Search results for: early exercise

Authors: Marjan Ghazisaeedi, Azadeh Bashiri

Abstract:

Background: Attention-Deficit/Hyperactivity Disorder(ADHD), is one of the most common psychiatric disorders in early childhood that in addition to its main symptoms provide significant deficits in the areas of educational, social and individual relationship. Considering the importance of rehabilitation in ADHD patients to control these problems, this study investigated the advantages of computer-based cognitive training in these patients. Methods: This review article has been conducted by searching articles since 2005 in scientific databases and e-Journals and by using keywords including computerized cognitive rehabilitation, computer-based training and ADHD. Results: Since drugs have short term effects and also they have many side effects in the rehabilitation of ADHD patients, using supplementary methods such as computer-based cognitive training is one of the best solutions. This approach has quick feedback and also has no side effects. So, it provides promising results in cognitive rehabilitation of ADHD especially on the working memory and attention. Conclusion: Considering different cognitive dysfunctions in ADHD patients, application of the computerized cognitive training has the potential to improve cognitive functions and consequently social, academic and behavioral performances in patients with this disorder.

Keywords: ADHD, computer-based cognitive training, cognitive functions, rehabilitation

Procedia PDF Downloads 281

Authors: Park Eri, Sklad Marcin, Tsirogianni Stavroula

Abstract:

In a world where there is increasing exchange and movement of populations groups, and interconnectedness, there are plenty of opportunities for mutual cultural enrichment. However, in everyday life, relations among different cultural groups do not go that smoothly often resulting in discrimination, inequalities and violence. The increasing differentiation of roles, values and worldviews raise a lot of tensions and dilemmas for the state and people -especially in western liberal societies- about issues of acceptance, fairness, justice, autonomy, plurality, freedom, equality and cohesion. Cultural diversity requires a deeper understanding of the roots, meaning and consequences of group differences. We argue, that a psychology from the standpoint of the subject needs to be developed further according to new societal needs. This means within a globalised society, issues regarding the construction of the other as another have become of utmost importance. In constructing the other human beings construct their ideal and possible worlds and meanings about their lives and their significance by drawing on a set of cultural norms, beliefs and values embedded in the different contexts whereby they find themselves in. In this article, we are describing a series of exercises developed in collaboration with University students in the Netherlands that have been piloted with undergraduate 2nd year University Psychology students. These exercises aimed at making tangible and obvious how students apply different moral principles and norms to regulate relationships, which are linked to hegemonic ideological forces. The exercises were in the form of thought experiments that included 8 moral dilemmas, inspired by the moral foundations theory, that touched on different moral principles. The moral dilemmas were built onto each other in incremental steps: from a very tangible/hands-on level to more challenging and demanding ones which require to step into pre-existing networks on knowledge and discourses. After the execution of every dilemma, a discussion followed, which is focused on building links between the ‘theme of the exercise’ and participants’ own lives experiences. In this paper, we provide an evaluation of the methodology used through a discursive analysis of the discussion between the students and the teacher.

Keywords: citizenship, moral dilemmas, social justice, education

Procedia PDF Downloads 324

Authors: Ya-Ting Chuang, Krystle Leung, Ya-Jen Chang, Rosemarie H. DeKruyff, Paul B. Savage, Richard Cruse, Christophe Benoit, Dirk Elewaut, Nicole Baumgarth, Dale T. Umetsu

Abstract:

We examined characteristics of a Natural Killer T (NKT) cell subpopulation that developed during influenza infection in neonatal mice, and that suppressed the subsequent development of allergic asthma in a mouse model. This NKT cell subset expressed CD38 but not CD4, produced IFN-γ, but not IL-17, IL-4 or IL-13, and inhibited the development of airway hyperreactivity (AHR) through contact-dependent suppressive activity against helper CD4 T cells. The NKT subset expanded in the lungs of neonatal mice after infection with influenza, but also after treatment of neonatal mice with a Th1-biasing α-GalCer glycolipid analogue, Nu-α-GalCer. These results suggest that early/neonatal exposure to infection or to antigenic challenge can affect subsequent lung immunity by altering the profile of cells residing in the lung and that some subsets of NKT cells can have direct inhibitory activity against CD4+ T cells in allergic asthma. Importantly, our results also suggest a potential therapy for young children that might provide protection against the development of asthma.

