Search results for: panel regression

Authors: Nicholas McNamara, John Brookes, Michael Williams, Manish Mathew, Elizabeth Brookes, Tristan Yan, Paul Bannon

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Objective: Pericardial effusions are an uncommon but potentially fatal complication after cardiac surgery. The goal of this study was to describe the incidence and risk factors associated with the development of pericardial effusion requiring drainage after coronary artery bypass graft surgery (CABG). Methods: A retrospective analysis was undertaken using prospectively collected data. All adult patients who underwent CABG at our institution between 1st January 2017 and 31st December 2018 were included. Pericardial effusion was diagnosed using transthoracic echocardiography (TTE) performed for clinical suspicion of pre-tamponade or tamponade. Drainage was undertaken if considered clinically necessary and performed via a sub-xiphoid incision, pericardiocentesis, or via re-sternotomy at the discretion of the treating surgeon. Patient demographics, operative characteristics, anticoagulant exposure, and postoperative outcomes were examined to identify those variables associated with the development of pericardial effusion requiring drainage. Tests of association were performed using the Fischer exact test for dichotomous variables and the Student t-test for continuous variables. Logistic regression models were used to determine univariate predictors of pericardial effusion requiring drainage. Results: Between January 1st, 2017, and December 31st, 2018, a total of 408 patients underwent CABG at our institution, and eight (1.9%) required drainage of pericardial effusion. There was no difference in age, gender, or the proportion of patients on preoperative therapeutic heparin between the study and control groups. Univariate analysis identified preoperative atrial arrhythmia (37.5% vs 8.8%, p = 0.03), reduced left ventricular ejection fraction (47% vs 56%, p = 0.04), longer cardiopulmonary bypass (130 vs 84 min, p < 0.01) and cross-clamp (107 vs 62 min, p < 0.01) times, higher drain output in the first four postoperative hours (420 vs 213 mL, p <0.01), postoperative atrial fibrillation (100% vs 32%, p < 0.01), and pleural effusion requiring drainage (87.5% vs 12.5%, p < 0.01) to be associated with development of pericardial effusion requiring drainage. Conclusion: In this study, the incidence of pericardial effusion requiring drainage was 1.9%. Several factors, mainly related to preoperative or postoperative arrhythmia, length of surgery, and pleural effusion requiring drainage, were identified to be associated with developing clinically significant pericardial effusions. High clinical suspicion and low threshold for transthoracic echo are pertinent to ensure this potentially lethal condition is not missed.

Keywords: coronary artery bypass, pericardial effusion, pericardiocentesis, tamponade, sub-xiphoid drainage

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Authors: Keiko Yamauchi, Motoyuki Nakao, Yoko Ishihara

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The increase in the number of women with breast cancer in Japan has required hospitals to provide a higher quality of medicine so that patients are satisfied with the treatment they receive. However, patients’ satisfaction following breast cancer treatment has not been sufficiently studied. Hence, we investigated the factors influencing patient satisfaction following breast cancer treatment among Japanese women. These women underwent either breast-conserving surgery (BCS) (n = 380) or total mastectomy (TM) (n = 247). In March 2016, we conducted a cross-sectional internet survey of Japanese women with breast cancer in Japan. We assessed the following factors: socioeconomic status, cancer-related information, the role of medical decision-making, the degree of satisfaction regarding the treatments received, and the regret arising from the medical decision-making processes. We performed logistic regression analyses with the following dependent variables: extreme satisfaction with the treatments received, and regret regarding the medical decision-making process. For both types of surgery, the odds ratio (OR) of being extremely satisfied with the cancer treatment was significantly higher among patients who did not have any regrets compared to patients who had. Also, the OR tended to be higher among patients who chose to play a wanted role in the medical decision-making process, compared with patients who did not. In the BCS group, the OR of being extremely satisfied with the treatment was higher if, at diagnosis, the patient’s youngest child was older than 19 years, compared with patients with no children. The OR was also higher if patient considered the stage and characteristics of their cancer significant. The OR of being extremely satisfied with the treatments was lower among patients who were not employed on full-time basis, and among patients who considered the second medical opinions and medical expenses to be significant. These associations were not observed in the TM group. The OR of having regrets regarding the medical decision-making process was higher among patients who chose to play a role in the decision-making process as they preferred, and was also higher in patients who were employed on either a part-time or contractual basis. For both types of surgery, the OR was higher among patients who considered a second medical opinion to be significant. Regardless of surgical type, regret regarding the medical decision-making process decreases treatment satisfaction. Patients who received breast-conserving surgery were more likely to have regrets concerning the medical decision-making process if they could not play a role in the process as they preferred. In addition, factors associated with the satisfaction with treatment in BCS group but not TM group included the second medical opinion, medical expenses, employment status, and age of the youngest child at diagnosis.

Keywords: medical decision making, breast-conserving surgery, total mastectomy, Japanese

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Authors: Arlene López-Sampson, Tony Page, Betsy Jackes

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Aquilaria genus produces a highly valuable fragrant oleoresin known as agarwood. Agarwood forms in a few trees in the wild as a response to injure or pathogen attack. The resin is used in perfume and incense industry and medicine. Cultivation of Aquilaria species as a sustainable source of the resin is now a common strategy. Physiological traits are frequently used as a proxy of crop and tree productivity. Aquilaria species growing in Queensland, Australia were studied to investigate relationship between leaf-productivity traits with tree growth. Specifically, 28 trees, representing 12 plus trees and 16 trees from yield plots, were selected to conduct carbon isotope analysis (δ13C) and monitor six leaf attributes. Trees were grouped on four diametric classes (diameter at 150 mm above ground level) ensuring the variability in growth of the whole population was sampled. Model averaging technique based on the Akaike’s information criterion (AIC) was computed to identify whether leaf traits could assist in diameter prediction. Carbon isotope values were correlated with height classes and leaf traits to determine any relationship. In average four leaves per shoot were recorded. Approximately one new leaf per week is produced by a shoot. Rate of leaf expansion was estimated in 1.45 mm day-1. There were no statistical differences between diametric classes and leaf expansion rate and number of new leaves per week (p > 0.05). Range of δ13C values in leaves of Aquilaria species was from -25.5 ‰ to -31 ‰ with an average of -28.4 ‰ (± 1.5 ‰). Only 39% of the variability in height can be explained by δ13C in leaf. Leaf δ13C and nitrogen content values were positively correlated. This relationship implies that leaves with higher photosynthetic capacities also had lower intercellular carbon dioxide concentrations (ci/ca) and less depleted values of 13C. Most of the predictor variables have a weak correlation with diameter (D). However, analysis of the 95% confidence of best-ranked regression models indicated that the predictors that could likely explain growth in Aquilaria species are petiole length (PeLen), values of δ13C (true13C) and δ15N (true15N), leaf area (LA), specific leaf area (SLA) and number of new leaf produced per week (NL.week). The model constructed with PeLen, true13C, true15N, LA, SLA and NL.week could explain 45% (R2 0.4573) of the variability in D. The leaf traits studied gave a better understanding of the leaf attributes that could assist in the selection of high-productivity trees in Aquilaria.

