, and general cognitive ability in leadership. Twenty-six graduate and postgraduate students were assessed on neuropsychological tests that measure important aspects of executive functions (EF) and completed self-reported questionnaires about trait EI, personality, leadership styles, and leadership effectiveness. Specifically, we examined four core EF—fluency (phonemic and semantic), information updating and monitoring, working memory, and inhibition of prepotent responses. Leadership effectiveness was positively associated with phonemic fluency (PF), which involves mental flexibility, in turn, an increasingly important ability for future leaders in this rapidly changing world. Transformational leadership was positively associated with trait EI, extraversion, and openness to experience, a result that is following previous findings. The relationship between specific EF constructs and leadership effectiveness emphasizes the role of higher-order cognitive functions in the field of leadership as an individual difference. EF brings a new perspective into leadership literature by providing a direct, non-invasive, scientifically-valid connection between brain function and leadership behavior.

Keywords: cognitive neuroscience, emotional intelligence, executive functions, leadership

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Authors: Soheila Sadeghi

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Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast project performance metrics, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category in an urban road reconstruction project. The proposed model utilizes time series forecasting techniques, including Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance based on historical data and project progress. The model also incorporates external factors, such as weather patterns and resource availability, as features to enhance the accuracy of forecasts. By applying the predictive power of machine learning, the performance forecasting model enables proactive identification of potential deviations from the baseline plan, which allows project managers to take timely corrective actions. The research aims to validate the effectiveness of the proposed approach using a case study of an urban road reconstruction project, comparing the model's forecasts with actual project performance data. The findings of this research contribute to the advancement of project management practices in the construction industry, offering a data-driven solution for improving project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, earned value management

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Authors: Wajih Abbassi, Zouhaier Ben Khelifa

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The present research points towards the empirical validation of three options valuation models, the ad-hoc Black-Scholes model as proposed by Berkowitz (2001), the constant elasticity of variance model of Cox and Ross (1976) and the Kou jump-diffusion model (2002). Our empirical analysis has been conducted on a sample of 26,974 options written on three indexes, the S&P 500, Nasdaq 100 and the Russell 2000 that were negotiated during the year 2007 just before the sub-prime crisis. We start by presenting the theoretical foundations of the models of interest. Then we use the technique of trust-region-reflective algorithm to estimate the structural parameters of these models from cross-section of option prices. The empirical analysis shows the superiority of the Kou jump-diffusion model. This superiority arises from the ability of this model to portray the behavior of market participants and to be closest to the true distribution that characterizes the evolution of these indices. Indeed the double-exponential distribution covers three interesting properties that are: the leptokurtic feature, the memory less property and the psychological aspect of market participants. Numerous empirical studies have shown that markets tend to have both overreaction and under reaction over good and bad news respectively. Despite of these advantages there are not many empirical studies based on this model partly because probability distribution and option valuation formula are rather complicated. This paper is the first to have used the technique of nonlinear curve-fitting through the trust-region-reflective algorithm and cross-section options to estimate the structural parameters of the Kou jump-diffusion model.

Keywords: jump-diffusion process, Kou model, Leptokurtic feature, trust-region-reflective algorithm, US index options

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Authors: Howaida I. Abd-Alla, Omnia Kutkat, Yassmin Moatasim, Magda T. Ibrahim, Marwa A. Mostafa, Mohamed GabAllah, Mounir M. El-Safty

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Artemisia judaica (known shih-balady), Azadirachta indica and Sophora tomentosa (known yellow necklace pod) are members of available medicinal plants well-known for their traditional medical use in Egypt which suggests that they probably harbor broad-spectrum antiviral, immunostimulatory and anti-inflammatory functions. Their ethyl acetate-dichloromethane (1:1, v/v) extracts were evaluated for the potential anti-Middle East respiratory syndrome-related coronavirus (anti-MERS-CoV) activity. Their cytotoxic activity was tested in Vero-E6 cells using 3-(4,-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method with minor modification. The plot of percentage cytotoxicity for each extract concentration has calculated the concentration which exhibited 50% cytotoxic concentration (TC50). A plaque reduction assay was employed using safe dose of extract to evaluate its effect on virus propagation. The highest inhibition percentage was recorded for the yellow necklace pod, followed by Shih-balady. The possible mode of action of virus inhibition was studied at three different levels viral replication, viral adsorption and virucidal activity. The necklace pod leaves have induced virucidal effects and direct effects on the replication of virus. Phytochemical investigation of the promising necklace pod led to the isolation and structure determination of nine compounds. The structure of each compound was determined by a variety of spectroscopic methods. Compounds 4-O-methyl sorbitol 1, 8-methoxy daidzin 6 and 6-methoxy apigenin-7-O-β-D-glucopyranoside 8 were isolated for the first time from the Sophora genus and the other six compounds were the first time that they were isolated from this species according to available works of literature. Generally, the highest anti-CoV 2 activity of S. tomentosa was associated with the crude ethanolic extract, indicating the possibility of synergy among the antiviral phytochemical constituents (1-9).

