Search results for: IS 17740:2022

Authors: Praniil Nagaraj

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This paper proposes a method to collect homeless data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. The 2022 Annual Homeless Assessment Report (AHAR) to Congress highlighted alarming statistics, emphasizing the need for effective decision-making and budget allocation within local planning bodies known as Continuums of Care (CoC). This paper's contributions can be categorized into three main areas. Firstly, a unique method for collecting homeless data is introduced, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, is anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data is addressed through simple classification methods, and historical data is utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining this new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data is collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homeless information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: crowdsourcing, homelessness, socio-economic policies, statistical regression

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Authors: Angela O. Ugwu, Sunday Ocheni

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Background: Cancer-associated thrombosis (CAT) is a cause of morbidity and mortality among cancer patients. Several risk factors for developing venous thromboembolism (VTE) also coexist with cancer patients, such as chemotherapy and immobilization, thus contributing to the higher risk of VTE in cancer patients when compared to non-cancer patients. This study aimed to determine if there is any correlation between levels of some inflammatory cytokines/haematological parameters and Khorana scores of newly diagnosed chemotherapy naïve ambulatory cancer patients (CNACP). Methods: This was a cross-sectional analytical study carried out from June 2021 to May 2022. Eligible newly diagnosed cancer patients 18 years and above (case group) were enrolled consecutively from the adult Oncology Clinics of the University of Nigeria Teaching Hospital, Ituku/Ozalla (UNTH). The control group was blood donors at UNTH Ituku/Ozalla, Enugu blood bank, and healthy members of the Medical and Dental Consultants Association of Nigeria (MDCAN), UNTH Chapter. Blood samples collected from the participants were assayed for IL-6, TNF-Alpha, and haematological parameters such as haemoglobin, white blood cell count (WBC), and platelet count. Data were entered into an Excel worksheet and were then analyzed using Statistical Package for Social Sciences (SPSS) computer software version 21.0 for windows. A P value of < 0.05 was considered statistically significant. Results: A total of 200 participants (100 cases and 100 controls) were included in the study. The overall mean age of the participants was 47.42 ±15.1 (range 20-76). The sociodemographic characteristics of the two groups, including age, sex, educational level, body mass index (BMI), and occupation, were similar (P > 0.05). Following One Way ANOVA, there were significant differences between the mean levels of interleukin-6 (IL-6) (p = 0.036) and tumor necrotic factor-α (TNF-α) (p = 0.001) in the three Khorana score groups of the case group. Pearson’s correlation analysis showed a significant positive correlation between the Khorana scores and IL-6 (r=0.28, p = 0.031), TNF-α (r= 0.254, p= 0.011), and PLR (r= 0.240, p=0.016). The mean serum levels of IL-6 were significantly higher in CNACP than in the healthy controls [8.98 (8-12) pg/ml vs. 8.43 (2-10) pg/ml, P=0.0005]. There were also significant differences in the mean levels of the haemoglobin (Hb) level (P < 0.001)); white blood cell (WBC) count ((P < 0.001), and platelet (PL) count (P = 0.005) between the two groups of participants. Conclusion: There is a significant positive correlation between the serum levels of IL-6, TNF-α, and PLR and the Khorana scores of CNACP. The mean serum levels of IL-6, TNF-α, PLR, WBC, and PL count were significantly higher in CNACP than in the healthy controls. Ambulatory cancer patients with high-risk Khorana scores may benefit from anti-inflammatory drugs because of the positive correlation with inflammatory cytokines. Recommendations: Ambulatory cancer patients with 2 Khorana scores may benefit from thromboprophylaxis since they have higher Khorana scores. A multicenter study with a heterogeneous population and larger sample size is recommended in the future to further elucidate the relationship between IL-6, TNF-α, PLR, and the Khorana scores among cancer patients in the Nigerian population.

Keywords: thromboprophylaxis, cancer, Khorana scores, inflammatory cytokines, haematological parameters

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Authors: Bowen Li, Dan Shu, Shiguang Pang, Li Wang, Qian Liu

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Background: Every year, approximately 429,000 adolescents aged 0-19 are diagnosed with cancer worldwide. The diagnosis brings about substantial psychological pressure and caregiving responsibilities for family members and impacts the families significantly. Family resilience has been found to reduce caregiver distress and can also foster post-traumatic growth in cancer survivors. However, current research on family resilience in childhood cancer mainly focuses on individual caregiver resilience and child adaptation, with less attention given to categorizing family resilience among caregivers of children with cancer. Method: A total of 292 caregivers of children with cancer were recruited from four tertiary hospitals in central China from July 2022 to March 2024. This study was approved by the ethics committee, and participants provided informed consent, with the option to withdraw at any time. The Family Resilience Assessment Scale was used to measure family resilience among caregivers of children with cancer. The Quality of Life scale-family, The Perceived Social Support Scale, and The Connor-Davidson Resilience Scale were used to measure potential influencing factors. This study used latent profile analysis (LPA) to identify latent categories of family resilience among caregivers of children with cancer. Binary logistic regression was used to analyze the influencing factors of family resilience. Results: The results reveal two distinct categories: "high family resilience" and "low family resilience." "Low family resilience" group accounts for 85.96% of the total while "high family resilience" group is 14.04%. "High family resilience" scores higher across all dimensions compared to "low family resilience". Within-group comparisons reveals that "family communication and problem-solving" and "empowering the meaning of adversity" received the highest scores, while "utilizing social and economic resources" scores the lowest. "Maintaining a positive attitude" scores similarly high to "family communication and problem-solving" in the high family resilience group, whereas it scores similarly low to "utilizing social and economic resources" in the low family resilience group. In single-factor analysis, residence, number of siblings, caregiver's education level, resilience, social support, quality of life, physical well-being and psychological well-being showed significant difference between two categories. In binary logistic regression analysis, households with only one child are more likely to exhibit low family resilience, whereas high personal resilience is associated with a high level of family resilience. Conclusion: Most families with children suffering from cancer require strengthened family resilience. Support for utilizing socio-economic resources is important for both high and low family resilience families. Single-child families and caregivers with lower resilience require more attention. These findings imply the development of targeted interventions to enhance family resilience among families with children of cancer. Future studies could involve children and other family members for a comprehensive understanding of family resilience. Longitudinal studies are necessary to explore the dynamic changes in family resilience throughout the cancer journey.

Keywords: cancer children, caregivers, family resilience, latent profile analysis

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Authors: Eyob Seife

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Immunization is a life-saving intervention which prevents needless suffering through sickness, disability, and death. Emphasis on data quality and use will become even stronger with the development of the immunization agenda 2030 (IA2030). Quality of data is a key factor in generating reliable health information that enables monitoring progress, financial planning, vaccine forecasting capacities, and making decisions for continuous improvement of the national immunization program. However, ensuring data of sufficient quality and promoting an information-use culture at the point of the collection remains critical and challenging, especially in hard-to-reach and pastoralist areas where Degehabur district is selected based on a hypothesis of ‘there is no difference in reported and recounted immunization data consistency. Data quality is dependent on different factors where organizational, behavioral, technical, and contextual factors are the mentioned ones. A cross-sectional quantitative study was conducted on September 2022 in the Degehabur district. The study used the world health organization (WHO) recommended data quality self-assessment (DQS) tools. Immunization tally sheets, registers, and reporting documents were reviewed at 5 health facilities (2 health centers and 3 health posts) of primary health care units for one fiscal year (12 months) to determine the accuracy ratio. The data was collected by trained DQS assessors to explore the quality of monitoring systems at health posts, health centers, and the district health office. A quality index (QI) was assessed, and the accuracy ratio formulated were: the first and third doses of pentavalent vaccines, fully immunized (FI), and the first dose of measles-containing vaccines (MCV). In this study, facility-level results showed both over-reporting and under-reporting were observed at health posts when computing the accuracy ratio of the tally sheet to health post reports found at health centers for almost all antigens verified where pentavalent 1 was 88.3%, 60.4%, and 125.6% for Health posts A, B, and C respectively. For first-dose measles-containing vaccines (MCV), similarly, the accuracy ratio was found to be 126.6%, 42.6%, and 140.9% for Health posts A, B, and C, respectively. The accuracy ratio for fully immunized children also showed 0% for health posts A and B and 100% for health post-C. A relatively better accuracy ratio was seen at health centers where the first pentavalent dose was 97.4% and 103.3% for health centers A and B, while a first dose of measles-containing vaccines (MCV) was 89.2% and 100.9% for health centers A and B, respectively. A quality index (QI) of all facilities also showed results between the maximum of 33.33% and a minimum of 0%. Most of the verified immunization data accuracy ratios were found to be relatively better at the health center level. However, the quality of the monitoring system is poor at all levels, besides poor data accuracy at all health posts. So attention should be given to improving the capacity of staff and quality of monitoring system components, namely recording, reporting, archiving, data analysis, and using information for decision at all levels, especially in pastoralist areas where such kinds of study findings need to be improved beside to improving the data quality at root and health posts level.

