Search results for: non-linear regression

Authors: Zelalem Markos Borko

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Work-related stress is a reaction that occurs when the work weight progress toward becoming excessive. Therefore, unless properly managed, stress leads to high employee turnover, decreased performance, illness and absenteeism. Yet, little has been addressed regarding work-related stress and its predictors in the study area. Therefore, the objective of this study was to assess stress prevalence and its predictors in the study area. To that effect, a cross-sectional study design was conducted on 281 employees from the Ethiopian Federal Bureau of Investigation by using stratified random sampling techniques. Survey questionnaire scales were employed to collect data. Data were analyzed by percentage, Pearson correlation coefficients, simple linear regression, multiple linear regressions, independent t-test and one-way ANOVA statistical techniques. In the present study13.9% of participants faced high stress, whereas 13.5% of participants faced low stress and the rest 72.6% of officers experienced moderate stress. There is no significant group difference among workers due to age, gender, marital status, educational level, years of service and police rank. This study concludes that factors such as role conflict, performance over-utilization, role ambiguity, and qualitative and quantitative role overload together predict 39.6% of work-related stress. This indicates that 60.4% of the variation in stress is explained by other factors, so other additional research should be done to identify additional factors predicting stress. To prevent occupational stress among police, the Ethiopian Federal Bureau of Investigation should develop strategies based on factors that will help to develop stress reduction management.

Keywords: work-related stress, Ethiopian federal bureau of investigation, predictors, Addis Ababa

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Authors: Alicia Carranza, Hildemar Dos Santos, W. Lawrence Beeson, R. Patti Herring, Kimberly R. Freeman, Adam Arechiga

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Early exposure to trauma can impact health-related behaviors later in life, which poses a considerable challenge for young adults transitioning into independence when they are lacking the necessary skills and support to live a healthy life. The study will be a non-experimental, mixed methods pre- and post-test (where subjects will serve as their own controls) to determine the impact of an eight-week trauma-informed healthy lifestyle program on self-efficacy for adopting health-promoting behaviors and health outcomes among young adults. Forty-two adults, ages 18-24 who are living in Orange County, CA will be recruited to participate in the eight-week trauma-informed healthy living program. Baseline and post-intervention assessments will be conducted to assess changes in self-efficacy for nutrition and physical exercise, sleep quality and quantity, body mass index (kg/m2), and coping skills used by comparing pre- to post-intervention. Some of the planned activities include cooking demonstrations, mindful eating activities and media literacy using Instagram. Frequencies analyses, paired t-test, and multiple regression will be used to determine if there was a change in coping skills. The results of this study can serve to assess the potential for mitigating the effects of Adverse Childhood Experiences (ACEs), or other toxic stress, experienced during adolescence across the lifespan. Young adults who learn how to cope with stress in a healthy way and engage in a healthy lifestyle can be better prepared to role model that behavior to their children.

Keywords: nutrition, healthy lifestyle, trauma-informed, stress management

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Authors: Linnan Zhang

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Linguists, as well as psychologists, have shown great interests in implicit causality in reference processing. However, most frequently-used approaches to this issue are psychological experiments (such as eye tracking or self-paced reading, etc.). This research is a corpus-based one and is assisted with statistical tool – software R. The main focus of the present study is about the competition between verb-based implicit causality and theme structure’s influence on anaphora bias in Mandarin Chinese sentences. In Accessibility Theory, it is believed that salience, which is also known as accessibility, and relevance are two important factors in reference processing. Theme structure, which is a special syntactic structure in Chinese, determines the salience of an antecedent on the syntactic level while verb-based implicit causality is a key factor to the relevance between antecedent and anaphora. Therefore, it is a study about anaphora, combining psychology with linguistics. With analysis of the sentences from corpus as well as the statistical analysis of Multinomial Logistic Regression, major findings of the present study are as follows: 1. When the sentence is stated in a ‘cause-effect’ structure, the theme structure will always be the antecedent no matter forward biased verbs or backward biased verbs co-occur; in non-theme structure, the anaphora bias will tend to be the opposite of the verb bias; 2. When the sentence is stated in a ‘effect-cause’ structure, theme structure will not always be the antecedent and the influence of verb-based implicit causality will outweigh that of theme structure; moreover, the anaphora bias will be the same with the bias of verbs. All the results indicate that implicit causality functions conditionally and the noun in theme structure will not be the high-salience antecedent under any circumstances.

Keywords: accessibility theory, anaphora, theme strcture, verb-based implicit causality

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Authors: Olabisi Badmos, Daniel Callo-Concha, Babatunde Agbola, Andreas Rienow, Klaus Greve, Carsten Jurgens

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Slums are important components of city development planning, especially in Africa where slum growth is on par with urban growth. Purposefully, our knowledge on the residential choice of slum dwellers, which contributes to population growth in slums, is limited. This is the case in Lagos, a megacity reportedly dominated by slum dwellers. Thus, this study aims to disclose the factors influencing the residential choices and causes of people to remain in Lagos slums. Data was collected through questionnaire administration and focus group discussions. Descriptive statistics were used to analyze and describe the factors influencing residential location choice; logistic regression was utilized to determine the extent to which the neighborhood and household attributes, influence slum dwellers decisions to remain in the slums. Results showed that movement to Lagos was the main cause of population growth in slums; most of the migrants were from closer geopolitical zones (in Nigeria). Further, the movement patterns observed support two theories of human mobility in slums: slum as a sink, and as a final destination. Also, the factors that brought most of the slum dwellers to the slums (cheap housing, proximity to work etc.) differs from the ones that made them stay (Gender, employment status, housing status etc.). This study concludes that residential choice and intention to stay are the major contributors to population growth in a slum. It is therefore important for Lagos state Government to incorporate these elements of residential choices of slum dwellers in their slum management policies if the city aims to be free of slums by 2030