Keywords: 13C, petiole length, specific leaf area, tree growth

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Authors: Sonia Tamanna, Akramul Hassan, Mohammad Shakil Mahmood, Farzana Ansari, Gowhar Rashid, Mir Fahim Faisal, M. Zakir Hossain Howlader

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Background: Preeclampsia (PE), a pregnancy-specific hypertensive disorder, significantly impacts maternal and fetal health. It is particularly prevalent in underdeveloped countries and is linked to preterm delivery and fetal growth. The renin-angiotensin system (RAS) plays a crucial role in ensuring a successful pregnancy outcome, with Angiotensin-Converting Enzyme 2 (ACE2) being a key component. ACE2 converts ANG II to Ang-(1-7), offering protection against ANG II-induced stress and inflammation while regulating blood pressure and osmotic balance during pregnancy. The reduced maternal plasma angiotensin-converting enzyme 2 (ACE2) seen in preeclampsia might contribute to its pathogenesis. However, there has been a dearth of comprehensive research into the association between ACE2 gene polymorphism and preeclampsia. In the South Asian population, hypertension is strongly linked to two SNPs: rs2285666 and rs879922. This genotype was therefore considered, and the possible association of maternal and fetal ACE2 gene polymorphism with preeclampsia within the Bangladeshi population was evaluated. Method: DNA was extracted from peripheral white blood cells (WBCs) using the organic method, and SNP genotyping was done via PCR-RFLP. Odds ratios (OR) with 95% confidence intervals (95% CI) were calculated using logistic regression to determine relative risk. Result: A comprehensive case-control study was conducted on 51 PE patients and their infants, along with 56 control subjects and their infants. Maternal single nuvleotide polymorphisms (SNP) (rs2285666) analysis revealed a strong association between the TT genotype and preeclampsia, with a four-fold increased risk in mothers (P=0.024, OR=4.00, 95% CI=1.36-11.37) compared to their ancestral genotype CC. However, the CT genotype (rs2285666) showed no significant difference (P=0.46, OR=1.54, 95% CI=0.57-4.14). Notably, no significant correlation was found in infants, regardless of their gender. For rs879922, no significant association was observed in both mothers and infants. This pioneering study suggests that mothers carrying the ACE2 gene variant rs2285666 (TT allele) may be at higher risk for preeclampsia, potentially influencing hypertension characteristics, whereas rs879922 does not appear to be associated with developing preeclampsia. Conclusion: This study sheds light on the role of ACE2 gene polymorphism, particularly the rs2285666 TT allele, in maternal susceptibility to preeclampsia. However, rs879922 does not appear to be linked to the risk of PE. This research contributes to our understanding of the genetic underpinnings of preeclampsia, offering insights into potential avenues for prevention and management.

Keywords: ACE2, PCR-RFLP, preeclampsia, single nuvleotide polymorphisms (SNPs)

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Authors: Irene Kretchy, Frances Owusu-Daaku, Samuel Danquah

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Hypertension is the leading risk factor for cardiovascular diseases, and a major cause of death and disability worldwide. This study examined whether psychosocial variables influenced patients’ perception and experience of side effects of their medicines, how they coped with these experiences and the impact on mental health and medication adherence to conventional hypertension therapies. Methods: A hospital-based mixed methods study, using quantitative and qualitative approaches was conducted on hypertensive patients. Participants were asked about side effects, medication adherence, common psychological symptoms, and coping mechanisms with the aid of standard questionnaires. Information from the quantitative phase was analyzed with the Statistical Package for Social Sciences (SPSS) version 20. The interviews from the qualitative study were audio-taped with a digital audio recorder, manually transcribed and analyzed using thematic content analysis. The themes originated from participant interviews a posteriori. Results: The experiences of side effects – such as palpitations, frequent urination, recurrent bouts of hunger, erectile dysfunction, dizziness, cough, physical exhaustion - were categorized as no/low (39.75%), moderate (53.0%) and high (7.25%). Significant relationships between depression (x 2 = 24.21, P < 0.0001), anxiety (x 2 = 42.33, P < 0.0001), stress (x 2 = 39.73, P < 0.0001) and side effects were observed. A logistic regression model using the adjusted results for this association are reported – depression [OR = 1.9 (1.03 – 3.57), p = 0.04], anxiety [OR = 1.5 (1.22 – 1.77), p = < 0.001], and stress [OR = 1.3 (1.02 – 1.71), p = 0.04]. Side effects significantly increased the probability of individuals to be non-adherent [OR = 4.84 (95% CI 1.07 – 1.85), p = 0.04] with social factors, media influences and attitudes of primary caregivers further explaining this relationship. The personal adoption of medication modifying strategies, espousing the use of complementary and alternative treatments, and interventions made by clinicians were the main forms of coping with side effects. Conclusions: Results from this study show that contrary to a biomedical approach, the experience of side effects has biological, social and psychological interrelations. The result offers more support for the need for a multi-disciplinary approach to healthcare where all forms of expertise are incorporated into health provision and patient care. Additionally, medication side effects should be considered as a possible cause of non-adherence among hypertensive patients, thus addressing this problem from a Biopsychosocial perspective in any intervention may improve adherence and invariably control blood pressure.