Keywords: accuracy ratio, Degehabur District, regular childhood immunization program, quality of monitoring system, Somali Region-Ethiopia

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Authors: Ashish Sinha, Pushpend Agrawal

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Background: Patients with undiagnosed pulmonary TB predominantly act as reservoirs for its transmission through 10-15 secondary infections in the next 1-5 Yrs. Delays in the diagnosis and treatment may worsen the disease with increase the risk of death. Factors responsible for such delays by tracking patient pathways to treatment may help in planning better interventions. The provision of ‘free diagnosis and treatment’ forms the cornerstone of the National Tuberculosis Elimination Programme (NTEP). OOPE is defined as the money spent by the patient during TB care other than public health facilities. Free TB care at all health facilities could reduce out-of-pocket expenses to the minimum possible levels. Material and Methods: This cross-sectional study was conducted among randomly selected 252 TB patients from Nov – Oct 2022 by taking in-depth interviews following informed verbal consent. We documented their journey from initial symptoms until they reached the public health facility, along with their ‘out-of-pocket expenditure’ (OOPE) pertaining to TB care. Results: Total treatment delay was 91±72 days on average (median: 77days, IQR: 45-104 days), while the isolated patient delay was 31±45 days (median: 15 days, IQR: 0 days to 43 days); diagnostic delay; 57±60 days (median: 42days, IQR 14-78 days), treatment delay 19 ± 18 days (median: 15days, IQR: 11-19 days). A patient delay (> 30 days) was significantly associated with ignorance about classic symptoms of pulmonary TB, adoption of self-medication, illiteracy, and middle and lower social class. Diagnostic delay was significantly higher among those who contacted private health facilities, were unaware of signs and symptoms, had >2 consultations, and not getting an appropriate referral for TB care. Most (97%) of the study participants interviewed claimed to have incurred some expenditure.Median total expenses were 6155(IQR: 2625-15175) rupees. More than half 141 (56%) of the study participants had expenses >5000 rupees. Median transport expenses were 525(IQR: 200-1012) rupees; Median consultation expenses were 700(IQR: 200-1600) rupees; Median investigation expenses were 1000(IQR: 0-3025) rupees and the Median medicine expenses were 3350(IQR: 1300-7525).OOPE for consultation, investigation, and medicine was observed to be significantly higher among patients who ignored classical signs& symptoms of TB, repeated visits to private health facilities, and due to self-medication practices. Transport expenses and delays in seeking care at facilities were observed to have an upward trend with OOP Expenses (r =1). Conclusion: Delay in TB care due to low awareness about signs and symptoms of TB and poor seeking care, lack of proper consultation, and appropriate referrals reported by the study subjects indicate the areas which need proper attention by the program managers. Despite a centrally sponsored programme, the financial burden on TB patients is still in the unacceptable range. OOPE could be reduced as low as possible by addressing the responsible factors linked to it.

Keywords: patient pathway, delay, pulmonary tuberculosis, out of pocket expenses

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Authors: Natcha Lueangapapong, Chariya Chuthapisith, Lunliya Thampratankul

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Background: There is a need to find an appropriate tool to help healthcare providers determine sleep problems in children for early diagnosis and management. The Japanese Sleep Questionnaire for Preschoolers (JSQ-P) is a parent-reported sleep questionnaire that has good psychometric properties and can be used in the context of Asian culture, which is likely suitable for Thai children. Objectives: This study aimed to translate and validate the Japanese Sleep Questionnaire for Preschoolers (JSQ-P) into a Thai version and to evaluate factors associated with sleep disorders in preschoolers. Methods: After approval by the original developer, the cross-cultural adaptation process of JSQ-P was performed, including forward translation, reconciliation, backward translation, and final approval of the Thai version of JSQ-P (TH-JSQ-P) by the original creator. This study was conducted between March 2021 and February 2022. The TH-JSQ-P was completed by 2,613 guardians whose children were aged 2-6 years twice in 10-14 days to assess its reliability and validity. Content validity was measured by an index of item-objective congruence (IOC) and a content validity index (CVI). Face validity, content validity, structural validity, construct validity (discriminant validity), criterion validity and predictive validity were assessed. The sensitivity and specificity of the TH-JSQ-P were also measured by using a total JSQ-P score cutoff point 84, recommended by the original JSQ-P and each subscale score among the clinical samples of obstructive sleep apnea syndrome. Results: Internal consistency reliability, evaluated by Cronbach’s α coefficient, showed acceptable reliability in all subscales of JSQ-P. It also had good test-retest reliability, as the intraclass correlation coefficient (ICC) for all items ranged between 0.42-0.84. The content validity was acceptable. For structural validity, our results indicated that the final factor solution for the Th-JSQ-P was comparable to the original JSQ-P. For construct validity, age group was one of the clinical parameters associated with some sleep problems. In detail, parasomnias, insomnia, daytime excessive sleepiness and sleep habits significantly decreased when the children got older; on the other hand, insufficient sleep was significantly increased with age. For criterion validity, all subscales showed a correlation with the Epworth Sleepiness Scale (r = -0.049-0.349). In predictive validity, the Epworth Sleepiness Scale was significantly a strong factor that correlated to sleep problems in all subscales of JSQ-P except in the subscale of sleep habit. The sensitivity and specificity of the total JSQ-P score were 0.72 and 0.66, respectively. Conclusion: The Thai version of JSQ-P has good internal consistency reliability and test-retest reliability. It passed 6 validity tests, and this can be used to evaluate sleep problems in preschool children in Thailand. Furthermore, it has satisfactory general psychometric properties and good reliability and validity. The data collected in examining the sensitivity of the Thai version revealed that the JSQ-P could detect differences in sleep problems among children with obstructive sleep apnea syndrome. This confirmed that the measure is sensitive and can be used to discriminate sleep problems among different children.

Keywords: preschooler, questionnaire, validation, Thai version

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Authors: Paul Moses Ndegwa, Teresia Kabucho, Lucy Wanjiru, Esther Wanjiru, Brian Githaiga, Jecinta Wambui

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Health outcome has improved in the country since 2013 following the adoption of the new constitution in Kenya with devolved governance with administration and health planning functions transferred to county governments. 2018-2022 development agenda prioritized universal healthcare coverage, food security, and nutrition, however, the emergence of Covid-19 and the increase of non-communicable diseases pose a challenge and constrain in an already overwhelmed health system. A study was conducted July-November 2021 to establish key challenges in achieving universal healthcare coverage within the county and best practices for improved non-communicable disease control. 14 health workers ranging from nurses, doctors, public health officers, clinical officers, and pharmaceutical technologists were purposely engaged to provide critical information through questionnaires by a trained duo observing ethical procedures on confidentiality. Data analysis. Communicable diseases are major causes of morbidity and mortality. Non-communicable diseases contribute to approximately 39% of deaths. More than 45% of the population does not have access to safe drinking water. Study noted geographic inequality with respect to distribution and use of health resources including competing non-health priorities. 56% of health workers are nurses, 13% clinical officers, 7% doctors, 9%public health workers, 2% are pharmaceutical technologists. Poor-quality data limits the validity of disease-burdened estimates and research activities. Risk factors include unsafe water, sanitation, hand washing, unsafe sex, and malnutrition. Key challenge in achieving universal healthcare coverage is the rise in the relative contribution of non-communicable diseases. Improve targeted disease control with effective and equitable resource allocation. Develop high infectious disease control mechanisms. Improvement of quality data for decision making. Strengthen electronic data-capture systems. Increase investments in the health workforce to improve health service provision and achievement of universal health coverage. Create a favorable environment to retain health workers. Fill in staffing gaps resulting in shortages of doctors (7%). Develop a multi-sectional approach to health workforce planning and management. Need to invest in mechanisms that generate contextual evidence on current and future health workforce needs. Ensure retention of qualified, skilled, and motivated health workforce. Deliver integrated people-centered health services.

