Search results for: systemic approaches

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

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

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

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Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi

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Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.

Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix

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Authors: İkbal Eski

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This investigation is researched on design of robust neural network predictors for analyzing vibration effects on moving parts of a drilling machine. Moreover, the research is divided two parts; first part is experimental investigation, second part is simulation analysis with neural networks. Therefore, a real time the drilling machine is used to vibrations during working conditions. The measured real vibration parameters are analyzed with proposed neural network. As results: Simulation approaches show that Radial Basis Neural Network has good performance to adapt real time parameters of the drilling machine.

Keywords: artificial neural network, vibration analyses, drilling machine, robust

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Authors: Bashar Dahiru Bashar

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Growing research reveals an unprecedented increase in African applicants for PhD positions across European universities. Meanwhile, a very small percentage is accepted as qualified candidates to marginalize, perpetuate stereotypes, and institute racial discrimination. Candidates of color very often encounter barriers and prejudices that not only diminish their sense of belonging but also hinder their academic progress. Although this issue has existed for quite some time, it attracts little attention, even from the academic community in higher education. Moreover, the focus is mostly on the applicants. In this contribution, concern has been raised that the African applicants for PhD positions in European Universities are the victims rather than the perpetrators. The Universities designed a recruitment process that is in all respects exclusive, biased, and European. The recruitment exercise is a hocus-post in order to cover language and racial and ethnic rejection. Just in the same way legacy admission is practiced in the US. The paper further expressed that the logic is to systematically maintain racial hierarchy and social dominance within the education sector. And because those at an advantage are also the ones that have the media and are predominant in academia, issues like this are not receiving deserved attention. Many people were victims of this recruitment process, while others survived severely wounded as a result of mental, social, and economic trauma. It is not the aim of this paper to provide an armchair solution to this issue but only to showcase the process with the hope of providing something that is needed to improve the present day's literacy and situation. The findings contribute to the broader discourse on diversity, equity, and inclusiveness within European Universities, emphasizing, amongst others, the need for cultivating an atmosphere where individuals are valued for their contributions rather than assessed based on race and ethnicity is essential for creating a vibrant and equitable global academic community, forging a path towards a just and harmonious educational landscape where everyone irrespective of race or ethnicity can thrive and contribute to the collective pursuit of knowledge.

Keywords: admission and recruitment for PhD position, globalization of education, systemic rejection, European university

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Authors: Lisa Gray, Henry Kronner, Tameca Harris-Jackson, Mimi Sodhi, Ruth Gerritsen-McKane, Donette Considine

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The MSW Peer Mentorship Program (PMP) was developed as one of several approaches to foster student success. The key purposes of the PMP are to help new graduate students transition to a graduate program, facilitate relationship building between students, grow and sustain student satisfaction, and build a strong connection to the MSW program. This pilot program also serves as an additional source of support for students during the era of the Covid-19 pandemic. Further, the long-term goals of the program are to assist in student retention. Preliminary findings suggest that both mentors and mentees enrolled in PMP find the peer mentoring relationship to have a positive impact on their graduate learning experience.

Keywords: covid-19, mentorship, peer support, student success

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Authors: Ouazoul Abdeloauhd, Jemjami Nadia

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The concept of well-being at work is one of today's significant challenges in maintaining quality of life and managing psycho-social risks at work. Indeed, work in the sports sector has evolved, and this exponential evolution, marked by increasing demands and psychological, physical, and social challenges, which sometimes exceed the resources of sports actors, influences their sense of well-being at work. Well-being and burnout as antagonists provide information on the quality of working life in sports. The Basic aim of this literature review is to analyze the scientific corpus dealing with the subject of well-being at work in the sports sector while exploring the link between sports burnout and well-being. The results reveal the richness of the conceptual approaches and the difficulties of implementing them. Prospects for future research have, therefore, been put forward.