Keywords: Lagos, population growth, residential decision choices, slum

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Authors: Faseluka Olamide Tope

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Giving quality education to students with special needs requires that all necessary resources should be harnessed and digital devices has become important part of resources used as instructional materials in educating students with special needs. Teachers who will make use of these technologies are considered as a part of the most important elements in any educational programme and the effective usage of these technologies largely depends on them. Out of numerous determinants of the effective use of these digital devices, this study examines teachers’ attitude and knowledge as predictors of effective use of digital technology for education of special needs student in Oyo state, Nigeria. The descriptive survey research design of the expo-facto type was adopted for the study, using simple random sampling technique. The study was carried out among sixty (60) participants. Two research questions and two research hypotheses were formulated and used. The data collected through the research instruments for the study were analysedusing frequency, percentage, mean and standard deviation, Pearson, Product, Moment Correlation (PPMC) and Multiple Regression Analysis. The study revealed a significant relationship between teachers attitude (50, < 0.05) and effective use of digital technologies for special needs students. Furthermore, there was a significant contribution F (F=4.289; R=0.876 and R2 =0.758) in the joint contribution of the independent variable  (teacher’s attitude and teacher’s knowledge) and dependent variable (effective use of digital technologies) while teachers knowledge have the highest contribution(b=7.926, t=4.376), the study therefore revealed that teachers attitude and knowledge are potent factors that predicts the effective usage of digital technologies for the education of special needs student. The study recommended that due to the ever-changing nature of technology which comes with new features, teachers should be equipped with appropriate knowledge in order to effectively make use of them and teachers should also develop right attitude toward the use of digital technologies

Keywords: teachers’ knowledge, teachers’ attitude, digital devices, special needs students

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Authors: Zixuan Zhao, Lingbin Du, Le Wang, Youqing Wang, Yi Yang, Jingjun Chen, Hengjin Dong

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Objectives: Few results from public attitudes for lung cancer screening are available both in China and abroad. This study aimed to identify preferred lung cancer screening modalities in a Chinese population and predict uptake rates of different modalities. Materials and Methods: A discrete choice experiment questionnaire was administered to 392 Chinese individuals aged 50–74 years who were at high risk for lung cancer. Each choice set had two lung screening options and an option to opt-out, and respondents were asked to choose the most preferred one. Both mixed logit analysis and stepwise logistic analysis were conducted to explore whether preferences were related to respondent characteristics and identify which kinds of respondents were more likely to opt out of any screening. Results: On mixed logit analysis, attributes that were predictive of choice at 1% level of statistical significance included the screening interval, screening venue, and out-of-pocket costs. The preferred screening modality seemed to be screening by low-dose computed tomography (LDCT) + blood test once a year in a general hospital at a cost of RMB 50; this could increase the uptake rate by 0.40 compared to the baseline setting. On stepwise logistic regression, those with no endowment insurance were more likely to opt out; those who were older and housewives/househusbands, and those with a health check habit and with commercial endowment insurance were less likely to opt out from a screening programme. Conclusions: There was considerable variance between real risk and self-perceived risk of lung cancer among respondents, and further research is required in this area. Lung cancer screening uptake can be increased by offering various screening modalities, so as to help policymakers further design the screening modality.

Keywords: lung cancer, screening, China., discrete choice experiment

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Authors: Harini Chakkera

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Background: Inpatient hyperglycemia is an established independent risk factor among several patient cohorts with hospital readmission. This has not been studied after kidney transplantation. Nearly one-third of patients who have undergone a kidney transplant reportedly experience 30-day readmission. Methods: Data on first-time solitary kidney transplantations were retrieved between September 2015 to December 2018. Information was linked to the electronic health record to determine a diagnosis of diabetes mellitus and extract glucometeric and insulin therapy data. Univariate logistic regression analysis and the XGBoost algorithm were used to predict 30-day readmission. We report the average performance of the models on the testing set on five bootstrapped partitions of the data to ensure statistical significance. Results: The cohort included 1036 patients who received kidney transplantation, and 224 (22%) experienced 30-day readmission. The machine learning algorithm was able to predict 30-day readmission with an average AUC of 77.3% (95% CI 75.30-79.3%). We observed statistically significant differences in the presence of pretransplant diabetes, inpatient-hyperglycemia, inpatient-hypoglycemia, and minimum and maximum glucose values among those with higher 30-day readmission rates. The XGBoost model identified the index admission length of stay, presence of hyper- and hypoglycemia and recipient and donor BMI values as the most predictive risk factors of 30-day readmission. Additionally, significant variations in the therapeutic management of blood glucose by providers were observed. Conclusions: Suboptimal glucose metrics during hospitalization after kidney transplantation is associated with an increased risk for 30-day hospital readmission. Optimizing the hospital blood glucose management, a modifiable factor, after kidney transplantation may reduce the risk of 30-day readmission.