Keywords: multi-sectional approach, equity, people-centered, health workforce retention

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Authors: Maya de Vries Kedem, Abir Jubran, Diana Baron

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Employment in Israel offers Palestinian workers an income double what they can earn in the West Bank. The need to support their families leads many educated Palestinians to forgo finding work in their profession in the Palestinian Authority and instead look for employment in those sectors open to them in Israel, particularly the construction, agriculture, and industry sectors. The International Labor Organization estimated that about 1,200 workers in Israel die every year because of occupational diseases (diseases caused by working conditions). Construction workers in Israel are constantly exposed to dust, noise, chemical materials, and work in awkward postures, which require prolonged bending, repetitive motion, and other risk factors that can lead to illnesses and death. Occupational health is vastly neglected in Israel and construction workers are particularly at risk . As of June 2022, the Israeli quota in the construction sector for Palestinian workers stood at 80,000. Kav LaOved released a new study on the state of occupational health among Palestinian workers employed in construction in Israel. The study Roadmap to Health: Palestinian Workers in Israel's Construction Sector reviews the extent to which the health of Palestinian workers is protected at work in Israel. The report includes analysis of a survey administered to 256 workers as well as interviews with 10 workers and with 5 Israeli occupational health experts. Report highlights: • Among survey respondents, 63.9% stated that safety procedures to protect their health are rarely followed in their workplace (e.g., taking breaks, using protective gear, following restrictions on lifting heavy items, and having inspectors regularly on site to monitor safety). • All 256 Palestinian workers who participated to the survey said that their health has been directly or indirectly harmed by working in Israel and reported suffering from the following problems: orthopedic problems such as joint, hand, leg or knee problems (100%); headaches (75%); back problems (36.3%); eye problems (23.8%); breathing problems (17.6%); chronic pain (14.8%); heart problems (7.8%); and skin problems (3.5%). • Workers who are injured or do not feel well often continue working for fear of losing their payment for that day. About half of the 256 survey respondents reported that they pay brokerage fees to find an employer with a work permit, often paying between 2,000 and 3,000 NIS per month. “I have an obligation—I pay about NIS 120 a day for my permit, [and] I have to pay for it whether I work or not" a worker said. • Most Palestinian construction workers suffer from stress and mental health problems. Workers pointed to several issues that greatly affect their mood and mental state: daily crossings at crowded checkpoints where workers stand for hours; lack of sleep due to leaving home daily at 3:00-3:30 am; commuting two to four hours to work in each direction; and abusive work environments. A worker told KLO that the sight of thousands of workers standing together at the checkpoint causes “high blood pressure and the feeling that you are going to be squeezed.” Another said, “I felt that my bones would break.” In the survey workers reported suffering from insomnia (70.1%), breathing difficulties (35.8%), chest pressure (27.6%), or rapid pulse rate (12.2%).

Keywords: construction sector, palestinian workers, occupational health, Israel, occupation

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Authors: Gift Udoh, Diane S. Rohlman, Benjamin Sindt

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BACKGROUND: There is concern regarding the widespread use of pesticides and impacts on public health. Farmers in Nigeria frequently apply pesticides, including organophosphate pesticides which are known neurotoxicants. They receive little guidance on how much to apply or information about safe handling practices. Pesticide poisoning is one of the major hazards that farmers face in Nigeria. Farmers continue to use highly neurotoxic pesticides for agricultural activities. Because farmers receive little or no information on safe handling and how much to apply, they continue to develop severe and mild illnesses caused by high exposures to pesticides. The project aimed to reduce pesticide exposure among rural farmers in Nigeria by identifying hazards associated with pesticide use and developing and pilot testing training to reduce exposures to pesticides utilizing the hierarchy of controls system. METHODS: Information on pesticide knowledge, behaviors, barriers to safety, and prevention methods was collected from farmers in Nigeria through workplace observations, questionnaires, and interviews. Pre and post-surveys were used to measure farmer’s knowledge before and after the delivery of pesticide safety training. Training topics included the benefits and risks of using pesticides, routes of exposure and health effects, pesticide label activity, use and selection of PPE, ways to prevent exposure and information on local resources. The training was evaluated among farmers and changes in knowledge, attitudes and behaviors were collected prior to and following the training. RESULTS: The training was administered to 60 farmers, a mean age of 35, with a range of farming experience (<1 year to > 50 years). There was an overall increase in knowledge after the training. In addition, farmers perceived a greater immediate risk from exposure to pesticides and their perception of their personal risk increased. For example, farmers believed that pesticide risk is greater to children than to adults, recognized that just because a pesticide is put on the market doesn’t mean it is safe, and they were more confident that they could get advice about handling pesticides. Also, there was greater awareness about behaviors that can increase their exposure (mixing pesticides with bare hands, eating food in the field, not washing hands before eating after applying pesticides, walking in fields recently sprayed, splashing pesticides on their clothes, pesticide storage). CONCLUSION: These results build on existing evidence from a 2022 article highlighting the need for pesticide safety training in Nigeria which suggested that pesticide safety educational programs should focus on community-based, grassroots-style, and involve a family-oriented approach. Educating farmers on agricultural safety while letting them share their experiences with their peers is an effective way of creating awareness on the dangers associated with handling pesticides. Also, for rural communities, especially in Nigeria, pesticide safety pieces of training may not be able to reach some locations, so intentional scouting of rural farming communities and delivering pesticide safety training will improve knowledge of pesticide hazards. There is a need for pesticide information centers to be situated in rural farming communities or agro supply stores, which gives rural farmers information.

Keywords: pesticide exposure, pesticide safety, nigeria, rural farming, pesticide education

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Authors: Alexandre Beaupré-Lavallée, Pier-André Bouchard St-Amant, Nathalie Beaulac

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The question of internal governance of universities is a political and scientific debate in the province of Quebec (Canada). Governments have called or set up inquiries on the subject on three separate occasions since the complete overhaul of the educational system in the 1960s: the Parent Commission (1967), the Angers Commission (1979) and the Summit on Higher Education (2013). All three produced reports that highlight the constant tug-of-war for authority and legitimacy within universities. Past and current research that cover Quebec universities have studied several aspects regarding internal governance: the structure as a whole or only some parts of it, the importance of certain key aspects such as collegiality or strategic planning, or of stakeholders, such as students or administrators. External governance has also been studied, though, as with internal governance, research so far as only covered well delineated topics like financing policies or overall impacts from wider societal changes such as New Public Management. The latter, NPM, is often brought up as a factor that influenced overall State policies like “steering-at-a-distance” or internal shifts towards “managerialism”. Yet, to the authors’ knowledge, there is not study that specifically maps how the Quebec State formally influences internal governance. In addition, most studies about the Quebec university system are not comparative in nature. This paper presents a portion of the results produced by a 2022- 2023 study that aims at filling these last two gaps in knowledge. Building on existing governmental, institutional, and scientific papers, we documented the legal and regulatory framework of the Quebec university system and of twenty-one other university systems in North America and Europe (2 in Canada, 2 in the USA, 16 in Europe, with the addition of the European Union as a distinct case). This allowed us to map the presence (or absence) of mandatory structures of governance enforced by States, as well as their composition. Then, using Clark’s “triangle of coordination”, we analyzed each system to assess the relative influences of the market, the State and the collegium upon the governance model put in place. Finally, we compared all 21 non-Quebec systems to characterize the province’s policies in an internal perspective. Preliminary findings are twofold. First, when all systems are placed on a continuum ranging from “no State interference in internal governance” to “State-run universities”, Quebec comes in the middle of the pack, albeit with a slight lean towards institutional freedom. When it comes to overall governance (like Boards and Senates), the dual nature of the Quebec system, with its public university and its coopted yet historically private (or ecclesiastic) institutions, in fact mimics the duality of all university systems. Second, however, is the sheer abundance of legal and regulatory mandates from the State that, while not expressly addressing internal governance, seems to require de facto modification of internal governance structure and dynamics to ensure institutional conformity with said mandates. This study is only a fraction of the research that is needed to better understand State-universities interactions regarding governance. We hope it will set the stage for future studies.