Keywords: NKT subset, asthma, airway hyperreactivity, hygiene hypothesis, influenza

Procedia PDF Downloads 240

Authors: Eric Ng, Freddy W. Wagey, Frank M. M. Wagey

Abstract:

Background: Cervical cancer is the fourth most common cancer in women worldwide and the most common cancer in many low- and middle-income countries. The main causes are the lack of prevention programs and effective therapy, as well as the lack of knowledge about cervical cancer and awareness for early detection. The Pap smear test and visual inspection with acetic acid (VIA) allow the cervical lesion to be detected so that progression to cervical cancer can be avoided. Objective: The purpose of this study was to evaluate the knowledge of Pap smear test and VIA in cervical cancer patients. Methodology: A total of 67 cervical cancer patients in Manado who volunteered to participate in the research were identified as the sample. The data were collected during the month of November 2019-January 2020 with a questionnaire about the respondents' knowledge relating to Pap smear test and VIA. Questionnaire data were analysed using descriptive statistics. Results: Knowledge of pap smear among cervical cancer patients were good in 9 respondents (13.4%), moderate in 20 respondents (29.9%), and bad in 38 respondents (56.7%), whereas the knowledge of VIA was good in 13 respondents (19.4%), moderate in 15 respondents (22.4%), and bad in 39 respondents (58.2%). Conclusion: Majority of cervical cancer patients in Manado still had bad knowledge about Pap smear tests and VIA.

Keywords: cervical cancer, knowledge, pap smear test, visual inspection with acetic acid

Procedia PDF Downloads 174

Authors: Barzan Hadi Hama Karim

Abstract:

The purpose of this research study is to determine how educators, students at the university level are using storytelling to support the educational process. This study provides a general framework about educational uses of storytelling as a pedagogical too to learn English language in the higher education and describes the different perceptions of people (teachers and students) at different levels. A survey is used to collect responses from a group of educators and students in educational settings to determine how they are using storytelling for educational purposes. The results show the current situation of educational uses of storytelling and explore some of the benefits and challenges educators face in implementing storytelling in their institutions. The purpose of our research is to investigate the impact of storytelling as a pedagogical tool to learn English language in higher education and its academic achievements on ESL students. It highlights findings that address the following questions: (1) How has storytelling been approached historically? (2) Is storytelling beneficial for students in early grades at university? (3) To what extent do teacher and student prefer storytelling as a pedagogical tool to teach and learn English language in higher education?

Keywords: storytelling, teacher's beliefs, student’s beliefs, student’s academic achievement, narrative, pedagogy, ESL

Procedia PDF Downloads 395

Authors: Christian Nounkeu Tatchou

Abstract:

The concept of mediatization of politics describes changes with regards to media and politics, as the political sphere is increasingly shaped by the media and conforms to its logic. The mediatization of politics in established democracies of the West has been the object of several researches. However, there is an overwhelming paucity of literature on this reconfiguration of the political life around the media in the emerging democracies of the Sub-Saharan Africa. A majority of Sub-Saharan countries have been progressively experiencing the modernization of their societies and significant developments with respect to political communication since the early 1990s. This has been facilitated by factors such as the adoption of democratic reforms, the development of mass media, the advent of social media and the rapid spread of new information and communication technologies. Thus, this paper investigates the extent to which political communication in Sub-Saharan Africa is mediatized, especially with regards to the social media. Through in-depths interviews with twenty political leaders and political observers in Cameroon and Ghana, this article argues that the social media has become the main arena of voters’ mobilization and political participation in Sub-Saharan Africa. However, a greater extent of freedom for political activism on social media is observed in the new democracy of Ghana, unlike in the enduring authoritarian political system of Cameroon where the government attempts to control the use and content of political discourse on social media.

Keywords: mediatization, political communication, social media, sub-saharan africa

Procedia PDF Downloads 354

Authors: Hari Sharan Pandit

Abstract:

Mathematics teaching in Nepal has been centralized and guided by the notion of transfer of knowledge and skills from teachers to students. The overemphasis on the ‘algorithm-centric’ approach to mathematics teaching and the focus on ‘role–learning’ as the ultimate way of solving mathematical problems since the early years of schooling have been creating severe problems in school-level mathematics in Nepal. In this context, the author argues that students should learn real-world mathematical problems through various interesting, creative and collaborative, as well as artistic and alternative ways of knowing. The collaboration-incorporated pedagogy is a distinct pedagogical approach that offers a better alternative as an integrated and interdisciplinary approach to learning that encourages students to think more broadly and critically about real-world problems. The paper, as a summarized report of action research designed, developed and implemented by the author, focuses on the needs and usefulness of collaboration-incorporated pedagogy in the Nepali context to make mathematics teaching more meaningful for producing creative and critical citizens. This paper is useful for mathematics teachers, teacher educators and researchers who argue on arts integration in mathematics teaching.

