Search results for: early childhood settings

Authors: Rabie Fadil, Parshuram Aarotale, Shubha Majumder, Bijay Guargain

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Hemorrhage is the loss of blood from the circulatory system and leading cause of battlefield and postpartum related deaths. Early detection of hemorrhage remains the most effective strategy to reduce mortality rate caused by traumatic injuries. In this study, we investigated the physiological changes via non-invasive cardiac signals at rest and under different hemorrhage conditions simulated through graded lower-body negative pressure (LBNP). Simultaneous electrocardiogram (ECG), photoplethysmogram (PPG), blood pressure (BP), impedance cardiogram (ICG), and phonocardiogram (PCG) were acquired from 10 participants (age:28 ± 6 year, weight:73 ± 11 kg, height:172 ± 8 cm). The LBNP protocol consisted of applying -20, -30, -40, -50, and -60 mmHg pressure to the lower half of the body. Beat-to-beat heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean aerial pressure (MAP) were extracted from ECG and blood pressure. Systolic amplitude (SA), systolic time (ST), diastolic time (DT), and left ventricle Ejection time (LVET) were extracted from PPG during each stage. Preliminary results showed that the application of -40 mmHg i.e. moderate stage simulated hemorrhage resulted significant changes in HR (85±4 bpm vs 68 ± 5bpm, p < 0.01), ST (191 ± 10 ms vs 253 ± 31 ms, p < 0.05), LVET (350 ± 14 ms vs 479 ± 47 ms, p < 0.05) and DT (551 ± 22 ms vs 683 ± 59 ms, p < 0.05) compared to rest, while no change was observed in SA (p > 0.05) as a consequence of LBNP application. These findings demonstrated the potential of cardiac signals in detecting moderate hemorrhage. In future, we will analyze all the LBNP stages and investigate the feasibility of other physiological signals to develop a predictive machine learning model for early detection of hemorrhage.

Keywords: blood pressure, hemorrhage, lower-body negative pressure, LBNP, machine learning

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Authors: Nomfundo Ngombane, Topside E. Mathonsi

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Remote sensing and satellite imaging have been widely used to detect wildfires; nevertheless, the technologies present some limitations in terms of early wildfire detection as the technologies are greatly influenced by weather conditions and can miss small fires. The fires need to have spread a few kilometers for the technologies to provide accurate detection. The South African Advanced Fire Information System uses MODIS (Moderate Resolution Imaging Spectroradiometer) as satellite imaging. MODIS has limitations as it can exclude small fires and can fall short in validating fire vulnerability. Thus in the future, a Machine Learning algorithm will be designed and implemented for the early detection of wildfires. A simulator will be used to evaluate the effectiveness of the proposed solution, and the results of the simulation will be presented.

Keywords: moderate resolution imaging spectroradiometer, advanced fire information system, machine learning algorithm, detection of wildfires

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Adel Al Hashlan

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Parent and family engagement plays a crucial role in supporting the success of students with special needs in educational settings. This paper explores the significance of parental involvement in special education, examining its impact on academic achievement, social-emotional development, and overall well-being. Meaningful collaboration between educators, parents, and families can promote positive outcomes for students with diverse learning needs. The study employs a mixed-methods approach, incorporating both qualitative and quantitative techniques. Data were collected through structured interviews, focus groups, and surveys involving students with special needs, their parents, and educators across diverse educational settings. The analysis identifies patterns, themes, and correlations to understand the impact of parent and family engagement on student outcomes. Major findings reveal that effective parent and family involvement initiatives, characterized by strong communication strategies, collaboration frameworks, and partnership-building approaches, significantly enhance students’ academic performance, social-emotional development, and overall well-being. The study also identifies common barriers to parental involvement, such as cultural differences and accessibility issues, and suggests strategies for overcoming these challenges. In conclusion, the study underscores the importance of systemic support and resource allocation to facilitate meaningful partnerships between schools and families. Ongoing research and professional development are crucial to enhancing the effectiveness of parent and family engagement initiatives in special education, ultimately maximizing student achievement and well-being.

Keywords: parental involvement, special education, student success, collaborative partnerships

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Authors: Achinthya Bandara

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The Portuguese were the first known European Nation to colonize Ceylon during the early 16th century. When the Portuguese set sail in the late 15th century towards the East and West, they first landed in Pondicherry (Pondicherry), an eastern coastal location of early India and established their trade in the Indian Oceanic regions. Sri Lanka (Ceylon until 1972) made its first contact with the Portuguese just a few years after they anchored in India, the Luso-Sri Lankan contact was initiated and became prominent across the time, even during the later colonial rules, i.e., Dutch and British. Such connections created a Luso-Asian hybrid culture in Ceylon that shared both Sri Lankan and European identities. Portuguese Creole communities were prominent among them as an ethnic group with Portuguese descent interwoven with local traditions and customs, yet outcast by the mainstream Portuguese colonials. Hugh Nevil, a British Civil Servant who served Ceylon in the early 1800s, had collected a considerable amount of such Luso-Asian Literature belonging to Sri Lankan Portuguese creole communities, including 180 Portuguese creole verses sung by the creole communities in Eastern Sri Lanka. Though the collection was studied to uncover literature traits, few or no known studies focused on the anti-colonial subaltern discourse appearing in the shades of this work. It is evident that these verses contain local anti-colonial ideologies that create a platform to place them as elements of Luso-Asian subaltern literature. This research explores how the language and content of these verses contradict the mainstream colonial ideologies we intend to position within a regional anti-colonial subaltern context. As this is part of a long-term research project that translates the whole collection into Sinhalese and Tamil, this study will show evidence from early 1800s verses to suggest how Luso-Asian communities create a unique subaltern linguistic and literary discourse.

