Search results for: partial least squares regression
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4478

Search results for: partial least squares regression

3278 A Hyperexponential Approximation to Finite-Time and Infinite-Time Ruin Probabilities of Compound Poisson Processes

Authors: Amir T. Payandeh Najafabadi

Abstract:

This article considers the problem of evaluating infinite-time (or finite-time) ruin probability under a given compound Poisson surplus process by approximating the claim size distribution by a finite mixture exponential, say Hyperexponential, distribution. It restates the infinite-time (or finite-time) ruin probability as a solvable ordinary differential equation (or a partial differential equation). Application of our findings has been given through a simulation study.

Keywords: ruin probability, compound poisson processes, mixture exponential (hyperexponential) distribution, heavy-tailed distributions

Procedia PDF Downloads 327
3277 Interactions between Residential Mobility, Car Ownership and Commute Mode: The Case for Melbourne

Authors: Solmaz Jahed Shiran, John Hearne, Tayebeh Saghapour

Abstract:

Daily travel behavior is strongly influenced by the location of the places of residence, education, and employment. Hence a change in those locations due to a move or changes in an occupation leads to a change in travel behavior. Given the interventions of housing mobility and travel behaviors, the hypothesis is that a mobile housing market allows households to move as a result of any change in their life course, allowing them to be closer to central services, public transport facilities and workplace and hence reducing the time spent by individuals on daily travel. Conversely, household’s immobility may lead to longer commutes of residents, for example, after a change of a job or a need for new services such as schools for children who have reached their school age. This paper aims to investigate the association between residential mobility and travel behavior. The Victorian Integrated Survey of Travel and Activity (VISTA) data is used for the empirical analysis. Car ownership and journey to work time and distance of employed people are used as indicators of travel behavior. Change of usual residence within the last five years used to identify movers and non-movers. Statistical analysis, including regression models, is used to compare the travel behavior of movers and non-movers. The results show travel time, and the distance does not differ for movers and non-movers. However, this is not the case when taking into account the residence tenure-type. In addition, car ownership rate and number found to be significantly higher for non-movers. It is hoped that the results from this study will contribute to a better understanding of factors other than common socioeconomic and built environment features influencing travel behavior.

Keywords: journey to work, regression models, residential mobility, commute mode, car ownership

Procedia PDF Downloads 116
3276 Interest Charges and Sustainability Challenges: The Case of OECD Countries

Authors: Aime Philombe Zapji Ymele

Abstract:

Servicing public debt is a significant budgetary burden. In the sense that the payment of interest charges is a liability on the balance sheet of the public budget and affects fiscal policy. Interest charges can sometimes become a burden if they crowd out private activities. In order to analyse and understand the determinants of the debt burden and its impact on the sustainability of public finances, the present work focuses on OECD countries. It is noted from the literature that the factors that determine interest charges are macroeconomic (inflation, GDP growth, and interest rates) and public finances (primary balance and public debt). After analysing a panel of 33 OECD countries and using ordinary least squares (OLS), we find that public debt, inflation, and long-term interest rates are positively correlated with interest charges. An increase in any of these variables leads to an increase in debt charges. On the other hand, a growth in GDP is negatively associated with interest charges. Indeed, an increase in GDP generates enough revenue to meet the repayment of debt charges. According to the empirical analysis, we can say that, despite the large and growing debt-to-GDP ratio of major OECD countries, interest charges are not a threat to the sustainability of public finances. However, it is important for these countries to reduce the ratio of public debt to GDP because, in the face of the many challenges (health, aging population, etc.) that are looming on the horizon, an increase in interest rates could bring with it considerable burdens that would threaten the budgetary balance of these states.

Keywords: interest charges, sustainability, public debt, interest rates

Procedia PDF Downloads 107
3275 Admission C-Reactive Protein Serum Levels and In-Hospital Mortality in the Elderly Admitted to the Acute Geriatrics Department

Authors: Anjelika Kremer, Irina Nachimov, Dan Justo

Abstract:

Background: C-reactive protein (CRP) serum levels are commonly measured in hospitalized patients. Elevated admission CRP serum levels and in-hospital mortality has been seldom studied in the general population of elderly patients admitted to the acute Geriatrics department. Methods: A retrospective cross-sectional study was conducted at a tertiary medical center. Included were all elderly patients (age 65 years or more) admitted to a single acute Geriatrics department from the emergency room between April 2014 and January 2015. CRP serum levels were measured routinely in all patients upon the first 24 hours of admission. A logistic regression analysis was used to study if admission CRP serum levels were associated with in-hospital mortality independent of age, gender, functional status, and co-morbidities. Results: Overall, 498 elderly patients were included in the analysis: 306 (61.4%) female patients and 192 (38.6%) male patients. The mean age was 84.8±7.0 years (median: 85 years; IQR: 80-90 years). The mean admission CRP serum levels was 43.2±67.1 mg/l (median: 13.1 mg/l; IQR: 2.8-51.7 mg/l). Overall, 33 (6.6%) elderly patients died during the hospitalization. A logistic regression analysis showed that in-hospital mortality was independently associated with history of stroke (p < 0.0001), heart failure (p < 0.0001), and admission CRP serum levels (p < 0.0001) – and to a lesser extent with age (p = 0.042), collagen vascular disease (p=0.011), and recent venous thromboembolism (p=0.037). Receiver operating characteristic (ROC) curve showed that admission CRP serum levels predict in-hospital mortality fairly with an area under the curve (AUC) of 0.694 (p < 0.0001). Cut-off value with maximal sensitivity and specificity was 19.7 mg/L. Conclusions: Admission CRP serum levels may be used to predict in-hospital mortality in the general population of elderly patients admitted to the acute Geriatrics department.