Keywords: peer teaching, metacognitive approach, mitigating, action research

Procedia PDF Downloads 29

Authors: Thapthep Paprach, Benya Lertsuwan

Abstract:

Investment fraud is not a new criminal, but there are still more victims during the Internet of Things era. This kind of criminal has been classified as a national and transnational financial crime problem all over the world. In Thailand, the country has also been attacked by this kind of crime. This research concerns whether the mass media that is supposed to cover news about online investment scams realized and warned Thais about this crime. Thus, this study explores the value of news about investment fraud in terms of frequency. The methodology uses web crawling from the top 5 news agency websites that have the most access. We pull out all information reporting about investment fraud. The findings revealed that the ‘Khaosod’ news agency was the first rank in reporting on investment crime. On the other hand, ‘Matichon’ was the least reported. Thairat news agencies frequently reported such criminals from midnight to very early in the morning, while other news agencies reported during the daytime. The results between the frequency of news reporting about investment fraud and the monthly number of victim reports are not correlated. Although the most cases reported to Thai police were in February 2023, but the most news reported was in January 2023. In conclusion, there might be a negative correlation between the amount of investment fraud news reported and the number of victims.

Keywords: investment fraud, news value, online news report, Ponzi schemes, Romance scam

Procedia PDF Downloads 78

Authors: Reza Behboodian

Abstract:

Monitoring the structural health and diagnosing their damage in the early stages has always been one of the topics of concern. Nowadays, research on structural damage detection methods based on vibration analysis is very extensive. Moreover, these methods can be used as methods of permanent and timely inspection of structures and prevent further damage to structures. Non-destructive methods are the low-cost and economical methods for determining the damage of structures. In this research, a non-destructive method for detecting and identifying the failure location in structures based on dynamic responses resulting from time history analysis is proposed. When the structure is damaged due to the reduction of stiffness, and due to the applied loads, the displacements in different parts of the structure were increased. In the proposed method, the damage position is determined based on the calculation of the strain energy difference in each member of the damaged structure and the healthy structure at any time. Defective members of the structure are indicated by the amount of strain energy relative to the healthy state. The results indicated that the proper accuracy and performance of the proposed method for identifying failure in structures.

Keywords: failure, time history analysis, dynamic response, strain energy

Procedia PDF Downloads 135

Authors: Kianoosh Samimi, Farhad Estakhr, Mahdi Mahdikhani, Faramaz Moodi

Abstract:

The self-consolidating concrete (SCC) performance over ordinary concrete is generally related to the ingredients used. The metakaolin can modify various properties of concrete, due to high pozzolanic reactions and also makes a denser microstructure. The objective of this paper is to examine the influence of three types of Portland cement and metakaolin on compressive strength and transport properties of SCC at early ages and up to 90 days. Six concrete mixtures were prepared with three types of different cements and substitution of 15% metakaolin. The results show that the highest value of compressive strength was achieved for Portland Slag Cement (PSC) and without any metakaolin at age of 90 days. Conversely, the lowest level of compressive strength at all ages of conservation was obtained for Pozzolanic Portland Cement (PPC) and containing 15% metakaolin. As can be seen in the results, compressive strength in SCC containing Portland cement type II with metakaolin is higher compared to that relative to SCC without metakaolin from 28 days of age. On the other hand, the samples containing PSC and PPC with metakaolin had a lower compressive strength than the plain samples. Therefore, it can be concluded that metakaolin has a negative effect on the compressive strength of SCC containing PSC and PPC. In addition, results show that metakaolin has enhanced chloride durability of SCCs and reduced capillary water absorption at 28, 90 days.

Keywords: SCC, metakaolin, cement type, compressive strength, chloride diffusion

Procedia PDF Downloads 222

Authors: Dania Baaboud, Renad Al-zahrani, Mahnoor Khan, Riya Afroz

Abstract:

Flo is a smart period-tracking tool that uses artificial intelligence (AI) to offer individualized reproductive health predictions and insights. Flo makes very accurate predictions about menstrual cycles, ovulation, and fertility windows by evaluating user inputs, including cycle duration, symptoms, and patterns. Its machine learning algorithms are constantly evolving, providing personalized health recommendations, instructional materials, and early identification of possible health abnormalities such as reproductive problems and hormone imbalances. Flo, which was introduced in 2015 and upgraded with AI in 2017, is a revolutionary use of technology in healthcare that empowers people to make knowledgeable decisions regarding their well-being. Despite its advantages, our study included drawbacks, such as limited access to premium services and a small sample size. While highlighting unique characteristics, a comparative comparison with similar applications such as Clue and Glow confirmed Flo's outstanding AI integration for individualized healthcare. All things considered, Flo is a prime example of how AI can be used to tackle intricate biological processes, giving consumers the ability to efficiently control their reproductive health and opening the door for improvements in individualized medical technology.