Keywords: well-being, burnout, quality of life, psycho-social risk, work on sports sector

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Authors: Mehrnaz Mostafavi

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Lung cancer is one of the most harmful forms of cancer. The long-term survival rate of lung cancer patients treated by conventional modalities such as surgical resection, radiation, and chemotherapy remains far from satisfactory. Systemic drug delivery is rarely successful because only a limited amount of the chemotherapeutic drug targets lung tumor sites, even when administered at a high dose. Targeted delivery of drug molecules to organs or special sites is one of the most challenging research areas in pharmaceutical sciences. By developing colloidal delivery systems such as liposomes, micelles and nanoparticles a new frontier was opened for improving drug delivery. Nanoparticles with their special characteristics such as small particle size, large surface area and the capability of changing their surface properties have numerous advantages compared with other delivery systems. Targeted nanoparticle delivery to the lungs is an emerging area of interest.Multimodal or combination therapy represents a promising new method to fight disease. Therefore, a combination of different therapeutic strategies may be the best alternative to improve treatment outcomes for lung cancer. Photothermal therapy was proposed as a novel approach to treatment. In this work, photothermal therapy with gold nanoparticles and near infrared laser (NIR) irradiation was investigated.Four types of small (<100nm), NIR absorbing gold nanoparticles (nanospheres, nanorods) were synthesized using wet chemical methods and characterized by transmission electron microscopy, dynamic light scattering and UV-vis spectroscopy. Their synthesis and properties were evaluated, to determine their feasibility as a photothermal agent for clinical applications. In vitro cellular uptake studies of the nanoparticles into lung cancer cell lines was measured using light scattering microscopy.Small gold nanorods had good photothermal properties and the greatest cellular uptake, and were used in photothermal studies. Under 4W laser irradiation, an increase in temperature of 10°C and decrease in cell viability of up to 80% were obtained.

Keywords: photothermal, therapy, cancer, gold nanorods

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Authors: Abbas Al-Refaie

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The research examines the factors that affect customer churn (CC) in the Jordanian telecom industry. A total of 700 surveys were distributed. Cluster analysis revealed three main clusters. Results showed that CC and customer satisfaction (CS) were the key determinants in forming the three clusters. In two clusters, the center values of CC were high, indicating that the customers were loyal and SC was expensive and time- and energy-consuming. Still, the mobile service provider (MSP) should enhance its communication (COM), and value added services (VASs), as well as customer complaint management systems (CCMS). Finally, for the third cluster the center of the CC indicates a poor level of loyalty, which facilitates customers churn to another MSP. The results of this study provide valuable feedback for MSP decision makers regarding approaches to improving their performance and reducing CC.

Keywords: cluster analysis, telecom industry, switching cost, customer churn

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Authors: Ghorab Sara, Meziani Lila, Rubin Harvey Stuart

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The rapid growth of deep learning has led to intricate and resource-intensive deep neural networks widely used in computer vision tasks. However, their complexity results in high computational demands and memory usage, hindering real-time application. To address this, research focuses on model compression techniques. The paper provides an overview of recent advancements in compressing neural networks and categorizes the various methods into four main approaches: network pruning, quantization, network decomposition, and knowledge distillation. This paper aims to provide a comprehensive outline of both the advantages and limitations of each method.

Keywords: model compression, deep neural network, pruning, knowledge distillation, quantization, low-rank decomposition

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Authors: Piroska Biró, Mária Csernoch, János Máth, Kálmán Abari

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Testing the first year students of Informatics at the University of Debrecen revealed that students start their tertiary studies in programming with a low level of programming knowledge and algorithmic skills. The possible reasons which lead the students to this very unfortunate result were examined. The results of the test were compared to the students’ results in the school leaving exams and to their self-assessment values. It was found that there is only a slight connection between the students’ results in the test and in the school leaving exams, especially at intermediate level. Beyond this, the school leaving exams do not seem to enable students to evaluate their own abilities.

Keywords: deep and surface approaches, metacognitive abilities, programming and algorithmic skills, school leaving exams, tracking code

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Authors: Manish Jain, Dinesh Gopalani

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Growing dependency of mankind on software technology increases the need for thorough testing of the software applications and automated testing techniques that support testing activities. We have outlined our testing strategy for performing various types of automated testing of Java applications using AspectJ which has become the de-facto standard for Aspect Oriented Programming (AOP). Likewise JUnit, a unit testing framework is the most popular Java testing tool. In this paper, we have evaluated our proposed AOP approach for automated testing and JUnit on various parameters. First we have provided the similarity between the two approaches and then we have done a detailed comparison of the two testing techniques on factors like lines of testing code, learning curve, testing of private members etc. We established that our AOP testing approach using AspectJ has got several advantages and is thus particularly more effective than JUnit.