Keywords: c-reactive protein, elderly, mortality, prediction

Procedia PDF Downloads 224
3274 Digitalization and High Audit Fees: An Empirical Study Applied to US Firms

Authors: Arpine Maghakyan

Abstract:

The purpose of this paper is to study the relationship between the level of industry digitalization and audit fees, especially, the relationship between Big 4 auditor fees and industry digitalization level. On the one hand, automation of business processes decreases internal control weakness and manual mistakes; increases work effectiveness and integrations. On the other hand, it may cause serious misstatements, high business risks or even bankruptcy, typically in early stages of automation. Incomplete automation can bring high audit risk especially if the auditor does not fully understand client’s business automation model. Higher audit risk consequently will cause higher audit fees. Higher audit fees for clients with high automation level are more highlighted in Big 4 auditor’s behavior. Using data of US firms from 2005-2015, we found that industry level digitalization is an interaction for the auditor quality on audit fees. Moreover, the choice of Big4 or non-Big4 is correlated with client’s industry digitalization level. Big4 client, which has higher digitalization level, pays more than one with low digitalization level. In addition, a high-digitalized firm that has Big 4 auditor pays higher audit fee than non-Big 4 client. We use audit fees and firm-specific variables from Audit Analytics and Compustat databases. We analyze collected data by using fixed effects regression methods and Wald tests for sensitivity check. We use fixed effects regression models for firms for determination of the connections between technology use in business and audit fees. We control for firm size, complexity, inherent risk, profitability and auditor quality. We chose fixed effects model as it makes possible to control for variables that have not or cannot be measured.

Keywords: audit fees, auditor quality, digitalization, Big4

Procedia PDF Downloads 284
3273 Interest Charges and Sustainability Challenges: The Case of OECD Countries

Authors: Zapji Ymele Aime Philombe

Abstract:

Servicing public debt is a significant budgetary burden in the sense that the payment of interest charges is a liability on the balance sheet of the public budget and affects fiscal policy. Interest charges can sometimes become a burden if they crowd out private activities. In order to analyse and understand the determinants of the debt burden and its impact on the sustainability of public finances, the present work focuses on OECD countries. It is noted from the literature that the factors that determine interest charges are macroeconomic (inflation, GDP growth and interest rates) and public finances (primary balance and public debt). After analysing a panel of 33 OECD countries and using ordinary least squares (OLS), we find that public debt, inflation and long-term interest rates are positively correlated with interest charges. An increase in any of these variables leads to an increase in debt charges. On the other hand, a growth in GDP is negatively associated with interest charges. Indeed, an increase in GDP generates enough revenue to meet the repayment of debt charges. According to the empirical analysis, we can say that, despite the large and growing debt-to-GDP ratio of major OECD countries, interest charges are not a threat to the sustainability of public finances. However, it is important for these countries to reduce the ratio of public debt to GDP because, in the face of the many challenges (health, aging population, etc.) that are looming on the horizon, an increase in interest rates could bring with it considerable burdens that would threaten the budgetary balance of these states.

Keywords: interests charges, public debt, sustainability, interest rates

Procedia PDF Downloads 105
3272 Simulation of I–V Characteristics of Lateral PIN Diode on Polysilicon Films

Authors: Abdelaziz Rabhi, Mohamed Amrani, Abderrazek Ziane, Nabil Belkadi, Abdelraouf Hocini

Abstract:

In this paper, a bedimensional simulation program of the electric characteristics of reverse biased lateral polysilicon PIN diode is presented. In this case we have numerically solved the system of partial differential equations formed by Poisson's equation and both continuity equations that take into account the effect of impact ionization. Therefore we will obtain the current-voltage characteristics (I-V) of the reverse-biased structure which may include the effect of breakdown.The geometrical model assumes that the polysilicon layer is composed by a succession of defined mean grain size crystallites, separated by lateral grain boundaries which are parallel to the metallurgic junction.

Keywords: breakdown, polycrystalline silicon, PIN, grain, impact ionization

Procedia PDF Downloads 359
3271 Replicating Brain’s Resting State Functional Connectivity Network Using a Multi-Factor Hub-Based Model

Authors: B. L. Ho, L. Shi, D. F. Wang, V. C. T. Mok

Abstract:

The brain’s functional connectivity while temporally non-stationary does express consistency at a macro spatial level. The study of stable resting state connectivity patterns hence provides opportunities for identification of diseases if such stability is severely perturbed. A mathematical model replicating the brain’s spatial connections will be useful for understanding brain’s representative geometry and complements the empirical model where it falls short. Empirical computations tend to involve large matrices and become infeasible with fine parcellation. However, the proposed analytical model has no such computational problems. To improve replicability, 92 subject data are obtained from two open sources. The proposed methodology, inspired by financial theory, uses multivariate regression to find relationships of every cortical region of interest (ROI) with some pre-identified hubs. These hubs acted as representatives for the entire cortical surface. A variance-covariance framework of all ROIs is then built based on these relationships to link up all the ROIs. The result is a high level of match between model and empirical correlations in the range of 0.59 to 0.66 after adjusting for sample size; an increase of almost forty percent. More significantly, the model framework provides an intuitive way to delineate between systemic drivers and idiosyncratic noise while reducing dimensions by more than 30 folds, hence, providing a way to conduct attribution analysis. Due to its analytical nature and simple structure, the model is useful as a standalone toolkit for network dependency analysis or as a module for other mathematical models.