Keywords: biopsychosocial, hypertension, medication adherence, psychological disorders

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Authors: I. Ling Tsai, Shu Fen Wu, Chen-Fuh Lam, Chia Yu Chen, Shu Jiuan Chen, Yen Lin Liu

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Purpose: Following the conduction of the National Health Insurance (NHI) system in Taiwan since 1995, the demand for anesthesia services continues to increase in the operating rooms and other medical units. It has been well recognized that increased work stress not only affects the clinical performance of the medical staff, long-term work load may also result in occupational burnout. Our study aimed to determine the influence of working environment, work stress and job satisfaction on the occupational burnout in nurse anesthetists. The ultimate goal of this research project is to develop a strategy in establishing a friendly, less stressful workplace for the nurse anesthetists to enhance their job satisfaction, thereby reducing occupational burnout and increasing the career life for nurse anesthetists. Methods: This was a cross-sectional, descriptive study performed in a metropolitan teaching hospital in southern Taiwan between May 2017 to July 2017. A structured self-administered questionnaire, modified from the Practice Environment Scale of the Nursing Work Index (PES-NWI), Occupational Stress Indicator 2 (OSI-2) and Maslach Burnout Inventory (MBI) manual was collected from the nurse anesthetists. The relationships between two numeric datasets were analyzed by the Pearson correlation test (SPSS 20.0). Results: A total of 66 completed questionnaires were collected from 75 nurses (response rate 88%). The average scores for the working environment, job satisfaction, and work stress were 69.6%, 61.5%, and 63.9%, respectively. The three perspectives used to assess the occupational burnout, namely emotional exhaustion, depersonalization and sense of personal accomplishment were 26.3, 13.0 and 24.5, suggesting the presence of moderate to high degrees of burnout in our nurse anesthetists. The presence of occupational burnout was closely correlated with the unsatisfactory working environment (r=-0.385, P=0.001) and reduced job satisfaction (r=-0.430, P=0.000). Junior nurse anesthetists (<1-year clinical experience) reported having higher satisfaction in working environment than the seniors (5 to 10-year clinical experience) (P=0.02). Although the average scores for work stress, job satisfaction, and occupational burnout were lower in junior nurses, the differences were not statistically different. The linear regression model, the working environment was the independent factor that predicted occupational burnout in nurse anesthetists up to 19.8%. Conclusions: High occupational burnout is more likely to develop in senior nurse anesthetists who experienced the dissatisfied working environment, work stress and lower job satisfaction. In addition to the regulation of clinical duties, the increased workload in the supervision of the junior nurse anesthetists may result in emotional stress and burnout in senior nurse anesthetists. Therefore, appropriate adjustment of clinical and teaching loading in the senior nurse anesthetists could be helpful to improve the occupational burnout and enhance the retention rate.

Keywords: nurse anesthetists, working environment, work stress, job satisfaction, occupational burnout

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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To develop a machine learning model to predict diabetes (DM) prevalence in the U.S. population using demographic characteristics, physical indicators, and lifestyle habits, and to analyze how these factors contribute to the likelihood of diabetes. We analyzed data from 23,546 participants aged 20 and older, who were non-pregnant, from the 2009-2018 National Health and Nutrition Examination Survey (NHANES). The dataset included key demographic (age, sex, ethnicity), physical (BMI, leg length, total cholesterol [TCHOL], fasting plasma glucose), and lifestyle indicators (smoking habits). A weighted sample was used to account for NHANES survey design features such as stratification and clustering. A classification machine learning model was trained to predict diabetes status. The target variable was binary (diabetes or non-diabetes) based on fasting plasma glucose measurements. The following models were evaluated: Logistic Regression (baseline), Random Forest Classifier, Gradient Boosting Machine (GBM), Support Vector Machine (SVM). Model performance was assessed using accuracy, F1-score, AUC-ROC, and precision-recall metrics. Feature importance was analyzed using SHAP values to interpret the contributions of variables such as age, BMI, ethnicity, and smoking status. The Gradient Boosting Machine (GBM) model outperformed other classifiers with an AUC-ROC score of 0.85. Feature importance analysis revealed the following key predictors: Age: The most significant predictor, with diabetes prevalence increasing with age, peaking around the 60s for males and 70s for females. BMI: Higher BMI was strongly associated with a higher risk of diabetes. Ethnicity: Black participants had the highest predicted prevalence of diabetes (14.6%), followed by Mexican-Americans (13.5%) and Whites (10.6%). TCHOL: Diabetics had lower total cholesterol levels, particularly among White participants (mean decline of 23.6 mg/dL). Smoking: Smoking showed a slight increase in diabetes risk among Whites (0.2%) but had a limited effect in other ethnic groups. Using machine learning models, we identified key demographic, physical, and lifestyle predictors of diabetes in the U.S. population. The results confirm that diabetes prevalence varies significantly across age, BMI, and ethnic groups, with lifestyle factors such as smoking contributing differently by ethnicity. These findings provide a basis for more targeted public health interventions and resource allocation for diabetes management.

Keywords: diabetes, NHANES, random forest, gradient boosting machine, support vector machine

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Authors: Beatriz Garcia-Juan, Ana B. Escrig-Tena, Vicente Roca-Puig

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The aim of this article is to conduct a theoretical and empirical study in order to examine how the goal orientation (GO) of public employees affects the relationship between the structural and psychological empowerment that they experience at their workplaces. In doing so, we follow structural empowerment (SE) and psychological empowerment (PE) conceptualizations, and relate them to the public administration framework. Moreover, we review arguments from GO theories, and previous related contributions. Empowerment has emerged as an important issue in the public sector organization setting in the wake of mainstream New Public Management (NPM), the new orientation in the public sector that aims to provide a better service for citizens. It is closely linked to the drive to improve organizational effectiveness through the wise use of human resources. Nevertheless, it is necessary to combine structural (managerial) and psychological (individual) approaches in an integrative study of empowerment. SE refers to a set of initiatives that aim the transference of power from managerial positions to the rest of employees. PE is defined as psychological state of competence, self-determination, impact, and meaning that an employee feels at work. Linking these two perspectives will lead to arrive at a broader understanding of the empowerment process. Specifically in the public sector, empirical contributions on this relationship are therefore important, particularly as empowerment is a very useful tool with which to face the challenges of the new public context. There is also a need to examine the moderating variables involved in this relationship, as well as to extend research on work motivation in public management. It is proposed the study of the effect of individual orientations, such as GO. GO concept refers to the individual disposition toward developing or confirming one’s capacity in achievement situations. Employees’ GO may be a key factor at work and in workforce selection processes, since it explains the differences in personal work interests, and in receptiveness to and interpretations of professional development activities. SE practices could affect PE feelings in different ways, depending on employees’ GO, since they perceive and respond differently to such practices, which is likely to yield distinct PE results. The model is tested on a sample of 521 Spanish local authority employees. Hierarchical regression analysis was conducted to test the research hypotheses using SPSS 22 computer software. The results do not confirm the direct link between SE and PE, but show that learning goal orientation has considerable moderating power in this relationship, and its interaction with SE affects employees’ PE levels. Therefore, the combination of SE practices and employees’ high levels of LGO are important factors for creating psychologically empowered staff in public organizations.