Keywords: Luso Asian creoles, Luso Asian subalterns, anti-colonial ideologies, Sri Lanka Portuguese creole

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Authors: Wiriranai Brilliant Masara

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The African Peace and Security Architecture is widely celebrated and revered as a paragon of the will to address peace and security challenges in Africa. However, like any other institution, it is embedded with operational and institutional challenges that prevent it from effectively carrying out its mandate and turning goals into achieved results. The article examines the fundamental flaws and weaknesses of the African Peace and Security Architecture by focusing on its institutions, norms, instruments, and its relationship to Africa’s Regional Economic Communities. Therefore, the article reviews the flaws of the five elements of the African Peace and Security Architecture which are the Peace and Security Council, Panel of the Wise, Continental Early Warning System, African Standby Force, and Peace Fund.

Keywords: African Union, African Peace and Security Architecture, peace and security council, continental early warning system, African Standby Force, Panel of the Wise, Peace Fund

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Authors: Roshan Kamal Topno, Maneesh Kumar, Manas Ranjan Dikhit, Krishna Pandey, Major Madhukar, Vidhya Nand Rabidas, Vahab Ali, Ganesh Chandra Sahoo, Bhawana, Devendra Prasad Yadav, Rishikesh Kumar, Pradeep Das

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A diagnostic marker for asymptomatic subject becomes a crucial need for advocating early prophylactic majors to control protozoal infection. The main issue in epidemiological affected regions is the presence of an asymptomatic individual that might potentially convert to a symptomatic visceral leishmaniasis (VL). The epidemiological study has been conducted at highly VL endemic Moriyama village in Patna district, Bihar, India that covers total population of 1540 individuals. Here, 1104(74.02%) people had been randomly screened and only 46 (4.17%) asymptomatic individuals were found sero-positive by the rK39 test. After taking signed informed consent form, blood samples were collected from 46 asymptomatic subjects for further hematological and immunological tests. Total leukocyte count, hemoglobin (gm%), neutrophil, lymphocyte, platelet count and interleukin-10 (IL-10) had been included as diagnostic markers. Interestingly only 5 (10.86%) individuals showed their asymptomatic conversion into symptomatic VL patients during quarterly surveillance. In overall analysis only two markers are suggestive for disease conversion that is hemoglobin (gm%) and IL-10. In all the infected patients, both the mean decrease in hemoglobin and mean increase of IL-10 was 19.23% from its normal value. The results might suggest that hematological and immunological changes would become helpful for early diagnosis of asymptomatic to symptomatic VL conversion.

Keywords: asymptomatic, epidemiological, symptomatic visceral leishmaniasis, hemoglobin (gm%), interleukin-10, diagnosis

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Authors: Soori Nnko, Zaina Mchome, John Dusabe, Angela Obasi

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In sub-Saharan Africa, adolescent girls living in urban and periurban settings are among the groups at increased risk of getting sexually transmitted infections. One of the challenges to improve uptake of sexual and reproductive health (SRH) services among adolescents is linked to little appreciation about their vulnerability and the knowledge on availability of the SRH services. Objective: This study assesses adolescents’ perceptions on risks for SRH problems and the availability of services to prevent against SRH problems. Methodology: The study was conducted in March 2011 in Mwanza region, Tanzania. Data collection techniques included 18 Participatory Group Discussions and 17 In-depth Interviews with adolescents and young mothers aged 15-20 years. Results: Adolescents indicated that risk places included their homes, bushes, commercial centers, roadsides as well as school settings. Risk for having unprotected sex varied depending on where you are, and the time of the day. For example, collection of firewood in the bushes or water from the wells exposed girls to men who forced or lured them to have sex. The girls reported to encounter motorcyclists who offered the ride in exchange for sex. Girls also knew myriads places to seek SRH services, including public and private clinics, drug shops and traditional healers. Despite being aware of risky environment, and places to seek the services, access to SRH services were limited due to the stigma and negative attitude of community regarding adolescents’ utilization of SRH services. Conclusion: Adolescents are exposed to various risky environments, yet due to social stigma they have difficult to access the available SRH services.

Keywords: adolescent girls, sexual and reproductive health, AIDS, risk, opportunities, interventions, sub Saharan africa

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Authors: Alicia Curtin, Kathy Hall

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This paper explores research and practice shared on a masters University module entitled Children's Literature as Pedagogy. Issues explored include the meaning of childhood and literature; the definition of what counts as text, textual and literacy practice for children and adolescents. A sociocultural framework is used to define literacy practice from this perspective and student voice and experience remains central. Lessons from classroom experience and the use of innovative, multi modal and non traditional texts and pedagogical approaches are offered as examples of innovative and inclusive pedagogy in the field of literacy practice.

