Search results for: logistic regression models

Authors: Ashenafi Ayele, Shewit Haftu, Tesfalem Araya

Abstract:

Background: “Post-psychotic depression”, “post schizophrenic depression”, and “secondary depression” have been used to describe the occurrence of depressive symptoms during the chronic phase of schizophrenia. Post-psychotic depression is the most common cause of death due to suicide in schizophrenia patients. Overall lifetime risk for patients with schizophrenia is 50% for suicide attempts and 9-13% lifetime risk for completed suicide and also it is associated with poor prognosis and poor quality of life. Objective: To assess determinant of post psychotic depression in schizophrenia patients ACSH and Mekelle General Hospital, Tigray Ethiopia 2019. Methods: An institutional based unmatched case control study was conducted among 69 cases and 138 controls with the ratio of case to control 1 ratio 2. The sample is calculated using epi-info 3.1 to assess the determinant factors of post-psychotic depression in schizophrenia patients. The cases were schizophrenia patients who have been diagnosed at least for more than one-year stable for two months, and the controls are any patients who are diagnosed as schizophrenia patients. Study subjects were selected using a consecutive sampling technique. The Calgary depression scale for schizophrenia self-administered questionnaire was used. Before the interview, it was assessed the client’s capacity to give intended information using a scale called the University of California, San Diego Brief Assessment of Capacity to Consent (UBACC). Bivariant and multiple Logistic regression analysis was performed to determine between the independent and dependent variables. The significant independent predictor was declared at 95% confidence interval and P-value of less than 0.05. Result: Females were affected by post psychotic depression with the (AOR=2.01, 95%CI: 1.003- 4.012, P= 0.49).Patients who have mild form of positive symptom of schizophrenia affected by post psychotic depression with (AOR =4.05, 95%CI: 1.888- 8.7.8, P=0001).Patients who have minimal form of negative symptom of schizophrenia are affected by post psychotic depression with (AOR =4.23, 95%CI: 1.081-17.092, P=.038). Conclusion: In this study, sex (female) and presence of positive and negative symptoms of schizophrenia were significantly associated. It is recommended that the post psychotic depression should be assessed in every schizophrenia patient to decrease the severity of illness, and to improve patient’s quality of life.

Keywords: determinants, post-psychotic depression, Mekelle city

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Authors: Roongtiwa Chobchuen, Siriporn Mongkholthawornchai, Boonsong Hatawaikarn, Uriwan Chaichangreet, Kobkaew Thongtid, Pusda Pukdeekumjorn, Panita Limpawattana

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Background: Age-friendly nursing service system in Srinagarind Hospital has been developed continuously based on the value and cultural background of Thailand which corporates with the modified WHO’s Age friendly Primary Care Service System. It consists of 3 issues; 1) development of staff training, 2) age-friendly service and 3) appropriate physical environment. Objective: To evaluate the efficacy of Age-friendly Nursing Service System: KKU (AFNS:KKU) model and to evaluate factors associated with nursing perception with AFN:KKU. Study design: Descriptive study Setting: 31 wards that served older patients in Srinagarind Hospital Populations: Nursing staff from 11 departments (31 wards) Instrument: Age-friendly nursing care scale as perceived by hospitalized older person Procedure and statistical analysis: All participants were asked questions using age-friendly nursing care scale as perceived by hospitalized older person questionnaires. Descriptive statistics and multiple logistic regression analyses were used to analyse the outcomes. Results: There were 337 participants recruited in this study. The majority of them were women (92%) with the mean ages of 29 years and 77.45% were nurse practitioners. They had average nursing experiences of 5 years. The average scores of age-friendly nursing care scale were high and highest in the area of attitude and communication. Age, sex, educational level, duration of work among, and having experience in aging training were not associated with nursing perception where type of department was an independent factor. Nurses from department of Surgery and Orthopedic, Eye and ENT, special ward and Obstetrics and Gynecological had significant greater perception than nurses from Internal Medicine Department (p < 0.05). Conclusion: Nurses had high scores in all dimensions of age-friendly concept. The result indicates that nurses have good attitude to aging care which can lead to improve quality of care. Organization should support other domains of ageing care to achieve greater effectiveness in geriatric care.