Keywords: Flo, period-tracking app, period symptoms, women’s health, machinery

Procedia PDF Downloads 7

Authors: Suzanne El Takach

Abstract:

The research study explored pre-service teachers’ attitudes towards 6 courses taught in 3rd till 6th semesters at the Faculty of Education, Lebanese University, during the academic year 2015-2016. They assessed science teaching courses that are essential for teacher preparation for Science at the primary and elementary level. These courses were: Action Research I and II in Teaching Science, New trends in Teaching Science, Teaching Science I and II for the elementary level and Teaching Science for Early Childhood Education. Qualitative and Quantitative Data were gathered from a) a survey questionnaire consisting of 23 closed-ended items; some were of Likert scale type, that aimed at collecting students’ opinions on courses, in terms of teaching, assessment and class interaction (N=102 respondents) and b) a second questionnaire of 10 questions was disseminated on a sample of 39 students in their last semester in science and Mathematics, in order to know more about students’ skills gained, suggestions for new courses and improvement. Students were satisfied with science teaching courses and they have admitted that they gained a good pedagogical content knowledge, such as, lesson planning, students’ misconceptions, and use of various teaching and assessment strategies.

Keywords: assessment in higher education, LMD program, pre-service teachers’ attitudes, pre-PCK skills

Procedia PDF Downloads 148

Authors: Pedro Martinez-Santos, Víctor Gómez-Escalonilla, Silvia Díaz-Alcaide, Esperanza Montero, Miguel Martín-Loeches

Abstract:

Groundwater monitoring networks are critical in evaluating the vulnerability of groundwater resources to depletion and contamination, both in space and time. Groundwater monitoring networks typically grow over decades, often in organic fashion, with relatively little overall planning. The groundwater monitoring networks in the Madrid area, Spain, were reviewed for the purpose of identifying gaps and opportunities for improvement. Spatial analysis reveals the presence of various monitoring networks belonging to different institutions, with several hundred observation wells in an area of approximately 4000 km2. This represents several thousand individual data entries, some going back to the early 1970s. Major issues included overlap between the networks, unknown screen depth/vertical distribution for many observation boreholes, uneven time series, uneven monitored species, and potentially suboptimal locations. Results also reveal there is sufficient information to carry out a spatial and temporal analysis of groundwater vulnerability based on machine learning applications. These can contribute to improve the overall planning of monitoring networks’ expansion into the future.

Keywords: groundwater monitoring, observation networks, machine learning, madrid

Procedia PDF Downloads 79

Authors: Muhammad Ali Syed, Arshad Saleem Bhatti, Chen-zhong Li, Habib Ali Bokhari

Abstract:

Surface plasmon resonance (SPR) biosensors have emerged as a promising technique for bioanalysis as well as microbial detection and identification. Real time, sensitive, cost effective, and label free detection of biomolecules from complex samples is required for early and accurate diagnosis of infectious diseases. Like many other types of optical techniques, SPR biosensors may also be successfully utilized for microbial detection for accurate, point of care, and rapid results. In the present study, we have utilized a commercially available automated SPR biosensor of BI company to study the microbial detection form water samples spiked with different concentration of Staphylococcus aureus bacterial cells. The gold thin film sensor surface was functionalized to react with proteins such as protein G, which was used for directed immobilization of monoclonal antibodies against Staphylococcus aureus. The results of our work reveal that this immunosensor can be used to detect very small number of bacterial cells with higher sensitivity and specificity. In our case 10^3 cells/ml of water have been successfully detected. Therefore, it may be concluded that this technique has a strong potential to be used in microbial detection and identification.

Keywords: surface plasmon resonance (SPR), Staphylococcus aureus, biosensors, microbial detection

Procedia PDF Downloads 476

Authors: Omer Cahana, Ofer Levi, Maya Herman

Abstract:

Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: magnetic resonance imaging, image reconstruction, pyramid network, deep learning

Procedia PDF Downloads 91

Authors: Angad Arora

Abstract:

In production operations/manufacturing, a cell or line is typically a bunch of similar machines (computer numerical control (CNCs), advanced cutting, 3D printing or special purpose machines. For qualifying a typical manufacturing line /cell / new process, Ideally, we need a sample of parts that can be flown through the process and then we make a judgment on the health of the line/cell. However, with huge volumes and mass production scope, such as in the mobile phone industry, for example, the actual cells or lines can go in thousands and to qualify each one of them with statistical confidence means utilizing samples that are very large and eventually add to product /manufacturing cost + huge waste if the parts are not intended to be customer shipped. To solve this, we come up with 2 steps statistical approach. We start with a small sample size and then objectively evaluate whether the process needs additional samples or not. For example, if a process is producing bad parts and we saw those samples early, then there is a high chance that the process will not meet the desired yield and there is no point in keeping adding more samples. We used this hypothesis and came up with 2 steps binomial testing approach. Further, we also prove through results that we can achieve an 18-25% reduction in samples while keeping the same statistical confidence.