Keywords: coronavirus, MERS-CoV, mode of action, necklace pod, shih-balady

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Authors: Gerhardt Boukes, Maryna Van De Venter, Sharlene Govender

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Macrofungi have been used for the past two thousand years in Asian countries, and more recently in Western countries, for their medicinal properties. Biological activities include antimicrobial, antioxidant, anti-inflammatory, antidiabetic, anticancer and immunomodulatory to name a few. Several biologically active compounds have been identified and isolated. Macrofungal research in Africa is poorly documented and to the best of our knowledge non-existent. South Africa has a rich macrofungal biodiversity, which includes endemic and exotic macrofungal species. Ethanolic extracts of 13 macrofungal species, including mushrooms, bracket fungi and puffballs, were prepared and screened for cytotoxicity against a panel of seven cell lines, including A549 (human lung adenocarcinoma), HeLa (human cervical adenocarcinoma), HT-29 (human colorectal adenocarcinoma), MCF7 (human breast adenocarcinoma), MIA PaCa-2 (human pancreatic ductal adenocarcinoma), PC-3 (human prostate adenocarcinoma) and Vero (African green monkey kidney epithelial) cells using MTT. Cell lines were chosen according to the most prevalent cancer types affecting males and females in South Africa and globally, and the mutations they contain. Preliminary results have shown that three of the macrofungal genera, i.e. Fomitopsis, Gymnopilus and Pycnoporus, have shown cytotoxic activity, ranging between IC50 ~20 and 200 µg/mL. The molecular mechanism of action contributing to cell death investigated and being investigated include apoptosis (i.e. DNA cell cycle arrest, caspase-3 activation and mitochondrial membrane potential), autophagy (i.e. acridine orange and LC3B staining) and ER stress (i.e. thioflavin T staining and caspase-12) in the presence of melphalan, chloroquine and thapsigargin/tuncamycin as positive controls, respectively. The genus, Pycnoporus, has shown the best cytotoxicity of the three macrofungal genera. Future work will focus on the identification and isolation of novel active compounds and elucidating the mechanism/s of action.

Keywords: cancer, cytotoxicity, macrofungi, mechanism/s of action

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Tamara Tallman

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Collaboration is a powerful tool for professional development and central for creating opportunities for teachers to reflect on their practice. However, school districts continue to have difficulty both implementing and sustaining collaboration. The purpose of this research was to investigate the experience of the teacher in a creative, instructional collaboration. The teachers in this study found that teacher-initiated collaboration offered them trust and they were more open with their partners. An interpretative phenomenological analysis was used for this study as it told the story of the teacher’s experience. Interpretative Phenomenological Analysis was chosen for this study to capture the complex and contextual nature of the teacher experience from a creative, instructional collaborative experience. This study sought to answer the question of how teachers in a private, faith-based school experience collaboration. In particular, the researcher engaged the study’s participants in interviews where they shared their unique perspectives on their experiences in relation to this phenomenon. Through the use of interpretative phenomenological analysis, the researcher interpreted the experiences of each participant in an attempt to gain deeper insight into how teachers made sense of their understanding of collaboration. In addition to the researcher’s interpreting the meaning of this construct for each research participant, this study gave a voice to the individual experiences and positionality of each participant at the research site. Moreover, the key findings presented in this study shed light on how teachers within this particular context participated in and made sense of their experience of creating an instructional collaborative. The research presented the findings that speak to the meaning that each research participant experienced in their relation to participating in building a collaborative culture and its effect on professional and personal growth. The researcher provided recommendations for future practice and research possibilities. The research findings demonstrated the unique experiences of each participant as well as a connection to the literature within the field of teacher professional development. The results also supported the claim that teacher collaboration can facilitate school reform. Participating teachers felt less isolation and developed more teacher knowledge.

