Search results for: early childhood curriculum

Authors: Harley Bray, Helen Pymar, Michelle Liu, Chau Pham, Tomislav Jelic, Fran Mulhall

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Background: Our study assesses the impact of the COVID-19 pandemic on early pregnancy assessment clinic (EPAC) referrals and the use of virtual consultation in Winnipeg, Manitoba. Our clinic expanded to accept referrals from all Winnipeg Emergency Department (ED)/Urgent Care (UC) sites beginning November 2019 to April 2020. By May 2020, the COVID-19 pandemic reached Manitoba and EPAC virtual care was expanded by performing hCG remotely and reviewing blood and ED/UC ultrasound results by phone. Methods: Emergency Department Information Systems (EDIS) and EPAC data reviewed ED/UC visits for pregnancy <20 weeks and vaginal bleeding 1-year pre-COVID (March 12, 2019, to March 11, 2020) and during COVID (March 12, 2020 (first case in Manitoba) to March 11, 2021). Results: There were fewer patient visits for vaginal bleeding or pregnancy of <20 weeks (4264 vs. 5180), diagnoses of threatened abortion (1895 vs. 2283), and ectopic pregnancy (78 vs. 97) during COVID compared with pre-COVID, respectively. ICD 10 codes were missing in 849 (20%) and 1183 (23%) of patients during COVID and pre-COVID, respectively. Wait times for all patient visits improved during COVID-19 compared to pre-COVID (5.1 ± 4.4 hours vs. 5.5 ± 3.8 hours), more patients received obstetrical ultrasounds, 761 (18%) vs. 787 (15%), and fewer patients returned within 30 days (1360 (32%) vs. 1848 (36%); p<0.01). EPAC saw 708 patients (218; 31% new ED/UC) during COVID-19 compared to 552 (37; 7% new ED/UC) pre-COVID. Fewer operative interventions for pregnancy loss (346 vs. 456) and retained products (236 vs. 272) were noted. Surgeries to treat ectopic pregnancy (106 vs 113) remained stable during the study time interval. Conclusion: Accurate identification of pregnancy complications was difficult, with over 20% missing ICD-10 diagnostic codes. There were fewer ED/UC visits and surgical management for threatened abortion during COVID-19, but ectopic pregnancy operative management remained unchanged.

Keywords: early pregnancy, ultrasound, COVID-19, obstetrics

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Authors: C. Silvestros, K. Mellou, T. Georgakopoulou, A. Koustenis, E. Kokkinou, C. Botsi, A. Terzidis

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'PHILOS – Emergency health response to refugee crisis' is a programme of the Greek Ministry of Health, implemented by the Hellenic Center for Disease Control and Prevention (HCDCP) funded by the Asylum, Migration and Integration Fund (AMIF) of EU’s DG Migration and Home Affairs. One of the main objectives of the program is the immunization coverage of the target – population to assure the prevention of vaccine-preventable diseases. The program foresees vaccination needs assessment of children hosted at camps at the mainland and implementation of interventions to cover the vaccination gaps in co-operation with the Ministry of Health. The National Immunization Advisory Committee in Greece recommended that MMR (Measles, Mumps, and Rubella), PCV (Pneumococcal conjugate vaccine) and HEXA (diphtheria, tetanus, pertussis, polio, hepatitis B and Haemophilus influenzae type b) vaccines should be performed in priority. Recording was completed at 24 camps (May - June 2017); 3381 children (0-18 years) were recorded. The median number of children hosted at each camp was 95 (range: 5-553). For 68% of the children, the WHO vaccination booklet was available. 44%, 48.5% and 61% of the children were vaccinated with at least one dose of PCV, HEXA, and MMR, respectively. The proportion of vaccinated children for the three vaccines mentioned above is significantly lower for the remaining doses; PCV (second dose 8%, third dose 1.3%), HEXA (second dose 13%, third dose 2.7%, forth dose 0.1%) and MMR (second dose 23%). None of the 37 (10 from Afghanistan, 3 from Bangladesh, 23 from Pakistan, 1 from Syria) recorded unaccompanied children did not have a WHO vaccination booklet and were considered unvaccinated. There is no differentiation in vaccination coverage among different ethnicities. Massive catch up vaccination was performed at 4 camps, and 671 vaccinations were performed (245 PCV, 307 HEXA, and 119 MMR). Similar interventions are planned for all camps of the country. Recording reveled gaps in vaccination coverage of the population, mainly because of the mobility of the population, the influx of refugees- which is still ongoing- and new births. Mass vaccination campaigns are considered vital in order to increase vaccination coverage, and continuous efforts are needed in order all children living at the camps to have full access to the National Childhood Immunization Program.