Keywords: internal governance, legislation, Quebec, universities

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Authors: Andrzej Wałęga, Marta Cebulska, Agnieszka Ziernicka-Wojtaszek, Wojciech Młocek, Agnieszka Wałęga, Tommaso Caloiero

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Drought is one of the natural phenomena influencing many aspects of human activities like food production, agriculture, industry, and the ecological conditions of the environment. In the area of the Polish Carpathians, there are periods with a deficit of rainwater and an increasing frequency in dry months, especially in the cold half of the year. The aim of this work is a spatial and temporal analysis of drought, expressed as SPI in a heterogenous area of the Polish Carpathian and of the highland Region in the Central part of Europe based on long-term precipitation data. Also, to our best knowledge, for the first time in this work, drought characteristics analyzed via the SPI were discussed based on the atmospheric circulation calendar. The study region is the Upper Vistula Basin, located in the southern and south-eastern part of Poland. In this work, monthly precipitation from 56 rainfall stations was analysed from 1961 to 2022. The 3-, 6-, 9-, and 12-month Standardized Precipitation Index (SPI) were used as indicators of meteorological drought. For the 3-month SPI, the main climatic mechanisms determining extreme droughts were defined based on the calendar of synoptic circulations. The Mann-Kendall test was used to detect the trend of extreme droughts. Statistically significant trends of SPI were observed on 52.7% of all analyzed stations, and in most cases, a positive trend was observed. Statistically significant trends were more frequently observed in stations located in the western part of the analyzed region. Long-term droughts, represented by the 12-month SPI, occurred in all stations but not in all years. Short-term droughts (3-month SPI) were most frequent in the winter season, 6 and 9-month SPI in winter and spring, and 12-month SPI in winter and autumn, respectively. The spatial distribution of drought was highly diverse. The most intensive drought occurred in 1984, with the 6-month SPI covering 98% of the analyzed region and the 9 and 12-month SPI covering 90% of the entire region. Droughts exhibit a seasonal pattern, with a dominant 10-year periodicity for all analyzed variants of SPI. Additionally, Fourier analysis revealed a 2-year periodicity for the 3-, 6-, and 9-month SPI and a 31-year periodicity for the 12-month SPI. The results provide insights into the typical climatic conditions in Poland, with strong seasonality in precipitation. The study highlighted that short-term extreme droughts, represented by the 3-month SPI, are often caused by anticyclonic situations with high-pressure wedges Ka and Wa, and anticyclonic West as observed in 52.3% of cases. These findings are crucial for understanding the spatial and temporal variability of short and long-term extreme droughts in Central Europe, particularly for the agriculture sector dominant in the northern part of the analyzed region, where drought frequency is highest.

Keywords: atmospheric circulation, drought, precipitation, SPI, the Upper Vistula Basin

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Authors: Sandra Arango-Caro, Kristine Callis-Duehl

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The Education Research and Outreach Lab at the Donald Danforth Plant Science Center established the Plant and Agriculture Augmented and Virtual Reality Learning Laboratory (PAVRLL) to promote science education through professional development, school programs, internships, and outreach events. Professional development is offered to high school and college science and agriculture educators on the use and applications of zSpace and Oculus platforms. Educators learn to use, edit, or create lesson plans in the zSpace platform that are aligned with the Next Generation Science Standards. They also learn to use virtual reality experiences created by the PAVRLL available in Oculus (e.g. The Soybean Saga). Using a cost-free loan rotation system, educators can bring the AVR units to the classroom and offer AVR activities to their students. Each activity has user guides and activity protocols for both teachers and students. The PAVRLL also offers activities for 3D plant modeling. High school students work in teams of art-, science-, and technology-oriented students to design and create 3D models of plant species that are under research at the Danforth Center and present their projects at scientific events. Those 3D models are open access through the zSpace platform and are used by PAVRLL for professional development and the creation of VR activities. Both teachers and students acquire knowledge of plant and agriculture content and real-world problems, gain skills in AVR technology, 3D modeling, and science communication, and become more aware and interested in plant science. Students that participate in the PAVRLL activities complete pre- and post-surveys and reflection questions that evaluate interests in STEM and STEM careers, students’ perceptions of three design features of biology lab courses (collaboration, discovery/relevance, and iteration/productive failure), plant awareness, and engagement and learning in AVR environments. The PAVRLL was established in the fall of 2019, and since then, it has trained 15 educators, three of which will implement the AVR programs in the fall of 2021. Seven students have worked in the 3D plant modeling activity through a virtual internship. Due to the COVID-19 pandemic, the number of teachers trained, and classroom implementations have been very limited. It is expected that in the fall of 2021, students will come back to the schools in person, and by the spring of 2022, the PAVRLL activities will be fully implemented. This will allow the collection of enough data on student assessments that will provide insights on benefits and best practices for the use of AVR technologies in the classrooms. The PAVRLL uses cutting-edge educational technologies to promote science education and assess their benefits and will continue its expansion. Currently, the PAVRLL is applying for grants to create its own virtual labs where students can experience authentic research experiences using real Danforth research data based on programs the Education Lab already used in classrooms.

Keywords: assessment, augmented reality, education, plant science, virtual reality

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Authors: Madina Tynybayeva, Sanya Zhumazhanova, Saltanat Kozhakhmetova, Merey Mussabayeva

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One of the leading indicators of the education quality is the level of students’ educational achievements. The processes of modernization of Kazakhstani education system have predetermined the need to improve the national system by assessing the quality of education. The results of assessment greatly contribute to addressing questions about the current state of the educational system in the country. The monitoring of students’ educational achievements (MEAS) is the systematic measurement of the quality of education for compliance with the state obligatory standard of Kazakhstan. This systematic measurement is independent of educational organizations and approved by the order of the Minister of Education and Scienceof Kazakhstan. The MEAS was conducted in the regions of Kazakhstanfor the first time in 2022 by the National Testing Centre. The measurement does not have legal consequences either for students or for educational organizations. Students’ achievements were measured in three subject areas: reading, mathematics and science literacy. MEAS was held for the first time in April this year, 105 thousand students from 1436 schools of Kazakhstan took part in the testing. The monitoring was accompanied by a survey of students, teachers, and school leaders. The goal is to identify which contextual factors affect learning outcomes. The testing was carried out in a computer format. The test tasks of MEAS are ranked according to the three levels of difficulty: basic, medium, and high. Fourth graders are asked to complete 30 closed-type tasks. The average score of the results is 21 points out of 30, which means 70% of tasks were successfully completed. The total number of test tasks for 9th grade students – 75 questions. The results of ninth graders are comparatively lower, the success rate of completing tasks is 63%. MEAS participants did not reveal a statistically significant gap in results in terms of the language of instruction, territorial status, and type of school. The trend of reducing the gap in these indicators is also noted in the framework of recent international studies conducted across the country, in particular PISA for schools in Kazakhstan. However, there is a regional gap in MOES performance. The difference in the values of the indicators of the highest and lowest scores of the regions was 11% of the success of completing tasks in the 4th grade, 14% in the 9thgrade. The results of the 4th grade students in reading, mathematics, and science literacy are: 71.5%, 70%, and 66.9%, respectively. The results of ninth-graders in reading, mathematics, and science literacy are 69.6%, 54%, and 60.8%, respectively. From the surveys, it was revealed that the educational achievements of students are considerably influenced by such factors as the subject competences of teachers, as well as the school climate and motivation of students. Thus, the results of MEAS indicate the need for an integrated approach to improving the quality of education. In particular, the combination of improving the content of curricula and textbooks, internal and external assessment of the educational achievements of students, educational programs of pedagogical specialties, and advanced training courses is required.

Keywords: assessment, secondary school, monitoring, functional literacy, kazakhstan

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Authors: Michael Rahme

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Over the past decade, there is an overwhelming consensus spanning across academia, government commissions, and civil societies that concede that individuals with disabilities (IWDs), particularly those with intellectual differences, are a demographic most ‘vulnerable’ to experiences of sexual violence. From this global accord, numerous policies have sprouted in the protection of this ‘pregnable’ sector of society, primarily framed around liberal obligations of stewardship over the ‘defenceless.’ As such, these initiatives mainly target post-incident or victim-based factors of sexual violence, which is apparent in proposals for more inclusive sexual education and accessible contact lines for IWDs. Yet despite the necessity of these initiatives, sexual incidents among this demographic persist and, in nations such as Australia, continue to rise. Culture of Violence theory reveals that such discrepancies in theory and practice stem from societal structures that frame individuals as ‘vulnerable’, ‘impregnable’, or ‘defenceless’ because of their disability, thus propagating their own likelihood of abuse. These structures, as embodied by the Australian experience, allow these sexual violences to endure through cultural ideologies that place the IWDs ‘failures’ at fault while sidelining the institutions that permit this abuse. Such is representative of the initiatives of preventative organizations like People with Disabilities Australia, which have singularly strengthened victim protection networks, despite abuse continuing to rise dramatically among individuals with intellectual disabilities alone. Yet regardless of this rise, screenings of families and workers remain inadequate and practically untouched, a reflection of a tremendous societal warp in understanding surrounding the lived experiences of IWDs. This theory is also representative of broader literature, where the study of the perpetrators of disability rights, particularly sexual rights, is almost unapparent in a field that is already seldom studied. Therefore, placing power on the abuser via stripping that of the victims. As such, the Culture of Violence theory (CVT) sheds light on the institutions that allow these perpetrators to prosper. This paper, taking a CVT approach, aims to dissipate this discrepancy in the Australian experience by way of a qualitative analysis of all available court proceedings and tribunals between 2020-2022. Through an analysis of the perpetrator, their relation to the IWD, and the motives for their actions granted by court and tribunal transcripts and the psychological, and behavioural reports, among other material, that have been presented and consulted during these proceedings. All of which would be made available under the 1982 Freedom of Information Act. The findings from this study, through the incorporation of CVT, determine the institutions in which these abusers function and the ideologies which motivate such behaviour; while being conscious of the issue of re-traumatization and language barriers of the abusees. Henceforth, this study aims to be a potential policy guide on strengthening support institutions that provide IWDs with their basic rights. In turn, undermining sexual violence among individuals with intellectual disabilities at its roots.