Keywords: goal orientation, moderating effect, psychological empowerment, structural empowerment

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Authors: Priyanka Mazumdar, Ananya Mukhopadhyay

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A lot of progress has been achieved in the research of turbidites during the last decades. However, their relationship to delta systems still deserves further attention. This paper addresses example of fine grained turbidite from a pro-deltaic deposit of a Proterozoic mixed energy delta system exposed along Chaossa-Baliana river section of the Chaossa Formation of the Simla Basin. Lithostratigraphic analysis of the Chaossa Formation reveals three major facies associations (prodelta deposit-FA1, delta slope deposit-FA2 and delta front deposit-FA3) based on lithofacies types, petrography and sedimentary structures. Detailed process-based facies and paleoenvironmental analysis of the study area have led to identification of more than150 m thick coarsening-upwards deltaic successions composed of fine grained turbidites overlain by delta slope deposits. Erosional features are locally common at the base of turbidite beds and still more widespread at the top. The complete sequence has eight sub-divisions that are here termed T1 to T8. The basal subdivision (T1) comprises a massive graded unit with a sharp, scoured base, internal parallel-lamination and cross-lamination. The overlying sequence shows textural and compositional grading through alternating silt and mud laminae (T2). T2 is overlying by T3 which is characterized by climbing ripple and cross lamination. Parallel laminae are the predominant facies attributes of T4 which caps the T3 unit. T5 has a loaded scour base and is mainly characterized laminated silt. The topmost three divisions, graded mud (T6), ungraded mud (T7) and laminated mud (T8). The proposed sequence is analogous to the Bouma (1962) structural scheme for sandy turbidites. Repetition of partial sequences represents deposition from different stages of evolution of a large, muddy, turbidity flow. Detailed facies analysis of the study area reveals that the sediments of the turbidites developed during normal regression at the stage of stable or marginally rising sea level. Thin-bedded turbidites were deposited predominantly by turbidity currents in the relatively shallower part of the Simla basin. The fine-grained turbidites are developed by resedimentation of delta-front sands and slumping of upper pro-delta muds.

Keywords: turbidites, prodelta, proterozoic, Simla Basin, Bouma sequence

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Authors: Keith T. S. Tung, Frederick K. Ho, Rosa S. Wong, Camilla K. M. Lo, Wilfred H. S. Wong, C. B. Chow, Patrick Ip

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Objectives: Underage drinking is an important public health problem both locally and globally. Conventional prevention/intervention relies on unidirectional knowledge transfer such as mail leaflets or health talks which showed mixed results in changing the target behaviour. Previously, we conducted a school internet-based intervention which was found to be effective in reducing alcohol use among adolescents, yet the underlying mechanisms have not been properly investigated. This study, therefore, examined the mechanisms that explain how the intervention produced a change in alcohol drinking behaviours among Chinese adolescent as observed in our previous clustered randomised controlled trial (RCT) study. Methods: This is a cluster randomised controlled trial with parallel group design. Participating schools were randomised to the Internet intervention or the conventional health education group (control) with a 1:1 allocation ratio. Secondary 1–3 students of the participating schools were enrolled in this study. The Internet intervention was a web-based quiz game competition, in which participating students would answer 1,000 alcohol-related multiple-choice quiz questions. Conventional health education group received a promotional package on equivalent alcohol-related knowledge. The participants’ alcohol-related attitude, knowledge, and perceived behavioural control were self-reported before the intervention (baseline) and one month and three months after the intervention. Results: Our RCT results showed that participants in the Internet group were less likely to drink (risk ratio [RR] 0.79, p < 0.01) as well as in lesser amount (β -0.06, p < 0.05) compared to those in the control group at both post-intervention follow-ups. Within the intervention group, regression analyses showed that high quiz scorer had greater improvement in alcohol-related knowledge (β 0.28, p < 0.01) and attitude (β -0.26, p < 0.01) at 1 month after intervention, which in turn increased their perceived behavioural control against alcohol use (β 0.10 and -0.26, both p < 0.01). Attitude, compared to knowledge, was found to be a stronger contributor to the intervention effect on perceived behavioural control. Conclusions: Our internet-based intervention has demonstrated effectiveness in reducing the risk of underage drinking when compared with conventional health education. Our study results further showed an attitude to be a more important factor than knowledge in changing health-related behaviour. This has an important implication for future prevention/intervention on an underage drinking problem.

Keywords: adolescents, internet-based intervention, randomized controlled trial, underage drinking

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Authors: Aksana N. Popel, Volha A. Sujayeva, Olga V. Kоshlataja, Irеna S. Karpava

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Introduction: It is a known fact that cardiovascular pathology and its complications cause a more severe course and worse prognosis in patients with comorbid kidney pathology. Chronic kidney disease (CKD) is associated with inflammation, endothelial dysfunction, and increased activity of the sympathoadrenal system. This circumstance increases the risk of cardiovascular diseases and the progression of kidney pathology. The above determines the need to identify cardiorenal changes at early stages to reduce the risks of cardiovascular complications and the progression of CKD. Objective: To identify risk factors (RF) for the development of CKD in elderly patients with chronic ischemic heart disease (CIHD). Methods: The study included 64 patients (40 women and 24 men) with a mean age of 74.4±4.5 years with coronary heart disease, without a history of structural kidney pathology and CKD. All patients underwent transthoracic echocardiography (TTE) and kidney ultrasound (KU) using GE Vivid 9 equipment (GE HealthCare, USA), and cardiac computed tomography (CCT) using Siemens Somatom Force equipment (Siemens Healthineers AG, Germany) in 3 months and in 1 year. Data obtained were analyzed using multiple regression analysis and nonparametric Mann-Whitney test. Statistical analysis was performed using the STATISTICA 12.0 program (StatSoft Inc.). Results: Initially, CKD was not diagnosed in all patients. In 3 months, CKD was diagnosed: stage C1 had 11 people (18%), stage C2 had 4 people (6%), stage C3A had 11 people (18%), stage C3B had 2 people (3%). After 1 year, CKD was diagnosed: stage C1 had 22 people (35%), stage C2 had 5 people (8%), stage C3A had 17 people (27%), stage C3B had 10 people (15%). In 3 months, statistically significant (p<0.05) risk factors were: 1) according to TTE: mitral peak E-wave velocity (U=678, p=0.039), mitral E-velocity DT (U=514, p=0.0168), mitral peak A-wave velocity (U=682, p=0.013). In 1 year, statistically significant (p<0.05) risk factors were: according to TTE: left ventricular (LV) end-systolic volume in B-mode (U=134, p=0.006), LV end-diastolic volume in B-mode (U=177, p=0.04), LV ejection fraction in B-mode (U=135, p=0.006), left atrial volume (U=178, p=0.021), LV hypertrophy (U=294, p=0.04), mitral valve (MV) fibrosis (U=328, p=0.01); according CCT: epicardial fat thickness (EFT) on the right ventricle (U=8, p=0.015); according to KU: interlobar renal artery resistance index (RI) (U=224, p=0.02), segmental renal artery RI (U=409, p=0.016). Conclusions: Both TTE and KU are very informative methods to determine the additional risk factors of CKD development and progression. The most informative risk factors were LV global systolic and diastolic functions, LV and LA volumes. LV hypertrophy, MV fibrosis, interlobar renal artery and segmental renal artery RIs, EFT.