Keywords: vaccine preventable, refugee–migrants camps, vaccination coverage, PCV, MMR, HEXA

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Authors: Khaled Mahmud Gaddah

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Cretaceous deposits in the southeast of the Sirt Basin of Libya occur in several grabens that formed during a major phase of rifting related to the opening of the Tethys. They include continental deposits of Early Cretaceous age that belong to the Nubian Formation and marginal to fully marine deposits of Late Cretaceous age that belong to the Lidam Formation and transitional beds. The sequence was extensively sampled from twenty-two boreholes and palynologically analysed. Much of the sequence is barren. However, subordinate shales in all formations yield diverse assemblages of poorly to well preserved and thermally middle to post mature palynomorphs. Most of the assemblages contain non-marine palynomorphs (spores, pollen, and freshwater algae), although some contain rare marine elements (dinoflagellate cysts and acritarchs). The palynofloras enabled the recognition of six assemblage zones of the late Barremian-Turonian age based on the dominant and base/top occurrences of stratigraphically useful palynomorphs: AI (Afropollisspp.-Aequitriraditesspinulosus) of late Barremian age; AIIa (Scenedesmusbifidus-S. sp.) of late Barremian?-early Aptian age; AIIb (Afropollisoperculatus-A. zonatus) of Aptian age; AIII (Crybelosporitespannuceus-Afropollisjardinus) of early Albian age; AIV (Subtilisphaera sp.-Lophosphaeridiumspp.) of Cenomanian-?Turonian age; AIV (Pediastrumbifidites-Leiosphaeridiaspp.) of Cenomanian?-Turonian age. These assemblages are comparable to others from Northern Gondwana (particularly from Libya and Egypt) and correspond to established Cretaceous palynofloral provinces. Palynofacies analysis is used to interpret the depositional environments, and five palynofacies types are recognised that reflect increasing marine influence up section.

Keywords: palynology, palynomorphs, palynofacies, tethys, sirt basin

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Authors: Fathi Ihmeideh

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The study aimed at investigating parents’ attitudes towards a school-based family program in developing kindergarten children’s literacy skills. The study surveyed 160 parents of preschool children, gathering information about their attitudes toward the development of children’s early literacy. Results indicated that parents hold positive attitudes towards the school-based family literacy program. The results also revealed statistically significant differences among parents due to a number of study variables. The study concludes with putting forward a number of practical and theoretical recommendations for the field of study. Acknowledgment: This paper was made possible by NPRP grant # (NPRP 8-921-5-122) from the Qatar national research fund (a member of Qatar foundation). The statements made herein are solely the responsibility of the authors.

Keywords: parents, literacy development, preschool children, family involvement

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Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship

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Authors: Arvind Srivastav, Tarun Kanti Bhattacharyya

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The north-eastern, Himalayan, and Eastern Ghats Belt of India comprise of earthquake-prone, remote, and hilly terrains. Earthquakes have caused enormous damages in these regions in the past. A wireless sensor network based earthquake early warning system (EEWS) is being developed to mitigate the damages caused by earthquakes. It consists of sensor nodes, distributed over the region, that perform majority voting of the output of the seismic sensors in the vicinity, and relay a message to a base station to alert the residents when an earthquake is detected. At the heart of the EEWS is a low-power two-stage seismic sensor that continuously tracks seismic events from incoming three-axis accelerometer signal at the first-stage, and, in the presence of a seismic event, triggers the second-stage P-wave detector that detects the onset of P-wave in an earthquake event. The parameters of the P-wave detector have been optimized for minimizing detection time and maximizing the accuracy of detection.Working of the sensor scheme has been verified with seven earthquakes data retrieved from IRIS. In all test cases, the scheme detected the onset of P-wave accurately. Also, it has been established that the P-wave onset detection time reduces linearly with the sampling rate. It has been verified with test data; the detection time for data sampled at 10Hz was around 2 seconds which reduced to 0.3 second for the data sampled at 100Hz.