Keywords: kidney, transplant, diabetes, insulin

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Authors: Said Belaaouad

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This study aimed to explore the quantitative structure-activity relationship (QSAR) of 1,2,4-Triazine-3(2H)-one derivative as a potential anticancer agent against breast cancer. The electronic descriptors were obtained using the Density Functional Theory (DFT) method, and a multiple linear regression techniques was employed to construct the QSAR model. The model exhibited favorable statistical parameters, including R2=0.849, R2adj=0.656, MSE=0.056, R2test=0.710, and Q2cv=0.542, indicating its reliability. Among the descriptors analyzed, absolute electronegativity (χ), total energy (TE), number of hydrogen bond donors (NHD), water solubility (LogS), and shape coefficient (I) were identified as influential factors. Furthermore, leveraging the validated QSAR model, new derivatives of 1,2,4-Triazine-3(2H)-one were designed, and their activity and pharmacokinetic properties were estimated. Subsequently, molecular docking (MD) and molecular dynamics (MD) simulations were employed to assess the binding affinity of the designed molecules. The Tubulin colchicine binding site, which plays a crucial role in cancer treatment, was chosen as the target protein. Through the simulation trajectory spanning 100 ns, the binding affinity was calculated using the MMPBSA script. As a result, fourteen novel Tubulin-colchicine inhibitors with promising pharmacokinetic characteristics were identified. Overall, this study provides valuable insights into the QSAR of 1,2,4-Triazine-3(2H)-one derivative as potential anticancer agent, along with the design of new compounds and their assessment through molecular docking and dynamics simulations targeting the Tubulin-colchicine binding site.

Keywords: QSAR, molecular docking, ADMET, 1, 2, 4-triazin-3(2H)-ones, breast cancer, anticancer, molecular dynamic simulations, MMPBSA calculation

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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Authors: Getnet Gedefaw, Fentanesh Endalew, Bitewush Azmeraw, Bethelhem Walelign, Eyob Shitie

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Introduction: The issue of menstrual hygiene is often overlooked and has not been sufficiently addressed in the fields of reproductive health in low and middle-income countries. Inadequate menstrual hygiene practices can increase the risk of various infectious and chronic obstetric and gynaecological complications for girls and adolescents. Hence, this study seeks to investigate the knowledge, attitudes, and practices related to menstrual hygiene, along with the factors influencing them, among high school students. Methods: A facility based cross-sectional study was conducted involving a total of 423 study subjects. A systematic random sampling technique was utilized. Data was entered and analyzed through Epi data 3.1 and SPSS 22, respectively. Both univariable and multivariable logistic regression models were employed. A p-value of less than 0.05 was considered statistically significant. Results: This study revealed that 365(89.2%), 200(48.9%) and 196(47.9%) of the study participants have good knowledge, good practice, and good attitudes about menstrual hygiene, respectively. Being higher grade students (grade 10) [AOR=3.96, 95% CI =2.0-7.8] and having good practice of menstrual hygiene (AOR=2.52, 95% CI= 1.26-5) had a positive association with menstrual hygiene knowledge. Whereas maternal education level (AOR=1.86, 95% CI=1.18-2.9) and being a grade 10 student (AOR=2.3, 95% CI=1.48-3.56) were associated factors for practising menstrual hygiene. Additionally, being higher grade students (AOR=1.9, 95% CI=1.2-2.8), age ≥18 years (AOR=1.67, 95% CI=1.09-2.55) were statistically and positively associated with the attitude of menstrual hygiene. Conclusion: The study findings indicated that the knowledge of the study participants regarding menstrual hygiene was high, while their attitudes and practices towards menstrual hygiene were low. It is suggested that raising awareness among reproductive health groups and educating their families and parents could potentially lead to a positive change in their poor practices and attitudes towards menstrual hygiene.

Keywords: menstrual hygiene, menstruation, students, reproductive health

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Authors: Muftah H. El-Naas, Ameera F. Mohammad, Mabruk I. Suleiman, Mohamed Al Musharfy, Ali H. Al-Marzouqi

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CO₂ capture and storage technologies play a significant role in contributing to the control of climate change through the reduction of carbon dioxide emissions into the atmosphere. The present study evaluates and optimizes CO₂ capture through a process, where carbon dioxide is passed into pH adjusted high salinity water and reacted with sodium chloride to form a precipitate of sodium bicarbonate. This process is based on a modified Solvay process with higher CO₂ capture efficiency, higher sodium removal, and higher pH level without the use of ammonia. The process was tested in a bubble column semi-batch reactor and was optimized using response surface methodology (RSM). CO₂ capture efficiency and sodium removal were optimized in terms of major operating parameters based on four levels and variables in Central Composite Design (CCD). The operating parameters were gas flow rate (0.5–1.5 L/min), reactor temperature (10 to 50 ^oC), buffer concentration (0.2-2.6%) and water salinity (25-197 g NaCl/L). The experimental data were fitted to a second-order polynomial using multiple regression and analyzed using analysis of variance (ANOVA). The optimum values of the selected variables were obtained using response optimizer. The optimum conditions were tested experimentally using desalination reject brine with salinity ranging from 65,000 to 75,000 mg/L. The CO₂ capture efficiency in 180 min was 99% and the maximum sodium removal was 35%. The experimental and predicted values were within 95% confidence interval, which demonstrates that the developed model can successfully predict the capture efficiency and sodium removal using the modified Solvay method.

Keywords: CO2 capture, water desalination, Response Surface Methodology, bubble column reactor

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Authors: Arun K. Yadav, Adam J. Carroll, Gonzalo M. Estavillo, Greg J. Rebetzke, Barry J. Pogson

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Water limits crop productivity, so selecting for minimal yield-gap in drier environments is critical to mitigate against climate change and land-use pressures. To date, no markers measured in glasshouses have been reported to predict field-based drought tolerance. In the field, the best measure of drought tolerance is yield-gap; but this requires multisite trials that are an order of magnitude more resource intensive and can be impacted by weather variation. We investigated the responses of relative water content (RWC), stomatal conductance (gs), chlorophyll content and metabolites in flag leaves of commercial wheat (Triticum aestivum L.) cultivars to three drought treatments in the glasshouse and field environments. We observed strong genetic associations between glasshouse-based RWC, metabolites and Yield gap-based Drought Tolerance (YDT): the ratio of yield in water-limited versus well-watered conditions across 24 field environments spanning sites and seasons. Critically, RWC response to glasshouse drought was strongly associated with both YDT (r2 = 0.85, p < 8E-6) and RWC under field drought (r2 = 0.77, p < 0.05). Multiple regression analyses revealed that 98% of genetic YDT variance was explained by drought responses of four metabolites: serine, asparagine, methionine and lysine (R2 = 0.98; p < 0.01). Fitted coefficients suggested that, for given levels of serine and asparagine, stronger methionine and lysine accumulation was associated with higher YDT. Collectively, our results demonstrate that high-throughput, targeted metabolic phenotyping of glasshouse-grown plants may be an effective tool for the selection of wheat cultivars with high YDT in the field.