Keywords: collaboration, personal grwoth, professional development, teachers

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Authors: Wang Qiaowei, Gao Yujiang

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With the economic growth and rapid urbanization after the reform and openness, some of China's fast-growing cities have demolished former dwellings and built modern residential quarters. The blind, incomplete reference to western modern cities and the one-off construction lacking feedback mechanism have intensified such phenomenon, causing the citizen gradually expanded their living scale with the popularization of car traffic, and the peer-to-peer lifestyle gradually settled. The construction of large-scale commercial centers has caused obstacles to small business around the residential areas, leading to space for residents' interaction has been compressed. At the same time, the advocated Central Business District (CBD) model even leads to the unsatisfactory reconstruction of many historical blocks such as the Hangzhou Southern Song Dynasty Imperial Street. However, the popularity of historical spaces such as Wuzhen and Hongcun also indicates the collective memory and needs of the street space for Chinese residents. The evolution of Shanghai TianZiFang also proves the importance of the motivation of space participants in space construction in the context of the “top-down” construction model in China. In fact, there are frequent occurrences of “reconstruction”, which may redefine the space, in various residential areas. If these activities can be selectively controlled and encouraged, it will be beneficial to activate the public space as well as the residents’ intercourse, so that the traditional Chinese street space can be reconstructed in the context of modern cities.

Keywords: rapid urbanization, traditional street space, space re-construction, bottom-up design

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Authors: Bharati Mehta, Manish Parakh, Bharti Bhandari, Sneha Ambwani

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Speech and language delay (SLD) is seen commonly as a co-morbidity in children having severe resistant focal and generalized, syndromic and symptomatic epilepsies. It is however not clear whether epilepsy contributes to or is a mere association in the pathogenesis of SLD. Also, it is acknowledged that Auditory Brainstem Evoked Responses (ABER), besides used for evaluating hearing threshold, also aid in prognostication of neurological disorders and abnormalities in the hearing pathway in the brainstem. There is no circumscribed or surrogate neurophysiologic laboratory marker to adjudge the extent of SLD. The current study was designed to evaluate the abnormalities in Electroencephalography (EEG) and ABER in children with SLD who do not have an overt hearing deficit or autism. 94 children of age group 2-8 years with predominant SLD and without any gross motor developmental delay, head injury, gross hearing disorder, cleft lip/palate and autism were selected. Standard video Electroencephalography using the 10:20 international system and ABER after click stimulus with intensities 110 db until 40 db was performed in all children. EEG was abnormal in 47.9% (n= 45; 36 boys and 9 girls) children. In the children with abnormal EEG, 64.5% (n=29) had an abnormal background, 57.8% (n=27) had presence of generalized interictal epileptiform discharges (IEDs), 20% (n=9) had focal epileptiform discharges exclusively from left side and 33.3% (n=15) had multifocal IEDs occurring both in isolation or associated with generalised abnormalities. In ABER, surprisingly, the peak latencies for waves I, III & V, inter-peak latencies I-III & I-V, III-V and wave amplitude ratio V/I, were found within normal limits in both ears of all the children. Thus in the current study it is certain that presence of generalized IEDs in EEG are seen in higher frequency with SLD and focal IEDs are seen exclusively in left hemisphere in these children. It may be possible that even with generalized EEG abnormalities present in these children, left hemispheric abnormalities as a part of this generalized dysfunction may be responsible for the speech and language dysfunction. The current study also emphasizes that ABER may not be routinely recommended as diagnostic or prognostic tool in children with SLD without frank hearing deficit or autism, thus reducing the burden on electro physiologists, laboratories and saving time and financial resources.