Keywords: statistics, data science, manufacturing process qualification, production planning

Procedia PDF Downloads 98

Authors: Ifueko Oghogho Ukponmwan, Mike O. Orji

Abstract:

This study investigated the antifungal activity of Bacilluss subtilis in the control of postharvest fungal rot of white yam (Dioscorea spp). Bacillus subtilis was isolated from the soil and fungi (Aspergillus spp, Mucor and yeasts) were isolated from rotten yam. The organisms were paired in yam nutrient agar (YNA) and yam Sabourraud dextrose agar media. In the yam dextrose agar media (YSDA) plates, the Bacillus grew rapidly and established itself and restricted the growth of the fungi organisms, but there was no zone of inhibition. This behaviour of Bacillus on the plates of YSDA was also observed in the yams where the fungi caused rot but the rot was suppressed by the presence of the Bacillus as compared to the degree of rot observed in the control that had only spoilage fungi. The control yam showed greater rot than other yams that contained a combination of Bacillus and fungi. The t-Test analysis showed that the difference in the rot between the treated samples and the control sample is significant and this implies that the presence of Bacillus significantly reduced the growth of fungi in the samples (yams). It was revealed from this study that Bacillus subtilis treatment can be successfully used to preserve white yams in storage. Its fast growth and early establishment in the sample accounts for its antifungal strength.

Keywords: Bacillus subtilis, rot, fungi, yam

Procedia PDF Downloads 182

Authors: Akor Omachile Opaluwah

Abstract:

Entrepreneurs are heralded as a very vital force in the growth of economies. This is because they create businesses, employ people, have direct access to the local consumer, and primarily utilize local sources of raw materials, have an understanding of the immediate need of consumers, and they have the capacity to keep in motion the economy. The rise of social enterprises takes these advantages further beyond the business and economic benefits. These Social enterprises help address developmental issues in the society while maintaining a profit for their investors and shareholders. These combined roles create a unique synergy between the civil society and the market, therefore placing the social enterprise in a position where they can access directly, the benefits of the market while meeting the needs of the citizens and their environment. With such a unique position, social enterprises hold a place in the development discourse that has previously been left unexplored. This hybridisation of the functions of civil societies and the market can provide to development, practices, and benefits that have previously been only available in trace amounts. It, therefore, is imperative to understand the efficacy of social enterprises. With the discourse of social enterprises still in its early stages. This paper looks at selected social enterprise cases in Nigeria and analyses their approach and contribution to development.

Keywords: business, civil society, development, entrepreneurs, innovation, market, Nigeria, social enterprise

Procedia PDF Downloads 390

Authors: Chandu Rathnayake, Isuri Anuradha

Abstract:

Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

Procedia PDF Downloads 74

Authors: A. Papachristou, A. Ntikoudi, L. Makris, V. Saridakis

Abstract:

Introduction: More than 10 million people are imprisoned or detained worldwide. Figures from 2011-12 show that prison inmates are more likely than the general population to suffer from chronic or infectious diseases, while most inmates are overweight or obese, and more than a quarter have high blood pressure. In 2011/12, the proportion of prisoners reporting diabetes or hyperglycemia was 899 per 10,000 prisoners, almost double the 2004 figure (483 per 10,000). It is important to ensure that this population has access to the same standard of care as people outside prisons, as access to services should be need-based. Diabetes is a public health problem associated with increased morbidity and mortality worldwide. According to the International Diabetes Federation (IDF) in 2017, approximately 425 million people worldwide had diabetes. This number is expected to increase to 629 million by 2045. Poor management of diabetes in prisons can lead to poor blood sugar control and increase the risk of complications. Aim: The aim of this review was to systematically evaluate all the available literature on diabetes care in custodial settings. Methods: An extensive literature search was conducted through electronic databases (PubMed, Scopus and CINAHL) with the terms ‘custody’, ‘diabetes Mellitus, ‘detention centers and ‘chronic disease’. Articles published in English until September 2022, were included; no other criteria on publication dates were set. Results: Most of the studies mentioned a diabetes prevalence of approximately 10%, among other common chronic. Hypertension, obesity, smoking, sedentary lifestyle were the most common comorbidities associated with diabetes. Conclusion: Good glycemic control is fundamental to managing diabetes, and while many prisoners enter prison poorly, access to regular medication and meals, as well as exercise, offers the potential for improvement. Not being able to get help as quickly as in the past can be extremely stressful, and some prisoners may deliberately raise their blood sugar levels to avoid the risk of developing hypoglycemia, especially if they know they have had previous episodes of nocturnal hypoglycemia. Thus, appropriate training and resources are critical to providing quality care to incarcerated people with diabetes.