Keywords: non traditional, pedagogy, practice, sociocultural

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Authors: Cassey Younghans

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Background: Current health care trends demonstrate that there is an increasing number of patients being hospitalized with complex comorbidities. These complex needs require advanced therapies, and treatment goals often focus on doing everything possible to prolong life rather than focusing on the individual patient’s quality of life which is the goal of palliative care efforts. Patients benefit from palliative care in the early stages of the illness rather than after the disease progressed or the state of acuity has advanced. The clinical problem identified was that palliative care was not being implemented early enough in the disease process with patients who had complex medical conditions and who would benefit from the philosophy and skills of palliative care professionals. Purpose: The purpose of this quality improvement study was to increase the number of palliative care screenings and consults completed on adults after being admitted to one Non-ICU and Non-COVID hospital unit. Methods: A retrospective chart review assessing for possible missed opportunities to introduce palliation was performed for patients with six primary diagnoses, including heart failure, liver failure, end stage renal disease, chronic obstructive pulmonary disease, cerebrovascular accident, and cancer in a population of adults over the ago of 19 on one medical-surgical unit over a three-month period prior to the intervention. An educational session with the nurses on the benefits of palliative care was conducted by the researcher, and a screening tool was implemented. The expected outcome was to have an increase in early palliative care consultation with patients with complex comorbid conditions and a decrease in missed opportunities for the implementation of palliative care. Another retrospective chart review was completed following completion of the three month piloting of the tool. Results: During the retrospective chart review, 46 patients were admitted to the medical-surgical floor with the primary diagnoses identified in the inclusion criteria. Six patients had palliative care consults completed during that time. Twenty-two palliative care screening tools were completed during the intervention period. Of those, 15 of the patients scored a 7 or higher, suggesting that a palliative care consultation was warranted. The final retrospective chart review identified that 4 palliative consults were implemented during that time of the 31 patients who were admitted over the three month time frame. Conclusion: Educating nurses and implementing a palliative care screening upon admission can be of great value in providing early identification of patients who might benefit from palliative care. Recommendations – It is recommended that this screening tool should be used to help identify the patents of whom would benefit from a palliative care consult, and nurses would be able to initiated a palliative care consultation themselves.

Keywords: palliative care, screening, early, palliative care consult

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Authors: George Abu-Aqil, Leah Tsror, Elad Shufan, Shaul Mordechai, Mahmoud Huleihel, Ahmad Salman

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Pectobacterium and Dickeya spp which negatively affect a wide range of crops are the main causes of the aggressive diseases of agricultural crops. These aggressive diseases are responsible for a huge economic loss in agriculture including a severe decrease in the quality of the stored vegetables and fruits. Therefore, it is important to detect these pathogenic bacteria at their early stages of infection to control their spread and consequently reduce the economic losses. In addition, early detection is vital for producing non-infected propagative material for future generations. The currently used molecular techniques for the identification of these bacteria at the strain level are expensive and laborious. Other techniques require a long time of ~48 h for detection. Thus, there is a clear need for rapid, non-expensive, accurate and reliable techniques for early detection of these bacteria. In this study, infrared spectroscopy, which is a well-known technique with all its features, was used for rapid detection of Pectobacterium and Dickeya spp. at the strain level. The bacteria were isolated from potato plants and tubers with soft rot symptoms and measured by infrared spectroscopy. The obtained spectra were analyzed using different machine learning algorithms. The performances of our approach for taxonomic classification among the bacterial samples were evaluated in terms of success rates. The success rates for the correct classification of the genus, species and strain levels were ~100%, 95.2% and 92.6% respectively.

Keywords: soft rot enterobacteriaceae (SRE), pectobacterium, dickeya, plant infections, potato, solanum tuberosum, infrared spectroscopy, machine learning

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Authors: Mahmoud Reza Hosseini

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The universe is in a continuous expansion process, resulting in the reduction of its density and temperature. Also, by extrapolating back from its current state, the universe at its early times has been studied known as the big bang theory. According to this theory, moments after creation, the universe was an extremely hot and dense environment. However, its rapid expansion due to nuclear fusion led to a reduction in its temperature and density. This is evidenced through the cosmic microwave background and the universe structure at a large scale. However, extrapolating back further from this early state reaches singularity which cannot be explained by modern physics and the big bang theory is no longer valid. In addition, one can expect a nonuniform energy distribution across the universe from a sudden expansion. However, highly accurate measurements reveal an equal temperature mapping across the universe which is contradictory to the big bang principles. To resolve this issue, it is believed that cosmic inflation occurred at the very early stages of the birth of the universe According to the cosmic inflation theory, the elements which formed the universe underwent a phase of exponential growth due to the existence of a large cosmological constant. The inflation phase allows the uniform distribution of energy so that an equal maximum temperature could be achieved across the early universe. Also, the evidence of quantum fluctuations of this stage provides a means for studying the types of imperfections the universe would begin with. Although well-established theories such as cosmic inflation and the big bang together provide a comprehensive picture of the early universe and how it evolved into its current state, they are unable to address the singularity paradox at the time of universe creation. Therefore, a practical model capable of describing how the universe was initiated is needed. This research series aims at addressing the singularity issue by introducing an energy conversion mechanism. This is accomplished by establishing a state of energy called a “neutral state”, with an energy level which is referred to as “base energy” capable of converting into other states. Although it follows the same principles, the unique quanta state of the base energy allows it to be distinguishable from other states and have a uniform distribution at the ground level. Although the concept of base energy can be utilized to address the singularity issue, to establish a complete picture, the origin of the base energy should be also identified. This matter is the subject of the first study in the series “A Conceptual Study for Investigating the Creation of Energy and Understanding the Properties of Nothing” which is discussed in detail. Therefore, the proposed concept in this research series provides a road map for enhancing our understating of the universe's creation from nothing and its evolution and discusses the possibility of base energy as one of the main building blocks of this universe.

Keywords: big bang, cosmic inflation, birth of universe, energy creation

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Authors: Shaik Asha Begum, S. Joshna Rani, Shaik Abdul Rahaman