Keywords: aspect oriented programming, AspectJ, aspects, JU-nit, software testing

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Authors: M.R Asghari Bejestani, Gh. R. Mohammad Khani, V.R. Nafisi

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Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works.

Keywords: brain computer interface, silent talk, imagined speech, classification, signal processing

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Authors: Janette Porter, Kay Standing

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The paper presents our experiences of working in both mainstream and Special Education Needs and Disabilities (SEND) schools in England from 2012-2019, using creative methodologies to deliver and evaluate healthy relationship education. It aims to explore to explore how young people's perceptions of relationships and their "perfect partner" are mediated by factors such as gender, body image, and social media. It will be an interactive session, inviting participants to reflect on their own experiences of relationship education, and to take part in an example of a classroom activity of 'a perfect partner'. Young people aged 16-25 are most at risk of relationship abuse and intimate partner violence. This can be enacted both on the body, through physical and sexual violence, but also emotional and psychological abuse. In England and Wales relationship education became compulsory in schools in September 2020. There is increasing recognition for the need for whole school approaches to prevent gender-based violence, in particular domestic abuse, from happening in the first place and for equipping schools to feel more confident supporting young people affected by gender-based violence. The project used creative methods, including arts, drama, music, poetry, song, and creative writing, to engage participants in sensitive topics related to relationship education. Interactive workshops with pupils aged 11-19 enabled young people to express themselves freely, pupils then used drama to share their knowledge with their peer group. We co-produced material with young people, including an accessible resource pack for use in SEND schools, particularly for children with visual and sensory impairments. The project was evaluated by questionnaires and interviews with pupils. The paper also reflects on the ethical issues involved in the research. After the project, young people had a better understanding of healthy and unhealthy relationships, improved knowledge of the early warning signs of abuse and knew where to go to for help and advice. It found that creative methods are an effective way to engage young people in relationship education and sensitive topics. We argue that age and ability appropriate relationship education should be compulsory across the curriculum and that implementing creative and art-based approaches to address sensitive topics can enhance the effectiveness of relationship education programs in promoting healthy relationships and preventing abuse. The paper provides academic and practitioner perspectives, providing a reflection on our research, looking at practical, methodological, and ethical issues involved in research on Gender Based Violence with young people in a school setting.

Keywords: relationship education, healthy relationships, creative methods, young people

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Authors: Desiree Llaguno Cerezo, Elizabeth Valdes-Miranda Fernandez

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Women have a critical role in sustaining the economy and in the development of trade. However, such a role has long been invisible due to orthodox conceptions that have ignored the gender variable in commercial analyses. Today, it is generally accepted that neither the economy nor business are gender-neutral and that the performance of these activities often impact negatively the lives of women. Women’s participation in trade, on equal terms as men, in any of the various possible roles -producer, wage earner, consumer, merchant, taxpayer- will not only favour the lives of women but also the performance of the economies in which they participate. Transparency, as a principle of the multilateral trading system, can play a significant role as a strategy for the empowerment of women.

Keywords: trade, human rights, gender equality, transparency, WTO, women workers, women's economic empowerment

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Authors: Naufal Ahmad Rijalul Alam

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This article presents a quality of education for the poor people in Indonesia and the offering of strategy to be done. It also investigates the influence of Islamic Education which stands behind the religious values in developing effort of government to respond the problem with using humanities approaches in medium society. The offering strategy resulted in four agenda: 1) building a shared commitment, 2) encouraging the improvement of the quality of public and private schools, 3) encouraging the use of 'the indicator of disaffection' for gifted children, and 4) encouraging the enlargement of vocational training centers and polytechnics. The conclusion is that the quality of education can be increased with these four agenda, although they are not too easy because it deals with other factors such as the economy, politics, and culture which is happening in the country.