Keywords: drought stress, grain yield, metabolomics, stomatal conductance, wheat

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Authors: Fazle Rabbi, Mashuda Khanom Tithi, Tasnim Mirza, Sanjida Rowshan Anannya, Ahmed Hossain

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Background: Low Back Pain (LBP) is one of the common health problems among the garment workers that causes workers absenteeism from the work. The purpose of the study is to identify the association between occupational factors and LBP among the female garment workers in Bangladesh. Materials and Methods: A cross-sectional study was conducted with 487 female garment workers from three compliant garment factories of Bangladesh. Face-to-face interview on four different LBP measures along with questions on socio-demographic, occupational, and physical factors were used to collect the data. Result: The prevalence rates for LBP lasts for at least one day during the last six months, chronic pain, intense pain, and seeking medical care for LBP were found 63.04%, 38.60%, 13.76%, and 18.89%, respectively among the female garments workers. The multivariate logistic regression analysis indicates that duration of employment (>5 years), regular weight bearing and extended weekly working hours (>48 hours) are positively associated with LBP. Besides, age, BMI, family income, marital status and number of children are also found positively associated with the LBP measures. Conclusion: The prevalence of LBP among female garment workers in Bangladesh is found high. The duration of employment (>5 years), regular weight bearing and extended weekly working hours (>48 hours) play a significant role in developing LBP among the female workers. Factories need to consider training programs on the appropriate technique of weight bearing. It is also important to conduct regular screening programs to identify LBP, especially with married, overweight/obese and older age group to reduce the occurrence of LBP.

Keywords: Bangladesh, garment workers, low back pain, occupational health

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Authors: Ni Wayan Sinthia Widiastuti, Komang Rahayu Indrawati

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The increasing number of tourists coming to Bali, causing accommodation facilities, such as hotels have increased. The existence of hotel needs will be the source of labor and cost efficiency, so that hotel management employs employees with different working status. The hospitality industry is one of the sectors that require organizational citizenship behavior because, the main goal of every hotel, in general, was to provide the best service and quality to tourists. The purpose of this study was to determine the differences in organizational citizenship behavior based on work status of employees at the Hotel in Bali in terms of quality of work life. Research sample was chosen randomly through two-stage cluster sampling which succeeds to obtain 126 samples from 11 hotels in Denpasar, Bali. The subjects consisted of 64 employees with Employment Agreement of Uncertain Time or who is often called a permanent employee and 62 employees with Employment Agreement of Certain Time or better known as contract employees, outsourcing, and daily workers. Instruments in this study were the scale of organizational citizenship behavior and the scale of quality of work life. The results of ANCOVA analysis showed there were differences in organizational citizenship behavior based on employee work status in terms of quality of work life. Differences in organizational citizenship behavior and quality of work life based on work status of employees using comparative test was analysis by independent sample t-test shows there were differences in organizational citizenship behavior and quality of work life between employees with different working status in hotels in Bali. The result of the regression analysis showed the functional relationship between quality of work life and organizational citizenship behavior.

Keywords: hotel in Bali, organizational citizenship behavior, quality of work life, work status of employees

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Bataineh Abdallah, Alabdallah Ghaith, Alkharabshe Abdalhameed

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Social media is an umbrella term for different types of online communication channels. The most prominent forms can be divided into four categories: Collaborative projects (e.g. Wikipedia, comparison-shopping sites), blogs (e.g. Twitter), content communities (e.g. Youtube), social networking sites (e.g. Facebook) social media allow consumers to share their opinions, criticisms and suggestions in public. Facebook launched in 2004, initially targeted college students and later started including everyone has become the most popular sites amongst the young generation for connecting with friends and relatives and for the communication of ideas. In 2013 Facebook penetration rate reached 41.4% of the population making it the most popular social networking site in Jordan. Accordingly, the purpose of this research is to examine the impact of perceived usefulness, perceived ease of use, perceived trust, perceived enjoyment and subjective norms on users' satisfaction and continuance intention to use Facebook in Jordan. Using a structured questionnaire, the primary data was collected from 584 users who have an active Facebook accounts. Multiple regression analysis was employed to test the research model and hypotheses. The research findings indicate that perceived usefulness, perceived ease of use, perceived trust, perceived enjoyment, and subjective norms have a positive and significant effect on users' satisfaction and continuance intention to use Facebook. The findings also indicated that the strongest predictors, based on beta values, on both users' satisfaction and continuance intention to use Facebook is subjective norms and respectively, perceived enjoyment, perceived usefulness, perceived ease of us, and perceived trust. Research results, recommendations, and future research opportunities are also discussed.