Keywords: custody, diabetes mellitus, detention centers, chronic disease

Procedia PDF Downloads 99

Authors: Kanda Janyam, Piyaporn Vijit

Abstract:

Background: As a consequence of sustained declines in fertility and mortality during the last three decades of the 20th century, Thailand faces a rapidly growing population of older persons. This demographic change directly affect Thailand workforce. Therefore, the study of health promotion behaviour of the older employees will benefit the employers as they can then develop the preparation for promoting well-being in older persons. Purpose: The current study aims to investigate health promotion behaviour and factors related to health promotion behaviour of older employees in factory. Methodology: The research instrument was questionnaire on health promotion behaviour and semi-structured interviews. The questionnaire was launched with 326 employees aged between 45-59 years in three factories in Songkhla Province, southern Thailand. The data collection started in December 2011. The data were analysed with mean, standard deviation, and correlation. Results: The results revealed that overall health promotion behaviour of the older employees in factory was at a high level. Moreover, when considered by aspect, it was found that their responsibility for health, nutrition, success in life, interpersonal relationship were at a high level while stress management, and exercise were at a moderate level. The results from correlation analysis indicated that the overall health promotion behaviour was positively related to knowledge of health promotion behaviour, attitude toward health promotion behaviour, health perception, the policy of health promotion, participation in health promotion activities, convenience in obtaining health promotion services, health resources, advice from people supporting health, and information received from the media. In addition, the results of the interviews with four key informants helped to confirm the factors related to health promotion behaviour of older employees in factory. Therefore, health promotion for elderly employees in factory is likely to be successful, if the support is given to the four health promotion factors that are divided into: leading factors consisting of attitude toward health promotion behaviour, and health perception, and supporting factors consisting of advice from other people, and information on health from various media. Practical implications: The results of the study identified the factors related to health promotion behaviour of older employees in factory. Such information will benefit employers as they can then develop specific strategies to increase their staffs’ well-being and, hence, presumably enhance the organization productivity.

Keywords: health promotion behavior, older, employee, factory

Procedia PDF Downloads 265

Authors: Mawa Abdelbagi Mohamed Mohamed, Eslam Alaa Elbahlawan

Abstract:

This study examines the complex social fabric woven within the Abu-Shouk internally displaced persons camp, shaped by the chaotic waves of armed conflict and displacement in the early 2000s. The impact of war, economic constraints, and altered living conditions have fundamentally reshaped families and traditions, presenting both challenges and opportunities. In this exploration, we navigate the resilience of a community thrust into adversity, spotlighting how it emerged as essential in rebuilding social bonds. Exchanges of culture, intertribal marriages, and communal gathering spots have become essential tools in fostering cohesion and understanding amidst diversity. However, this resilience has been tested by the intrusion of politics, leading to shifts in governance structures and community dynamics. As we conclude, it is evident that while the scars of displacement and political disruptions are present, the community's enduring spirit and adaptability shine through. Empowering the community to rebuild their social tapestry, bridging the gaps, and restoring unity amid evolving political realities remain the beacon guiding their journey toward a shared, purposeful future.

Keywords: darfur, internally displaced person, social fabric, conflict

Procedia PDF Downloads 65

Authors: D. R. T. N. K. Dissanayake, H. M. S. K. Herath, H. K. S. G. Gunadasa, P. Weerasinghe

Abstract:

Luffa is a tropical and subtropical vegetable, belongs to family Cucurbiteceae. It is predominantly monoecious in sex expression and provides an ample scope for utilization of hybrid vigor. Hybrid varieties develop through open pollination, produce higher yields due to its hybrid vigor. Naga F1 hybrid variety consists number of desirable traits other than higher yield such as strong and vigorous plants, fruits with long deep ridges, attractive green color fruits ,better fruit weight, length and early maturity compared to the local Luffa cultivars. Unavailability of fertilizer recommendations for hybrid cucurbit vegetables leads to an excess fertilizer application causing a vital environmental issue that creates undesirable impacts on nature and the human health. Main Objective of this research is to determine effect of different nitrogen and potassium fertilizer rates on growth and yield of Naga F1 Variety. Other objectives are, to evaluate specific growth parameters and yield, to identify the optimum nitrogen and potassium fertilizer levels based on growth and yield of hybrid Luffa variety. As well as to formulate the general fertilizer recommendation for hybrid Luffa -Naga F1 variety.