Keywords: quality education, poor people, strategy of Islamic education, medium community

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Authors: Fergal Fouhy, Alan O’Keeffe, Sean Costelloe, Michael Clarkson

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Background: Sarcoidosis is a systemic, non-infectious disease of unknown aetiology, characterized by non-caseating granulomatous inflammation. The lung is most often affected (90%); however, the condition can affect all organs, including the kidneys. There is limited evidence describing the incidence and characteristics of renal involvement in sarcoidosis. Serum angiotensin-converting enzyme (ACE) is a recognised biomarker used in the diagnosis and monitoring of sarcoidosis. Methods: A single-centre, retrospective cohort study of patients presenting to Cork University Hospital (CUH) in 2015 with first-time elevations of serum ACE was performed. This included an initial database review of ACE and other biochemistry results, followed by a medical chart review to confirm the presence or absence of sarcoidosis and management thereof. Acute kidney injury (AKI) was staged using the AKIN criteria, and chronic kidney disease (CKD) was staged using the KDIGO criteria. Follow-up was assessed over five years tracking serum creatinine, serum calcium, and estimated glomerular filtration rates (eGFR). Results: 119 patients were identified as having a first raised serum ACE in 2015. Seventy-nine male patients and forty female patients were identified. The mean age of patients identified was 47 years old. 11% had CKD at baseline. 18% developed an AKI at least once within the next five years. A further 6% developed CKD during this time period. 13% developed hypercalcemia. The patients within the lowest quartile of serums ACE had an incidence of sarcoidosis of 5%. None of this group developed hypercalcemia, 23% developed AKI, and 7% developed CKD. Of the patients with a serum ACE in the highest quartile, almost all had documented diagnoses of sarcoidosis with an incidence of 96%. 3% of this group developed hypercalcemia, 13% AKI and 3% developed CKD. Conclusions: There was an unexpectedly high incidence of AKI in patients who had a raised serum ACE. Not all patients with a raised serum ACE had a confirmed diagnosis of sarcoidosis. There does not appear to be a relationship between increased serum ACE levels and increased incidence of hypercalcaemia, AKI, and CKD. Ideally, all patients should have biopsy-proven sarcoidosis. This is an initial study that should be replicated with larger numbers and including multiple centres.

Keywords: sarcoidosis, acute kidney injury, chronic kidney disease, hypercalcemia

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Authors: Chantelle Francis, Karen McKenzie, Charlotte Emmerson

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In the context of the rise in mental health difficulties amongst pupils, this review explores the factors that have been indicated as affecting psychological well-being in mainstream school contexts. Search terms relating to school-based psychological well-being were entered into five databases, and twenty-two studies were included in the review. The results suggested that pupil psychological well-being is affected by both direct and indirect factors. The former included a sense of belonging and inclusion, relationships with teachers, and academic attainment. The latter included family socioeconomic status, whole-school approaches, and individual differences factors, such as gender and Special Educational Needs. The implications for policymakers and practitioners are discussed.

Keywords: psychological wellbeing, mainstream schools, special educational needs, school-based wellbeing

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Authors: Mahfoud Djebbar

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The past two decades or so have witnessed phenomenal growth of the Islamic financial services industry. The whole industry has been thriving at about 15 percent per annum. This development entails the Islamic financial engineering, IFE, to some kind of crossroads, lagging behind its conventional counterpart. Therefore, IFE, and particularly traded products development, and in order to achieve its goals, two approaches are available, i.e., replicating engineering and innovative engineering. We also try to emphasis the innovative strategy since it guards the Islamic identity of different financial products and processes, and thereby, improves the creativity in the Islamic financial industry. The attempt also centers on sukukization (Islamic securitization), innovation, liquidity management, and risk management and hedging in the Islamic financial system. Finally, the challenges facing IFE are also addressed.

Keywords: islamic financial engineering, hedging and risk management, innovation, securitization, money market instruments, islamic capital markets

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Authors: Deniss Rozkov, Hendrik Idema

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This paper researches the gender-based differences among US-American institutional investors regarding their preferences for sustainable development goals (SDGs) when investing. After employing a structured questionnaire as well as applying a choice-based conjoint analysis, it is found that female investors place significantly more emphasis on SDGs, especially in the social and ecological domain, exhibiting significantly stronger “other-regarding” characteristics compared to their male counterparts. Further, the results of the survey show that females show significantly higher risk aversion than males by selecting moderately conservative and moderate risk approaches.