Keywords: criminal profiling, intellectual disabilities, prevention, sexual violence

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Authors: Nuno Biga

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Artificial Intelligence (AI) allows machines to interpret information and learn from context analysis, giving them the ability to make predictions adjusted to each specific situation. In addition to learning by performing deterministic and probabilistic calculations, the 'artificial brain' also learns through information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) that provides users with useful suggestions, namely to pursue the following operations: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time the bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed in a pilot project. Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of this information is materialised in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" that players can use during the Game. Each participant in the Virtual Assisted-BIGAMES permanently asks himself about the decisions he should make during the game in order to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, and as the participants gain a better understanding of the game, they will more easily dispense with the VA's recommendations and rely more on their own experience, capability, and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator (Serious Game Controller) is responsible for supporting the players with further analysis and the recommended action may be (or not) aligned with the previous recommendations of the VA. All the information should be jointly analysed and assessed by each player, who are expected to add “Emotional Intelligence”, a component absent from the machine learning process.

Keywords: artificial intelligence (AI), gamification, key performance indicators (KPI), machine learning, management simulators, serious games, virtual assistant

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Authors: Min Wang, Hui Tian

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Health promotion of high school students is essential for the construction of ‘Healthy China’, and increasing high school students’ physical activity is a must for their health promotion. School plays a crucial role in increasing high school students’ physical activity. Therefore, to have a comprehensive command of the school physical activity promotion strategies is of great significance for the health promotion of high school students in China and will shed some light on physical activity promotion worldwide. Literature review and interview survey are the main methods adopted for this research. It has been found that reforms of P.E. classes, improving the overall quality of P.E. teachers, and construction of school fields and facilities are among the major strategies to promote students’ physical activities. Even though it has been stipulated that primary and middle school students should take 3-4 times of P.E. classes per week, the execution is greatly influenced by the exam-oriented educational system. Randomly canceling P.E. classes or taking up the time to study other subjects is common, so it is difficult to guarantee the quantity of P.E. classes. According to national surveys, only 20%-40% of schools have 3-4 times of P.E. classes per week. In order to reduce the hindering effects of the exam-oriented educational system, a physical education test is included in the senior middle school entrance exam. The exam items include 1000m run for boys, 800m run for girls, and the basic skills for basketball/football/volleyball. The scores of the physical education test will greatly influence the admission of senior middle schools. China is now developing the ‘campus football’ policy and has established 20,000 football featured schools by 2017. Especially in these schools, football has become an important part of the students’ P.E. classes and a major means to promote students’ physical activity. As the Winter Olympics will be held in Beijing in 2022, China has promoted the ‘winter sports for all’ movement. The aim is to encourage 300 million people to winter sports, and the high school students are among the most potential participants. The primary and middle schools in Beijing have introduced winter sports to their P.E. curriculum, providing opportunities for the students to experience ice hockey and curling. Some Winter Olympics champions also go to the schools to popularize winter sports among the students. This greatly adds variety to the students’ physical activity regimen at school. In November 2017, seven ministries, including the General Administration of Sport of China and Ministry of Education of the People’s Republic of China, release Youth Sport Promotion Strategy. The strategy stipulates to strengthen the construction of youth sport facilities and implement the cultivation plan for P.E. teachers. It also emphasizes that school sport facilities should be open to students during holidays and vacations for free or at an affordable price. Overall speaking, the Chinese government stresses the importance of youth physical activity promotion and has issued a series of related policies and strategies, but the implementation still needs improvement.

Keywords: China, physical activity, promotion, school

Procedia PDF Downloads 88

Authors: Amirah Azzeri, Fatiha H. Shabaruddin, Scott A. McDonald, Rosmawati Mohamed, Maznah Dahlui

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Objective: A scaled-up treatment cascade with direct-acting antiviral (DAA) therapy is necessary to achieve global WHO targets for hepatitis C virus (HCV) elimination in Malaysia. Recently, limited access to Sofosbuvir/Daclatasvir (SOF/DAC) is available through compulsory licensing, with future access to Sofosbuvir/Velpatasvir (SOF/VEL) expected through voluntary licensing due to recent agreements. SOF/VEL has superior clinical outcomes, particularly for cirrhotic stages, but has higher drug acquisition costs compared to SOF/DAC. It has been proposed that a stratified treatment cascade might be the most cost-efficient approach for Malaysia whereby all HCV patients are treated with SOF/DAC except for patients with cirrhosis who are treated with SOF/VEL. This study aimed to conduct a five-year budget impact analysis from the provider perspective of the proposed stratified treatment cascade for HCV treatment in Malaysia. Method: A disease progression model that was developed based on model-predicted HCV epidemiology data in Malaysia was used for the analysis, where all HCV patients in scenario A were treated with SOF/DAC for all disease stages while in scenario B, SOF/DAC was used only for non-cirrhotic patients and SOF/VEL was used for the cirrhotic patients. The model projections estimated the annual numbers of patients in care and the numbers of patients to be initiated on DAA treatment nationally. Healthcare costs associated with DAA therapy and disease stage monitoring was included to estimate the downstream cost implications. For scenario B, the estimated treatment uptake of SOF/VEL for cirrhotic patients were 25%, 50%, 75%, 100% and 100% for 2018, 2019, 2020, 2021 and 2022 respectively. Healthcare costs were estimated based on standard clinical pathways for DAA treatment described in recent guidelines. All costs were reported in US dollars (conversion rate US$1=RM4.09, the price year 2018). Scenario analysis was conducted for 5% and 10% reduction of SOF/VEL acquisition cost anticipated from the competitive market pricing of generic DAA in Malaysia. Results: The stratified treatment cascade with SOF/VEL in Scenario B was found to be cost-saving compared to Scenario A. A substantial portion of the cost reduction was due to the costs associated with DAA therapy which resulted in USD 40 thousand (year 1) to USD 443 thousand (year 5) savings annually, with cumulative savings of USD 1.1 million after 5 years. Cost reductions for disease stage monitoring were seen in year three onwards which resulted in cumulative savings of USD 1.1 thousand. Scenario analysis estimated cumulative savings of USD 1.24 to USD 1.35 million when the acquisition cost of SOF/VEL was reduced. Conclusion: A stratified treatment cascade with SOF/VEL was expected to be cost-saving and can results in a budget impact reduction in overall healthcare expenditure in Malaysia compared to treatment with SOF/DAC. The better clinical efficacy with SOF/VEL is expected to halt patients’ HCV disease progression and may reduce downstream costs of treating advanced disease stages. The findings of this analysis may be useful to inform healthcare policies for HCV treatment in Malaysia.