Keywords: ABER, EEG, speech, language delay

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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: Sultan Alharby, Nick Harris, Alex Weddell, Jeff Reeve

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The concept of the Internet of Things (IoT) has received much attention over the last five years. It is predicted that the IoT will influence every aspect of our lifestyles in the near future. Wireless Sensor Networks are one of the key enablers of the operation of IoTs, allowing data to be collected from the surrounding environment. However, due to limited resources, nature of deployment and unattended operation, a WSN is vulnerable to various types of attack. Security is paramount for reliable and safe communication between IoT embedded devices, but it does, however, come at a cost to resources. Nodes are usually equipped with small batteries, which makes energy conservation crucial to IoT devices. Nevertheless, security cost in terms of energy consumption has not been studied sufficiently. Previous research has used a security specification of 802.15.4 for IoT applications, but the energy cost of each security level and the impact on quality of services (QoS) parameters remain unknown. This research focuses on the cost of security at the IoT media access control (MAC) layer. It begins by studying the energy consumption of IEEE 802.15.4 security levels, which is followed by an evaluation for the impact of security on data latency and throughput, and then presents the impact of transmission power on security overhead, and finally shows the effects of security on memory footprint. The results show that security overhead in terms of energy consumption with a payload of 24 bytes fluctuates between 31.5% at minimum level over non-secure packets and 60.4% at the top security level of 802.15.4 security specification. Also, it shows that security cost has less impact at longer packet lengths, and more with smaller packet size. In addition, the results depicts a significant impact on data latency and throughput. Overall, maximum authentication length decreases throughput by almost 53%, and encryption and authentication together by almost 62%.

Keywords: energy consumption, IEEE 802.15.4, IoT security, security cost evaluation

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Authors: Henry Kelly, Helena Shaw

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This paper will seek how innovative methods from Health Economics and, to a lesser extent, wellbeing analysis can be applied in the Cost-Benefit Analysis (CBA) of transport infrastructure and policy interventions. The context for this will focus on the framework articulated by the UK Treasury (finance department) and the English Department for Transport. Both have well-established methods for undertaking CBA, but there is increased policy interest, particularly at a regional level of exploring broader strategic goals beyond those traditionally associated with transport user benefits, productivity gains, and labour market access. Links to different CBA approaches internationally, such as New Zealand, France, and Wales will be referenced. By exploring a complementary method of accessing the impacts of policies through the quantification of health impacts is a fruitful line to explore. In a previous piece of work, 14 impact pathways were identified, mapping the relationship between transport and health. These are wide-ranging, from improved employment prospects, the stress of unreliable journey times, and air quality to isolation and loneliness. Importantly, we will consider these different measures of health from an intersectional point of view to ensure that the basis that remains in the health industry does not get translated across to this work. The objective is to explore how a CBA based on these pathways may, through quantifying forecast impacts in terms of Quality-Adjusted Life Years may, produce different findings than a standard approach. Of particular interest is how a health-based approach may have different distributional impacts on socio-economic groups and may favour distinct types of interventions. Consideration will be given to the degree this approach may double-count impacts or if it is possible to identify additional benefits to the established CBA approach. The investigation will explore a range of schemes, from a high-speed rail link, highway improvements, rural mobility hubs, and coach services to cycle lanes. The conclusions should aid the progression of methods concerning the assessment of publicly funded infrastructure projects.

Keywords: cost-benefit analysis, health, QALYs transport

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Authors: Fae Princess Bermudez

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Background: One of the least significant leads on a 12-lead electrocardiogram is the augmented right lead (aVR), as it is not as specific compared to the other leads. In this case series, the value of lead aVR, which is more often than not ignored, is highlighted. Three cases of aVR ST segment elevation on 12-lead electrocardiogram are described, with the end outcome of demise of all three patients. The importance of immediate revascularization is described to improve prognosis in this group of patients. Objectives: This case series aims to primarily present under-reported cases of isolated aVR ST-segrment elevation myocardial infarction (STEMI), their course and outcome. More specific aims are to identify the criteria in determination of isolated aVR STEMI, know its clinical significance, and determine appropriate management for patients with this ECG finding. Method: A short review of previous studies, case reports, articles and guidelines from 2011-2016 was done. The author reviewed available literature, sorted out those that proved to be significant for the presented cases, and described them in conjunction with the aforementioned cases. Findings: Based on the limited information on these rare or under-reported cases, it was found that isolated aVR STEMI had a poorer prognosis that led to significant mortality and morbidity of patients. The significance of aVR ST-elevation was that of an occlusion of the left coronary artery or a severe three-vessel disease in the presence of an Acute Coronary Syndrome. Guidelines from American Heart Association/American College of Cardiology Foundation in 2013 already recognized ST-elevation of lead aVR in isolation as a STEMI; hence, recommended that patients with this particular ECG finding should undergo reperfusion strategies to improve prognosis. Conclusion: The indispensability of isolated aVR ST-segment elevation on ECG should alert physicians, especially Emergency physicians, to the high probability of Acute Coronary Syndrome with a very poor prognosis. If this group of patients is not promptly managed, demise may ensue, with cardiogenic shock as the most probable cause. With this electrocardiogram finding, physicians must be quick to make clinical decisions to increase chances of survival of this group of patients.