Keywords: sustainable development goals, investing, socially responsible investor, gender, conjoint analysis

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Authors: Fatima Sohail, Faizan Iftikhar

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This paper studies the relationship between digital finance, renewable energy, and the economic development of Pakistan and least developed countries from 2000 to 2022. The paper used panel analysis and generalized method of moments Arellano-Bond approaches. The findings show that under the growth model, renewable energy (RE) has a strong and favorable link with fixed broadband and mobile subscribers. However, FB and MD have a strong but negative association with the uptake of renewable energy (RE) in the average and simple model. This paper provides valuable insights for policymakers, investors of the digital economy.

Keywords: digital finance, renewable energy, economic development, mobile subscription, fixed broadband

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Authors: Joanne Robertson, Awneet Sivia

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Preparing aspiring teachers to become advocates for social justice reflects a fundamental commitment for teacher education programs in Canada to create systemic educational change. The goal is ultimately to address inequities in K-12 education for students from multiple identity groups that have historically been marginalized and oppressed in schools. Social justice is described as an often undertheorized and vague concept in the literature, which increases the risk that teaching for social justice remains a lofty goal. Another concern is that the social justice agenda in teacher education in North America ignores pedagogies related to subject-matter knowledge and discipline-based teaching methods. The question surrounding how teacher education programs can address these issues forms the basis for the research undertaken in this study. The paper focuses on a qualitative research project that examines how an Equity Literature Circles (ELC) framework within a language arts methods course in a Bachelor of Education program may help pre-service teachers better understand the inherent relationship between literacy instructional practices and teaching about and for social justice. Grounded in the Freireian (2018) principle of praxis, this study specifically seeks to understand the impact of Equity Literature Circles on pre-service teachers’ understanding of current social justice issues (reflection), their development of professional competencies in literacy instruction (practice), and their identity as advocates of social justice (action) who address issues related to student diversity, equity, and human rights within the English Language Arts program. In this paper presentation, participants will be provided with an overview of the Equity Literature Circle framework, a summary of key findings and recommendations from the qualitative study, an annotated bibliography of suggested Young Adult novels, and opportunities for questions and dialogue.

Keywords: literacy, language, equity, social justice, diversity, human rights

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Authors: Hyekyung Woo, Gwihyun Kim

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mHealth, which encompasses mobile health technologies and interventions, is rapidly evolving in various medical specialties, and its impact is evident in oncology. This review describes current trends in research addressing the integration of mHealth into the management of breast cancer by examining evaluations of mHealth and its contributions across the cancer care continuum. Mobile technologies are perceived as effective in prevention and as feasible for managing breast cancer, but the diagnostic accuracy of these tools remains in doubt. Not all phases of breast cancer treatment involve mHealth, and not all have been addressed by research. These drawbacks in the application of mHealth to breast cancer management call for intensified research to strengthen its role in breast cancer care.

Keywords: mobile application, breast cancer, content analysis, mHealth

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Authors: Phillipa Denise Peart