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INTRODUCTION: Breast cancer is a disease that creates in breast cells. "KAP" study estimates the Knowledge, Attitude, and Practices of a local area. More than 1.5 million ladies (25% of all ladies with malignancy) are determined to have bosom disease consistently all through the world. Understanding the degrees of Knowledge, Attitude and Practice will empower a more effective cycle of mindfulness creation as it will permit the program to be custom-made all the more properly to the necessities of the local area. OBJECTIVES: The objective of this study is to assess the knowledge on signs and symptoms, risk factors, provide awareness on the practicing of the early detection techniques of breast cancer and provide knowledge on the overall breast cancer including preventive techniques. METHODOLOGY: This is an expressive cross-sectional investigation. This investigation of KAP was done in the Nirmala Educational Institutions from January to April 2021. A total of 300 participants are included from women students in pharmacy graduates & lecturers, and also from graduates other than the pharmacy. The examiners are taken from the BCAM (Breast Cancer Awareness Measure), tool compartment (Version 2). RESULT: According to the findings of the study, the majority of the participants were not well informed about breast cancer. A lump in the breast was the most commonly mentioned sign of breast cancer, followed by pain in the breast or nipple. The percentage of knowledge related to the breast cancer risk factors was also very less. The correct answers for breast cancer risk factors were radiation exposure (58.20 percent), a positive family history (47.6 percent), obesity (46.9 percent), a lack of physical activity (43.6 percent), and smoking (43.2 percent). Breast cancer screening, on the other hand, was uncommon (only 30 and 11.3 percent practiced clinical breast examination and mammography respectively). CONCLUSION: In this study, the knowledge on the signs and symptoms, risk factors of breast cancer - pharmacy graduates have more knowledge than the non-pharmacy graduates but in the preventive techniques and early detective tools of breast cancer -had poor knowledge in the pharmacy and non-pharmacy graduate. After the awareness program, pharmacy and non-pharmacy graduates got supportive knowledge on the preventive techniques and also practiced the early detective techniques of breast cancer.

Keywords: breast cancer, mammography, KAP study, early detection

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Authors: Angélique Laurent, Marie-Josée Letarte, Jean-Pascal Lemelin, Marie-France Morin

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This study aims at exploring teacher-child interactions within learning contexts in public prekindergartens of the province of Québec (Canada). It is based on previous research showing that teacher-child interactions in preschools have direct and determining effects on the quality of early childhood education and could directly or indirectly influence child development. However, throughout a typical preschool day, children experience different learning contexts to promote their learning opportunities. Depending on these specific contexts, teacher-child interactions could vary, for example, between free play and shared book reading. Indeed, some studies have found that teacher-directed or child-directed contexts might lead to significant variations in teacher-child interactions. This study drew upon both the bioecological and the Teaching Through Interactions frameworks. It was conducted through a descriptive and correlational design. Fifteen teachers were recruited to participate in the study. At Time 1 in October, they completed a diary to report the learning contexts they proposed in their classroom during a typical week. At Time 2, seven months later (May), they were videotaped three times in the morning (two weeks’ time between each recording) during a typical morning class. The quality of teacher-child interactions was then coded with the Classroom Assessment Scoring System (CLASS) through the contexts identified. This tool measures three main domains of interactions: emotional support, classroom organization, and instruction support, and10 dimensions scored on a scale from 1 (low quality) to 7 (high quality). Based on the teachers’ reports, five learning contexts were identified: 1) shared book reading, 2) free play, 3) morning meeting, 4) teacher-directed activity (such as craft), and 5) snack. Based on preliminary statistical analyses, little variation was observed within the learning contexts for each domain of the CLASS. However, the instructional support domain showed lower scores during specific learning contexts, specifically free play and teacher-directed activity. Practical implications for how preschool teachers could foster specific domains of interactions depending on learning contexts to enhance children’s social and academic development will be discussed.

Keywords: teacher practices, teacher-child interactions, preschool education, learning contexts, child development

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Authors: Cangir Uyarlar, Ismail Bayram, Ibrahim Sadi Cetingul, Mustafa Kabu, Eyup Eren Gultepe

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This study was conducted to determine the effects of organic chromium and organic chromium+propylene glycol on milk yield and some blood parameters related with liver fatty acid metabolism in early lactation dairy cows. Thirty multiparous Holstein dairy cows were used as study material. Cows assigned to three groups as control (C), chromium (Cr) and chromium+propylene glycol (CP). Live weight, parity and body condition score were used as covariates for statistical analyses. The study began at calving and finished at 3 weeks after calving. All cows were consumed same diet. Organic chromium and organic chromium+propylene glycol were orally administrated to cows in treatment groups shortly after the morning milking. Blood samples were collected from all cows on 0 (calving), 3rd, 6th, 9th, 12th, 15th, 18th, 21th days after calving. Then, samples were analyzed for BHBA (Betahydroxybutiric acids), NEFA (Non Esterified Fatty Acids), urea, total protein (TP) and glucose concentrations. Weekly milk yields were calculated from daily milk data on farm. Organic chromium treatment had no significant differences on serum biochemical parameters and milk yields. However, administration of organic chromium and propylene glycol combination decreased serum urea and total protein concentration, helped to protection from subclinical metabolic diseases via decreasing serum NEFA and BHBA concentrations. Also, this combination decreased serum glucose levels of cows. Neither only chromium nor chromium and propylene glycol combination did not affect milk yield throughout the study. These findings were suggested that orally administrations of chromium and propylene glycol combination improved liver glucose and fatty acid metabolism, decreased serum parameters which are representing subclinical diseases in early lactation dairy cows.

Keywords: chromium, early lactation dairy cows, propylene glycol, milk yield

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Authors: Vijaykumar M. Baragi, Ramtilak Gattu, Gabriela Trifan, John L. Woodard, K. Meyers, Tim S. Halstead, Eric Hipple, Ewart Mark Haacke, Randall R. Benson

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NFL players, by virtue of their exposure to repetitive head injury, are at least twice as likely to develop Alzheimer's disease (AD) and dementia as the general population. Early recognition and intervention prior to onset of clinical symptoms could potentially avert/delay the long-term consequences of these diseases. Since AD is thought to have a long preclinical incubation period, the aim of the current research was to determine whether former NFL players, referred to a depression center, showed evidence of incipient dementia in their structural imaging prior to diagnosis of dementia. Thus, to identify neuroimaging markers of AD, against which former NFL players would be compared, we conducted a comprehensive volumetric analysis using a cohort of early stage AD patients (ADNI) to produce a set of brain regions demonstrating sensitivity to early AD pathology (i.e., the “AD fingerprint”). A cohort of 46 former NFL players’ brain MRIs were then interrogated using the AD fingerprint. Brain scans were done using a T1-weighted MPRAGE sequence. The Free Surfer image analysis suite (version 6.0) was used to obtain the volumetric and cortical thickness data. A total of 55 brain regions demonstrated significant atrophy or ex vacuo dilatation bilaterally in AD patients vs. healthy controls. Of the 46 former NFL players, 19 (41%) demonstrated a greater than expected number of atrophied/dilated AD regions when compared with age-matched controls, presumably reflecting AD pathology.