Keywords: age-friendly, nursing service system, excellence model, geriatric care

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Authors: Sherry Ann Ganase, Sandra Sookram

Abstract:

This study examines adaptation measures and factors that influence adaptation decisions in Bequia by using multiple linear regression and a structural equation model. Using survey data, the results suggest that households are knowledgeable and concerned about climate change but lack knowledge about the measures needed to adapt. The findings from the SEM suggest that a positive relationship exist between vulnerability and adaptation, vulnerability and perception, along with a negative relationship between perception and adaptation. This suggests that being aware of the terms associated with climate change and knowledge about climate change is insufficient for implementing adaptation measures; instead the risk and importance placed on climate change, vulnerability experienced with household flooding, drainage and expected threat of future sea level are the main factors that influence the adaptation decision. The results obtained in this study are beneficial to all as adaptation requires a collective effort by stakeholders.

Keywords: adaptation, Bequia, multiple linear regression, structural equation model

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Authors: Florian Tille, Heide Weishaar, Bernhard Gibis, Susanne Schnitzer

Abstract:

Introduction: The quality of patient-doctor communication and of written health information is central to organizational health literacy (HL). Whether patients understand their doctors’ explanations and textual material on health, however, is understudied. This study identifies the overall levels of patient understanding of health information and its associations with patients’ social characteristics in outpatient health care in Germany. Materials & Methods: This analysis draws on data collected via a 2017 national health survey with a sample of 6,105 adults. Quality of communication was measured for consultations with general practitioners (GPs) and specialists (SPs) via the Ask Me 3 program questions, and through a question on written health material. Correlations with social characteristics were explored employing bivariate and multivariate logistic regression analyses. Results: Over 90% of all respondents reported that they had understood their doctors’ explanations during the last consultation. Failed understanding was strongly correlated with patients’ very poor health (Odds Ratio [OR]: 5.19; 95% confidence interval [CI]: 2.23–12.10; ref. excellent/very good health), current health problem (OR: 6.54, CI: 1.70–25.12; ref. preventive examination) and age 65 years and above (OR: 2.97, CI: 1.10–8.00; ref. 18 to 34 years). Fewer patients answered they understood written material well (86.7% for las visit at GP, 89.7% at SP). Understanding written material poorly was highly associated with basic education (OR: 4.20, CI: 2.76–6.39; ref. higher education) and 65 years old and above (OR: 2.66, CI: 1.43–4.96). Discussion: Overall ratings of oral patient-doctor communication and written communication of health information are high. Yet, a considerable share of patients reports not-understanding their doctors and poor understanding of the written health-related material. Interventions that can contribute to improving organizational HL in outpatient care in Germany include HL training for doctors, reducing system barriers to easily-accessible health information for patients and combining oral and written health communication means. Conclusion: This work adds to the study of organizational HL in Germany. To increase patient understanding of health-relevant information and thereby possibly reduce health disparities, meeting the communication needs especially of persons in different age groups, with basic education and in very poor health is suggested.

Keywords: health survey, organizational health literacy, patient-doctor communication, social characteristics, outpatient care, Ask Me 3

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Authors: Ahmet Kayabasi, Ali Akdagli

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In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: a-shaped compact microstrip antenna, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM)

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Authors: Mohammad Yousefikia, Sara Moridpour, Ehsan Mazloumi

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Perceiving track geometry deterioration decisively influences the optimization of track maintenance operations. The effective management of this deterioration and increasingly utilized system with limited financial resources is a significant challenge. This paper provides a review of degradation models relevant for railroad tracks. Furthermore, due to the lack of long term information on the condition development of tram infrastructures, presents the methodology which will be used to derive degradation models from the data of Melbourne tram network.

Keywords: deterioration modeling, asset management, railway, tram

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Authors: Rufus Temidayo Akinnubi, M. O. Adeniyi

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Existing diurnal air temperature models simulate night time air temperature over Nigeria with high biases. An improved parameterization is presented for modeling the diurnal pattern of air temperature (Ta) which is applicable in the calculation of turbulent heat fluxes in Global climate models, based on Nigeria Micrometeorological Experimental site (NIMEX) surface layer observations. Five diurnal Ta models for estimating hourly Ta from daily maximum, daily minimum, and daily mean air temperature were validated using root-mean-square error (RMSE), Mean Error Bias (MBE) and scatter graphs. The original Fourier series model showed better performance for unstable air temperature parameterizations while the stable Ta was strongly overestimated with a large error. The model was improved with the inclusion of the atmospheric cooling rate that accounts for the temperature inversion that occurs during the nocturnal boundary layer condition. The MBE and RMSE estimated by the modified Fourier series model reduced by 4.45 oC and 3.12 oC during the transitional period from dry to wet stable atmospheric conditions. The modified Fourier series model gave good estimation of the diurnal weather patterns of Ta when compared with other existing models for a tropical environment.