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Black Asian and Minority Ethnic (BAME) people are more at risk of developing mental health disorders because they are more exposed to unfavorable social, economic, and environmental circumstances. These include housing, education, employment, community development, stigma, and discrimination. However, the majority of BAME mental health intervention studies focus on treatment with therapeutically effective drugs and use basic economic methods to evaluate their effectiveness; as a result, little is invested in the economic assessment of psychosocial interventions in BAME mental health. The UK government’s austerity programme and reduced funds for mental health services, has increased the need for the evaluation and assessment of initiatives to focus on value for money. The No Health without Mental Health policy (2011) provides practice guidance to practitioners, but there is little or no mention of the need to provide mental health initiatives targeted at BAME communities that are effective in terms of their impact and the cost-effectiveness. This, therefore, appears to contradict with and is at odds with the wider political discourse, which suggests there should be an increasing focus on health economic evaluation. As a consequence, it could be argued that whilst such policies provide direction to organisations to provide mental health services to the BAME community, by not requesting effective governance, assurance, and evaluation processes, they are merely paying lip service to address these problems and not helping advance knowledge and practice through evidence-based approaches. As a result, BAME communities suffer due to lack of efficient resources that can aid in the recovery process. This research study explores the mental health initiatives targeted at BAME communities, and analyses the techniques used when examining the cost effectiveness of mental health initiatives for BAME mental health communities. Using critical discourse analysis as an approach and method, mental health services will be selected as case studies, and their evaluations will be examined, alongside the political drivers that frame, shape, and direct their work. In doing so, it will analyse what the mental health policies initiatives are, how the initiatives are directed and demonstrate how economic models of evaluation are used in mental health programmes and how the value for money impacts and outcomes are articulated by mental health programme staff. It is anticipated that this study will further our understanding in order to provide adequate mental health resources and will deliver creative, supportive research to ensure evaluation is effective for the government to provide and maintain high quality and efficient mental health initiatives targeted at BAME communities.

Keywords: black, Asian and ethnic minority, economic models, mental health, health policy

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Authors: Prasamsha Panta, Da Yeon Kim, Ja Yong Jang, Min Jae Kim, Jae Ho Kim, Moon Suk Kim

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Introduction: Among the many anticancer drugs used clinically, doxorubicin (Dox), was one of widely used drugs to treat many types of solid tumors such as liver, colon, breast, or lung. Intratumoral injection of chemotherapeutic agents is a potentially more effective alternative to systemic administration because direct delivery of the anticancer drug to the target may improve both the stability and efficacy of anticancer drugs. Injectable in situ-forming gels have attracted considerable attention because they can achieve site specific drug delivery, long term action periods, and improved patient compliance. Objective: Objective of present study is to confirm clinical benefit of intratumoral chemotherapy using injectable in situ-forming poly(ethylene glycol)-b-polycaprolactone diblock copolymer (MP) and Dox with increase in efficacy and reducing the toxicity in patients with cancer diseases. Methods and methodology: We prepared biodegradable MP hydrogel and measured viscosity for the evaluation of thermo-sensitive property. In vivo antitumor activity was performed with normal saline, MP only, single free Dox, repeat free Dox, and Dox-loaded MP gel. The remaining amount of Dox drug was measured using HPLC after the mouse was sacrified. For cytotoxicity studies WST-1 assay was performed. Histological analysis was done with H&E and TUNEL processes respectively. Results: The works in this experiment showed that Dox-loaded MP have biodegradable drug depot property. Dox-loaded MP gels showed remarkable in vitro cytotoxicity activities against cancer cells. Finally, this work indicates that injection of Dox-loaded MP allowed Dox to act effectively in the tumor and induced long-lasting supression of tumor growth. Conclusion: This work has examined the potential clinical utility of intratumorally injected Dox-loaded MP gel, which shows significant effect of higher local Dox retention compared with systemically administered Dox.

Keywords: injectable in-situ forming hydrogel, anticancer, doxorubicin, intratumoral injection

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Authors: Muhammad Ali Tariq

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Grid-connected PV systems have drawn tremendous attention of researchers in the past recent years. The report elucidates the development of efficient and stable solar PV energy conversion systems after thorough analysis at various facets like PV module characteristics, its arrangement, power electronics and MPPT topologies, the stability of the grid, and economic viability over its lifetime. This report and feasibility study will try to bring all optimizing approaches and design calculations which are required for generating energy from BIPV and roof-mounted solar PV in a convenient, sustainable, and user-friendly way.

Keywords: building integrated photovoltaic system, grid integration, solar resource assessment, return on investment, multi MPPT-inverter, levelised cost of electricity

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Authors: Claude Tadonki

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We address the issues related to the computation of the covariance matrix. This matrix is likely to be ill conditioned following its canonical expression, thus consequently raises serious numerical issues. The underlying linear system, which therefore should be solved by means of iterative approaches, becomes computationally challenging. A huge number of iterations is expected in order to reach an acceptable level of convergence, necessary to meet the required accuracy of the computation. In addition, this linear system needs to be solved at each iteration following the general form of the covariance matrix. Putting all together, its comes that we need to compute as fast as possible the associated matrix-vector product. This is our purpose in the work, where we consider and discuss skillful formulations of the problem, then propose a parallel implementation of the matrix-vector product involved. Numerical and performance oriented discussions are provided based on experimental evaluations.