Keywords: alzheimers, neuroimaging biomarkers, traumatic brain injury, free surfer, ADNI

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Authors: Hyun-Woo Cho

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Automatic process monitoring schemes are designed to give early warnings for unusual process events or abnormalities as soon as possible. For this end, various techniques have been developed and utilized in various industrial processes. It includes multivariate statistical methods, representation skills in reduced spaces, kernel-based nonlinear techniques, etc. This work presents a nonlinear empirical monitoring scheme for batch type production processes with incomplete process measurement data. While normal operation data are easy to get, unusual fault data occurs infrequently and thus are difficult to collect. In this work, noise filtering steps are added in order to enhance monitoring performance by eliminating irrelevant information of the data. The performance of the monitoring scheme was demonstrated using batch process data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: batch process, monitoring, measurement, kernel method

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Authors: Claudia Carbajal, Jija Dutt, Smriti Pahwa, Sumukhi Vaid, Karishma Vats

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ASER Centre, the research and assessment arm of Pratham Education Foundation sees measurement as the first stage of action. ASER uses primary research to push and give empirical foundations to policy discussions at a multitude of levels. At a household level, common citizens use a simple assessment (a floor-level test) to measure learning across rural India. This paper presents the evidence on the applicability of an ASER approach to the health sector. A citizen-led assessment was designed and executed that collected information from young mothers with children up to a year of age. The pilot assessments were rolled-out in two different models: Paid surveyors and student volunteers. The survey covered three geographic areas: 1,239 children in the Jaipur District of Rajasthan, 2,086 in the Rae Bareli District of Uttar Pradesh, and 593 children in the Bhuj Block in Gujarat. The survey tool was designed to study knowledge of health-related issues, daily practices followed by young mothers and access to relevant services and programs. It provides insights on behaviors related to infant and young child feeding practices, child and maternal nutrition and supplementation, water and sanitation, and health services. Moreover, the survey studies the reasons behind behaviors giving policy-makers actionable pathways to improve implementation of social sector programs. Although data on health outcomes are available, this approach could provide a rapid annual assessment of health issues with indicators that are easy to understand and act upon so that measurements do not become an exclusive domain of experts. The results give many insights into early childhood health behaviors and challenges. Around 98% of children are breastfed, and approximately half are not exclusively breastfed (for the first 6 months). Government established diet diversity guidelines are met for less than 1 out of 10 children. Although most households are satisfied with the quality of drinking water, most tested households had contaminated water.

Keywords: citizen-led assessment, rapid health assessment, Infant and Young Children Feeding, water and sanitation, maternal nutrition, supplementation

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Authors: Merav Ben Natan, May Revach, Or Sade, Yaniv Yonay, Yaron Berkovich

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Background: The inclusion of nurse practitioners (NPs) specializing in orthopedics holds promise for enhancing the quality of care for orthopedic patients. Understanding patients’ perspectives on this role is crucial for evaluating the feasibility and acceptance of integrating NPs into orthopedic settings. This study aims to explore the receptiveness of orthopedic patients to treatment by orthopedic NPs and examines potential associations between patients’ willingness to engage with NPs, their familiarity with the NP role, perceptions of nursing, and satisfaction with orthopedic nursing care. Methods: This cross-sectional study involved patients admitted to an orthopedic department at a central Israeli hospital between January and February 2023. Data was collected using a validated questionnaire consisting of five sections, reviewed by content experts. Statistical analyses were conducted using SPSS and included descriptive statistics, independent samples t-tests, Pearson correlations, and linear regression. Results: Participants in the study showed a moderate willingness to receive treatment from orthopedic NPs, with more than two-thirds expressing strong openness. Patients were generally receptive to NPs performing various clinical tasks, though there was less enthusiasm for NPs’ involvement in medication management and preoperative evaluations. Positive attitudes towards nurses and familiarity with the NP role were significant predictors of patient receptiveness to NP treatment. Conclusion: Patient acceptance of orthopedic NPs varies across different aspects of care. While there is a general willingness to receive care from NPs, these nuanced preferences must be considered when implementing NPs in orthopedic settings. Awareness and positive perceptions of the NP role play crucial roles in shaping patients’ willingness to engage with NPs.

Keywords: orthopedic nurse practitioners, patient receptiveness, perceptions of nursing, clinical tasks

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Authors: Alireza Fallahfard, Ludwig Vinches, Stephane Halle