Keywords: Malaysia, direct acting antiviral, compulsory licensing, voluntary licensing

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Authors: Fangfang Wang, Tianjing Wang, Leyi Fu, Feng Yun, Ningning Xie, Jue Zhou, Fan Qu

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Background: Ferroptosis, a recently discovered form of programmed cell death characterized by iron-dependent lipid peroxidation, may be linked to polycystic ovary syndrome (PCOS). Diseases marked by iron overload have been correlated with ferroptosis. Coincidently, investigations have revealed anomalies in iron metabolism among women with PCOS; however, there were inconsistencies in the evidence. Objective and Rationale: This review aimed to comprehensively explore the potential relationship between ferroptosis and PCOS by investigating the differences in iron metabolism among women with PCOS in comparison to a control group. Additionally, a narrative synthesis was provided on the past research status regarding the association between PCOS and ferroptosis. Methods: A systematic search of the literature was performed using PubMed, Embase, Web of Science from inception up to December 2022. Search terms relating to assisted PCOS, ferroptosis, and iron metabolism were used. PRISMA guidance was followed. RevMan 5.4 was utilized for conducting the meta-analysis, wherein the investigated outcomes included iron status (ferritin, iron, transferrin saturation) and a systemic iron-regulatory hormone (hepcidin). A narrative synthesis was performed to explore the correlation between PCOS and ferroptosis. Results: In the meta-analysis comprising a total of 16 studies, significant differences in serum ferritin levels between the PCOS group and the control group were observed (15 studies, standardized mean difference (SMD): 0.41, 95% CI: 0.22 to 0.59, P<0.01). This indicates elevated serum ferritin levels in PCOS patients compared to women without PCOS. The transferrin saturation in PCOS patients was significantly higher than that in the control group (3 studies, mean difference (MD): 4.39, 95% CI: 1.67 to 7.11, P<0.01). Regarding serum iron (6 studies, SMD: 0.05, 95% CI: -0.24 to 0.33, P=0.75) and serum hepcidin (4 studies, SMD: -0.44, 95% CI: -1.41 to 0.52, P=0.37), no statistically significant differences were observed between the PCOS group and the control group. Other studies have found that ferroptosis is involved in the occurrence and development of PCOS, offering valuable insights for guiding potential treatment measures and prognosis evaluation of PCOS. In addition, ferroptosis is involved in the miscarriage of PCOS-like rats; thus, controlling ferroptosis might improve pregnancy outcomes in PCOS. Conclusions: The observation of a significant elevation in serum ferritin and transferrin saturation levels in women with PCOS may suggest an underlying disturbance in iron metabolism, potentially inducing the activation of ferroptosis. Further research is imperative to elucidate the underlying pathophysiology, providing insights for potential preventive measures and therapeutic strategies. Limitation: There are some limitations as follows: First, due to limited extractable information, we excluded purely abstract publications and non-English publications. Second, the majority of original articles were case-control studies, making it difficult to determine the causal relationship between iron metabolism abnormalities and the onset of PCOS. Third, there is substantial heterogeneity in the definition of PCOS.

Keywords: polycystic ovary syndrome, ferroptosis, iron metabolism, systematic review and meta-analysis

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Authors: Dan W. Rhodes, Juliane Hey, Magali Karagueuzian, Florianne Martinez, Yael Sandowski, Vanessa Roulet, Mahmoud Badawi, Mohammed-Amine Chakir, Valérie Simon, Jérémie Gautier, Françoise Le Boulaire, Catherine Coignard, Claire Vincent, Sandrine Greaume, Isabelle Voisin

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Background: Beckman Coulter, Inc. (BEC) has recently developed a fully automated second-generation anti-HCV test on a new immunoassay platform. The objective of this multicenter study conducted in Europe was to evaluate the performance of the ACCESS anti-HCV assay on the recently CE-marked DxI 9000 ACCESS Immunoassay Analyzer as an aid in the diagnosis of HCV (Hepatitis C Virus) infection and as a screening test for blood and plasma donors. Methods: The clinical specificity of the ACCESS anti-HCV assay was determined using HCV antibody-negative samples from blood donors and hospitalized patients. Sample antibody status was determined by a CE-marked anti-HCV assay (Abbott ARCHITECTTM anti-HCV assay or Abbott PRISM HCV assay) with an additional confirmation method (Immunoblot testing with INNO-LIATM HCV Score - Fujirebio), if necessary, according to pre-determined testing algorithms. The clinical sensitivity was determined using known HCV antibody-positive samples, identified positive by Immunoblot testing with INNO-LIATM HCV Score - Fujirebio. HCV RNA PCR or genotyping was available on all Immunoblot positive samples for further characterization. The false initial reactive rate was determined on fresh samples from blood donors and hospitalized patients. Thirty (30) commercially available seroconversion panels were tested to assess the sensitivity for early detection of HCV infection. The study was conducted from November 2019 to March 2022. Three (3) external sites and one (1) internal site participated. Results: Clinical specificity (95% CI) was 99.7% (99.6 – 99.8%) on 5852 blood donors and 99.0% (98.4 – 99.4%) on 1527 hospitalized patient samples. There were 15 discrepant samples (positive on ACCESS anti-HCV assay and negative on both ARCHITECT and Immunoblot) observed with hospitalized patient samples, and of note, additional HCV RNA PCR results showed five (5) samples had positive HCV RNA PCR results despite the absence of HCV antibody detection by ARCHITECT and Immunoblot, suggesting a better sensitivity of the ACCESS anti-HCV assay with these five samples compared to the ARCHITECT and Immunoblot anti-HCV assays. Clinical sensitivity (95% CI) on 510 well-characterized, known HCV antibody-positive samples was 100.0% (99.3 – 100.0%), including 353 samples with known HCV genotypes (1 to 6). The overall false initial reactive rate (95% CI) on 6630 patient samples was 0.02% (0.00 – 0.09%). Results obtained on 30 seroconversion panels demonstrated that the ACCESS anti-HCV assay had equivalent sensitivity performances, with an average bleed difference since the first reactive bleed below one (1), compared to the ARCHITECTTM anti-HCV assay. Conclusion: The newly developed ACCESS anti-HCV assay from BEC for use on the DxI 9000 ACCESS Immunoassay Analyzer demonstrated high clinical sensitivity and specificity, equivalent to currently marketed anti-HCV assays, as well as a low false initial reactive rate.

Keywords: DxI 9000 ACCESS Immunoassay Analyzer, HCV, HCV antibody, Hepatitis C virus, immunoassay

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Authors: Marc Toutain, Pascale Leconte, Antoine Gauthier

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Introduction: Eating Disorders (ED), such as anorexia, bulimia, and binge eating, are psychiatric illnesses that mostly affect young people. The main symptoms concern eating (restriction, excessive food intake) and weight control behaviors (laxatives, vomiting). Psychological comorbidities (depression, executive function disorders, etc.) and problematic behaviors toward physical activity (PA) are commonly associated with ED. Acquaintances on ED risk factors are still lacking, and more community sample studies are needed to improve prevention and early detection. To our knowledge, studies are needed to specifically investigate the link between ED risk level, PA, and psychological risk factors in a community sample of adolescents. The aim of this study is to assess the relation between ED risk level, exercise (type, frequency, and motivations for engaging in exercise), and psychological factors based on the Jacobi risk factors model. We suppose that a high risk of ED will be associated with the practice of high caloric cost PA, motivations oriented to weight and shape control, and psychological disturbances. Method: An online survey destined for students has been sent to several middle schools and colleges in northwest France. This survey combined several questionnaires, the Eating Attitude Test-26 assessing ED risk; the Exercise Motivation Inventory–2 assessing motivations toward PA; the Hospital Anxiety and Depression Scale assessing anxiety and depression, the Contour Drawing Rating Scale; and the Body Esteem Scale assessing body dissatisfaction, Rosenberg Self-esteem Scale assessing self-esteem, the Exercise Dependence Scale-Revised assessing PA dependence, the Multidimensional Assessment of Interoceptive Awareness assessing interoceptive awareness and the Frost Multidimensional Perfectionism Scale assessing perfectionism. Machine learning analysis will be performed in order to constitute groups with a tree-based model clustering method, extract risk profile(s) with a bootstrap method comparison, and predict ED risk with a prediction method based on a decision tree-based model. Expected results: 1044 complete records have already been collected, and the survey will be closed at the end of May 2022. Records will be analyzed with a clustering method and a bootstrap method in order to reveal risk profile(s). Furthermore, a predictive tree decision method will be done to extract an accurate predictive model of ED risk. This analysis will confirm typical main risk factors and will give more data on presumed strong risk factors such as exercise motivations and interoceptive deficit. Furthermore, it will enlighten particular risk profiles with a strong level of proof and greatly contribute to improving the early detection of ED and contribute to a better understanding of ED risk factors.