Keywords: air temperature, mean bias error, Fourier series analysis, surface energy balance,

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Authors: Hugo M. Gonzales, Ke Ni Chai, Deanne Mary King

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International students are underrepresented in Australian health literature, and this population is especially vulnerable to the well-documented negative impacts associated with racial microaggressions in their adjustment to settling in the new society, as well as to the many challenges they already face as international students. This study investigated the prevalence of racial microaggressions among international students and their impact on stress and psychological well-being. This research was conducted during the COVID-19 pandemic, which has been documented to contribute to anti-Asian racism. Participants included 54 international students, of which 72% were Asian. The Racial and Ethnic Microaggressions Scale (REMS), Perceived Stress Scale (PSS), and the Perceived General Wellbeing Indicator (PGWBI) were used to measure the participants’ responses. All participants reported experiencing racial microaggression in the last six months, and significant correlations and regression models were found between REMS, certain elements of the PSS scale, and time in Australia. Despite the small sample size, this research corroborated outcomes from recent studies and provided insight into the prevalence and impact of racial microaggressions among such populations, highlighting the need for further exploration.

Keywords: racial microaggressions, international students, racism, REMS, microaggressions in Australia, stress, psychological wellbeing

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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An estimating equation technique is an alternative method of the widely used maximum likelihood methods, which enables us to ease some complexity due to the complex characteristics of time-varying covariates. In the situations, when both the time-varying covariates and left-truncation are considered in the model, the maximum likelihood estimation procedures become much more burdensome and complex. To ease the complexity, in this study, the modified estimating equations those have been given high attention and considerations in many researchers under semiparametric transformation model was proposed. The purpose of this article was to develop the modified estimating equation under flexible and general class of semiparametric transformation models for left-truncated and right censored survival data with time-varying covariates. Besides the commonly applied Cox proportional hazards model, such kind of problems can be also analyzed with a general class of semiparametric transformation models to estimate the effect of treatment given possibly time-varying covariates on the survival time. The consistency and asymptotic properties of the estimators were intuitively derived via the expectation-maximization (EM) algorithm. The characteristics of the estimators in the finite sample performance for the proposed model were illustrated via simulation studies and Stanford heart transplant real data examples. To sum up the study, the bias for covariates has been adjusted by estimating density function for the truncation time variable. Then the effect of possibly time-varying covariates was evaluated in some special semiparametric transformation models.

Keywords: EM algorithm, estimating equation, semiparametric transformation models, time-to-event outcomes, time varying covariate

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Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are playing an increasingly important role in automated customer service. These models, which are able to recognize complex relationships between input and output sequences, are crucial for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the focus of the model during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the domain of chatbots using the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Utilizing the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k=3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k=3). These results emphasize the crucial influence of selecting an appropriate attention-scoring function in improving the performance of seq2seq models for chatbots. Particularly, the model that integrates tanh activation proves to be a promising approach to improve the quality of chatbots in the customer support context.

Keywords: attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence

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Authors: Sukhvinder Kaur, Jayanta Bora, Ashok Agarwal, Sangeeta Kaul

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Background: HIV and STI transmission can be prevented if condoms are used properly, but condom tear may lead to infections even if are used consistently. Studies reveal high rates of condom breakage among Female Sex Workers (FSWs). USAID PHFI-PIPPSE is piloting a prevention model among high risk groups at Thane district of Maharashtra, India by implementing prevention and advocacy efforts for such risk behaviors. The current analysis highlights the correlates of condom breakage among FSWs from Thane. Method: A Behavioral Tracking Survey was conducted in 2014-15 among 503 FSWs through probability-based two stage random sampling from 3,660 FSWs at 100 hotspots, to understand levels of high risk behaviors, awareness and exposure to prevention programs. Bi-variate and multivariate-logistic regression methods used to assess the association of condom breakage while having sex with age, STI occurrence, anal sex with clients and alcohol consumption. Only self-reported STIs (Genital sore/ulcer, yellowish/ greenish discharge from vagina with/without foul smell, lower abdominal pain without diarrhea/dysentery or menses) were considered. Major Findings: Results depicted FSWs who reported condom breakage while having sex with any type of partner (paying clients, non-paying partners and other than main partner husband/boyfriend) had significantly high number of STIs (42.3% vs 16.9 %, P, 0.000) and had started sexual relationship in <16 years of age (31.0% vs 16.4 %, P, 0.000). Multivariate analysis after controlling the age at sex, knowledge about HIV and literacy, highlighted significantly higher odds of condom breakage among FSWs who have reported currently suffering with STI [AOR 2.91, 95% CI 1.75 - 4.83; P, 0.000]; who had anal sex with their paying client [AOR 2.59, 95% CI 1.59 - 4.19; P, 0.000]; and who consumed alcohol in the last 12 months [AOR 1.89, 95% CI 1.01 - 3.53; P, 0.047]. Conclusion: Risky behavior like anal sex with paying clients and impact of alcohol while having sex are main factors for condom breakage among young sex workers; and condom breakage leads to STIs. Hence, program interventions should address measures for prevention of condom breakage for HIV/STI prevention.