Keywords: perceived usefulness, perceived ease of use, perceived trust, perceived enjoyment, perceived subjective norms, users' satisfaction, continuance intention, Facebook

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Authors: Wondmnew Derebe Yohannis

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The enhanced utilization of modern beehives holds significant potential to enhance the livelihoods of smallholder farmers who heavily rely on mixed crop-livestock farming for their income. Recognizing this, the distribution of improved beehives has been implemented across various regions in Ethiopia, including the Bugina district. However, the precise impact of these improved beehives on farmers' income has received limited attention. To address this gap, this study aims to assess the influence of adopting upgraded beehives on rural households' income and asset accumulation. To conduct this research, survey data was gathered from a sample of 350 households selected through random sampling. The collected data was then analyzed using an econometric stochastic frontier model (ESRM) approach. The findings reveal that the adoption of improved beehives has resulted in higher annual income and asset growth for beekeepers. On average, those who adopted the improved beehives earned approximately 6,077 Ethiopian Birr (ETB) more than their counterparts who did not adopt these beehives. However, it is worth noting that the impact of adoption would have been even greater for non-adopters, as evidenced by the negative transitional heterogeneity effect of 1792 ETB. Furthermore, the analysis indicates that the decision to adopt or not adopt improved beehives was driven by individual self-selection. The adoption of improved beehives also led to an increase in fixed assets for households, establishing it as a viable strategy for poverty reduction. Overall, this study underscores the positive effect of adopting improved beehives on rural households' income and asset holdings, showcasing its potential to uplift smallholder farmers and serve as an alternative mechanism for reducing poverty.

Keywords: impact, adoption, endogenous switching regression, income, improved beehives

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Authors: Xu Yifei, Le Yining, Yang Qingluan, Tu Yanjie

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Objective: This study aims to investigate the distribution features of Traditional Chinese Medicine (TCM) syndromes and syndrome elements in Epstein-Barr virus-associated diseases and then explores the relations between TCM syndromes or syndrome elements and laboratory indicators of Epstein-Barr virus-associated diseases. Methods: A cross-sectional study of 70 patients with EBV infection was described. We assessed the diagnostic information and laboratory indicators of these patients from Huashan Hospital Affiliated to Fudan University between November 2017 and July 2019. The disease diagnosis and syndrome differentiation were based on the diagnostic criteria of EBV-associated diseases and the theory of TCM respectively. Confidence correlation analysis, logistic regression analysis, cluster analysis, and the Sankey diagram were used to analyze the correlation between the data. Results: The differentiation of the 4 primary TCM syndromes in the collected patients was correlated with the indexes of immune function, liver function, inflammation, and anemia, especially the relationship between Qifen syndrome and high lactic acid dehydrogenase level. The common 11 TCM syndrome elements were associated with the increased CD3+ T cell rate, low hemoglobin level, high procalcitonin level, high lactic acid dehydrogenase level, and low albumin level. Conclusion: The changes in immune function indexes, procalcitonin, and liver function-related indexes in patients with EBV-associated diseases were consistent with the evolution law of TCM syndromes. This study provides a reference for judging the pathological stages of these kinds of diseases, predicting their prognosis, and guiding subsequent treatment strategies based on TCM syndrome type.

Keywords: EBV-associated diseases, traditional Chinese medicine syndrome, syndrome element, diagnostics

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Authors: Haykal. Kay-Anne

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The health and well-being of students is a priority for the Faculty of Medicine at the University of Ottawa. The demands of medical studies are extreme, and many studies confirm that the prevalence of psychological distress is very high among medical students and that it is higher than that of the general population of the same age. The main goal is to identify risk factors for mental health among medical students at the University of Ottawa. The secondary objectives are to determine the variation of these risk factors according to demographic variables, as well as to determine if there is a change in the mental health of students during the 1st and 3rd years of their study. Medical students have a mandatory first and third-year wellness check meeting. This assessment includes a questionnaire on demographic information, mental health, and risk factors such as physical health, sleep, social support, financial stress, education and career, stress and drug use and/or alcohol. Student responses were converted to numerical values and analyzed statistically. The results show that 61% of the variation in the mean of the mental health score is explained by the following risk factors (R2 = 0.61, F (9.396) = 67.197, p < 0.01): lack of sleep and fatigue (β = 0.281, p < 0.001), lack of social support (β = 0.217, p <0.001), poor study or career development (β = 0.195, p < 0.001) and an increase stress and drug and alcohol use (β = -0.239, p < 0.001). No demographic variable has a significant effect on the presence of risk factors. In addition, fixed-effects regression demonstrated significantly lower mental health (p < 0.1) among first-year students (M = 0.587, SD = 0.072) than among third-year students (M = 0.719, SD = 0.071). This preliminary study indicates the need to continue data collection and analysis to increase the significance of the study results. As risk factors are present at the beginning of medical studies, it is important to offer resources to students very early in their medical studies and to have close monitoring and supervision.

Keywords: assessment of mental health, medical students, risk factors for mental health, wellness assessment

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Authors: Alban Igwe, Ijeoma Kalu, Alloy Ezirim

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Food insecurity is a global problem, and the search for food security has assumed a central stage in the global development agenda as the United Nations currently placed zero hunger as a goal number in its sustainable development goals. Nigeria currently ranks 107th out of 113 countries in the global food security index (GFSI), a metric that defines a country's ability to furnish its citizens with food and nutrients for healthy living. Paradoxically, Nigeria is a global leader in food production, ranking 1st in yam (over 70% of global output), beans (over 41% of global output), cassava (20% of global output) and shea nuts, where it commands 53% of global output. Furthermore, it ranks 2nd in millet, sweet potatoes, and cashew nuts. It is Africa's largest producer of rice. So, it is apparent that Nigeria's food insecurity woes must relate to a factor other than food production. We investigated the nexus between food security and downstream supply chain losses in the yam industry with secondary data from the Food and Agricultural Organization (FAOSTAT) and the National Bureau of Statics for the decade 2012-2021. In analyzing the data, multiple regression techniques were used, and findings reveal that downstream losses have a strong positive correlation with food security (r = .763*) and a 58.3% variation in food security is explainable by post-downstream supply chain food losses. The study discovered that yam supply chain losses within the period under review averaged 50.6%, suggestive of the fact that downstream supply chain losses are the drainpipe and the major source of food insecurity in Nigeria. Therefore, the study concluded that there is a significant relationship between downstream supply chain losses and food insecurity and recommended the establishment of food supply chain structures and policies to enhance food security in Nigeria.