Keywords: functional magnetic resonance imaging, multivariate regression, network hubs, resting state functional connectivity

Procedia PDF Downloads 137
3270 Effect of Micro Credit Access on Poverty Reduction among Small Scale Women Entrepreneurs in Ondo State, Nigeria

Authors: Adewale Oladapo, C. A. Afolami

Abstract:

The study analyzed the effect of micro credit access on poverty reduction among small scale women entrepreneurs in Ondo state, Nigeria. Primary data were collected in a cross-sectional survey of 100 randomly selected woman entrepreneurs. These were drawn in multistage sampling process covering four local government areas (LGAS). Data collected include socio economics characteristics of respondents, access to micro credit, sources of micro credit, and constraints faced by the entrepreneur in sourcing for micro credit. Data were analyzed using descriptive statistics, Foster, Greer and Thorbecke (FGT) index of poverty measure, Gini coefficients and probit regression analysis. The study found that respondents sampled for the survey were within the age range of 31-40 years with mean age 38.6%. Mostly (56.0%) of the respondents were educated to the tune of primary school. Majority (87.0%) of the respondents were married with fairly large household size of (4-5). The poverty index analysis revealed that most (67%) of the sample respondents were poor. The result of the Probit regression analyzed showed that income was a significant variable in micro credit access, while the result of the Gini coefficient revealed a very high income inequality among the respondents. The study concluded that most of the respondents were poor and return on investment (income) was an important variable that increased the chance of respondents in sourcing for micro-credit loan and recommended that income realized by entrepreneur should be properly documented to facilitate loan accessibility.

Keywords: entrepreneurs, income, micro-credit, poverty

Procedia PDF Downloads 114
3269 Factors Influencing Family Resilience and Quality of Life in Pediatric Cancer Patients and Their Caregivers: A Cluster Analysis

Authors: Li Wang, Dan Shu, Shiguang Pang, Lixiu Wang, Bing Xiang Yang, Qian Liu

Abstract:

Background: Cancer is one of the most severe diseases in childhood; long-term treatment and its side effects significantly impact the patient's physical, psychological, social functioning and quality of life while also placing substantial physical and psychological burdens on caregivers and families. Family resilience is crucial for children with cancer, helping them cope better with the disease and supporting the family in facing challenges together. As a family-level variable, family resilience requires information from multiple family members. However, to our best knowledge, there is currently no research investigating family resilience from both the perspectives of pediatric cancer patients and their caregivers. Therefore, this study aims to investigate the family resilience and quality of life of pediatric cancer patients from a patient–caregiver dyadic perspective. Methods: A total of 149 dyads of patients diagnosed with pediatric cancer patients and their principal caregivers were recruited from oncology departments of 4 tertiary hospitals in Wuhan and Taiyuan, China. All participants completed questionnaires that identified their demographic and clinical characteristics as well as assessed their family resilience and quality of life for both the patients and their caregivers. K-means cluster analysis was used to identify different clusters of family resilience based on the reports from patients and caregivers. Multivariate logistic regression and linear regression are used to analyze the factors influencing family resilience and quality of life, as well as the relationship between the two. Results: Three clusters of family resilience were identified: a cluster of high family resilience (HR), a cluster of low family resilience (LR), and a cluster of discrepant family resilience (DR). Most (67.1%) families fell into the cluster with low resilience. Characteristics such as the types of caregivers perceived social support of the patient were different among the three clusters. Compared to the LR group, families where the mother is the caregiver and where the patient has high social support are more likely to be assigned to the HR. The quality of life for caregivers was consistently highest in the HR cluster and lowest in the LR cluster. The patient's quality of life is not related to family resilience. In the linear regression analysis of the patient's quality of life, patients who are the first-born have higher quality of life, while those living with their parents have lower quality of life. The participants' characteristics were not associated with the quality of life for caregivers. Conclusions: In most families, family resilience was low. Families with maternal caregivers and patients receiving high levels of social support are more inclined to be higher levels of family resilience. Family resilience was linked to the quality of life of caregivers of pediatric cancer patients. The clinical implications of this findings suggest that healthcare and social support organizations should prioritize and support the participation of mothers in caregiving responsibilities. Furthermore, they should assist families in accessing social support to enhance family resilience. This study also emphasizes the importance of promoting family resilience for enhancing family health and happiness, as well as improving the quality of life for caregivers.

Keywords: pediatric cancer, cluster analysis, family resilience, quality of life

Procedia PDF Downloads 18
3268 Evaluation of Short-Term Load Forecasting Techniques Applied for Smart Micro-Grids

Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

Abstract:

Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, gain

Procedia PDF Downloads 450
3267 Dual Solutions in Mixed Convection Boundary Layer Flow: A Stability Analysis

Authors: Anuar Ishak

Abstract:

The mixed convection stagnation point flow toward a vertical plate is investigated. The external flow impinges normal to the heated plate and the surface temperature is assumed to vary linearly with the distance from the stagnation point. The governing partial differential equations are transformed into a set of ordinary differential equations, which are then solved numerically using MATLAB routine boundary value problem solver bvp4c. Numerical results show that dual solutions are possible for a certain range of the mixed convection parameter. A stability analysis is performed to determine which solution is linearly stable and physically realizable.

Keywords: dual solutions, heat transfer, mixed convection, stability analysis

Procedia PDF Downloads 375
3266 Association Between Advanced Parental Age and Implantation Failure: A Prospective Cohort Study in Anhui, China

Authors: Jiaqian Yin, Ruoling Chen, David Churchill, Huijuan Zou, Peipei Guo, Chunmei Liang, Xiaoqing Peng, Zhikang Zhang, Weiju Zhou, Yunxia Cao

Abstract:

Purpose: This study aimed to explore the interaction of male and female age on implantation failure from in vitro fertilisation (IVF)/ intracytoplasmic sperm injection (ICSI) treatments in couples following their first cycles using the Anhui Maternal-Child Health Study (AMCHS). Methods: The AMCHS recruited 2042 infertile couples who were physically fit for in vitro fertilisation (IVF) or intracytoplasmic sperm injection (ICSI) treatment at the Reproductive Centre of the First Affiliated Hospital of Anhui Medical University between May 2017 to April 2021. This prospective cohort study analysed the data from 1910 cohort couples for the current paper data analysis. The multivariate logistic regression model was used to identify the effect of male and female age on implantation failure after controlling for confounding factors. Male age and female age were examined as continuous and categorical (male age: 20-<25, 25-<30, 30-<35, 35-<40, ≥40; female age: 20-<25, 25-<30, 30-<35, 35-<40, ≥40) predictors. Results: Logistic regression indicated that advanced maternal age was associated with increased implantation failure (P<0.001). There was evidence of an interaction between maternal age (30-<35 and ≥ 35) and paternal age (≥35) on implantation failure. (p<0.05). Only when the male was ≥35 years of increased maternal age was associated with the risk of implantation failure. Conclusion: In conclusion, there was an additive effect on implantation failure with advanced parental age. The impact of advanced maternal age was only seen in the older paternal age group. The delay of childbearing in both men and women will be a serious public issue that may contribute to a higher risk of implantation failure in patients needing assisted reproductive technology (ART).