Keywords: female sex workers, condom breakage, anal sex, young sex workers

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Authors: Christopher Mkirema Maghanga, Maurice Mghendi Mwamburi

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Parametric modeling provides a means to deeper understand the properties of materials. Drude, Brendel, Lorentz and OJL incorporated in SCOUT® software are some of the models used to study dielectric films. In our work, we utilized Brendel and Drude models to extract the optical constants from spectroscopic data of fabricated undoped and niobium doped titanium oxide thin films. The individual contributions by the two models were studied to establish how they influence the dielectric function. The effect of dopants on their influences was also analyzed. For the undoped films, results indicate minimal contribution from the Drude term due to the dielectric nature of the films. However as doping levels increase, the rise in the concentration of free electrons favors the use of Drude model. Brendel model was confirmed to work well with dielectric films - the undoped titanium Oxide films in our case.

Keywords: modeling, Brendel model, optical constants, titanium oxide, Drude Model

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Authors: Muhammad Asim

Abstract:

Background: Less than half of women in South Asia (SA) use any modern contraceptive method which leads to a huge burden of unintended pregnancies, unsafe abortions, maternal deaths, and socioeconomic loss. Women empowerment plays a pivotal role in improving various health seeking behaviours, including contraceptive use. The objective of this study to explore the association between women's empowerment and modern contraceptive, among rich and poor segment of population in SA. Methods: We used the most recent, large-scale, demographic health survey data of five South Asian countries, namely Afghanistan, Pakistan, Bangladesh, India, and Nepal. The outcome variable was the current use of modern contraceptive methods. The main exposure variable was a combination (interaction) of socio-economic status (SES) and women’s level of empowerment (low, medium, and high), where SES was bifurcated into poor and rich; and women empowerment was divided into three categories: decision making, attitude to violence and social independence. Moreover, overall women empowerment indicator was also created by using three dimensions of women empowerment. We applied both descriptive statistics and multivariable logistic regression techniques for data analyses. Results: Most of the women possessed ‘medium’ level of empowerment across South Asian Countries. The lowest attitude to violence empowerment was found in Afghanistan, and the lowest social independence empowerment was observed in Bangladesh across SA. However, Pakistani women have the lowest decision-making empowerment in the region. The lowest modern contraceptive use (22.1%) was found in Afghanistan and the highest (53.2%) in Bangladesh. The multivariate results depict that the overall measure of women empowerment does not affect modern contraceptive use among poor and rich women in most of South Asian countries. However, the decision-making empowerment plays a significant role among both poor and rich women to use modern contraceptive methods across South Asian countries. Conclusions: The effect of women’s empowerment on modern contraceptive use is not consistent across countries, and among poor and rich segment of population. Of the three dimensions of women’s empowerment, the autonomy of decision making in household affairs emerged as a stronger determinant of mCPR as compared with social independence and attitude towards violence against women.

Keywords: women empowerment, contraceptive use, South Asia, women autonomy

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Authors: Aayushi Lyngwa, Bimal Kishore Sahoo

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The study discusses the relationship between cognitive ability and the level of education attained by the tribal street entrepreneurs on their financial literacy. It is driven by the objective of examining the effect of cognitive ability on financial ability on the one hand and determining the effect of the same on financial literacy on the other. A field experiment was conducted on 203 tribal street vendors in the north-eastern Indian state of Mizoram. This experiment's calculations are conditioned by providing each question scores like math score (cognitive ability), financial score and debt score (financial ability). After that, categories for each of the variables, like math category (math score), financial category (financial score) and debt category (debt score), are generated to run the regression model. Since the dependent variable is ordinal, an ordered logit regression model was applied. The study shows that street vendors' cognitive and financial abilities are highly correlated. It, therefore, confirms that cognitive ability positively affects the financial literacy of street vendors through the increase in attainment of educational levels. It is also found that concerning the type of street vendors, regular street vendors are more likely to have better cognitive abilities than temporary street vendors. Additionally, street vendors with more cognitive and financial abilities gained better monthly profits and performed habits of bookkeeping. The study attempts to draw a particular focus on a set-up which is economically and socially marginalized in the Indian economy. Its finding contributes to understanding financial literacy in an understudied area and provides policy implications through inclusive financial systems solutions in an economy limited to tribal street vendors.