Keywords: food security, downstream supply chain losses, yam, nigeria, supply chain

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Authors: Tan Swee Liang

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This paper estimates bank and stock market efficiency associations with real per capita GDP growth by examining panel-data across three different regions using Panel-Corrected Standard Errors (PCSE) regression developed by Beck and Katz (1995). Data from five economies in ASEAN (Singapore, Malaysia, Thailand, Philippines, and Indonesia), five economies in Asia (Japan, China, Hong Kong SAR, South Korea, and India) and seven economies in OECD (Australia, Canada, Denmark, Norway, Sweden, United Kingdom U.K., and United States U.S.), between 1990 and 2017 are used. Empirical findings suggest one, for Asia-5 high bank net interest margin means greater bank profitability, hence spurring economic growth. Two, for OECD-7 low bank overhead costs (as a share of total assets) may reflect weak competition and weak investment in providing superior banking services, hence dampening economic growth. Three, stock market turnover ratio has negative association with OECD-7 economic growth, but a positive association with Asia-5, which suggest the relationship between liquidity and growth is ambiguous. Lastly, for ASEAN-5 high bank overhead costs (as a share of total assets) may suggest expenses have not been channelled efficiently to income generating activities. One practical implication of the findings is that policy makers should take necessary measures toward financial liberalisation policies that boost growth through the efficiency channel, so that funds are efficiently allocated through the financial system between financial and real sectors.

Keywords: financial development, banking system, capital markets, economic growth

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Authors: Ranjeet Sable, Mahotsavi Patil, Aadesh Nimbalkar, Prajakta Palaskar, Ritu Sagar

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The exact amount of water used by various crops in different climatic conditions is necessary to step for design, planning, and management of irrigation schemes, water resources, scheduling of irrigation systems. Evaporation and transpiration are combinable called as evapotranspiration. Water loss from trees during photosynthesis is called as transpiration and when water gets converted into gaseous state is called evaporation. For calculation of correct evapotranspiration, we have to choose the method in such way that is should be suitable and require minimum climatic data also it should be applicable for wide range of climatic conditions. In hydrology, there are multiple correlations and regression is generally used to develop relationships between three or more hydrological variables by knowing the dependence between them. This research work includes the study of various methods for calculation of evapotranspiration and selects reasonable and suitable one Pune region (Maharashtra state). As field methods are very costly, time-consuming and not give appropriate results if the suitable climate is not maintained. Observation recorded at Pune metrological stations are used to calculate evapotranspiration with the help of Radiation Method (RAD), Modified Penman Method (MPM), Thornthwaite Method (THW), Blaney-Criddle (BCL), Christiansen Equation (CNM), Hargreaves Method (HGM), from which Hargreaves and Thornthwaite are temperature based methods. Performance of all these methods are compared with Modified Penman method and method which showing less variation with standard Modified Penman method (MPM) is selected as the suitable one. Evapotranspiration values are estimated on a monthly basis. Comparative analysis in this research used for selection for raw data-dependent methods in case of missing data.

Keywords: Blaney-Criddle, Christiansen equation evapotranspiration, Hargreaves method, precipitations, Penman method, water use efficiency

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Authors: Thananyada Buapian

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Overnutrition is emerging as a morbid disease in developing and Westernized countries. Because of its comorbidity diseases, it is cost-effective to prevent and manage this disease earlier. In Thailand, this alarming disease has long been studied, but the prevalence is still higher than that in the past. Physicians should recognize it well and have a definite direction to face and combat this dangerous disease. Rapid changes in the tremendous figure of overnutrition students indicate that genetic factors are not the primary determinants since human genes have remained unchanged for a century. This study aims to assess the prevalence of overnutrition students and to investigate the non-genetic factors affecting over nutrition students. A cross-sectional school-based survey was conducted. A two-stage sampling was adopted. Respondents included 1,850 students in grades 4 to 6 in Ayutthaya Province. An anthropometric measurement and questionnaire were developed. Childhood over nutrition was defined as a weight-for-height Z-score above +2SD of NCHS/WHO references. About thirty three percent of the children were over nutrition in Ayutthaya province. Stepwise multiple logistic regression analysis showed that 8 statistically significant non genetic factors explain the variation of childhood over nutrition by 18 percent. Sex is the prime factor to explain the variation of childhood over nutrition, followed by duration of light physical activities, duration of moderate physical activities, having been breastfed, the presence of a healthy role model of the caregiver, number of siblings, birth order, and occupation of the caregiver, respectively. Non genetic factors, especially the subjects’ demographic and physical activities, as well as the caregivers’ background and family environment, should be considered in viable approach to remedy this health imbalance in children.