Keywords: parental age, infertility, cohort study, IVF

Procedia PDF Downloads 133
3265 Role of Imaging in Predicting the Receptor Positivity Status in Lung Adenocarcinoma: A Chapter in Radiogenomics

Authors: Sonal Sethi, Mukesh Yadav, Abhimanyu Gupta

Abstract:

The upcoming field of radiogenomics has the potential to upgrade the role of imaging in lung cancer management by noninvasive characterization of tumor histology and genetic microenvironment. Receptor positivity like epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) genotyping are critical in lung adenocarcinoma for treatment. As conventional identification of receptor positivity is an invasive procedure, we analyzed the features on non-invasive computed tomography (CT), which predicts the receptor positivity in lung adenocarcinoma. Retrospectively, we did a comprehensive study from 77 proven lung adenocarcinoma patients with CT images, EGFR and ALK receptor genotyping, and clinical information. Total 22/77 patients were receptor-positive (15 had only EGFR mutation, 6 had ALK mutation, and 1 had both EGFR and ALK mutation). Various morphological characteristics and metastatic distribution on CT were analyzed along with the clinical information. Univariate and multivariable logistic regression analyses were used. On multivariable logistic regression analysis, we found spiculated margin, lymphangitic spread, air bronchogram, pleural effusion, and distant metastasis had a significant predictive value for receptor mutation status. On univariate analysis, air bronchogram and pleural effusion had significant individual predictive value. Conclusions: Receptor positive lung cancer has characteristic imaging features compared with nonreceptor positive lung adenocarcinoma. Since CT is routinely used in lung cancer diagnosis, we can predict the receptor positivity by a noninvasive technique and would follow a more aggressive algorithm for evaluation of distant metastases as well as for the treatment.

Keywords: lung cancer, multidisciplinary cancer care, oncologic imaging, radiobiology

Procedia PDF Downloads 109
3264 Driving Forces of Bank Liquidity: Evidence from Selected Ethiopian Private Commercial Banks

Authors: Tadele Tesfay Teame, Tsegaye Abrehame, Hágen István Zsombor

Abstract:

Liquidity is one of the main concerns for banks, and thus achieving the optimum level of liquidity is critical. The main objective of this study is to discover the driving force of selected private commercial banks’ liquidity. In order to achieve the objective explanatory research design and quantitative research approach were used. Data has been collected from a secondary source of the sampled Ethiopian private commercial banks’ financial statements, the National Bank of Ethiopia, and the Minister of Finance, the sample covering the period from 2011 to 2022. Bank-specific and macroeconomic variables were analyzed by using the balanced panel fixed effect regression model. Bank’s liquidity ratio is measured by the total liquid asset to total deposits. The findings of the study revealed that bank size, capital adequacy, loan growth rate, and non-performing loan had a statistically significant impact on private commercial banks’ liquidity, and annual inflation rate and interest rate margin had a statistically significant impact on the liquidity of Ethiopian private commercial banks measured by L1 (bank liquidity). Thus, banks in Ethiopia should not only be concerned about internal structures and policies/procedures, but they must consider both the internal environment and the macroeconomic environment together in developing their strategies to efficiently manage their liquidity position and private commercial banks to maintain their financial proficiency shall have bank liquidity management policy by assimilating both bank-specific and macro-economic variables.

Keywords: liquidity, Ethiopian private commercial banks, liquidity ratio, panel data regression analysis

Procedia PDF Downloads 76
3263 Survival Analysis of Identifying the Risk Factors of Affecting the First Recurrence Time of Breast Cancer: The Case of Tigray, Ethiopia

Authors: Segen Asayehegn

Abstract:

Introduction: In Tigray, Ethiopia, next to cervical cancer, breast cancer is one of the most common cancer health problems for women. Objectives: This article is proposed to identify the prospective and potential risk factors affecting the time-to-first-recurrence of breast cancer patients in Tigray, Ethiopia. Methods: The data were taken from the patient’s medical record that registered from January 2010 to January 2020. The study considered a sample size of 1842 breast cancer patients. Powerful non-parametric and parametric shared frailty survival regression models (FSRM) were applied, and model comparisons were performed. Results: Out of 1842 breast cancer patients, about 1290 (70.02%) recovered/cured the disease. The median cure time from breast cancer is found at 12.8 months. The model comparison suggested that the lognormal parametric shared a frailty survival regression model predicted that treatment, stage of breast cancer, smoking habit, and marital status significantly affects the first recurrence of breast cancer. Conclusion: Factors like treatment, stages of cancer, and marital status were improved while smoking habits worsened the time to cure breast cancer. Recommendation: Thus, the authors recommend reducing breast cancer health problems, the regional health sector facilities need to be improved. More importantly, concerned bodies and medical doctors should emphasize the identified factors during treatment. Furthermore, general awareness programs should be given to the community on the identified factors.