Keywords: financial literacy, education, street entrepreneurs, tribals, cognitive ability, financial ability, ordered logit regression.

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Authors: M. Firoz Kalam, Wilfried Schuetz, Jan Hendrik Bredehoeft

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Thiophene sulfur compounds' removal from diesel oil by batch adsorption process using commercial powdered activated carbon was designed and optimized in two-level factorial design method. This design analysis was used to find out the effects of operating parameters directing the adsorption process, such as amount of adsorbent, temperature and stirring time. The desulfurization efficiency was considered the response or output variable. Results showed that the stirring time had the largest effects on sulfur removal efficiency as compared with other operating parameters and their interactions under the experimental ranges studied. A regression model was generated to observe the closeness between predicted and experimental values. The three-dimensional plots and contour plots of main factors were generated according to the regression results to observe the optimal points.

Keywords: activated carbon, adsorptive desulfurization, factorial design, process optimization

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Authors: B. Varaprasad, C. Srinivasa Rao

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Hard turning has been explored as an alternative to the conventional one used for manufacture of Parts using tool steels. In the present study, the effects of cutting speed, feed rate and Depth of Cut (DOC) on cutting forces, specific cutting force, power and surface roughness in the hard turning are experimentally investigated. Experiments are carried out using mixed ceramic(Al2O3+TiC) cutting tool of corner radius 0.8mm, in turning operations on AISI H13 tool steel, heat treated to a hardness of 62 HRC. Based on Design of Experiments (DOE), a total of 20 tests are carried out. The range of each one of the three parameters is set at three different levels, viz, low, medium and high. The validity of the model is checked by Analysis of variance (ANOVA). Predicted models are derived from regression analysis. Comparison of experimental and predicted values of specific cutting force, power and surface roughness shows that good agreement has been achieved between them. Therefore, the developed model may be recommended to be used for predicting specific cutting force, power and surface roughness in hard turning of tool steel that is AISI H13 steel.

Keywords: hard turning, specific cutting force, power, surface roughness, AISI H13, mixed ceramic

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Authors: Gizachew Assefa Tessema, Mohammad Afzal Mahmood, Judith Streak Gomersall, Caroline O. Laurence

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Introduction: Improving access to quality family planning services is the key to improving health of women and children. However, there is currently little evidence on the quality and scope of family planning services provided by private facilities, and this compares to the services provided in public facilities in Ethiopia. This is important, particularly in determining whether the government should further expand the roles of the private sector in the delivery of family planning facility. Methods: This study used the 2014 Ethiopian Services Provision Assessment Plus (ESPA+) survey dataset for comparing the structural aspects of quality of care in family planning services. The present analysis used a weighted sample of 1093 primary health care facilities (955 public and 138 private). This study employed logistic regression analysis to compare key structural variables between public and private facilities. While taking the structural variables as an outcome for comparison, the facility type (public vs private) were used as the key exposure of interest. Results: When comparing availability of basic amenities (infrastructure), public facilities were less likely to have functional cell phones (AOR=0.12; 95% CI: 0.07-0.21), and water supply (AOR=0.29; 95% CI: 0.15-0.58) than private facilities. However, public facilities were more likely to have staff available 24 hours in the facility (AOR=0.12; 95% CI: 0.07-0.21), providers having family planning related training in the past 24 months (AOR=4.4; 95% CI: 2.51, 7.64) and possessing guidelines/protocols (AOR= 3.1 95% CI: 1.87, 5.24) than private facilities. Moreover, comparing the availability of equipment, public facilities had higher odds of having pelvic model for IUD demonstration (AOR=2.60; 95% CI: 1.35, 5.01) and penile model for condom demonstration (AOR=2.51; 95% CI: 1.32, 4.78) than private facilities. Conclusion: The present study suggests that Ethiopian government needs to provide emphasis towards the private sector in terms of providing family planning guidelines and training on family planning services for their staff. It is also worthwhile for the public health facilities to allocate funding for improving the availability of basic amenities. Implications for policy and/ or practice: This study calls policy makers to design appropriate strategies in providing opportunities for training a health care providers working in private health facility.