Keywords: chronic kidney disease, ischemic heart disease, prognosis, risk factors

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Authors: Marlin Mubarak

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Background: Endometriosis is a complex disabling disease affecting young females in the reproductive period mainly. The aim of this project is to generate a diagnostic model to predict severity and stage of endometriosis prior to Laparoscopic surgery. This will help to improve the pre-operative diagnostic accuracy of stage 3 & 4 endometriosis and as a result, refer relevant women to a specialist centre for complex Laparoscopic surgery. The model is based on the British Society of Gynaecological Endoscopy (BSGE) pain questionnaire, clinical examination and ultrasound scan. Design: This is a prospective, observational, study, in which women completed the BSGE pain questionnaire, a BSGE requirement. Also, as part of the routine preoperative assessment patient had a routine ultrasound scan and when recto-vaginal and deep infiltrating endometriosis was suspected an MRI was performed. Setting: Luton & Dunstable University Hospital. Patients: Symptomatic women (n = 56) scheduled for laparoscopy due to pelvic pain. The age ranged between 17 – 52 years of age (mean 33.8 years, SD 8.7 years). Interventions: None outside the recognised and established endometriosis centre protocol set up by BSGE. Main Outcome Measure(s): Sensitivity and specificity of endometriosis diagnosis predicted by symptoms based on BSGE pain questionnaire, clinical examinations and imaging. Findings: The prevalence of diagnosed endometriosis was calculated to be 76.8% and the prevalence of advanced stage was 55.4%. Deep infiltrating endometriosis in various locations was diagnosed in 32/56 women (57.1%) and some had DIE involving several locations. Logistic regression analysis was performed on 36 clinical variables to create a simple clinical prediction model. After creating the scoring system using variables with P < 0.05, the model was applied to the whole dataset. The sensitivity was 83.87% and specificity 96%. The positive likelihood ratio was 20.97 and the negative likelihood ratio was 0.17, indicating that the model has a good predictive value and could be useful in predicting advanced stage endometriosis. Conclusions: This is a hypothesis-generating project with one operator, but future proposed research would provide validation of the model and establish its usefulness in the general setting. Predictive tools based on such model could help organise the appropriate investigation in clinical practice, reduce risks associated with surgery and improve outcome. It could be of value for future research to standardise the assessment of women presenting with pelvic pain. The model needs further testing in a general setting to assess if the initial results are reproducible.

Keywords: deep endometriosis, endometriosis, minimally invasive, MRI, ultrasound.

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Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: Chia-Ching Sun, Li-Yin Chien, Chun-Ting Hsiao

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Background: Appropriate gestation weight gain benefits pregnant women and their children; however, excessive weight gain could raise the risk of adverse health outcomes and chronicle diseases. Nevertheless, there is currently limited evidence on the effect of physical activities on pregnant women’s gestational weight gain. Purpose: This study aimed to explore the correlation between the level of physical activity and gestation weight gain during the second and third trimester of pregnancy. Methods: This longitudinal study enrolled 800 healthy pregnant women aged over 20 from six hospitals in northern Taiwan. Structured questionnaires were used to collect data twice for each participant during 14-27 and 28-40 weeks of gestation. Variables included demographic data, maternal health history, and lifestyle. The International Physical Activity Questionnaire-short form was used to measure the level of physical activity from walking and of moderate-intensity and vigorous-intensity before and during pregnancy. Weight recorded at prenatal checkups were used to calculate average weight gain in each trimester of pregnancy. T-tests, ANOVA, chi-squared tests, and multivariable logistic regression models were applied to determine the predicting factors for weight gain during the second and third trimester. Result: Participants who had achieved recommended physical activity level (150 minutes of moderate physical activity or 75 minutes of vigorous physical activity a week) before pregnancy (aOR=1.85, 95% CI=1.27-2.67) or who achieved recommended walking level (150 minutes a week) during the second trimester of pregnancy (aOR=1.43, 95% CI= 1.00-2.04) gained significantly more weight during the second trimester. Compared with those who did not reach recommended level of moderate-intensity physical activity (150 minutes a week), women who had reached that during the second trimester were more likely to be in the less than recommended weight gain group than in the recommended weight gain group (aOR=2.06, CI=1.06-4.00). However, there was no significant correlation between physical activity level and weight gain in the third trimester. Other predicting factors of excessive weight gain included education level which showed a negative correlation (aOR=0.38, CI=0.17-0.88), whereas overweight and obesity before pregnancy showed a positive correlation (OR=3.97, CI=1.23-12.78). Conclusions/implications for practice: Participants who had achieved recommended physical activity level before pregnancy significantly reduced exercise during pregnancy and gained excessive weight during the second trimester. However, women who engaged in the practice of physical activity as recommended could effectively control weight gain in the third trimester. Healthcare professionals could suggest that pregnant women who exercise maintain their pre-pregnancy level of physical activity, given activities requiring physical contact or causing falls are avoided. For those who do not exercise, health professionals should encourage them to gradually increase the level of physical activity. Health promotion strategies related to weight control and physical activity level achievement should be given to women before pregnancy.