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In the workplace, the exposure level of airborne contaminants should be evaluated due to health and safety issues. It can be done by numerical models or experimental measurements, but the numerical approach can be useful when it is challenging to perform experiments. One of the simplest models is the well-mixed room (WMR) model, which has shown its usefulness to predict inhalation exposure in many situations. However, since the WMR is limited to gases and vapors, it cannot be used to predict exposure to aerosols. The main objective is to modify the WMR model to expand its application to exposure scenarios involving aerosols. To reach this objective, the standard WMR model has been modified to consider the deposition of particles by gravitational settling and Brownian and turbulent deposition. Three deposition models were implemented in the model. The time-dependent concentrations of airborne particles predicted by the model were compared to experimental results conducted in a 0.512 m3 chamber. Polystyrene particles of 1, 2, and 3 µm in aerodynamic diameter were generated with a nebulizer under two air changes per hour (ACH). The well-mixed condition and chamber ACH were determined by the tracer gas decay method. The mean friction velocity on the chamber surfaces as one of the input variables for the deposition models was determined by computational fluid dynamics (CFD) simulation. For the experimental procedure, the particles were generated until reaching the steady-state condition (emission period). Then generation stopped, and concentration measurements continued until reaching the background concentration (decay period). The results of the tracer gas decay tests revealed that the ACHs of the chamber were: 1.4 and 3.0, and the well-mixed condition was achieved. The CFD results showed the average mean friction velocity and their standard deviations for the lowest and highest ACH were (8.87 ± 0.36) ×10-2 m/s and (8.88 ± 0.38) ×10-2 m/s, respectively. The numerical results indicated the difference between the predicted deposition rates by the three deposition models was less than 2%. The experimental and numerical aerosol concentrations were compared in the emission period and decay period. In both periods, the prediction accuracy of the modified model improved in comparison with the classic WMR model. However, there is still a difference between the actual value and the predicted value. In the emission period, the modified WMR results closely follow the experimental data. However, the model significantly overestimates the experimental results during the decay period. This finding is mainly due to an underestimation of the deposition rate in the model and uncertainty related to measurement devices and particle size distribution. Comparing the experimental and numerical deposition rates revealed that the actual particle deposition rate is significant, but the deposition mechanisms considered in the model were ten times lower than the experimental value. Thus, particle deposition was significant and will affect the airborne concentration in occupational settings, and it should be considered in the airborne exposure prediction model. The role of other removal mechanisms should be investigated.

Keywords: aerosol, CFD, exposure assessment, occupational settings, well-mixed room model, zonal model

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Authors: Chiang Wei, Hui-Chung Yeh, Yen-Chang Chen

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The objective of this study is to estimate the rainfall using the new generation Himawari-8 meteorological satellite with multi-band, high-bit format, and high spatiotemporal resolution, ground rainfall data at the Chen-Yu-Lan watershed of Joushuei River Basin (443.6 square kilometers) in Central Taiwan. Accurate and fine-scale rainfall information is essential for rugged terrain with high local variation for early warning of flood, landslide, and debris flow disasters. 10-minute and 2 km pixel-based rainfall of Typhoon Megi of 2016 and meiyu on June 1-4 of 2017 were tested to demonstrate the new generation Himawari-8 meteorological satellite can capture rainfall variation in the rugged mountainous area both at fine-scale and watershed scale. The results provide the valuable rainfall information for early warning of future disasters.

Keywords: estimation, Himawari-8, rainfall, satellite imagery

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Authors: Marja A. Bernardo, Coreena A. Bueser, Cybele Lara R. Abad, Raul V. Destura

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Pneumocystis jirovecii pneumonia (PCP) is the most common opportunistic infection among people with HIV. Early consideration of PCP should be made even in patients whose HIV status is unknown as delay in treatment may be fatal. The use of absolute lymphocyte count (ALC) has been suggested as an alternative predictor of PCP especially in resource limited settings where PCR testing is costly or delayed. Objective: To determine whether the absolute lymphocyte count (ALC) can be used as a screening tool to predict Pneumocystis pneumonia in patients with unknown HIV status admitted at a private tertiary hospital. Methods: A retrospective cross-sectional study was conducted at a private tertiary medical center. Inpatient medical records of patients aged 18 years old and above from January 2012 to May 2014, in whom a clinical diagnosis of Pneumocystis jirovecii pneumonia was made were reviewed for inclusion. Demographic data, clinical features, hospital course, PCP PCR and HIV results were recorded. Independent t-test and chi-square analysis was used to determine any statistical difference between PCP-positive and PCP-negative groups. Mann-Whitney U-test was used for comparison of hospital stay. Results: There were no statistically significant differences in baseline characteristics between PCP positive and negative groups. While both the percent lymphocyte count (0.14 ± 0.13 vs 0.21 ± 0.16) and ALC (1160 ± 528.67 vs 1493.70 ± 988.61) were lower for the PCP-positive group, only the percent lymphocyte count reached a statistically significant difference (p= 0.067 vs p= 0.042). Conclusion: A quick determination of the ALC may be useful as an additional parameter to help screen for and diagnose pneumocystis pneumonia. In our study, the ALC of patients with PCP appear to be lower than in patients without PCP. A low ALC (e.g. below 1200) may help with the decision regarding empiric treatment. However, it should be used in conjunction with the patient’s clinical presentation, as well as other diagnostic tests. Larger, prospective studies incorporating the ALC with other clinical predictors are necessary to optimally predict those who would benefit from empiric or expedited management for potential PCP.

Keywords: Pneumocystis carinii pneumonia, Absolute Lymphocyte Count, infection, PCP

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Authors: Kara Rosenblatt, Kevin Badgett, James Eldridge

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There is a preponderance of information regarding the overall effectiveness of charter schools and their ability to increase academic achievement compared to traditional district schools. Most research on the topic is focused on comparing long and short-term outcomes, academic achievement in mathematics and reading, and locale (i.e., urban, v. Rural). While the lingering unanswered questions regarding effectiveness continue to loom for school leaders, data on charter schools suggests that enrollment increases by 10% annually and that charter schools educate more than 2 million U.S. students across 40 states each year. Given the increasing share of U.S. students educated in charter schools, it is important to better understand possible differences in student achievement defined in multiple ways for students in charter schools and for those in Independent School District (ISD) settings in the state of Texas. Data were retrieved from the Texas Education Agency’s (TEA) repository that includes data organized annually and available on the TEA website. Specific data points and definitions of achievement were based on characterizations of achievement found in the relevant literature. Specific data points include but were not limited to graduation rate, student performance on standardized testing, and teacher-related factors such as experience and longevity in the district. Initial findings indicate some similarities with the current literature on long-term student achievement in English/Language Arts; however, the findings differ substantially from other recent research related to long-term student achievement in social studies. There are a number of interesting findings also related to differences between achievement for students in charters and ISDs and within different types of charter schools in Texas. In addition to findings, implications for leadership in different settings will be explored.