Keywords: earthquake early warning system, EEWS, STA/LTA, polarization, wavelet, event detector, P-wave detector

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Mastewal Endeshaw Getnet

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Imunization is one of the most cost-effective and extensively adopted public health strategies for preventing child disability and mortality. Expanded Program on Immunization (EPI) was launched in 1974 with the goal of providing life-saving vaccines to all children in all and building on the success of the global smallpox eradication program. According to World Health Organization report, by 2020, all countries should have achieved 90% vaccination coverage. Many developing countries still have not achieved the goal. Ethiopia is one of Africa's developing countries. The Ethiopian Ministry of health (MoH) launched the EPI program in 1980, with the goal of achieving 90% coverage among children under the age of 1 year by 1990. Among children aged 12-23 months, complete immunization coverage was 47% based on the Ethiopian Demographic and Health Survey (EDAS) 2019 report. The coverage varies depending on the administrative region, ranging from 21% in Afar region to 89% in Amhara region, Ethiopia. Therefore, identifying risk factors for incomplete immunization among children is a key challenge, particularly in Ethiopia, which has a large geographical diversity and a predicted with 119.96 million projected population size in the year 2022. Despite its critical and challenging issue, this issue is still open and has not yet been fully investigated. Recently, a few previous studies have been conducted on the assessment of incomplete children immunization determinants. However, the majority of the studies were cross-sectional surveys that assessed only EPI coverage. Motivated by the above investigation, this study focuses on investigating determinants associated with incomplete immunization among Ethiopian children to facilitate the rate of full immunization coverage. Moreover, we consider both individual immunization and service performance-related factors to investigate incomplete children's determinants. Consequently, we adopted an ecological model in this study. Individual and environmental factors are combined in the Ecological model, which provides multilevel framework for exploring different determinants related with health behaviors. The Ethiopian Demographic and Health Survey will be used as a source of data from 2021 to achieve the objective of this study. The findings of this study will be useful to the Ethiopian government and other public health institutes to improve the coverage score of childhood immunization based on the identified risk determinants.

Keywords: incomplete immunization, children, ethiopia, ecological model

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Authors: Anna-Maria Saarela

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At the Savonia University of Applied Sciences (UAS), curriculum and studies have been improved by applying an Open Innovation Space approach (OIS). It is based on multidisciplinary action learning. The key elements of OIS-ideology are work-life orientation, and student-centric communal learning. In this approach, every participant can learn from each other and innovations will be created. In this social innovation educational approach, all practices are carried out in close collaboration with enterprises in real-life settings, not in classrooms. As an example, in this paper, Savonia UAS’s Future Food RDI hub (FF) shows how OIS practices are implemented by providing food product development and consumer research services for enterprises in close collaboration with academicians, students and consumers. In particular one example of OIS experimentation in the field is provided by a consumer research carried out utilizing verbal analysis protocol combined with audio-visual observation (VAP-WAVO). In this case, all co-learners were acting together in supermarket settings to collect the relevant data for a product development and the marketing department of a company. The company benefitted from the results obtained, students were more satisfied with their studies, educators and academicians were able to obtain good evidence for further collaboration as well as renewing curriculum contents based on the requirements of working life. In addition, society will benefit over time as young university adults find careers more easily through their OIS related food science studies. Also this knowledge interaction model re-news education practices and brings working-life closer to educational research institutes.

Keywords: collaboration, education, food science, industry, knowledge transfer, RDI, student

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Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

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A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme gradient boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impair, multiclass classification, ADNI, support vector machine, random forest

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Authors: Hui-Fang Lee, Hsuan-Jung Hsieh, Wen-Chi Lu, Meng-Chu Liu

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The purpose of the study was to examine abnormal BMI students of Chien Hsin University of Science and Technology, implement teaching aerobics course through elementary and advanced curriculum design, dietary education and three-day dietary record, analyze participant fitness improvement, an 10-week course as well as pre-test and post-test were carried out to evaluate the effect of the aerobics course on the fitness ability. The actual participate elementary and advanced courses each of 40 people, with low participation deduction course unfinished fitness testing, access to elementary curriculum valid samples 35 (87.5%) people, advanced courses valid samples 38(95%) people, 16 students participated in two consecutive courses. The fitness activities included sit-bending, one-minute sit-ups, standing long jump, and three minutes to board the stage. Analysis and comparison to the average three-day dietary record difference, an independent samples t-test was conducted to analyze the differences in the four activities between pre-test and post-test. The results showed that the elementary course had significant effects on females’ sit-bending and one minute sit-ups, the females also had high fat intake in three-day dietary record. The advanced course had significant effects on males’ sit-bending and on females’ BMI, sit-bending and standing long jump, males and females in three-day dietary record carbohydrate intake slightly low, slightly higher protein and fat intake. In conclusion, aerobics course teaching, dietary education and three-day, dietary record implementation can significantly enhance the physical fitness indicators, and continued to participate in advanced courses better. In the practice of sport should be the future course planning elementary and advanced courses, while introducing dietary education, achieve concrete results in improving physical fitness.