Keywords: acceleration factor, breast cancer, Ethiopia, shared frailty survival models, Tigray

Procedia PDF Downloads 121
3262 Supplementation of Mannan Oligosaccharides in Guinea Pigs: Mortality and Growth Performance

Authors: C. Minguez, J. Bueso-Rodenas, C. Ibanez, A. Calvo

Abstract:

Mannan oligosaccharides (MOS) is one of the prebiotic most used in livestock nutrition. In this research, the effect of MOS dietary supplementation on growth performance and mortality in meat guinea pigs were studied. Three different experimental groups were compared: Control group (no additives); MOS 1 (1.5 g kg−1); MOS 2 (2 g kg−1). Guinea pigs were housed in 15 collective cages (n = 50 animals in each trial; 10 animals per cage). The young guinea pigs were weaning at day 28 and individually identified by a little ear tag. The fattening period was 49 days. Guinea pigs in both groups were fed ad libitum, with a standard commercial pellet diet (10 MJ of digestible energy/kg, 17% crude protein, 11% crude fiber, and 4.5% crude fat) and alfalfa (Medicago sativa) as forage. Growth traits, including body weight (BW), average daily gain (ADG), feed intake (FI), and feed conversion ratio (FCR), were measured weekly. On day 74, the animals were slaughtered. Contrasts between groups were obtained by calculated generalized least squares values. Mortality were evaluated by Fisher's exact test. Between MOS groups no significant differences were observed for growth traits and mortality. However, significant differences against the control group were observed for traits studied (pvalue < 0.05). In conclusion, the use of MOS could be a good prebiotic supplement to raise guinea pigs because it MOS has shown positive effects in growth traits and immune response in animals.

Keywords: guinea pig, growth, mannan oligosaccharides, mortality

Procedia PDF Downloads 120
3261 The Impact of Socio-Economic and Type of Religion on the Behavior of Obedience among Arab-Israeli Teenagers

Authors: Sadhana Ghnayem

Abstract:

This article examines the relationship between several socio-economic and background variables of Arab-Israeli families and their effect on the conflict management style of forcing, where teenage children are expected to obey their parents without questioning. The article explores the inter-generational gap and the desire of Arab-Israeli parents to force their teenage children to obey without questioning. The independent variables include: the sex of the parent, religion (Christian or Muslim), income of the parent, years of education of the parent, and the sex of the teenage child. We use the dependent variable of “Obedience Without Questioning” that is reported twice: by each of the parents as well as by the children. We circulated a questionnaire and collected data from a sample of 180 parents and their adolescent child living in the Galilee area during 2018. In this questionnaire we asked each of the parent and his/her teenage child about whether the latter is expected to follow the instructions of the former without questioning. The outcome of this article indicates, first, that Christian-Arab families are less authoritarian than Muslims families in demanding sheer obedience from their children. Second, female parents indicate more than male parents that their teenage child indeed obeys without questioning. Third, there is a negative correlation between the variable “Income” and “Obedience without Questioning.” Yet, the regression coefficient of this variable is close zero. Fourth, there is a positive correlation between years of education and obedience reported by the children. In other words, more educated parents are more likely to demand obedience from their children.  Finally, after running the regression, the study also found that the impact of the variables of religion as well as the sex of the child on the dependent variable of obedience is also significant at above 95 and 90%, respectively.

Keywords: conflict, religion, conflict management style, obedience

Procedia PDF Downloads 158
3260 Intelligent Indoor Localization Using WLAN Fingerprinting

Authors: Gideon C. Joseph

Abstract:

The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

Procedia PDF Downloads 327
3259 Integrative-Cyclical Approach to the Study of Quality Control of Resource Saving by the Use of Innovation Factors

Authors: Anatoliy A. Alabugin, Nikolay K. Topuzov, Sergei V. Aliukov

Abstract:

It is well known, that while we do a quantitative evaluation of the quality control of some economic processes (in particular, resource saving) with help innovation factors, there are three groups of problems: high uncertainty of indicators of the quality management, their considerable ambiguity, and high costs to provide a large-scale research. These problems are defined by the use of contradictory objectives of enhancing of the quality control in accordance with innovation factors and preservation of economic stability of the enterprise. The most acutely, such factors are felt in the countries lagging behind developed economies of the world according to criteria of innovativeness and effectiveness of management of the resource saving. In our opinion, the following two methods for reconciling of the above-mentioned objectives and reducing of conflictness of the problems are to solve this task most effectively: 1) the use of paradigms and concepts of evolutionary improvement of quality of resource-saving management in the cycle "from the project of an innovative product (technology) - to its commercialization and update parameters of customer value"; 2) the application of the so-called integrative-cyclical approach which consistent with complexity and type of the concept, to studies allowing to get quantitative assessment of the stages of achieving of the consistency of these objectives (from baseline of imbalance, their compromise to achievement of positive synergies). For implementation, the following mathematical tools are included in the integrative-cyclical approach: index-factor analysis (to identify the most relevant factors); regression analysis of relationship between the quality control and the factors; the use of results of the analysis in the model of fuzzy sets (to adjust the feature space); method of non-parametric statistics (for a decision on the completion or repetition of the cycle in the approach in depending on the focus and the closeness of the connection of indicator ranks of disbalance of purposes). The repetition is performed after partial substitution of technical and technological factors ("hard") by management factors ("soft") in accordance with our proposed methodology. Testing of the proposed approach has shown that in comparison with the world practice there are opportunities to improve the quality of resource-saving management using innovation factors. We believe that the implementation of this promising research, to provide consistent management decisions for reducing the severity of the above-mentioned contradictions and increasing the validity of the choice of resource-development strategies in terms of parameters of quality management and sustainability of enterprise, is perspective. Our existing experience in the field of quality resource-saving management and the achieved level of scientific competence of the authors allow us to hope that the use of the integrative-cyclical approach to the study and evaluation of the resulting and factor indicators will help raise the level of resource-saving characteristics up to the value existing in the developed economies of post-industrial type.