Keywords: hybrid, nitrogen, phosphorous, potassium

Procedia PDF Downloads 595

Authors: Issam Alnader, Aboubaker Lasebae, Rand Raheem

Abstract:

Wireless sensor networks (WSNs) are distributed network systems used in a wide range of applications, including safety-critical systems. The latter provide critical services, often concerned with human life or assets. Therefore, ensuring the dependability requirements of Safety critical systems is of paramount importance. The purpose of this paper is to utilize the Hidden Markov Model (HMM) to elongate the service availability of WSNs by increasing the time it takes a node to become obsolete via optimal load balancing. We propose an HMM algorithm that, given a WSN, analyses and predicts undesirable situations, notably, nodes dying unexpectedly or prematurely. We apply this technique to improve on C. Lius’ algorithm, a scheduling-based algorithm which has served to improve the lifetime of WSNs. Our experiments show that our HMM technique improves the lifetime of the network, achieved by detecting nodes that die early and rebalancing their load. Our technique can also be used for diagnosis and provide maintenance warnings to WSN system administrators. Finally, our technique can be used to improve algorithms other than C. Liu’s.

Keywords: wireless sensor networks, IoT, dependability of safety WSNs, energy conservation, sleep awake schedule

Procedia PDF Downloads 101

Authors: Nisa Ertoy Inci, Cengiz Toker

Abstract:

Winter or autumn-sown faba bean (Vicia faba L.) is one the most efficient ways to overcome drought since faba bean is usually grown under rainfed where drought and high-temperature stresses are the main growth constraints. The objectives of this study were assessment of (i) relationships between cold tolerance and agro-morphological traits, and (ii) the most suitable agro-morphological trait(s) under cold conditions. Three species of the genus Vicia L. includes 109 genotypes of faba bean (Vicia faba L.), three genotypes of narbon bean (V. narbonensis L.) and two genotypes of V. montbretii Fisch. & C.A. Mey. Davis and Plitmann were sown in autumn at highland of Mediterranean region of Turkey. All relatives of faba bean were more cold-tolerant than the faba bean genotypes. Three faba bean genotypes, ACV-42, ACV-84 and ACV-88, were selected as sources of cold tolerance under field conditions. Path and correlation coefficients and factor and principal component analyses indicated that biological yield should be evaluated in selection for cold tolerance under cold conditions ahead of many agro-morphological traits. The seed weight should be considered for selection in early breeding generations because they had the highest heritability.

Keywords: cold tolerance, faba bean, narbon bean, selection

Procedia PDF Downloads 399

Authors: Omer Cahana, Maya Herman, Ofer Levi

Abstract:

Magnetic resonance imaging (MRI) is a long medical scan that stems from a long acquisition time. This length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach, such as compress sensing (CS) or parallel imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. In order to achieve that, two properties have to exist: i) the signal must be sparse under a known transform domain, ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm needs to be applied to recover the signal. While the rapid advance in the deep learning (DL) field, which has demonstrated tremendous successes in various computer vision task’s, the field of MRI reconstruction is still in an early stage. In this paper, we present an extension of the state-of-the-art model in MRI reconstruction -VarNet. We utilize VarNet by using dilated convolution in different scales, which extends the receptive field to capture more contextual information. Moreover, we simplified the sensitivity map estimation (SME), for it holds many unnecessary layers for this task. Those improvements have shown significant decreases in computation costs as well as higher accuracy.

Keywords: MRI, deep learning, variational network, computer vision, compress sensing

Procedia PDF Downloads 163

Authors: Sampada Katekar, Namdeo Hedaoo

Abstract:

Cold Bituminous Emulsion Mixtures (CBEMs) are generally produced by mixing unheated aggregate, binder and filler at ambient temperature. Cold bituminous emulsion mixtures have several environmental and cost-effective benefits. But CBEMs offer poor early life properties too and they require long curing time to achieve maximum strength. The main focus of this study is to overcome inferiority of CBEMs by incorporating Rice Husk Ash (RHA) and Ordinary Portland Cement (OPC). In this study, RHA and OPC are substituted for conventional mineral filler in an increased percentage from 0 to 3% with an increment of 1%. Marshall stability, retained stability and tensile strength tests were conducted to evaluate the enhancement in performance of CBEMs. The experimental results have shown that Marshall stability and tensile strength of CBEMs increased significantly by replacing the conventional mineral filler with RHA and OPC. The addition of RHA and OPC in CBEMs result in a reduction in moisture induced damages. However, stability and tensile strength values of RHA modified CBEMs are higher than that of OPC modified CBEMs.