Keywords: physical fitness, aerobics course, dietary education, three-day dietary record

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Authors: Jinhui Bak, Bumjin Kim

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The purpose of this study is to analyze how the scientific and mathematical fields (STEM) and liberal arts (A) work together in the STEAM program. In the future STEAM programs that have been designed and developed, the humanities will act not just as a 'tool' for science technology and mathematics, but as a 'core' content to have an equivalent status. STEAM was first introduced to the Republic of Korea in 2011 when the Ministry of Education emphasized fostering creative convergence talent. Many programs have since been developed under the name STEAM, but with the majority of programs focusing on technology education, arts and humanities are considered secondary. As a result, arts is most likely to be accepted as an option that can be excluded from the teachers who run the STEAM program. If what we ultimately pursue through STEAM education is in fostering STEAM literacy, we should no longer turn arts into a tooling area for STEM. Based on this consciousness, this study analyzed over 160 STEAM programs in middle and high schools, which were produced and distributed by the Ministry of Education and the Korea Science and Technology Foundation from 2012 to 2017. The framework of analyses referenced two criteria presented in the related prior studies: normative convergence and technological convergence. In addition, we divide Arts into fine arts and liberal arts and focused on Korean Language Course which is in liberal arts and analyzed what kind of curriculum standards were selected, and what kind of process the Korean language department participated in teaching and learning. In this study, to ensure the reliability of the analysis results, we have chosen to cross-check the individual analysis results of the two researchers and only if they are consistent. We also conducted a reliability check on the analysis results of three middle and high school teachers involved in the STEAM education program. Analyzing 10 programs selected randomly from the analyzed programs, Cronbach's α .853 showed a reliable level. The results of this study are summarized as follows. First, the convergence ratio of the liberal arts was lowest in the department of moral at 14.58%. Second, the normative convergence is 28.19%, which is lower than that of the technological convergence. Third, the language and achievement criteria selected for the program were limited to functional areas such as listening, talking, reading and writing. This means that the convergence of Korean language departments is made only by the necessary tools to communicate opinions or promote scientific products. In this study, we intend to compare these results with the STEAM programs in the United States and abroad to explore what elements or key concepts are required for the achievement criteria for Korean language and curriculum. This is meaningful in that the humanities field (A), including Korean, provides basic data that can be fused into 'equivalent qualifications' with science (S), technical engineering (TE) and mathematics (M).

Keywords: Korean STEAM Programme, liberal arts, STEAM curriculum, STEAM Literacy, STEM

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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: 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: Lauren B. Birney

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The project utilizes the Billion Oyster Project (BOP-CCERS) place-based “restoration through education” model to promote computational thinking in NYC high school teachers and their students. Key learning standards such as Next Generation Science Standards and the NYC CS4All Equity and Excellence initiative are used to develop a computer science curriculum that connects students to their Harbor through hands-on activities based on BOP field science and educational programming. Project curriculum development is grounded in BOP-CCERS restoration science activities and data collection, which are enacted by students and educators at two Restoration Science STEM Hubs or conveyed through virtual materials. New York City Public School teachers with relevant experience are recruited as consultants to provide curriculum assessment and design feedback. The completed curriculum units are then conveyed to NYC high school teachers through professional learning events held at the Pace University campus and led by BOP educators. In addition, Pace University educators execute the Summer STEM Institute, an intensive two-week computational thinking camp centered on applying data analysis tools and methods to BOP-CCERS data. Both qualitative and quantitative analyses were performed throughout the five-year study. STEM+C – Community Based Restoration STEM Hubs. STEM Hubs are active scientific restoration sites capable of hosting school and community groups of all grade levels and professional scientists and researchers conducting long-term restoration ecology research. The STEM Hubs program has grown to include 14 STEM Hubs across all five boroughs of New York City and focuses on bringing in-field monitoring experience as well as coastal classroom experience to students. Restoration Science STEM Hubs activities resulted in: the recruitment of 11 public schools, 6 community groups, 12 teachers, and over 120 students receiving exposure to BOP activities. Field science protocols were designed exclusively around the use of the Oyster Restoration Station (ORS), a small-scale in situ experimental platforms which are suspended from a dock or pier. The ORS is intended to be used and “owned” by an individual school, teacher, class, or group of students, whereas the STEM Hub is explicitly designed as a collaborative space for large-scale community-driven restoration work and in-situ experiments. The ORS is also an essential tool in gathering Harbor data from disparate locations and instilling ownership of the research process amongst students. As such, it will continue to be used in that way. New and previously participating students will continue to deploy and monitor their own ORS, uploading data to the digital platform and conducting analysis of their own harbor-wide datasets. Programming the STEM Hub will necessitate establishing working relationships between schools and local research institutions. NYHF will provide introductions and the facilitation of initial workshops in school classrooms. However, once a particular STEM Hub has been established as a space for collaboration, each partner group, school, university, or CBO will schedule its own events at the site using the digital platform’s scheduling and registration tool. Monitoring of research collaborations will be accomplished through the platform’s research publication tool and has thus far provided valuable information on the projects’ trajectory, strategic plan, and pathway.