Keywords: integrative-cyclical approach, quality control, evaluation, innovation factors. economic sustainability, innovation cycle of management, disbalance of goals of development

Procedia PDF Downloads 230
3258 Extent of Derivative Usage, Firm Value and Risk: An Empirical Study on Pakistan Non-Financial Firms

Authors: Atia Alam

Abstract:

Growing liberalisation and intense market competition increase firm’s risk exposure and induce corporations to use derivatives extensively as a risk management instrument, which results in decrease in firm’s risk, and increase in value. Present study contributes towards existing literature by providing an in-depth analysis regarding the effect of extent of derivative usage on firm’s risk and value by using panel data models and seemingly unrelated regression technique. New evidence is established in current literature by dividing the sample data based on firm’s Exchange Rate (ER) and Interest Rate (IR) exposure. Analysis is performed for the effect of extent of derivative usage on firm’s risk and value and its variation with respect to the ER and IR exposure. Sample data consists of 166 Pakistani firms listed on Pakistan stock exchange for the period of 2004-2010. Results show that extensive usage of derivative instruments significantly increases firm value and reduces firm’s risk. Furthermore, comprehensive analysis depicts that Pakistani corporations having higher exchange rate exposure, with respect to foreign sales, and higher interest rate exposure, on the basis of industry adjusted leverage, have higher firm value and lower risk. Findings from seemingly unrelated regression also provide robustness to results obtained through panel data analysis. Study also highlights the role of derivative usage as a risk management instrument in high and low ER and IR risk and helps practitioners in understanding how value increasing effect of extent of derivative usage varies with the intensity of firm’s risk exposure.

Keywords: extent of derivative usage, firm value, risk, Pakistan, non-financial firms

Procedia PDF Downloads 339
3257 Receptiveness of Market Segmentation Towards Online Shopping Attitude: A Quality Management Strategy for Online Passenger Car Market

Authors: Noor Hasmini Abdghani, Nik Kamariah Nikmat, Nor Hayati Ahmad

Abstract:

Rapid growth of the internet technology led to changes in the consumer lifestyles. This involved customer buying behaviour-based internet that create new kind of buying strategy. Hence, it has summoned many of world firms including Malaysia to generate new quality strategy in preparation to face new customer buying lifestyles. Particularly, this study focused on identifying online customer segment of automobile passenger car customers. Secondly, the objective is to understand online customer’s receptiveness towards internet technologies. This study distributed 700 questionnaires whereby 582 were returned representing 83% response rate. The data were analysed using factor and regression analyses. The result from the factor analysis precipitates four online passenger car segmentations in Malaysia, which are: Segment (1)- Automobile Online shopping Preferences, Segment (2)- Automobile Online Brand Comparison, Segment (3)- Automobile Online Information Seeking and Segment (4)- Automobile Offline Shopping Preferences. In understanding the online customer’s receptiveness towards internet, the regression result shows that there is significant relationship between each of four segments of online passenger car customer with attitude towards automobile online shopping. This implies that, for online customers to have receptiveness toward internet technologies, he or she must have preferences toward online shopping or at least prefer to browse any related information online even if the actual purchase is made at the traditional store. With this proposed segmentation strategy, the firms especially the automobile firms will be able to understand their online customer behavior. At least, the proposed segmentation strategy will help the firms to strategize quality management approach for their online customers’ buying decision making.

Keywords: Automobile, Market Segmentation, Online Shopping Attitude, Quality Management Strategy

Procedia PDF Downloads 528
3256 Hypergeometric Solutions to Linear Nonhomogeneous Fractional Equations with Spherical Bessel Functions of the First Kind

Authors: Pablo Martin, Jorge Olivares, Fernando Maass

Abstract:

The use of fractional derivatives to different problems in Engineering and Physics has been increasing in the last decade. For this reason, we have here considered partial derivatives when the integral is a spherical Bessel function of the first kind in both regular and modified ones simple initial conditions have been also considered. In this way, the solution has been found as a combination of hypergeometric functions. The case of a general rational value for α of the fractional derivative α has been solved in a general way for alpha between zero and two. The modified spherical Bessel functions of the first kind have been also considered and how to go from the regular case to the modified one will be also shown.

Keywords: caputo fractional derivatives, hypergeometric functions, linear differential equations, spherical Bessel functions

Procedia PDF Downloads 308
3255 Effective Factors on Farmers' Attitude toward Multifunctional Agriculture

Authors: Mohammad Sadegh Allahyari, Sorush Marzban

Abstract:

The main aim of this study was to investigate the factors affecting farmers' attitude of the Shanderman District in Masal (Guilan Province in the north of Iran), towards the concepts of multifunctional agriculture. The statistical population consisted of all 4908 in Shanderman.The sample of the present study consisted of 209 subjects who were selected from the total population using the Bartlett et al. Table. Questionnaire as the main tool of data collection was divided in two parts. The first part of questionnaire consisted of farmers' profiles regarding individual, technical-agronomic, economic and social characteristics. The second part included items to identify the farmers’ attitudes regarding different aspects of multifunctional agriculture. The validity of the questionnaire was assessed by professors and experts. Cronbach's alpha was used to determine the reliability (α= 0.844), which is considered an acceptable reliability value. Overall, the average scores of attitudes towards multifunctional agriculture show a positive tendency towards multifunctional agriculture, considering farmers' attitudes of the Shanderman district (SD = 0.53, M = 3.81). Results also highlight a significant difference between farmers' income source levels (F = 0.049) and agricultural literature review (F = 0.022) toward farmers' attitudes considering multifunctional agriculture (p < 0.05). Pearson correlations also indicated that there is a positive relationship between positive attitudes and family size (r = 0.154), farmers' experience (r = 0.246), size of land under cultivation (r = 0.186), income (r = 0.227), and social contribution activities (r = 0.224). The results of multiple regression analyses showed that the variation in the dependent variable depended on the farmers' experience in agricultural activities and their social contribution activities. This means that the variables included in the regression analysis are estimated to explain 12 percent of the variation in the dependent variable.