Keywords: AVR ST-elevation, diffuse ST-segment depression, left coronary artery infarction, myocardial infarction

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Authors: Denis Mustafov, Emmanouil Karteris, Maria Braoudaki

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Glioblastoma multiform (GBM) is a heterogenous primary brain tumour that kills most affected patients. To the authors best knowledge, despite all research efforts there is no early diagnostic biomarker for GBM. MicroRNAs (miRNAs) are short non-coding RNA molecules which are deregulated in many cancers. The aim of this research was to determine miRNAs with a diagnostic impact and to potentially identify promising therapeutic targets for glioblastoma multiform. In silico analysis was performed to identify deregulated miRNAs with diagnostic relevance for glioblastoma. The expression profiles of the chosen miRNAs were then validated in vitro in the human glioblastoma cell lines A172 and U-87MG. Briefly, RNA extraction was carried out using the Trizol method, whilst miRNA extraction was performed using the mirVANA miRNA isolation kit. Quantitative Real-Time Polymerase Chain Reaction was performed to verify their expression. The presence of five target proteins within the A172 cell line was evaluated by Western blotting. The expression of the CORO1C protein within 32 GBM cases was examined via immunohistochemistry. The miRNAs identified in silico included miR-21-5p, miR-34a and miR-128a. These miRNAs were shown to target deregulated GBM genes, such as CDK6, E2F3, BMI1, JAG1, and CORO1C. miR-34a and miR-128a showed low expression profiles in comparison to a control miR-RNU-44 in both GBM cell lines suggesting tumour suppressor properties. Opposing, miR-21-5p demonstrated greater expression indicating that it could potentially function as an oncomiR. Western blotting revealed expression of all five proteins within the A172 cell line. In silico analysis also suggested that CORO1C is a target of miR-128a and miR-34a. Immunohistochemistry demonstrated that 75% of the GBM cases showed moderate to high expression of CORO1C protein. Greater understanding of the deregulated expression of miR-128a and the upregulation of CORO1C in GBM could potentially lead to the identification of a promising diagnostic biomarker signature for glioblastomas.

Keywords: non-coding RNAs, gene expression, brain tumours, immunohistochemistry

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Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: L. Freeborn

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This paper discusses the application of complex dynamic system theory (DST) to the study of individual differences in second language development. This transdisciplinary framework allows researchers to view the trajectory of language development as a dynamic, non-linear process. A DST approach views language as multi-componential, consisting of multiple complex systems and nested layers. These multiple components and systems continuously interact and influence each other at both the macro- and micro-level. Dynamic systems theory aims to explain and describe the development of the language system, rather than make predictions about its trajectory. Such a holistic and ecological approach to second language development allows researchers to include various research methods from neurological, cognitive, and social perspectives. A DST perspective would involve in-depth analyses as well as mixed methods research. To illustrate, a neurobiological approach to second language development could include non-invasive neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to investigate areas of brain activation during language-related tasks. A cognitive framework would further include behavioural research methods to assess the influence of intelligence and personality traits, as well as individual differences in foreign language aptitude, such as phonetic coding ability and working memory capacity. Exploring second language development from a DST approach would also benefit from including perspectives from the field of applied linguistics, regarding the teaching context, second language input, and the role of affective factors such as motivation. In this way, applying mixed research methods from neurobiological, cognitive, and social approaches would enable researchers to have a more holistic view of the dynamic and complex processes of second language development.

Keywords: dynamic systems theory, mixed methods, research design, second language development