Keywords: pregnant woman, physical activity, gestation weight gain, obesity, overweight

Procedia PDF Downloads 156

Authors: Gabriela Silva-Maceda, Silvia Romero-Contreras

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Spanish is a more transparent language than English given that it has more direct correspondences between sounds and letters. It has become important to understand how decoding and linguistic comprehension contribute to reading comprehension in the framework of the widely known Simple View Model. This study aimed to identify the level of prediction by these two components in a sample of 1st to 4th grade children attending two schools in central Mexico (one public and one private). Within each school, ten children were randomly selected in each grade level, and their parents were asked about reading habits and socioeconomic information. In total, 79 children completed three standardized tests measuring decoding (pseudo-word reading), linguistic comprehension (understanding of paragraphs) and reading comprehension using subtests from the Clinical Evaluation of Language Fundamentals-Spanish, Fourth Edition, and the Test de Lectura y Escritura en Español (LEE). The data were analyzed using hierarchical regression, with decoding as a first step and linguistic comprehension as a second step. Results showed that decoding accounted for 19.2% of the variance in reading comprehension, while linguistic comprehension accounted for an additional 10%, adding up to 29.2% of variance explained: F (2, 75)= 15.45, p <.001. Socioeconomic status derived from parental questionnaires showed a statistically significant association with the type of school attended, X2 (3, N= 79) = 14.33, p =.002. Nonetheless when analyzing the Simple View components, only decoding differences were statistically significant (t = -6.92, df = 76.81, p < .001, two-tailed); reading comprehension differences were also significant (t = -3.44, df = 76, p = .001, two-tailed). When socioeconomic status was included in the model, it predicted a 5.9% unique variance, even when already accounting for Simple View components, adding to a 35.1% total variance explained. This three-predictor model was also significant: F (3, 72)= 12.99, p <.001. In addition, socioeconomic status was significantly correlated with the amount of non-textbook books parents reported to have at home for both adults (rho = .61, p<.001) and children (rho= .47, p<.001). Results converge with a large body of literature finding socioeconomic differences in reading comprehension; in addition this study suggests that these differences were also present in decoding skills. Although linguistic comprehension differences between schools were expected, it is argued that the test used to collect this variable was not sensitive to linguistic differences, since it came from a test to diagnose clinical language disabilities. Even with this caveat, results show that the components of the Simple View Model can predict less than a third of the variance in reading comprehension in Spanish. However, the results also suggest that a fuller model of reading comprehension is obtained when considering the family’s socioeconomic status, given the potential differences shown by the socioeconomic status association with books at home, factors that are particularly important in countries where inequality gaps are relatively large.

Keywords: decoding, linguistic comprehension, reading comprehension, simple view model, socioeconomic status, Spanish

Procedia PDF Downloads 329

Authors: Siti Badriyah Rushayati, Resti Meilani, Rachmad Hermawan

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A biosphere reserve is developed to create harmony amongst economic development, community development, and environmental protection, through partnership between human and nature. Giam Siak Kecil Bukit Batu Biosphere Reserve (GSKBB BR) in Riau Province, Indonesia, is unique in that it has peat soil dominating the area, many springs essential for human livelihood, high biodiversity. Furthermore, it is the only biosphere reserve covering privately managed production forest areas. The annual occurrences of deforestation and forest fire pose a threat toward such unique biosphere reserve. Forest fire produced smokes that along with mass airflow reached neighboring countries, particularly Singapore and Malaysia. In this research, we aimed at analyzing the threat of deforestation and forest fire, and the potential of CO2 emission at GSKBB BR. We used Landsat image, arcView software, and ERDAS IMAGINE 8.5 Software to conduct spatial analysis of land cover and land use changes, calculated CO2 emission based on emission potential from each land cover and land use type, and exercised simple linear regression to demonstrate the relation between CO2 emission potential and deforestation. The result showed that, beside in the buffer zone and transition area, deforestation also occurred in the core area. Spatial analysis of land cover and land use changes from years 2010, 2012, and 2014 revealed that there were changes of land cover and land use from natural forest and industrial plantation forest to other land use types, such as garden, mixed garden, settlement, paddy fields, burnt areas, and dry agricultural land. Deforestation in core area, particularly at the Giam Siak Kecil Wildlife Reserve and Bukit Batu Wildlife Reserve, occurred in the form of changes from natural forest in to garden, mixed garden, shrubs, swamp shrubs, dry agricultural land, open area, and burnt area. In the buffer zone and transition area, changes also happened, what once swamp forest changed into garden, mixed garden, open area, shrubs, swamp shrubs, and dry agricultural land. Spatial analysis on land cover and land use changes indicated that deforestation rate in the biosphere reserve from 2010 to 2014 had reached 16 119 ha/year. Beside deforestation, threat toward the biosphere reserve area also came from forest fire. The occurrence of forest fire in 2014 had burned 101 723 ha of the area, in which 9 355 ha of core area, and 92 368 ha of buffer zone and transition area. Deforestation and forest fire had increased CO2 emission as much as 24 903 855 ton/year.

Keywords: biosphere reserve, CO2 emission, deforestation, forest fire

Procedia PDF Downloads 488

Authors: Stephanie Watson, Fabrice Stephenson, Conrad Pilditch, Carolyn Lundquist

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Spatial data detailing both the distribution and density of functionally important marine species are needed to inform management decisions. Species distribution models (SDMs) have proven helpful in this regard; however, models often focus only on species occurrences derived from spatially expansive datasets and lack the resolution and detail required to inform regional management decisions. Boosted regression trees (BRT) were used to produce high-resolution SDMs (250 m) at two spatial scales predicting probability of occurrence, abundance (count per sample unit), density (count per km2) and uncertainty for seven coastal seafloor taxa that vary in habitat usage and distribution to examine prediction differences and implications for coastal management. We investigated if small scale regionally focussed models (82,000 km2) can provide improved predictions compared to data-rich national scale models (4.2 million km2). We explored the variability in predictions across model type (occurrence vs abundance) and model scale to determine if specific taxa models or model types are more robust to geographical variability. National scale occurrence models correlated well with broad-scale environmental predictors, resulting in higher AUC (Area under the receiver operating curve) and deviance explained scores; however, they tended to overpredict in the coastal environment and lacked spatially differentiated detail for some taxa. Regional models had lower overall performance, but for some taxa, spatial predictions were more differentiated at a localised ecological scale. National density models were often spatially refined and highlighted areas of ecological relevance producing more useful outputs than regional-scale models. The utility of a two-scale approach aids the selection of the most optimal combination of models to create a spatially informative density model, as results contrasted for specific taxa between model type and scale. However, it is vital that robust predictions of occurrence and abundance are generated as inputs for the combined density model as areas that do not spatially align between models can be discarded. This study demonstrates the variability in SDM outputs created over different geographical scales and highlights implications and opportunities for managers utilising these tools for regional conservation, particularly in data-limited environments.

Keywords: Benthic ecology, spatial modelling, multi-scalar modelling, marine conservation.