Keywords: cold bituminous emulsion mixtures, Marshall stability test, ordinary Portland cement, rice husk ash

Procedia PDF Downloads 168

Authors: Marc S. Paolella, Pawel Polak

Abstract:

The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and non-ellipticity. It introduces a so-called risk fear portfolio strategy which combines portfolio optimization with active risk monitoring. The former selects optimal portfolio weights. The latter, independently, initiates market exit in case of excessive risks. The strategy agrees with the stylized fact of stock market major sell-offs during the initial stage of market downturns. The advantages of the new framework are illustrated with an extensive empirical study. It leads to superior multivariate density and Value-at-Risk forecasting, and better portfolio performance. The proposed risk fear portfolio strategy outperforms various competing types of optimal portfolios, even in the presence of conservative transaction costs and frequent rebalancing. The risk monitoring of the optimal portfolio can serve as an early warning system against large market risks. In particular, the new strategy avoids all the losses during the 2008 financial crisis, and it profits from the subsequent market recovery.

Keywords: comfort, financial crises, portfolio optimization, risk monitoring

Procedia PDF Downloads 525

Authors: Sirajdin Olagoke Adeshina, Haidi Ibrahim, Akeem Salawu

Abstract:

large lecture theatres cannot be covered by a single camera but rather by a multicamera setup because of their size, shape, and seating arrangements. Although, classroom capture is achievable through a single camera. Therefore, a design and implementation of a multicamera setup for a large lecture hall were considered. Researchers have shown emphasis on the impact of class attendance taken on the academic performance of students. However, the traditional method of carrying out this exercise is below standard, especially for large lecture theatres, because of the student population, the time required, sophistication, exhaustiveness, and manipulative influence. An automated large classroom attendance system is, therefore, imperative. The common approach in this system is face detection and recognition, where known student faces are captured and stored for recognition purposes. This approach will require constant face database updates due to constant changes in the facial features. Alternatively, face counting can be performed by cropping the localized faces on the video or image into a folder and then count them. This research aims to develop a face localization-based approach to detect student faces in classroom images captured using a multicamera setup. A selected Haar-like feature cascade face detector trained with an asymmetric goal to minimize the False Rejection Rate (FRR) relative to the False Acceptance Rate (FAR) was applied on Raspberry Pi 4B. A relationship between the two factors (FRR and FAR) was established using a constant (λ) as a trade-off between the two factors for automatic adjustment during training. An evaluation of the proposed approach and the conventional AdaBoost on classroom datasets shows an improvement of 8% TPR (output result of low FRR) and 7% minimization of the FRR. The average learning speed of the proposed approach was improved with 1.19s execution time per image compared to 2.38s of the improved AdaBoost. Consequently, the proposed approach achieved 97% TPR with an overhead constraint time of 22.9s compared to 46.7s of the improved Adaboost when evaluated on images obtained from a large lecture hall (DK5) USM.

Keywords: automatic attendance, face detection, haar-like cascade, manual attendance

Procedia PDF Downloads 73

Authors: Byeal-I Han, Michael Lee

Abstract:

Ageing is associated with an increased risk of diseases such as cancer, and neurodegenerative disorders. Increased autophagy delays ageing and extends longevity. In this study, we investigated the role of autophagy in longevity using human foreskin fibroblast HS68 cells, in which a senescence-like growth arrest can be induced. In particular, cellular senescence is manifested by the irreversible cell cycle arrest, and may contribute to the ageing of organisms. The senescence state was measured with staining for senescence-associated β-galactosidase (SA-β-gal) activity that represents a sensitive and reliable marker to quantify senescent cells. We detected a significantly increased percentage (%) of SA-β-gal positive cells in HS68 cultures at passage 40 (63%) when compared with younger ones at passage 15 (0.5%). As expected, HS68 cells at passage 40 exhibited much lower proliferation rate than cells at passage 15. The basal levels of LC3 were measured by immunoblotting showing a comparison of LC3-I and LC3-II levels at 3 age-points in serially passaged HS68 cells. LC3-II/LC3-I ratio at different passage levels relative to β-actin levels of each band confirmed that cells at passage 34 showed lower conversion of non-autophagic LC3-I to autophagic LC3-II than the cells at passage 16. Furthermore, Cyto-ID autophagy assay also revealed that late passage cells showed lower autophagy than the early passage cells. Together, our findings suggest that senescence induction might be associated with decreased autophagy.

Keywords: ageing, autophagy, senescence, HS68

Procedia PDF Downloads 255