Keywords: multifunctional agriculture, attitude, effective factor, sustainable agriculture

Procedia PDF Downloads 219
3254 Accelerated Structural Reliability Analysis under Earthquake-Induced Tsunamis by Advanced Stochastic Simulation

Authors: Sai Hung Cheung, Zhe Shao

Abstract:

Recent earthquake-induced tsunamis in Padang, 2004 and Tohoku, 2011 brought huge losses of lives and properties. Maintaining vertical evacuation systems is the most crucial strategy to effectively reduce casualty during the tsunami event. Thus, it is of our great interest to quantify the risk to structural dynamic systems due to earthquake-induced tsunamis. Despite continuous advancement in computational simulation of the tsunami and wave-structure interaction modeling, it still remains computationally challenging to evaluate the reliability (or its complement failure probability) of a structural dynamic system when uncertainties related to the system and its modeling are taken into account. The failure of the structure in a tsunami-wave-structural system is defined as any response quantities of the system exceeding specified thresholds during the time when the structure is subjected to dynamic wave impact due to earthquake-induced tsunamis. In this paper, an approach based on a novel integration of the Subset Simulation algorithm and a recently proposed moving least squares response surface approach for stochastic sampling is proposed. The effectiveness of the proposed approach is discussed by comparing its results with those obtained from the Subset Simulation algorithm without using the response surface approach.

Keywords: response surface model, subset simulation, structural reliability, Tsunami risk

Procedia PDF Downloads 363
3253 Screening for Larvicidal Activity of Aqueous and Ethanolic Extracts of Fourteen Selected Plants and Formulation of a Larvicide against Aedes aegypti (Linn.) and Aedes albopictus (Skuse) Larvae

Authors: Michael Russelle S. Alvarez, Noel S. Quiming, Francisco M. Heralde

Abstract:

This study aims to: a) obtain ethanolic (95% EtOH) and aqueous extracts of Selaginella elmeri, Christella dentata, Elatostema sinnatum, Curculigo capitulata, Euphorbia hirta, Murraya koenigii, Alpinia speciosa, Cymbopogon citratus, Eucalyptus globulus, Jatropha curcas, Psidium guajava, Gliricidia sepium, Ixora coccinea and Capsicum frutescens and screen them for larvicidal activities against Aedes aegypti (Linn.) and Aedes albopictus (Skuse) larvae; b) to fractionate the most active extract and determine the most active fraction; c) to determine the larvicidal properties of the most active extract and fraction against by computing their percentage mortality, LC50, and LC90 after 24 and 48 hours of exposure; and d) to determine the nature of the components of the active extracts and fractions using phytochemical screening. Ethanolic (95% EtOH) and aqueous extracts of the selected plants will be screened for potential larvicidal activity against Ae. aegypti and Ae. albopictus using standard procedures and 1% malathion and a Piper nigrum based ovicide-larvicide by the Department of Science and Technology as positive controls. The results were analyzed using One-Way ANOVA with Tukey’s and Dunnett’s test. The most active extract will be subjected to partial fractionation using normal-phase column chromatography, and the fractions subsequently screened to determine the most active fraction. The most active extract and fraction were subjected to dose-response assay and probit analysis to determine the LC50 and LC90 after 24 and 48 hours of exposure. The active extracts and fractions will be screened for phytochemical content. The ethanolic extracts of C. citratus, E. hirta, I. coccinea, G. sepium, M. koenigii, E globulus, J. curcas and C. frutescens exhibited significant larvicidal activity, with C. frutescens being the most active. After fractionation, the ethyl acetate fraction was found to be the most active. Phytochemical screening of the extracts revealed the presence of alkaloids, tannins, indoles and steroids. A formulation using talcum powder–300 mg fraction per 1 g talcum powder–was made and again tested for larvicidal activity. At 2 g/L, the formulation proved effective in killing all of the test larvae after 24 hours.

Keywords: larvicidal activity screening, partial purification, dose-response assay, capsicum frutescens

Procedia PDF Downloads 315
3252 Machine Learning Techniques for Estimating Ground Motion Parameters

Authors: Farid Khosravikia, Patricia Clayton

Abstract:

The main objective of this study is to evaluate the advantages and disadvantages of various machine learning techniques in forecasting ground-motion intensity measures given source characteristics, source-to-site distance, and local site condition. Intensity measures such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Estimating these variables for future earthquake events is a key step in seismic hazard assessment and potentially subsequent risk assessment of different types of structures. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as a statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The algorithms are adjusted to quantify event-to-event and site-to-site variability of the ground motions by implementing them as random effects in the proposed models to reduce the aleatory uncertainty. All the algorithms are trained using a selected database of 4,528 ground-motions, including 376 seismic events with magnitude 3 to 5.8, recorded over the hypocentral distance range of 4 to 500 km in Oklahoma, Kansas, and Texas since 2005. The main reason of the considered database stems from the recent increase in the seismicity rate of these states attributed to petroleum production and wastewater disposal activities, which necessities further investigation in the ground motion models developed for these states. Accuracy of the models in predicting intensity measures, generalization capability of the models for future data, as well as usability of the models are discussed in the evaluation process. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available.

Keywords: artificial neural network, ground-motion models, machine learning, random forest, support vector machine

Procedia PDF Downloads 112
3251 Assessment of the Work-Related Stress and Associated Factors among Sanitation Workers in Public Hospitals during COVID-19, Addis Ababa, Ethiopia

Authors: Zerubabel Mihret

Abstract:

Background: Work-related stress is a pattern of reactions to work demands unmatched by worker’s knowledge, skills, or abilities. Healthcare institutions are considered high-risk and intensive work areas for work-related stress. However, there is the nonexistence of clear and strong data about the magnitude of work-related stress on sanitation workers in hospitals in Ethiopia. The aim of this study was to determine the magnitude of work-related stress among sanitation workers in public hospitals during COVID-19 in Addis Ababa, Ethiopia. Methods: Institution-based cross-sectional study was conducted from October 2021 to February 2022 among 494 sanitation workers who were selected from 4 hospitals. HSE (Health and Safety Executive of UK) standard data collection tool was used, and an interviewer-administered questionnaire was used to collect the data using KOBO collect application. The collected data were cleaned and analyzed using SPSS version 20.0. Both binary and multivariable logistic regression analyses were done to identify important factors having an association with work-related stress. Variables with p-value ≤ 0.25 in the bivariate analysis were entered into the multivariable logistic regression model. A statistically significant level was declared at a p-value ≤ 0.05. Results: This study revealed that the magnitude of work-related stress among sanitation workers was 49.2% (95% CI 45-54). Significant proportions (72.7%) of sanitation workers were dissatisfied with their current job. Sex, age, experience, and chewing khat were significantly associated with work-related stress. Conclusion: Work-related stress is significantly high among sanitation workers. Sex, age, experience, and chewing khat were identified as factors associated with work-related stress. Intervention program focusing on the prevention and control of stress is desired by hospitals.

Keywords: work-related stress, sanitation workers, Likert scale, public hospitals, Ethiopia

Procedia PDF Downloads 62
3250 An Investigation about the Health-Promoting Lifestyle of 1389 Emergency Nurses in China

Authors: Lei Ye, Min Liu, Yong-Li Gao, Jun Zhang

Abstract:

Purpose: The aims of the study are to investigate the status of health-promoting lifestyle and to compare the healthy lifestyle of emergency nurses in different levels of hospitals in Sichuan province, China. The investigation is mainly about the health-promoting lifestyle, including spiritual growth, health responsibility, physical activity, nutrition, interpersonal relations, stress management. Then the factors were analyzed influencing the health-promoting lifestyle of emergency nurses in hospitals of Sichuan province in order to find the relevant models to provide reference evidence for intervention. Study Design: A cross-sectional research method was adopted. Stratified cluster sampling, based on geographical location, was used to select the health facilities of 1389 emergency nurses in 54 hospitals from Sichuan province in China. Method: The 52-item, six-factor structure Health-Promoting Lifestyle Profile II (HPLP- II) instrument was used to explore participants’ self-reported health-promoting behaviors and measure the dimensions of health responsibility, physical activity, nutrition, interpersonal relations, spiritual growth, and stress management. Demographic characteristics, education, work duration, emergency nursing work duration and self-rated health status were documented. Analysis: Data were analyzed through SPSS software ver. 17.0. Frequency, percentage, mean ± standard deviation were used to describe the general information, while the Nonparametric Test was used to compare the constituent ratio of general data of different hospitals. One-way ANOVA was used to compare the scores of health-promoting lifestyle in different levels hospital. A multiple linear regression model was established. P values which were less than 0.05 determined statistical significance in all analyses. Result: The survey showed that the total score of health-promoting lifestyle of nurses at emergency departments in Sichuan Province was 120.49 ± 21.280. The relevant dimensions are ranked by scores in descending order: interpersonal relations, nutrition, health responsibility, physical activity, stress management, spiritual growth. The total scores of the three-A hospital were the highest (121.63 ± 0.724), followed by the senior class hospital (119.7 ± 1.362) and three-B hospital (117.80 ± 1.255). The difference was statistically significant (P=0.024). The general data of nurses was used as the independent variable which includes age, gender, marital status, living conditions, nursing income, hospital level, Length of Service in nursing, Length of Service in emergency, Professional Title, education background, and the average number of night shifts. The total score of health-promoting lifestyle was used as dependent variable; Multiple linear regression analysis method was adopted to establish the regression model. The regression equation F = 20.728, R2 = 0.061, P < 0.05, the age, gender, nursing income, turnover intention and status of coping stress affect the health-promoting lifestyle of nurses in emergency department, the result was statistically significant (P < 0.05 ). Conclusion: The results of the investigation indicate that it will help to develop health promoting interventions for emergency nurses in all levels of hospital in Sichuan Province through further research. Managers need to pay more attention to emergency nurses’ exercise, stress management, self-realization, and conduct intervention in nurse training programs.

Keywords: emergency nurse, health-promoting lifestyle profile II, health behaviors, lifestyle

Procedia PDF Downloads 269
3249 A Five-Year Follow-up Survey Using Regression Analysis Finds Only Maternal Age to Be a Significant Medical Predictor for Infertility Treatment

Authors: Lea Stein, Sabine Rösner, Alessandra Lo Giudice, Beate Ditzen, Tewes Wischmann

Abstract:

For many couples bearing children is a consistent life goal; however, it cannot always be fulfilled. Undergoing infertility treatment does not guarantee pregnancies and live births. Couples have to deal with miscarriages and sometimes even discontinue infertility treatment. Significant medical predictors for the outcome of infertility treatment have yet to be fully identified. To further our understanding, a cross-sectional five-year follow-up survey was undertaken, in which 95 women and 82 men that have been treated at the Women’s Hospital of Heidelberg University participated. Binary logistic regressions, parametric and non-parametric methods were used for our sample to determine the relevance of biological (infertility diagnoses, maternal and paternal age) and lifestyle factors (smoking, drinking, over- and underweight) on the outcome of infertility treatment (clinical pregnancy, live birth, miscarriage, dropout rate). During infertility treatment, 72.6% of couples became pregnant and 69.5% were able to give birth. Suffering from miscarriages 27.5% of couples and 20.5% decided to discontinue an unsuccessful fertility treatment. The binary logistic regression models for clinical pregnancies, live births and dropouts were statistically significant for the maternal age, whereas the paternal age in addition to maternal and paternal BMI, smoking, infertility diagnoses and infections, showed no significant predicting effect on any of the outcome variables. The results confirm an effect of maternal age on infertility treatment, whereas the relevance of other medical predictors remains unclear. Further investigations should be considered to increase our knowledge of medical predictors.

Keywords: advanced maternal age, assisted reproductive technology, female factor, male factor, medical predictors, infertility treatment, reproductive medicine

Procedia PDF Downloads 94