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Authors: Elida Cena

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Return migration is receiving increased attention as the phenomenon challenges assumptions of natural ‘homecomings’. This talk outlines preliminary findings from an ongoing PhD study which explores return migration of Albanian migrants (aged 30-50 years) and their children (aged 7-18 years). Participants (n=51) were purposively recruited from two Albanian cities with divergent social and economic conditions, and the majority had returned from Greece following the recent economic downturn in that country. Qualitative data were collected through in-depth interviews with respondents aged 13 years and above, and were augmented with focus groups and family case studies. Data collection for case studies was aided by photo elicitation, interviews and participatory techniques (drawing) were employed for children aged 7-12 years. Through a multidisciplinary perspective, findings will uncover experiences of migrants and children upon return, the quest to identify with the originating country and create a sense of belongingness. Narrative analysis reveals that the abrupt return was associated with ambivalent feelings and disillusionment about their (re)settlement for both younger and older participants. Faced with unexpected realities and lack of opportunities, particularly for the children of migrants, Albania is viewed as a ‘transit country’, a temporary solution to escape the crisis in the destination country and move to a more developed western country. Adult return migrants articulate lack of employment and insecurity for the future. Apart from school difficulties, children experience isolation and social exclusion, marked by stigmatized labelling from other peers which exacerbates their belonging. Such mobilities have had deeper effects in complicating family relationships as influenced by many disintegration factors. Feelings of alienation and being emigrant for the second time were common in participants' accounts. Findings concerning the difficulties of individuals (re)connecting with their ethnic background and the impact on their identities are discussed in relation to the literature on return migration and identification.

Keywords: return migration, belonging, identity, disintegration, integration

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Authors: Gabriella Dravecz, László Péter, Zsolt Kis

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Abstract— The growth of optical LiNbO3 single crystal and its physical and chemical properties are well known on the macroscopic scale. Nowadays the rare-earth doped single crystals became important for coherent quantum optical experiments: electromagnetically induced transparency, slow down of light pulses, coherent quantum memory. The expansion of applications is increasingly requiring the production of nano scaled LiNbO3 particles. For example, rare-earth doped nanoscaled particles of lithium niobate can be act like single photon source which can be the bases of a coding system of the quantum computer providing complete inaccessibility to strangers. The polyol method is a chemical synthesis where oxide formation occurs instead of hydroxide because of the high temperature. Moreover the polyol medium limits the growth and agglomeration of the grains producing particles with the diameter of 30-200 nm. In this work nano scaled LiNbO3 was prepared by the polyol method. The starting materials (niobium oxalate and LiOH) were diluted in H2O2. Then it was suspended in ethylene glycol and heated up to about the boiling point of the mixture with intensive stirring. After the thermal equilibrium was reached, the mixture was kept in this temperature for 4 hours. The suspension was cooled overnight. The mixture was centrifuged and the particles were filtered. Dynamic Light Scattering (DLS) measurement was carried out and the size of the particles were found to be 80-100 nms. This was confirmed by Scanning Electron Microscope (SEM) investigations. The element analysis of SEM showed large amount of Nb in the sample. The production of LiNbO3 nano particles were succesful by the polyol method. The agglomeration of the particles were avoided and the size of 80-100nm could be reached.

Keywords: lithium-niobate, nanoparticles, polyol, SEM

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Authors: Anna Siegler

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Bullying among peers is not uncommon; however, adults can notice only a fragment of the cases of harassment during everyday life. The systemic approaches of bullying investigation put the whole school community in the focus of attention and propose that the solution should emerge from the culture of the school. Bystanders are essential in the prevention and intervention processes as an active agent rather than passive. For combating exclusion, stigmatization and harassment, it is important that the bystanders have to realize they have the power to take action. To prevent the escalation of violence, victims must believe that students and teachers will help them and their environment is able to provide safety. The study based on scientific narrative psychological approach, and focuses on the examination of the different perspectives of students, how peers are mentalizing with each other in case of bullying. The data collection contained responses of students (N = 138) from three schools in Hungary, and from three different area of the country (Budapest, Martfű and Barcs). The test battery include Bullying Prevalence Questionnaire, Interpersonal Reactivity Index and an instruction to get narratives about bullying, which effectiveness was tested during a pilot test. The obtained results are in line with the findings of previous bullying research: the victims are mentalizing less with their peers and experience greater personal distress when they are in identity threatening situations, thus focusing on their own difficulties rather than social signals. This isolation is an adaptive response in short-term although it seems to lead to a deficit in social skills later in life and makes it difficult for students to become socially integrated to society. In addition the results also show that students use more mental state attribution when they report verbal bullying than in case of physical abuse. Those who witness physical harassment also witness concrete answers to the problem from teachers, in contrast verbal abuse often stays without consequences. According to the results students mentalizing more in these stories because they have less normative explanation to what happened. To expanding bullying literature, this research helps to find ways to reduce school violence through community development.