Keywords: quality of care, family planning, public-private, Ethiopia

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Authors: Muhammad Asim

Abstract:

Background: Less than half of women in South Asia (SA) use any modern contraceptive method which leads to a huge burden of unintended pregnancies, unsafe abortions, maternal deaths, and socioeconomic loss. Women empowerment plays a pivotal role in improving various health seeking behaviours, including contraceptive use. The objective of this study to explore the association between women's empowerment and modern contraceptive, among rich and poor segment of population in SA. Methods: We used the most recent, large-scale, demographic health survey data of five South Asian countries, namely Afghanistan, Pakistan, Bangladesh, India, and Nepal. The outcome variable was the current use of modern contraceptive methods. The main exposure variable was a combination (interaction) of socio-economic status (SES) and women’s level of empowerment (low, medium, and high), where SES was bifurcated into poor and rich; and women empowerment was divided into three categories: decision making, attitude to violence and social independence. Moreover, overall women empowerment indicator was also created by using three dimensions of women empowerment. We applied both descriptive statistics and multivariable logistic regression techniques for data analyses. Results: Most of the women possessed ‘medium’ level of empowerment across South Asian Countries. The lowest attitude to violence empowerment was found in Afghanistan, and the lowest social independence empowerment was observed in Bangladesh across SA. However, Pakistani women have the lowest decision-making empowerment in the region. The lowest modern contraceptive use (22.1%) was found in Afghanistan and the highest (53.2%) in Bangladesh. The multivariate results depict that the overall measure of women empowerment does not affect modern contraceptive use among poor and rich women in most of South Asian countries. However, the decision-making empowerment plays a significant role among both poor and rich women to use modern contraceptive methods across South Asian countries. Conclusions: The effect of women’s empowerment on modern contraceptive use is not consistent across countries, and among poor and rich segment of population. Of the three dimensions of women’s empowerment, the autonomy of decision making in household affairs emerged as a stronger determinant of mCPR as compared with social independence and attitude towards violence against women.

Keywords: women empowerment, modern contraceptive use, South Asia, women autonomy

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Authors: Zsanett Bahor, Cristina Nunes-Fonseca, Gillian L. Currie, Emily S. Sena, Lindsay D.G. Thomson, Malcolm R. Macleod

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Psychosis is ranked as the third most disabling medical condition in the world by the World Health Organization. Despite a substantial amount of research in recent years, available treatments are not universally effective and have a wide range of adverse side effects. Since many clinical drug candidates are identified through in vivo modelling, a deeper understanding of these models, and their strengths and limitations, might help us understand reasons for difficulties in psychosis drug development. To provide an unbiased summary of the preclinical psychosis literature we performed a systematic electronic search of PubMed for publications modelling a psychotic disorder in vivo, identifying 14,721 relevant studies. Double screening of 11,000 publications from this dataset so far established 2403 animal studies of psychosis, with the most common model being schizophrenia (95%). 61% of these models are induced using pharmacological agents. For all the models only 56% of publications test a therapeutic treatment. We propose a systematic review of these studies to assess the prevalence of reporting of measures to reduce risk of bias, and a meta-analysis to assess the internal and external validity of these animal models. Our findings are likely to be relevant to future preclinical studies of psychosis as this generation of strong empirical evidence has the potential to identify weaknesses, areas for improvement and make suggestions on refinement of experimental design. Such a detailed understanding of the data which inform what we think we know will help improve the current attrition rate between bench and bedside in psychosis research.

Keywords: animal models, psychosis, systematic review, schizophrenia

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Authors: Frederik Schulte, Stefan Voß

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The adverse effects of air pollution on public health are an increasingly vital problem in planning for urban regions in many parts of the world. The issue is addressed from various angles and by distinct disciplines in research. Epidemiological studies model the relative increase of numerous diseases in response to an increment of different forms of air pollution. A significant share of air pollution in urban regions is related to transport emissions that are often measured and stored in emission inventories. Though, most approaches in transport planning, engineering, and operational design of transport activities are restricted to general emission limits for specific air pollutants and do not consider more nuanced exposure models. We conduct an extensive literature review on exposure models and emission inventories used to study the health impact of transport emissions. Furthermore, we review methods applied in both domains and use emission inventory data of transportation hubs such as ports, airports, and urban traffic for an in-depth analysis of public health impacts deploying medical exposure models. The results reveal specific urban health risks related to transport emissions that may improve urban planning for environmental health by providing insights in actual health effects instead of only referring to general emission limits.

Keywords: emission inventories, exposure models, transport emissions, urban health

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Authors: Nadjib Dahdouh, Samira Amokrane, Elhadj Mekatel, Djamel Nibou

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The removal of Basic Yellow 28 (BY28) from aqueous solutions by plastic wastes PMMA was investigated. The characteristics of plastic wastes PMMA were determined by SEM, FTIR and chemical composition analysis. The effects of solution pH, initial Basic Yellow 28 (BY28) concentration C, solid/liquid ratio R, and temperature T were studied in batch experiments. The Freundlich and the Langmuir models have been applied to the adsorption process, and it was found that the equilibrium followed well Langmuir adsorption isotherm. A comparison of kinetic models applied to the adsorption of BY28 on the PMMA was evaluated for the pseudo-first-order and the pseudo-second-order kinetic models. It was found that used models were correlated with the experimental data. Intraparticle diffusion model was also used in these experiments. The thermodynamic parameters namely the enthalpy ∆H°, entropy ∆S° and free energy ∆G° of adsorption of BY28 on PMMA were determined. From the obtained results, the negative values of Gibbs free energy ∆G° indicated the spontaneity of the adsorption of BY28 by PMMA. The negative values of ∆H° revealed the exothermic nature of the process and the negative values of ∆S° suggest the stability of BY28 on the surface of SW PMMA.