Keywords: charter schools, ISDs, student achievement, implications for PK-12 school leadership

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Authors: Hang T. T. Tran, Ha T. Le, Hanh T. P. Tran, Hung V. Cao, Giang T. H. Nguyen, Dien M. Tran, Tobias Alfvén, Linus Olson

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Background: Hypoxic Ischemic Encephalopathy is one of the major causes of neonatal death and those who survive with severe encephalopathy are more likely to develop adverse long-term outcomes such as neurocognitive impairment and cerebral palsy, which is a huge burden, especially in low-middle income countries. It is important to have a long-term follow-up for early detection and promote early intervention for these groups of high-risk infants. Aim: To determine the neurological outcome of cooling infants at 18 months and identify an optimized neurological examination scale for Hypoxic Ischemic Encephalopathy infants in Vietnam. Method: Descriptive study of neurodevelopmental outcomes at 18 months of HIE infants who underwent therapeutic hypothermia treatment in Vietnam. All survived cooling infants were assessed at discharge and at 6, 12, and 18 months by a pediatric physical therapist and a neurologist using two assessment tools: Ages and Stages Questionnaires and the Hammersmith Infant Neurological Examination scale to detect impairments and promote early intervention for those who require it. Results: During a 3-year period, a total of 130 neonates with moderate to severe HIE underwent therapeutic hypothermia treatment using Phase change material mattress (65% moderate, 35% severe – Sarnat). 43 (33%) died during hospitalization and infancy; among survivors, 69 (79%) completed 3 follow-ups at 18 months. At 18 months, 25 had cerebral palsy, 11 had mild delayed neurodevelopment. At each time-point, infants with a normal/mildly delayed neurodevelopment had significantly higher Ages and Stages Questionnaires and Hammersmith Infant Neurological Examination scores (p<0.05) than those with cerebral palsy. Conclusion: The study showed that the Ages and Stages Questionnaires and Hammersmith Infant Neurological Examination is a helpful tool in the process of early diagnosis of infants at low and high neurological risk and identifying those infants needing specific rehabilitation programme.

Keywords: encephalopathy, phase-change-material, neurodevelopment, cerebral palsy

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Authors: Rıza Gürhan Korkut, Metin Çelik, Süleyman Özkaynak

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The early-stage design and development projects for the freight village initiatives require a comprehensive analysis of both qualitative and quantitative data. Considering the literature review on structural and operational management requirements, this study proposed an original taxonomy on criterion structure to assess freight village conceptualization. The potential challenges and uncertainties of the developed taxonomy are extended. Besides requirement analysis, this study is also expected to contribute to forthcoming research on benchmarking of freight villages in different regions. The methodology used in this research is a systematic review on several articles as per their modelling approaches, sustainability, entities and decisions made together with the uncertainties and features of their models taken into consideration. The major findings of the study that are the categories for assessing the projects attributes on their environmental, socio-economical, accessibility and location aspects.

Keywords: logistics centers, freight village, operational management, taxonomy

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Authors: Linyi Fan, C.J. Schumaker

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Background: Biomedical efforts to treat Alzheimer’s disease (AD) have typically produced mixed to poor results, while more lifestyle-focused treatments such as exercise may fare better than existing biomedical treatments. A few promising studies have indicated that activities of daily life (ADL) may be a useful way of predicting AD. However, the existing cross-sectional studies fail to show how functional-related issues such as ADL in early years predict AD and how social factors influence health either in addition to or in interaction with individual risk factors. This study would helpbetterscreening and early treatments for the elderly population and healthcare practice. The findings have significance academically and practically in terms of creating positive social change. Methodology: The purpose of this quantitative historical, correlational study was to examine the relationship between early years’ ADL and the development of AD in later years. The studyincluded 4,526participantsderived fromRAND HRS dataset. The Health and Retirement Study (HRS) is a longitudinal household survey data set that is available forresearchof retirement and health among the elderly in the United States. The sample was selected by the completion of survey questionnaire about AD and dementia. The variablethat indicates whether the participant has been diagnosed with AD was the dependent variable. The ADL indices and changes in ADL were the independent variables. A four-step multilevel regression model approach was utilized to address the research questions. Results: Amongst 4,526 patients who completed the AD and dementia questionnaire, 144 (3.1%) were diagnosed with AD. Of the 4,526 participants, 3,465 (76.6%) have high school and upper education degrees,4,074 (90.0%) were above poverty threshold. The model evaluatedthe effect of ADL and change in ADL on onset of AD in late years while allowing the intercept of the model to vary by level of education. The results suggested that the only significant predictor of the onset of AD was changes in early years’ ADL (b = 20.253, z = 2.761, p < .05). However, the result of the sensitivity analysis (b = 7.562, z = 1.900, p =.058), which included more control variables and increased the observation period of ADL, are not supported this finding. The model also estimated whether the variances of random effect vary by Level-2 variables. The results suggested that the variances associated with random slopes were approximately zero, suggesting that the relationship between early years’ ADL were not influenced bysociodemographic factors. Conclusion: The finding indicated that an increase in changes in ADL leads to an increase in the probability of onset AD in the future. However, this finding is not support in a broad observation period model. The study also failed to reject the hypothesis that the sociodemographic factors explained significant amounts of variance in random effect. Recommendations were then made for future research and practice based on these limitations and the significance of the findings.