Keywords: covariance-matrix, multicore, numerical computing, parallel computing

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Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

Abstract:

Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: Yunus Emre Kara, Atilla Kuzu, Levent Cirpici

Abstract:

Recently, in the interior design of hospitals, the effect of the physical environment on the healing process has been frequently emphasized, and the importance of psychological and behavioral factors has increased day by day. When designing new hospital interiors, it became important to create spaces that not only meet medical requirements but also support the healing process of patients with interior design. In this study, the patient rooms, corridor, atrium area, waiting area, and entrance counter in a hospital were handled with patient-centered design, evidence-based design, and remedial architectural approaches, and it was seen that the healing and reassuring elements in hospitals were extremely important.

Keywords: evidence based design, healing architecture, hospital, organic design, parametric design

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Authors: Jwana Khateeb, Lamar Bawazeer, Hayat Sharbatly, Mozoun Alghamdi

Abstract:

This research paper explores the idea of learning new languages through an innovative-mobile based learning technology. Throughout this paper we will discuss and examine a mobile-based application called Duolingo. Duolingo is a college standard application for learning foreign languages such as Spanish and English. It is a smart application where it uses smart adaptive technologies to advance the level of their students at each period of time by offering new tasks. Furthermore, we will discuss the history of the application and the methodology used within it. We have conducted a study in which we surveyed ten people about their experience using Duolingo. The results are examined and analyzed in which it indicates the effectiveness on Duolingo students who are seeking to learn new languages. Thus, the research paper will furthermore discuss the diverse methods and approaches in learning new languages through this mobile-based application.

Keywords: Duolingo, AI, personalized, customized

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Authors: Stefan Papastefanou

Abstract:

Artificial intelligence (AI) is an interdisciplinary field of computer science with the aim of creating intelligent machine behavior. Early approaches to AI have been configured to operate in very constrained environments where the behavior of the AI system was previously determined by formal rules. Knowledge was presented as a set of rules that allowed the AI system to determine the results for specific problems; as a structure of if-else rules that could be traversed to find a solution to a particular problem or question. However, such rule-based systems typically have not been able to generalize beyond the knowledge provided. All over the world and especially in IT-heavy industries such as the United States, the European Union, Singapore, and China, machine learning has developed to be an immense asset, and its applications are becoming more and more significant. It has to be examined how such products of machine learning models can and should be protected by IP law and for the purpose of this paper patent law specifically, since it is the IP law regime closest to technical inventions and computing methods in technical applications. Genetic breeding models are currently less popular than recursive neural network method and deep learning, but this approach can be more easily described by referring to the evolution of natural organisms, and with increasing computational power; the genetic breeding method as a subset of the evolutionary algorithms models is expected to be regaining popularity. The research method focuses on patentability (according to the world’s most significant patent law regimes such as China, Singapore, the European Union, and the United States) of AI inventions and machine learning. Questions of the technical nature of the problem to be solved, the inventive step as such, and the question of the state of the art and the associated obviousness of the solution arise in the current patenting processes. Most importantly, and the key focus of this paper is the problem of patenting inventions that themselves are developed through machine learning. The inventor of a patent application must be a natural person or a group of persons according to the current legal situation in most patent law regimes. In order to be considered an 'inventor', a person must actually have developed part of the inventive concept. The mere application of machine learning or an AI algorithm to a particular problem should not be construed as the algorithm that contributes to a part of the inventive concept. However, when machine learning or the AI algorithm has contributed to a part of the inventive concept, there is currently a lack of clarity regarding the ownership of artificially created inventions. Since not only all European patent law regimes but also the Chinese and Singaporean patent law approaches include identical terms, this paper ultimately offers a comparative analysis of the most relevant patent law regimes.

Keywords: algorithms, inventor, genetic breeding models, machine learning, patentability

Procedia PDF Downloads 106