Keywords: removal, Waste PMMA, BY28 dye, equilibrium, kinetic study, thermodynamic study

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Authors: Ni'mal Baroya, Andrei Ramani, Irma Prasetyowati

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The access to reproduction health services, including with safe and effective contraception were human rights regardless of social stratum and residence. In addition to individual factors, family and contextual factors were also believed to be the cause in the use of contraceptive methods. This study aimed to assess the determinants of long-term contraceptive methods (LTCM) by considering all the factors at either the individual level or contextual level. Thereby, this study could provide basic information for program development of prevalence enhancement of MKJP in East Java. The research, which used cross-sectional design, utilized Riskesdas 2013 data, particularly in East Java Province for further analysis about multilevel modeling of MKJP application. The sample of this study consisted of 20.601 married women who were not in pregnant that were drawn by using probability sampling following the sampling technique of Riskesdas 2013. Variables in this study were including the independent variables at the individual level that consisted of education, age, occupation, access to family planning services (KB), economic status and residence. As independent variables in district level were the Human Development Index (HDI, henceforth as IPM) in each districts of East Java Province, the ratio of field officers, the ratio of midwives, the ratio of community health centers and the ratio of doctors. As for the dependent variable was the use of Long-Term Contraceptive Method (LTCM or MKJP). The data were analyzed by using chi-square test and Pearson product moment correlation. The multivariable analysis was using multilevel logistic regression with 95% of Confidence Interval (CI) at the significance level of p < 0.05 and 80% of strength test. The results showed a low CPR LTCM was concentrated in districts in Madura Island and the north coast. The women which were 25 to 35 or more than 35 years old, at least high school education, working, and middle-class social status were more likely to use LTCM or MKJP. The IPM and low PLKB ratio had implications for poor CPR LTCM / MKJP.

Keywords: multilevel, long-term contraceptive methods, east java, contextual factor

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Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

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Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and time-consuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil, geotechnical engineering

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Authors: Lina Wu, Wenyi Lu, Ye Li

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Regarding heavy video game players for boys and super online chat lovers for girls as a symbolic phrase in the current adolescent culture, this project of data analysis verifies the displacement effect on deteriorating mathematics performance. To evaluate correlation or regression coefficients between a factor of playing video games or chatting online and mathematics performance compared with other factors, we use multivariate analysis technique and take gender difference into account. We find the most important reason for the negative sign of the displacement effect on mathematics performance due to students’ poor academic background. Statistical analysis methods in this project could be applied to study internet users’ academic performance from the high school education to the college education.

Keywords: correlation coefficients, displacement effect, multivariate analysis technique, regression coefficients

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Authors: T. Lazzarini, M. Imbiki, P. E. Sutter, G. Borragan

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While several strategies, such as the development of more efficient appliances, the financing of insulation programs or the rolling out of smart meters represent promising tools to reduce future energy consumption, their implementation relies on people’s decisions-actions. Likewise, engaging with consumers to reshape their behavior has shown to be another important way to reduce energy usage. For these reasons, integrating the human factor in the energy transition has become a major objective for researchers and policymakers. Digital education programs based on tangible and gamified user interfaces have become a new tool with potential effects to reduce energy consumption4. The B2020 program, developed by the firm “Économie d’Énergie SAS”, proposes a digital platform to encourage pro-environmental behavior change among employees and citizens. The platform integrates 160 eco-behaviors to help saving energy and water and reducing waste and CO2 emissions. A total of 13,146 citizens have used the tool so far to declare the range of eco-behaviors they adopt in their daily lives. The present work seeks to build on this database to identify the potential impact of adopted energy-saving behaviors (n=62) to reduce the use of energy in buildings. To this end, behaviors were classified into three categories regarding the nature of its implementation (Eco-habits: e.g., turning-off the light, Eco-actions: e.g., installing low carbon technology such as led light-bulbs and Home-Refurbishments: e.g., such as wall-insulation or double-glazed energy efficient windows). General Linear Models (GLM) disclosed the existence of a significantly higher frequency of Eco-habits when compared to the number of home-refurbishments realized by the platform users. While this might be explained in part by the high financial costs that are associated with home renovation works, it also contrasts with the up to three times larger energy-savings that can be accomplished by these means. Furthermore, multiple regression models failed to disclose the expected relationship between energy-savings and frequency of adopted eco behaviors, suggesting that energy-related practices are not necessarily driven by the correspondent energy-savings. Finally, our results also suggested that people adopting more Eco-habits and Eco-actions were more likely to engage in Home-Refurbishments. Altogether, these results fit well with a growing body of scientific research, showing that energy-related practices do not necessarily maximize utility, as postulated by traditional economic models, and suggest that other variables might be triggering them. Promoting home refurbishments could benefit from the adoption of complementary energy-saving habits and actions.