Keywords: eating disorders, risk factors, physical activity, machine learning

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Dalila Chaid, Yacine Houmel, Mohamed Lamine Belloulou

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Peripheral neuropathy is a rare but worrying complication of peripheral local anaesthesia. It is caused either by needle contact with the nerve root or by the direct toxicity of local anaesthetics, leading to nerve damage, injury or irritation. Although uncommon, it remains a major concern for anaesthetists. The aim of the study was to assess the prevalence of nerve block-associated neuropathy in knee surgery and to identify the contributing factors in order to minimise the occurrence of this complication. The study also assessed the severity and evolution of lesions, as well as the factors leading to neuropathic pain. Methodology: It is a retrospective observational study on cases of neuropathy related to nerve blocks of the lower limb for knee surgery over a period of seven years (2016-2022). The study included a total of 6,000 patients Analyse the anaesthetic and neuropathic pain-related parameters received from these patients to determine the prevalence and severity of neuropathy. Findings: the prevalence of nerve block-related neuropathy in our study is 5.8‰ for the sciatic nerve and 0.9‰ for the femoral nerve. This was higher compared to the reported rates in the literature, which were between 0.0 to 5‰ for the Sciatic nerve and 0.0 to 3.4‰ for the femoral nerve. These findings highlight the importance of identifying and implementing an ideal anesthesia procedure to reduce the risk of neuropathy associated with nerve blocks. Theoretical Importance: The findings of this study contribute to the existing literature on peripheral neuropathy following locoregional anesthesia. By identifying the prevalence and severity of neuropathy related to nerve blocks, as well as the underlying factors, we provide valuable insights for anesthetists to improve patient safety. This study also emphasizes the need for compliance with technical safety rules to minimize the occurrence of neuropathy. Data Collection and Analysis Procedures: For this study, 25 clinics with retrospective data were collected of neuropathy associated with nerve blocks for knee surgery over a span of seven years. Parameters related to anaesthesia and neuropathic pain were analysed to determine prevalence,severity, and progression of neuropathy. Comparison of our results with the existing literature in order to assess their significance. Questions Addressed: This study aims to define the following points: 1. The prevalence of neuropathy associated with nerve blocks for knee surgery. 2. The factors underlying the development of neuropathy after nerve blocks. 3. Reducing the risk of neuropathy by complying with technical safety rules. 4. Assessing the severity and evolution of neuropathic pain in these cases. Conclusion: this study highlights the need for careful consideration and implementation of anesthesia procedures during nerve blocks for knee surgery. The prevalence of neuropathy linked to these blocks was higher compared to the literature, emphasizing the importance of identifying and minimizing contributing factors. Compliance with technical safety rules is crucial to reduce the risk of peripheral neuropathy. This study provides valuable insights to anesthetists and contributes to improving patient safety in the field of locoregional anesthesia.

Keywords: phantom limb, neuropathic pain, lower limb amputee, ultrasound-guided locoreginal anesthesia

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Authors: Niamh Higgins, Dawn Howard

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The Irish agri-food sector is of major importance to Ireland’s manufacturing sector and to the Irish economy through employment and the exporting of animal products worldwide. Infectious diseases and parasites have an impact on farm animal health causing profitability and productivity to be affected. For the sustainability of Irish dairy farming, there must be the highest standard of animal health. There can be a lack of information in accounting for > 1% of complete microbial diversity in an environment. There is the tendency of culture-based methods of microbial identification to overestimate the prevalence of species which grow easily on an agar surface. There is a need for new technologies to address these issues to assist with animal health. Metagenomic approaches provide information on both the whole genome and transcriptome present through DNA sequencing of total DNA from environmental samples producing high determination of functional and taxonomic information. Nanopore Next Generation Technologies have the ability to be powerful sequencing technologies. They provide high throughput, low material requirements and produce ultra-long reads, simplifying the experimental process. The aim of this study is to use a metagenomics approach to analyze dairy cattle faecal samples using the Oxford Nanopore MinION Next Generation Sequencer and to establish an in-house pipeline for metagenomic characterization of complex samples. Faecal samples will be obtained from Irish dairy farms, DNA extracted and the MinION will be used for sequencing, followed by bioinformatics analysis. Of particular interest, will be the parasite Buxtonella sulcata, which there has been little research on and which there is no research on its presence on Irish dairy farms. Preliminary results have shown the ability of the MinION to produce hundreds of reads in a relatively short time frame of eight hours. The faecal samples were obtained from 90 dairy cows on a Galway farm. The results from Oxford Nanopore ‘What’s in my pot’ (WIMP) using the Epi2me workflow, show that from a total of 926 classified reads, 87% were from the Kingdom Bacteria, 10% were from the Kingdom Eukaryota, 3% were from the Kingdom Archaea and < 1% were from the Kingdom Viruses. The most prevalent bacteria were those from the Genus Acholeplasma (71 reads), Bacteroides (35 reads), Clostridium (33 reads), Acinetobacter (20 reads). The most prevalent species present were those from the Genus Acholeplasma and included Acholeplasma laidlawii (39 reads) and Acholeplasma brassicae (26 reads). The preliminary results show the ability of the MinION for the identification of microorganisms to species level coming from a complex sample. With ongoing optimization of the pipe-line, the number of classified reads are likely to increase. Metagenomics has the potential in animal health for diagnostics of microorganisms present on farms. This would support wprevention rather than a cure approach as is outlined in the DAFMs National Farmed Animal Health Strategy 2017-2022.

Keywords: animal health, buxtonella sulcata, infectious disease, irish dairy cattle, metagenomics, minION, next generation sequencing

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Authors: Kenji Tanaka, Kazumi Sugita, Yuto Mizushima

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This paper introduces a noteworthy form of English communication training for the officers and operators of the Osaka-Bay Marine Traffic Information Service (Osaka MARTIS) of the Japan Coast Guard working in the congested area at the Akashi Strait in Hyogo Prefecture, Japan. The authors of this paper, Marine Technical College’s (MTC) English language instructors, have been holding about forty lectures and exercises in basic and normal Maritime English (ME) for several groups of MARTIS personnel at Osaka MARTIS annually since they started the training in 2005. Trainees are expected to be qualified Maritime Third-Class Radio Operators who are responsible for providing safety information to a daily average of seven to eight hundred vessels that pass through the Akashi Strait, one of Japan’s narrowest channels. As of 2022, the instructors are conducting 55 remote lessons at MARTIS. One lesson is 90 minutes long. All 26 trainees are given oral and written assessments. The trainees need to pass the examination to become qualified operators every year, requiring them to train and maintain their linguistic levels even during the pandemic of Corona Virus Disease-19 (COVID-19). The vessel traffic information provided by Osaka MARTIS in Maritime English language is essential to the work involving the use of very high frequency (VHF) communication between MARTIS and vessels in the area. ME is the common language mainly used on board merchant, fishing, and recreational vessels, normally at sea. ME was edited and recommended by the International Maritime Organization in the 1970s, was revised in 2002, and has undergone continual revision. The vessel’s circumstances are much more serious at the strait than those at the open sea, so these vessels need ME to receive guidance from the center when passing through the narrow strait. The imminent and challenging situations at the strait necessitate that textbooks’ contents include the basics of the phrase book for seafarers as well as specific and additional navigational information, pronunciation exercises, notes on keywords and phrases, explanations about collocations, sample sentences, and explanations about the differences between synonyms especially those focusing on terminologies necessary for passing through the strait. Additionally, short Japanese-English translation quizzes about these topics, as well as prescribed readings about the maritime sector, are include in the textbook. All of these exercises have been trained in the remote education system since the outbreak of COVID-19. According to the guidelines of ME edited in 2009, the lowest level necessary for seafarers is B1 (lower individual users) of The Common European Framework of Reference for Languages: Learning, Teaching, Assessment (CEFR). Therefore, this vocational ME language training at Osaka MARTIS aims for its trainees to communicate at levels higher than B1. A noteworthy proof of improvement from this training is that most of the trainees have become qualified marine radio communication officers.

Keywords: akashi strait, B1 of CEFR, maritime english communication training, osaka martis

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Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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Authors: Siphesihle Hlongwane

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Background: Globally, alcohol consumption, smoking, and the use of illicit drugs kill more than 11.8 million people each year. In sub-Saharan Africa, substance abuse is responsible for more than 6.4% of all deaths recorded and about 4.7% of all Disability Adjusted Life Years (DALYs), with numbers still expected to grow if no drastic measures are taken to curb and address drug use. In a setting where substance use is rife, understanding contextual factors that influence an individual’s perceived eligibility to seek rehabilitation is paramount. Using the candidacy framework, we unpack how situational factors influence an individual’s perceived eligibility for healthcare uptake in adolescents and youth with substance use disorder (SUD). Methods: The candidacy framework is concerned with how people consider their eligibility for accessing a health service. The study collected and analyzed primary qualitative data to answer the research question. Data were collected between January and July 2022 on participants aged between 18 and 35 for drug users and 18 to 60 for family members. Participants include 20 previous and current drug users and 20 family members that experience the effects of addiction. A pre-drafted semi-structured interview guide was administered to a conveniently sampled population supplemented with a referral sampling method. Data were thematically analyzed using the NVivo 12pro software to manage the data. Findings: Our findings show that people with substance use disorders are aware of their drug use habits and acknowledge their candidacy for health services. Candidacy for health services is also acknowledged by those around them, such as family members and peers, and as such, information on the navigation of health services for drug users is shared by those who have attended health services, those affected by drug use, and this includes health service research by family members to identify accessible health services. While participants reported willingness to quit drug use if assistance is provided, the permeability of health care services is hindered by both individual determinations to quit drug use from long-time use and the availability of health services for drug users, such as rehabilitation centers. Our findings also show that drug users are conscious and can articulate their ailments; however, the hunt for the next dose of drugs and long waiting cues for health service acquisition overshadows their claim to health services. Participants reported a mixture of treatments prescribed, with some more gruesome than others prescribed, thus serving as both a facilitator and barrier for health service uptake. Despite some unorthodox forms of treatments prescribed in health care, the majority of those who enter treatment complete the process of treatment, although some are met with setbacks and sometimes relapse after treatment has finished. Conclusion: Drug users are able to ascertain their candidacy for health services; however, individual and environmental characteristics relating to drug use hinder the use of health services. Drug use interventions need to entice health service uptake as a way to improve candidacy for health use.