Procedia PDF Downloads 79

Authors: Suparna Bharadwaj, Sriganesh Kamath, Gopalakrishna K. N., Subhas Konar

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Introduction: Post-operative cognitive dysfunction (POCD) is a spectrum of clinical syndrome presenting as emergence delirium (ED) and/or post-operative delirium (POD). ED is a transient state (minutes to hours) of marked agitation after the discontinuation of general anesthesia, which does not respond to consoling measures. On the other hand, POD without identifiable etiology is not temporally related to emergence from anesthesia. These patients often emerge smoothly and may be lucid in the post-anesthesia care unit (PACU), but may develop fluctuating mental status, most commonly between postoperative days one and three. General anesthesia (GA) has been identified as a risk factor for POCD. Cranial surgeries involve brain handling in addition to exposure to GA. We hypothesize that the incidence of postoperative delirium after cranial surgery is twice that of spinal surgery. The primary objective of this study was to evaluate the incidence of emergence delirium and postoperative delirium in patients undergoing cranial and spinal neurosurgeries. The secondary objective was to identify the perioperative risk factors of ED and POD. Methods: This was a prospective cohort observation study conducted from March 2020 to September 2023 conducted at a tertiary neurocentre. After obtaining institutional ethics committee approval, adult patients undergoing cranial or spinal surgery with a Glasgow coma scale of 15 were included in the study. Patients undergoing cranial surgery are considered exposed to risk factors, while patients undergoing spinal surgery are considered unexposed. All study subjects received standard general anesthesia. About twenty perioperative parameters were identified as risk factors for POCD. ED was assessed using the Riker sedation agitation scale, and POD was assessed using the confusion assessment method. A sample size of 2000 patients was planned with 1000 each cranial and spinal cases. However, around 700 spinal patients could be recruited for this study. Results: In this study, about two thousand patients were screened for inclusion. However, 1185 cranial cases and 742 spinal cases were considered for final analysis. Both the groups were similar in terms of demographics. Incidence of ED was 25.8% after cranial surgery vs 10.24% after spinal surgery (relative risk 2.5). The incidence of POD after cranial surgery is 20.25% vs 2.15% after cranial surgery (relative risk 9.3). All the proposed risk factors were assessed using binomial logistic regression. Conclusion: Cranial cases expose patients to a nine times higher risk for the development of postoperative delirium. The presence of ED predisposes to POD representing a spectrum.

Keywords: post operative cognitive dysfunction, Neurosurgical patients cohort study, cohort study, emergence delirium

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Authors: Rudainah Alkhazam, Özlem Yaşar Uğurlu

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Immigrant entrepreneurship arises from the start of entrepreneurial activity by immigrants in the country they relocate to. The future prosperity and stability of the refugee-hosting countries depends on the mutual social and economic benefits between the residents and the refugees. Syrian refugees and workers in host countries necessitate efforts to assist their residents and refugees in meeting their daily needs, contributing lawfully to local and possibly regional economies through trade, and instilling hope in their future. This study investigates the effects of Syrian refugee entrepreneurs on host communities' business sectors, focusing on Turkey. Specifically, we examine entrepreneurship in general and its role in the country's economy. Because Turkey is the most popular resettlement destination for Syrian refugees, this study will shed light on the challenges of successful migrant entrepreneurship in Turkey and their role in the business sector. The research relies on a mixed-method approach which helps identify recurring themes, favorable results, and conflicting results across methods, allowing us to draw accurate conclusions. The study will adopt a quantitative method in collecting numerical data from Syrian refugees in Turkey. The self-administered survey would be translated into Arabic to ensure that the respondents understood the questions and possible replies. The research will use survey questionnaires to gather the majority of the data. These surveys would have closed-ended questions with nominal ratio and Likert scales. The data will be analyzed using linear regression and the Statistical Package for Social Sciences (SPSS) to ascertain the role of Syrian entrepreneurs in the business sectors of Turkey. The research will use the findings to make future recommendations. Syrian entrepreneurs, among the migrant entrepreneurs, contribute to the labor market, the majority of whom are young people. This research noted the significant participation of Syrian immigrant women in the entrepreneurship sector. The previous experience of Syrians in the field of trade and running their own business plays a vital role in the success of their business in the host countries. The study shows that Syrian entrepreneurs could integrate effectively into the various Turkish business sectors and could rely on themselves, open and manage their projects, and market them in the Turkish market. Syrian entrepreneurs consider that the investment and labor laws, commercial arrangements, and facilities for obtaining financial resources in Turkey need to be more flexible and available to immigrant entrepreneurs.

Keywords: entrepreneurship, immigration, Syrian, Turkey, refugees, investors, socio-economic benefits, unemployment

Procedia PDF Downloads 66

Authors: Shaine Mehta, Neelam Parmar, Patrick White, Mark Ashworth

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Patients with a history of substance have a high prevalence of comorbidities, including asthma and chronic obstructive pulmonary disease (COPD). Mortality rates are higher than that of the general population and the link to respiratory disease is reported. Randomised controlled trials (RCTs) support opioid substitution therapy as an effective means for harm reduction. However, whilst a high proportion of patients receiving opioid substitution therapy are smokers, to the author’s best knowledge there have been no studies of respiratory disease and smoking intensity in these patients. A cross sectional prevalence study was conducted using an anonymised patient-level database in primary care, Lambeth DataNet (LDN). We included patients aged 18 years and over who had records of ever having been prescribed methadone in primary care. Patients under 18 years old or prescribed buprenorphine (because of uncertainty about the prescribing indication) were excluded. Demographic, smoking, alcohol and asthma and COPD coding data were extracted. Differences between methadone and non-methadone users were explored with multivariable analysis. LDN contained data on 321, 395 patients ≥ 18 years; 676 (0.16%) had a record of methadone prescription. Patients prescribed methadone were more likely to be male (70.7% vs. 50.4%), older (48.9yrs vs. 41.5yrs) and less likely to be from an ethnic minority group (South Asian 2.1% vs. 7.8%; Black African 8.9% vs. 21.4%). Almost all those prescribed methadone were smokers or ex-smokers (97.3% vs. 40.9%); more were non-alcohol drinkers (41.3% vs. 24.3%). We found a high prevalence of COPD (12.4% vs 1.4%) and asthma (14.2% vs 4.4%). Smoking intensity data shows a high prevalence of ≥ 20 cigarettes per day (21.5% vs. 13.1%). Risk of COPD, adjusted for age, gender, ethnicity and deprivation, was raised in smokers: odds ratio 14.81 (95%CI 11.26, 19.47), and in the methadone group: OR 7.51 (95%CI: 5.78, 9.77). Furthermore, after adjustment for smoking intensity (number of cigarettes/day), the risk was raised in methadone group: OR 4.77 (95%CI: 3.13, 7.28). High burden of respiratory disease compounded by the high rates of smoking is a public health concern. This supports an integrated approach to health in patients treated for opiate dependence, with access to smoking cessation support. Further work may evaluate the current structure and commissioning of substance misuse services, including smoking cessation. Regression modelling highlights that methadone as a ‘risk factor’ was independently associated with COPD prevalence, even after adjustment for smoking intensity. This merits further exploration, as the association may be related to unexplored aspects of smoking (such as the number of years smoked) or may be related to other related exposures, such as smoking heroin or crack cocaine.