Keywords: environmental science, citizen science, STEM, technology

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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: Paula Smith

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During adolescence, many students engage in maladaptive behaviors that may reflect a lack of knowledge in social-emotional skills. Oftentimes these behaviors lead to conflicts and school-related disciplinary actions. Therefore, conflict resolution skills are vital for academic and social success. Conflict resolution is one component of a social-emotional learning (SEL) pedagogy that can effectively reduce discipline referrals and build students' social-emotional capacity. This action research study utilized a researcher-developed virtual SEL curriculum to provide instruction to eight adolescent students in an urban school in New York City with the goal of fostering their emotional intelligence (EI), reducing aggressive behaviors, and supporting instruction beyond the core academic content areas. Adolescent development, EI, and SEL frameworks were used to formulate this curriculum. Using a qualitative approach, this study inquired into how effectively participants responded to SEL instruction offered in virtual, Zoom-based workshops. Data included recorded workshop sessions, researcher field notes, and Zoom transcripts. Descriptive analysis involved manual coding/re-coding of transcripts to understand participants’ lived experience with conflict and the ideas presented in the workshops. Findings highlighted several themes and cultural norms that provided insight into adolescents' lived experiences and helped explain their past ideas about conflict. Findings also revealed participants' perspectives about the importance of SEL skills. This study illustrates one example of how evidence-based SEL programs might offer adolescents an opportunity to share their lived experiences. Programs such as this also address both individual and group needs, enabling practitioners to help students develop practical conflict resolution skills.

Keywords: social, emotional, learning, conflict, resolution

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Authors: Bruce Wrightsman

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Traditionally, in architectural education, we develop studio projects with learning agendas that try to minimize conflict and reveal clear design objectives. Knowledge is gleaned only tacitly through confronting the reciprocity of site and form, space and light, structure and envelope. This institutional reality can limit student learning to the latent learning opportunities they will have to confront later in practice. One intent of academic design-build projects is to address the learning opportunities which one can discover in the messy grey areas of design. In this immersive experience, students confront the limitations of classroom learning and are exposed to challenges that demand collaborative practice. As a result, design-build has been widely adopted in an attempt to address perceived deficiencies in design education vis a vis the integration of building technology and construction. Hands-on learning is not a new topic, as espoused by John Dewey, who posits a debate between static and active learning in his book Democracy and Education. Dewey espouses the concept that individuals should become participants and not mere observers of what happens around them. Advocates of academic design-build programs suggest a direct link between Dewey’s speculation. These experiences provide irreplaceable life lessons: that real-world decisions have real-life consequences. The goal of the paper is not to confirm or refute the legitimacy and efficacy of online virtual learning. Rather, the paper aims to foster a deeper, honest discourse on the meaning of ‘making’ in architectural education and present projects that confronted the burdens of a global pandemic and developed unique teaching strategies that challenged design thinking as an observational and constructive effort to expand design student’s making skills and foster student agency.

Keywords: design/build, making, remote teaching, architectural curriculum

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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: 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: Abebe Tibebu

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This study investigates the quality of training factors in Ethiopian Technical and Vocational Education and Training (TVET) colleges and their impact on declining enrollment rates. Employing a descriptive survey design, both quantitative and qualitative data were collected from diverse stakeholders, including Grade 12 graduates, current TVET trainees, trainers, college deans, community members, high school directors, teachers, and officials from TVET government agencies. The sample included 20 TVET centers from various Ethiopian regions. Secondary data were obtained from college and government documents, while primary data were gathered through questionnaires, interviews, focus group discussions, and observations. Analysis was conducted using descriptive statistics with SPSS, capturing response frequencies and percentages. The study's findings highlight several key factors affecting TVET enrollment: limited infrastructure capacity, insufficient trainer competency, misaligned curriculum, low-quality training delivery particularly in cooperative training implementation and industry partnership and low success rates on Certification of Competency (CoC) exams. Many TVET institutions lack qualified trainers, adequate machinery, and timely provision of materials for practical skills training. Based on these findings, the study recommends enhanced infrastructure investment, professional development for trainers, curriculum adjustments to better align with industry needs, and standardized assessment practices. Addressing these areas through collaborative efforts with government bodies and industry stakeholders is essential to improving the quality and appeal of Ethiopian TVET programs, ultimately strengthening enrollment and outcomes.

Keywords: TVET, quality factors, enrollment, potentially enrolled

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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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