Keywords: substance use disorder, rehabilitation, drug use, relapse, South Africa, candidacy framework

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Authors: Luisa Müting, Wisnu Harto Adiwijoyo

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Agroforestry systems transform the agricultural landscapes in the Sahel region of Africa, providing food and farming products consumed for subsistence or sold for income. In the incrementally dry climate of the Sahel region, the spreading of agroforestry practices is integral for policymaker efforts to counteract land degradation and provide soil restoration in the region. Several measures on agroforestry practices have been implemented in the region by governmental and non-governmental institutions in recent years. However, despite the efforts, past research shows that awareness of how policies and interventions are being consumed and perceived by the public remains low. Therefore, interpreting public policy dilemmas by analyzing the public perception regarding agroforestry concepts and practices is necessary. Public perceptions and discourses can be an essential driver or constraint for the adoption of agroforestry practices in the region. Thus, understanding the public discourse behavior of crucial stakeholders could assist policymakers in developing inclusive and contextual policies that are relevant to the context of agroforestry adoption in Sahel region. To answer how information about agroforestry spreads and is perceived by the public. As internet usage increased drastically over the past decade, reaching a share of 33 percent of the population being connected to the internet, this research is based on online conversation data. Social media data from Facebook are gathered daily between April 2021 and April 2022 in Djibouti, Senegal, Mali, and Nigeria based on their share of active internet users compared to other countries in the Sahel region. A systematic methodology was applied to the extracted social media using discourse network analysis (DNA). This study then clustered the data by the types of agroforestry practices, sentiments, and country. Additionally, this research extracted the text data from online news media during the same period to pinpoint events related to the topic of agroforestry. The preliminary result indicates that tree management, crops, and livestock integration, diversifying species and genetic resources, and focusing on interactions and productivity across the agricultural system; are the most notable keywords in agroforestry-related conversations within the four countries in the Sahel region. Additionally, approximately 84 percent of the discussions were still dominated by big actors, such as NGO or government actors. Furthermore, as a subject of communication within agroforestry discourse, the Great Green Wall initiative generates almost 60 percent positive sentiment within the captured social media data, effectively having a more significant outreach than general agroforestry topics. This study provides an understanding for scholars and policymakers with a springboard for further research or policy design on agroforestry in the four countries of the Sahel region with systematically uncaptured novel data from the internet.

Keywords: sahel, djibouti, senegal, mali, nigeria, social networks analysis, public discourse analysis, sentiment analysis, content analysis, social media, online news, agroforestry, land restoration

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Authors: Vangelis Papadimitropoulos

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This paper is part of the research program “Techno-Social Innovation in the Collaborative Economy”, funded by the Hellenic Foundation for Research and Innovation (H.F.R.I.) for the years 2022-2024. The paper showcases the Open Food Network (OFN) as an open-sourced digital platform supporting short food supply chains in local agricultural production and consumption. The paper outlines the research hypothesis, the theoretical framework, and the methodology of research as well as the findings and conclusions. Research hypothesis: The model of open cooperativism as a vehicle for systemic change in the agricultural sector. Theoretical framework: The research reviews the OFN as an illustrative case study of the three-zoned model of open cooperativism. The OFN is considered a paradigmatic case of the model of open cooperativism inasmuch as it produces commons, it consists of multiple stakeholders including ethical market entities, and it is variously supported by local authorities across the globe, the latter prefiguring the mini role of a partner state. Methodology: Research employs Ernesto Laclau and Chantal Mouffe’s discourse analysis -elements, floating signifiers, nodal points, discourses, logics of equivalence and difference- to analyse the breadth of empirical data gathered through literature review, digital ethnography, a survey, and in-depth interviews with core OFN members. Discourse analysis classifies OFN floating signifiers, nodal points, and discourses into four themes: value proposition, governance, economic policy, and legal policy. Findings: OFN floating signifiers align around the following nodal points and discourses: “digital commons”, “short food supply chains”, “sustainability”, “local”, “the elimination of intermediaries” and “systemic change”. The current research identifies a lack of common ground of what the discourse of “systemic change” signifies on the premises of the OFN’s value proposition. The lack of a common mission may be detrimental to the formation of a common strategy that would be perhaps deemed necessary to bring about systemic change in agriculture. Conclusions: Drawing on Laclau and Mouffe’s discourse theory of hegemony, research introduces a chain of equivalence by aligning discourses such as “agro-ecology”, “commons-based peer production”, “partner state” and “ethical market entities” under the model of open cooperativism, juxtaposed against the current hegemony of neoliberalism, which articulates discourses such as “market fundamentalism”, “privatization”, “green growth” and “the capitalist state” to promote corporatism and entrepreneurship. Research makes the case that for OFN to further agroecology and challenge the current hegemony of industrial agriculture, it is vital that it opens up its supply chains into equivalent sectors of the economy, civil society, and politics to form a chain of equivalence linking together ethical market entities, the commons and a partner state around the model of open cooperativism.

Keywords: sustainability, the digital commons, open cooperativism, innovation

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Authors: Lauren Beth Birney

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BOP-CCERS is a consortium of scientists, K-16 New York City students, faculty, academicians, teachers, stakeholders, STEM Industry professionals, CBO’s, NPO’s, citizen scientists, and local businesses working in partnership to restore New York Harbor’s oyster populations while at the same time providing clean water in New York Harbor. BOP-CCERS gives students an opportunity to learn hands-on about environmental stewardship as well as environmental law and policy by giving students real responsibility. The purpose of this REU will allow for the BOP CCERS Project to further broaden its parameters into the focus of environmental law and policy where further change can be affected. Creating opportunities for undergraduates to work collaboratively with graduate students in law and policy and envision themselves in STEM careers in the field of law continues to be of importance in this project. More importantly, creating opportunities for underrepresented students to pursue careers in STEM Education has been a goal of the project over the last ten years. By raising the level of student interest in community-based citizen science integrated into environmental law and policy, a more diversified workforce will be fostered through the momentum of this dynamic program. The continuing climate crisis facing our planet calls for 21st-century skill development that includes learning and innovation skills derived from critical thinking, which will help REU students address the issues of climate change facing our planet. The demand for a climate-friendly workforce will continue to be met through this community-based citizen science effort. Environmental laws and policies play a crucial role in protecting humans, animals, resources, and habitats. Without these laws, there would be no regulations concerning pollution or contamination of our waterways. Environmental law serves as a mechanism to protect the land, air, water, and soil of our planet. To protect the environment, it is crucial that future policymakers and legal experts both understand and value the importance of environmental protection. The Environmental Law and Policy REU provides students with the opportunity to learn, through hands-on work, the skills, and knowledge needed to help foster a legal workforce centered around environmental protection while participating alongside the BOP CCERS researchers in order to gain research experience. Broadening this area to law and policy will further increase these opportunities and permit students to ultimately affect and influence larger-scale change on a global level while further diversifying the STEM workforce. Students’ findings will be shared at the annual STEM Institute at Pace University in August 2022. Basic research methodologies include qualitative and quantitative analysis performed by the research team. Early findings indicate that providing students with an opportunity to experience, explore and participate in environmental science programs such as these enhances their interests in pursuing STEM careers in Law and Policy, with the focus being on providing opportunities for underserved, marginalized, and underrepresented populations.

Keywords: environmental restoration science, citizen science, environmental law and policy, STEM education

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

Procedia PDF Downloads 59