Keywords: energy-saving behavior, human performance, behavioral change, energy efficiency

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Authors: Corina E. Niculaescu, Ivan Sangiorgi, Adrian R. Bell

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The COVID-19 pandemic has been life-changing in many aspects of people’s daily and social lives, but has it also changed attitudes towards investments? This paper explores the effect of the COVID-19 pandemic on retail investors’ levels of investments in the U.S. during the first COVID-19 wave in summer 2020. This is an unprecedented health crisis, which could lead to changes in investment behavior, including irrational behavior in retail investors. As such, this study aims to inform policymakers of what happened to investment decisions during the COVID-19 pandemic so that they can protect retail investors during extreme events like a global health crisis. The study aims to answer two research questions. First, was the level of investments affected by the COVID-19 pandemic, and if so, why? Second, how were investments affected by retail investors’ personal experience with COVID-19? The research analysis is based on primary survey data collected on the Amazon Mechanical Turk platform from a representative sample of U.S. respondents. Responses were collected between the 15th of July and 28th of August 2020 from 1,148 U.S. retail investors who hold mutual fund investments and a savings account. The research explores whether being affected by COVID-19, change in the level of savings, and risk capacity can explain the change in the level of investments by using regression analysis. The dependent variable is changed in investments measured as decrease, no change, and increase. For this reason, the methodology used is ordered probit regression models. The results show that retail investors in the U.S. increased their investments during the first wave of COVID-19, which is unexpected as investors are usually more cautious in crisis times. Moreover, the study finds that those who were affected personally by COVID-19 (e.g., tested positive) were more likely to increase their investments, which is irrational behavior and contradicts expectations. An increase in the level of savings and risk capacity was also associated with increased investments. Overall, the findings show that having personal experience with a health crisis can have an impact on one’s investment decisions as well. Those findings are important for both retail investors and policymakers, especially now that online trading platforms have made trading easily accessible to everyone. There are risks and potential irrational behaviors associated with investment decisions during times of crisis, and it is important that retail investors are aware of them before making financial decisions.

Keywords: COVID-19, financial decision-making, health crisis retail investors, survey

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Authors: Beulah Rani Inbanathan

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In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

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Authors: Hamid Ahmadi, Neda Azari-Dodaran

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A total of 270 nonlinear steady-state finite element (FE) analyses were performed on 54 FE models of two-planar circular hollow section (CHS) KK-joints subjected to axial loading at five different temperatures (20 ºC, 200 ºC, 400 ºC, 550 ºC, and 700 ºC). The primary goal was to investigate the effects of temperature and geometrical characteristics on the ultimate strength, modes of failure, and initial stiffness of the KK-joints. Results indicated that on an average basis, the ultimate load of a two-planar tubular KK-joint at 200 ºC, 400 ºC, 550 ºC, and 700 ºC is 90%, 75%, 45%, and 16% of the joint’s ultimate load at ambient temperature, respectively. Outcomes of the parametric study showed that replacing the yield stress at ambient temperature with the corresponding value at elevated temperature to apply the EN 1993-1-8 equations for the calculation of the joint’s ultimate load at elevated temperatures may lead to highly unconservative results that might endanger the safety of the structure. Results of the parametric study were then used to develop a set of design formulas, through nonlinear regression analyses, to calculate the ultimate load of two-planar tubular KK-joints subjected to axial loading at elevated temperatures.

Keywords: ultimate load, two-planar tubular KK-joint, axial loading, elevated temperature, parametric equation

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Authors: Catherine Maware, Olufemi Adetunji

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The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: impact measurement model, lean bundles, lean manufacturing, organizational performance

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Authors: Panudet Saengseedam, Nanthachai Kantanantha

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This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, linear mixed model, multivariate conditional autoregressive model, spatial time series

Procedia PDF Downloads 395