Keywords: non genetic factors, non-genetic, over nutrition, over nutrition students

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Authors: Sangwoo Han, Saeed Khaleghi Rahimian, Ying Liu

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Vehicle electrification is gaining momentum, and many car manufacturers promise to deliver more electric vehicle (EV) models to consumers in the coming years. In controlling the battery pack, the battery management system (BMS) must maintain optimal battery performance while ensuring the safety of a battery pack. Tasks related to battery performance include determining state-of-charge (SOC), state-of-power (SOP), state-of-health (SOH), cell balancing, and battery charging. Safety related functions include making sure cells operate within specified, static and dynamic voltage window and temperature range, derating power, detecting faulty cells, and warning the user if necessary. The BMS often utilizes an RC circuit model to model a Li-ion cell because of its robustness and low computation cost among other benefits. Because an equivalent circuit model such as the RC model is not a physics-based model, it can never be a prognostic model to predict battery state-of-health and avoid any safety risk even before it occurs. A physics-based Li-ion cell model, on the other hand, is more capable at the expense of computation cost. To avoid the high computation cost associated with a full-order model, many researchers have demonstrated the use of a single particle model (SPM) for BMS applications. One drawback associated with the single particle modeling approach is that it forces to use the average current density in the calculation. The SPM would be appropriate for simulating drive cycles where there is insufficient time to develop a significant current distribution within an electrode. However, under a continuous or high-pulse electrical load, the model may fail to predict cell voltage or Li⁺ plating potential. To overcome this issue, a multi-particle reduced-order model is proposed here. The use of multiple particles combined with either linear or nonlinear charge-transfer reaction kinetics enables to capture current density distribution within an electrode under any type of electrical load. To maintain computational complexity like that of an SPM, governing equations are solved sequentially to minimize iterative solving processes. Furthermore, the model is validated against a full-order model implemented in COMSOL Multiphysics.

Keywords: battery management system, physics-based li-ion cell model, reduced-order model, single-particle and multi-particle model

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Authors: Wei Wen Yang, Emily Chia Yu Su

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Dengue fever is a mosquito-borne tropical infectious disease caused by the dengue virus. After infection, symptoms usually start from three to fourteen days. Dengue virus may cause a high fever and at least two of the following symptoms, severe headache, severe eye pain, joint pains, muscle or bone pain, vomiting, feature skin rash, and mild bleeding manifestation. In addition, recovery will take at least two to seven days. Dengue fever has rapidly spread in tropical and subtropical areas in recent years. Several phenomena around the world such as global warming, urbanization, and international travel are the main reasons in boosting the spread of dengue. In Taiwan, epidemics occur annually, especially during summer and fall seasons. On the other side, Singapore government also has announced the amounts number of dengue cases spreading in Singapore. As the serious epidemic of dengue fever outbreaks in Taiwan and Singapore, countries around the Asia-Pacific region are becoming high risks of susceptible to the outbreaks and local hub of spreading the virus. To improve public safety and public health issues, firstly, we are going to use Microsoft Excel and SAS EG to do data preprocessing. Secondly, using support vector machines and decision trees builds predict model, and analyzes the infectious cases between Taiwan and Singapore. By comparing different factors causing vector mosquito from model classification and regression, we can find similar spreading patterns where the disease occurred most frequently. The result can provide sufficient information to predict the future dengue infection outbreaks and control the diffusion of dengue fever among countries.

Keywords: dengue fever, Taiwan, Singapore, Aedes aegypti

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Authors: Buchh Aqsa, Inayat Umar

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Background- Clonidine, α 2 agonist, possesses several properties to make it valuable adjuvant for spinal anesthesia. The study was aimed to evaluate the clinical effects of oral clonidine premedication for laparoscopic gynecological procedures under subarachnoid block. Patients and method- Sixtyfour adult female patients of ASA physical status I and II, aged 25 to 45 years and scheduled for laparoscopic gynecological procedures under the subarachnoid block, were randomized into two comparable equal groups of 32 patients each to received either oral clonidine, 100 µg (Group I) or placebo (Group II), 90 minutes before the procedure. Subarachnoid block was established with of 3.5 ml of 0.5% hyperbaric bupivacaine in all patients. Onset and duration of sensory and motor block, maximum cephalad level, and the regression time to reach S1 sensory level were assessed as primary end points. Sedation, hemodynamic variability, and respiratory depression or any other side effects were evaluated as secondary outcomes. Results- The demographic profile was comparable. The intraoperative hemodynamic parameters showed significant differences between groups. Oral clonidine was accelerated the onset time of sensory and motor blockade and extended the duration of sensory block (216.4 ± 23.3 min versus 165 ± 37.2 min, P <0.05). The duration of motor block showed no significant difference. The sedation score was more than 2 in the clonidine group as compared to the control group. Conclusion- Oral clonidine premedication has extended the duration of sensory analgesia with arousable sedation. It also prevented the post spinal shivering of the subarachnoid block.

Keywords: oral clonidine, subarachnoid block, sensory analgesia, laparoscopic gynaecological

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Authors: Ajit Kumar Behera, Saranya P., Sudhir Kumar, Krishnakumar A

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The stable isotope (δ¹⁸ O and δ²H) composition of groundwater of the coastal areas of Periyar and Mahanadi basins falling along East and West coast of India during North-East (NE) monsoon season have been studied. The east and west coast regions are surrounded by the Bay of Bengal and the Arabian Sea respectively, which are considered to be the primary sources for precipitation over India. The major difference between the Bay of Bengal and the Arabian Sea is that a number of large rivers feed the Bay of Bengal, whereas the Arabian Sea is fed by very few small rivers, resulting in enriched stable isotopic composition of the Arabian Sea than the Bay of Bengal. Previous studies have reported depleted ratios of stable isotopes during Northeast monsoon along East and West coasts due to the influence of the Bay of Bengal moisture source. The isotopic composition of groundwater of the Mahanadi delta in the east coast region varies from -6.87 ‰ to -3.40 ‰ for δ¹⁸ O and -45.42 ‰ to -22.43‰ for δ²H. However, the groundwater of the Periyar basin in the west coast has enriched stable isotope value varying from -4.3‰ to -2.5 ‰ for δ¹⁸ O and for δ²H from -23.7 to -6.4 ‰ which is a characteristic of South-West monsoon season. This suggests the groundwater system of the Mahanadi delta and the Periyar basins are influenced by dissimilar moisture sources. The δ¹⁸ O and δ² H relationship (δ²H= 6.513 δ¹⁸ O - 1.39) and d-excess value (< 10) in the east coast region indicates the influence of NE monsoon implying the quick groundwater recharge after precipitation with significant amount of evaporation. In contrast, the δ¹⁸ O and δ²H regression line (δ²H= 8.408 δ¹⁸ O + 11.71) with high d-excess value (>10) in the west coast region implies delayed recharge due to SW monsoon. The observed isotopic enrichment in west coast suggests that NE winter monsoon rainfall does not replenish groundwater quick enough to produce isotopic depletion during the season.