Keywords: bullying, mentalization, narrative, school culture

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Authors: Junita Batubara

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Children with special needs, especially those with disability in mental, physical or social/emotional interactions, are marginalized. Many people still view them as troublesome, inconvenience, having learning difficulties, unproductive and burdensome to society. This study intends to investigate; how musical drama can develop the ability to control the coordination of mental functions; how musical dramas can assist children to work together; how musical dramas can assist to maintain the child's emotional and physical health; how musical dramas can improve children creativity. The objectives of the research are: To know whether musical drama can control the coordination of mental function of children; to know whether musical drama can improve communication ability and expression of children; to know whether musical drama can help children work with people around them; to find out if musical dramas can develop the child's emotional and physical health; to find out if musical drama can improve children's creativity. The study employed a qualitative research approach. Data was collecting by listening, observing in depth through public hearings that select the key informants who were teachers and principals, parents and children. The data obtained from each public hearing was then processed (reduced), conclusion drawing/verification, presentation of data (data display). Furthermore, the model obtained was implementing for musical performance, where the benefits of the show are: musical drama can improve language skills; musical dramas are capable of developing memory and storage of information; developing communication skills and express themselves; helping children work together; assisting emotional and physical health; enhancing creativity.

Keywords: children Down syndrome, music, drama script, performance

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Authors: Mohamed Trigui, Fatma Masmoudi, Imen Zouari

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Massive utilizations of chemical fertilizer and chemical pesticides in agriculture sector to improve the farming productivity have created increasing environmental damages. Then, agriculture must become sustainable, focusing on production systems that respect the environment and help to reduce climate change. Isolation and microbial identification of new bacterial strains from naturally saline habitats and compost extracts could be a prominent way in pest management and crop production under saline conditions. In this study, potential mechanisms involved in plant growth promotion and suppressive activity against fungal diseases of a compost extract produced from poultry manure/olive husk compost and halotolerant and halophilic bacterial strains under saline stress were investigated. On the basis of the antimicrobial tests, different strains isolated from Sfax solar saltern (Tunisia) and from compost extracts were selected and tested for their plant growth promoting traits, such as siderophores production, nitrogen fixation, phosphate solubilization and the production of extracellular hydrolytic enzymes (protease and lipase) under in-vitro conditions. Among 450 isolated bacterial strains, 16 isolates showed potent antifungal activity against the tested plant pathogenic fungi. Their identification based on 16S rRNA gene sequence revealed they belonged to different species. Some of these strains were also characterized for their plant growth promoting capacities. Obtained results showed the ability of four strains belonging to Bacillus genesis to ameliorate germination rate and root elongation compared to the untreated positive controls. Combinatorial capacity of halotolerant bacteria with antimicrobial activity and plant growth promoting traits could be promising sources of interesting bioactive substances under saline stress.

Keywords: abiotic stress, biofertilizer, biotic stress, compost extract, halobacteria, plant growth promoting (PGP), soil fertility

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Authors: Ayan Handulle, Memory J. Tembo-Pankuku

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The social work profession utilizes Western and Eurocentric perspectives on social structures, culture, history, belief systems, and education. This affects social work practice with indigenous groups as well as other minorities who have different perspectives. Some of the challenges that characterize social work with families, especially immigrants in western countries, are a result of different world views on child-rearing practices in the global north and the global south. A shift towards cultural sensitivity and the promotion of cultural competence has been a move towards addressing some of the challenges in child welfare practice with immigrants. However, emphasis on cultural differences presents other challenges of stereotyping and discrimination, which call for the examination of current practices to fit other groups of people. In this paper, we introduce the need for emancipatory social work in child welfare practice with immigrant parents. Emancipatory social work is directed at heightening awareness of external sources of oppression and/or privilege that hold the possibility of increasing self-esteem and courage to confront structural sources of marginalization, oppression, and exclusion. This paper draws on two research projects, respectively, “Immigrant parents’ perceptions and experiences of the welfare system” and “Norwegian- Somali parents’ fears of the Norwegian Child welfare service. The first data set comprises 15 in-depth interviews with 18 nonWestern immigrant parents, representing 10 families. The second data set consists of nine months of ethnography, seven months in Oslo, and two months in Somalia among returnees from Norway. Based on these data sets, we explore how immigrant parents’ child-rearing practices might be perceived through a racialized lens.

Keywords: child welfare, immigrants, racialization, social work

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