Keywords: alzheimer’s disease, epidemiology, moderation, multilevel modeling

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Authors: Tanmay Bisen, Aastha Shayla, Susham Biswas

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Oil spills from tankers can cause significant harm to the environment and local communities, as well as have economic consequences. Early predictions of oil spills can help to minimize these impacts. Our proposed system uses machine learning and neural networks to predict potential oil spills by monitoring data from ship Automatic Identification Systems (AIS). The model analyzes ship movements, speeds, and changes in direction to identify patterns that deviate from the norm and could indicate a potential spill. Our approach not only identifies anomalies but also predicts spills before they occur, providing early detection and mitigation measures. This can prevent or minimize damage to the reputation of the company responsible and the country where the spill takes place. The model's performance on the MV Wakashio oil spill provides insight into its ability to detect and respond to real-world oil spills, highlighting areas for improvement and further research.

Keywords: Anomaly Detection, Oil Spill Prediction, Machine Learning, Image Processing, Graph Neural Network (GNN)

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Authors: Amit Syal, Madeline Grade, Alister Martin

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Background: Cross-sectional and longitudinal studies demonstrate an association between health and voting. Furthermore, voting enables populations to support policies that impact their health via social determinants like income, education, housing, and healthcare access. Unfortunately, many barriers exist which disproportionately affect the civic participation of certain minority groups. Health professionals have an important role to play in addressing the civic health of all patients and empowering underrepresented communities. Description: Vot-ER is a non-partisan, nonprofit organization that aims to reduce barriers to civic participation by helping patients register to vote while in healthcare settings. The initial approach involved iPad-based kiosks in the emergency department waiting rooms, allowing patients to register themselves while waiting. After the COVID-19 pandemic began, Vot-ER expanded its touchless digital approaches. Vot-ER provides healthcare workers across the country with “Healthy Democracy Kits” consisting of badge backers, posters, discharge paperwork, and other resources. These contain QR and text codes that direct users to an online platform for registering to vote or requesting a mail-in ballot, available in English or Spanish. Outcomes: From May to November 2020, Vot-ER helped prepare 46,320 people to vote. 13,192 individual healthcare providers across all 50 states signed up for and received Healthy Democracy Kits. 80 medical schools participated in the Healthy Democracy Campaign competition. Over 500 institutions ordered site-based materials. Conclusions: A healthy democracy is one in which all individuals in a community have equal and fair opportunities for their voices to be heard. Healthcare settings, such as hospitals, are appropriate and effective venues for increasing both voter registration and education.

Keywords: civic health, enfranchisement, physician, voting

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Authors: Hazratullah Khattak, Abdul Waheed Mughal, Inamullah Khattak

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This study is envisaged as vital contribution as it intends to develop norms for the Sit and Reach Test in the Local Environment of Khyber Pakhtunkhwa Pakistan, for the age group between 12-14 years which will be used to measure the flexibility level of early adolescents (12-14 years). Sit and Reach test was applied on 2000 volunteers, 400 subjects from each selected district (Five (5) Districts, Peshawar, Nowshera, Karak, Dera Ismail Khan and Swat (20% percent of the total 25 districts) using convenient sampling technique. The population for this study is comprised of all the early adolescents aging 12-14 years (Age Mean 13 + 0.63, Height 154 + 046, Weight 46 + 7.17, BMI 19 + 1.45) representing various public and private sectors educational institutions of the Khyber Pakhtunkhwa. As for as the norms developed for Sit and Reach test, the score below 6.8 inches comes in the category of poor, 6.9 to 9.6 inches (below Average), 9.7 to 10.8 inches (Average), 10.9 to 13 inches (Above average) and above 13 inches score is considered as Excellent.

Keywords: fitness, flexibility, norms, sit and reach

Procedia PDF Downloads 280

Authors: Anoop T. R., Otman Basir, Robert F. Hess, Eileen E. Birch, Brooke A. Koritala, Reed M. Jost, Becky Luu, David Stager, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. We developed a two-stage method for strabismus detection and classification based on photographs of the face. The first stage detects the presence or absence of strabismus, and the second stage classifies the type of strabismus. The first stage comprises face detection using Haar cascade, facial landmark estimation, face alignment, aligned face landmark detection, segmentation of the eye region, and detection of strabismus using VGG 16 convolution neural networks. Face alignment transforms the face to a canonical pose to ensure consistency in subsequent analysis. Using facial landmarks, the eye region is segmented from the aligned face and fed into a VGG 16 CNN model, which has been trained to classify strabismus. The CNN determines whether strabismus is present and classifies the type of strabismus (exotropia, esotropia, and vertical deviation). If stage 1 detects strabismus, the eye region image is fed into stage 2, which starts with the estimation of pupil center coordinates using mask R-CNN deep neural networks. Then, the distance between the pupil coordinates and eye landmarks is calculated along with the angle that the pupil coordinates make with the horizontal and vertical axis. The distance and angle information is used to characterize the degree and direction of the strabismic eye misalignment. This model was tested on 100 clinically labeled images of children with (n = 50) and without (n = 50) strabismus. The True Positive Rate (TPR) and False Positive Rate (FPR) of the first stage were 94% and 6% respectively. The classification stage has produced a TPR of 94.73%, 94.44%, and 100% for esotropia, exotropia, and vertical deviations, respectively. This method also had an FPR of 5.26%, 5.55%, and 0% for esotropia, exotropia, and vertical deviation, respectively. The addition of one more feature related to the location of corneal light reflections may reduce the FPR, which was primarily due to children with pseudo-strabismus (the appearance of strabismus due to a wide nasal bridge or skin folds on the nasal side of the eyes).

Keywords: strabismus, deep neural networks, face detection, facial landmarks, face alignment, segmentation, VGG 16, mask R-CNN, pupil coordinates, angle deviation, horizontal and vertical deviation

Procedia PDF Downloads 93