Keywords: Arabian sea, bay of Bengal, groundwater, monsoon, stable isotope

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Authors: Mehmet Akif Bütüner, İlhan Koşalay

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Hydroelectric power plants (HEPPs) are renewable energy power plants with the highest installed power in the world. While the control systems operating in these power plants ensure that the system operates at the desired operating point, it is also responsible for stopping the relevant unit safely in case of any malfunction. While these control systems are expected not to miss signals that require stopping, on the other hand, it is desired not to cause unnecessary stops. In traditional control systems including modern systems with SCADA infrastructure, alarm conditions to create warnings or trip conditions to put relevant unit out of service automatically are usually generated with predefined limits regardless of different operating conditions. This approach results in alarm/trip conditions to be less likely to detect minimal changes which may result in serious malfunction scenarios in near future. With the methods proposed in this research, routine behavior of the oil circulation of hydraulic governor of a HEPP will be modeled with machine learning methods using historical data obtained from SCADA system. Using the created model and recently gathered data from control system, oil pressure of hydraulic accumulators will be estimated. Comparison of this estimation with the measurements made and recorded instantly by the SCADA system will help to foresee failure before becoming worse and determine remaining useful life. By using model outputs, maintenance works will be made more planned, so that undesired stops are prevented, and in case of any malfunction, the system will be stopped or several alarms are triggered before the problem grows.

Keywords: hydroelectric, governor, anomaly detection, machine learning, regression

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Authors: Edvard Kokanyan, Narine Babajanyan, Ninel Kokanyan, Marco Bazzan

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Lithium niobate (LN) crystals, renowned for their exceptional nonlinear optical, electro-optical, piezoelectric, and photorefractive properties, stand as foundational materials in diverse fields of study and application. While they have long been utilized in frequency converters of laser radiation, electro-optical modulators, and holographic information recording media, LN crystals doped with rare earth ions represent a compelling frontier for modern compact devices. These materials exhibit immense potential as key components in infrared lasers, optical sensors, self-cooling systems, and radiation balanced laser setups. In this study, we present the successful synthesis of Ho-doped lithium niobate (LN:Ho) thin films on sapphire substrates employing the Sol-Gel technique. The films exhibit a strong crystallographic orientation along the perpendicular direction to the substrate surface, with X-ray diffraction analysis confirming the predominant alignment of the film's "c" axis, notably evidenced by the intense (006) reflection peak. Further characterization through Raman spectroscopy, employing a confocal Raman microscope (LabRAM HR Evolution) with exciting wavelengths of 532 nm and 785 nm, unraveled intriguing insights. Under excitation with a 785 nm laser, Raman scattering obeyed selection rules, while employing a 532 nm laser unveiled additional forbidden lines reminiscent of behaviors observed in bulk LN:Ho crystals. These supplementary lines were attributed to luminescence induced by excitation at 532 nm. Leveraging data from anti-Stokes Raman lines facilitated the disentanglement of luminescence spectra from the investigated samples. Surface scanning affirmed the uniformity of both structure and luminescence across the thin films. Notably, despite the robust orientation of the "c" axis perpendicular to the substrate surface, Raman signals indicated a stochastic distribution of "a" and "b" axes, validating the mosaic structure of the films along the mentioned axis. This study offers valuable insights into the structural properties of Ho-doped lithium niobate thin films, with the observed luminescence behavior holding significant promise for potential applications in optoelectronic devices.

Keywords: lithium niobate, Sol-Gel, luminescence, Raman spectroscopy

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Authors: Yujun Liu, Maosheng Ran

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Background: Chinese rural-to-urban migrant workers’ mental health problems raise attentions from different social sectors. However, situation of present mental health services provided to this population has not been discovered. This study attempts to describe the current mental health service situation, identify the gaps and give the future directions based on the quantitative data. Methods: Questionnaire surveys were conducted among 2017 rural-to-urban migrant workers in 13 cities and 100 social work service organizations in 5 cities in 2014. Data was collected by face-to-face structured interview by trained interviewers. Findings: Migrant workers’ mental health status was not good. Compared to the severity of mental distress, mental health service for this population was lacking and insufficient, which accounted for only 14.4% of all services in our sample. And the group work and case work were the most frequently-used methods. By estimating a series of regression models, we revealed that life experiences and working conditions were significantly associated with migrant workers’ mental health status. Therefore, the macro social work practices aimed at this whole group were advocated to promote their mental wellbeing. That is, practitioners should not only focus on the improvement of migrant workers’ emotion management capacity, but also pay attention to raise awareness and improve their living and working condition; not only concentrate on the solving of individuals’ dilemma, but also promote gradual reformation of present labor regime and hukou system in China.

Keywords: Chinese rural-to-urban migrant workers, macro social work practice, mental health service needs, mental health status

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