Keywords: methadone, respiratory disease, smoking cessation, substance misuse

Procedia PDF Downloads 146

Authors: Armin Taheri

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Testosterone levels can impact physical and mental health, with abnormal levels potentially leading to chronic diseases and attention disorders. Further exploration is needed to understand how extremely high testosterone levels affect different population groups. The primary aim of this study is to examine the impact of extremely high levels of testosterone in the blood on chronic diseases and attention disorders. The specific objectives are as follows: i. to compare testosterone levels in athletes and non-athletes, ii. to analyze the association between extremely high testosterone levels and the incidence of chronic diseases, iii. to evaluate the impact of testosterone on attention in hyperactive and typical students. This research was conducted as a cross-sectional study using advanced statistical and technological methods. The study population included male students from boys' schools and male athletes from sports clubs in Shiraz, Iran. Random sampling was performed from 10 schools and 5 sports clubs. The total sample size was 300 participants divided into three groups: 100 professional athletes from sports clubs, 100 non-athletes with no physical activity from boys' schools, 100 students (50 hyperactive and 50 typical) from boys' schools. Testosterone levels were measured using Liquid Chromatography-Mass Spectrometry (LC-MS/MS). This method provides high accuracy in determining hormone concentrations in blood. Data were analyzed using statistical tests, including ANOVA and linear regression, to examine differences and correlations. Professional athletes had significantly higher testosterone levels compared to non-athletes. This increase was associated with improved physical performance and a reduced risk of chronic diseases. Non-athletes with no physical activity generally exhibited lower testosterone levels, which were linked to a higher risk of diabetes and cardiovascular diseases. Hyperactive students had higher testosterone levels, which may be associated with attention disorders and impulsive behaviors. Typical students showed balanced testosterone levels, correlating with better cognitive performance and increased attention. The findings of this study indicate that extremely high levels of testosterone can have varying effects on physical and mental health. While athletes benefit from higher testosterone levels, such levels in hyperactive students may lead to attention disorders and unstable behaviors. The use of LC-MS/MS for precise testosterone measurement is a valuable tool for analyzing these effects. These results emphasize the importance of regulating physical activity and managing hormone levels to promote health.

Keywords: attention disorders, chronic diseases, different population groups, extremely high testosterone levels

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Authors: Rahab Kisio

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The persistent underrepresentation of female miltary in United Nations (UN) peacekeeping missions remains a critical concern for addressing the multifaceted challenges in conflict-affected regions. This research explores the factors influencing countries’ decisions to deploy female military troops to UN peacekeeping operations, examining data ranging from 2010 to 2020. The study highlights the urgent need for policymakers and international organizations to recognize gender equality as key instrument in dealing with sexual exploitation and abuse within these missions. The study suggests three reasons for the low female military troops deployment. Firstly, countries actively breaking down barriers for women in the workforce are more likely to send female military troops. Secondly, nations supporting women in politics are more likely to deploy female military troops, showing their value for gender equality. Lastly, countries with a history of conflict may send more female military troops to align with the UN's call and potentially gain international support in future conflicts. Theoretical approaches are presented to explore these motivations further, and the study uses negative binomial regression with country-year as the unit of analysis to test various explanations for a country's contribution of female military troops to UN peacekeeping missions. Findings shows that there is a connection between troop contributing countries’ gender equality and the participation of female military troops in peacekeeping operations. Nations that prioritize gender equality and empower women have a higher likelihood of deploying more female military personnel. The study emphasizes the significance of women in political leadership, indicating that countries actively addressing barriers to women's political representation are more willing to contribute higher numbers of female military troops to peacekeeping missions. While the research supports hypotheses related to gender equality and political representation, it finds no significant evidence that a country's history of conflict directly influences the deployment of female military troops in other conflict-ridden nations. This research contributes valuable insights into gender equality within peacekeeping forces, shedding light on factors influencing the deployment of female military personnel. The implications underscore the importance of actively addressing discrimination, promoting women's political participation, and understanding the influence of a nation's conflict history. The interdisciplinary nature of this work calls for collaborative efforts from policymakers, international organization, and researchers to formulate strategies for effectively increasing female military troops participation in UN peacekeeping

Keywords: UN peacekeeping, gender diversity, female military troops, discrimination

Procedia PDF Downloads 51

Authors: Praniil Nagaraj

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

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

Procedia PDF Downloads 48

Authors: Roger WUMBA

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The objective of this study was to determine the prevalence of intestinal parasites, with special emphasis on microsporidia and Cryptosporidium, as well as their association with human immunodeficiency virus (HIV) symptoms, risk factors, and other digestive parasites. We also wish to determine the molecular biology definitions of the species and genotypes of microsporidia and Cryptosporidium in HIV patients. In this cross-sectional study, carried out in Kinshasa, Democratic Republic of the Congo, stool samples were collected from 242 HIV patients (87 men and 155 women) with referred symptoms and risk factors for opportunistic intestinal parasites. The analysis of feces specimen were performed using Ziehl–Neelsen stainings, real-time polymerase chain reaction (PCR), immunofluorescence indirect monoclonal antibody, nested PCR-restriction fragment length polymorphism, and PCR amplification and sequencing. Odds ratio (OR) and 95% confidence intervals were used to quantify the risk. Of the 242 HIV patients, 7.8%, 0.4%, 5.4%, 0.4%, 2%, 10.6%, and 2.8% had Enterocytozoon bieneusi, Encephalitozoon intestinalis, Cryptosporidium spp., Isospora belli, pathogenic intestinal protozoa, nonpathogenic intestinal protozoa, and helminths, respectively. We found five genotypes of E. bieneusi: two older, NIA1 and D, and three new, KIN1, KIN2, and KIN3. Only 0.4% and 1.6% had Cryptosporidium parvum and Cryptosporidium hominis, respectively. Of the patients, 36.4%, 34.3%, 31%, and 39% had asthenia, diarrhea, a CD4 count of ,100 cells/mm³, and no antiretroviral therapy (ART), respectively. The majority of those with opportunistic intestinal parasites and C. hominis, and all with C. parvum and new E. bieneusi genotypes, had diarrhea, low CD4+ counts of ,100 cells/mm³, and no ART. There was a significant association between Entamoeba coli, Kaposi sarcoma, herpes zoster, chronic diarrhea, and asthenia, and the presence of 28 cases with opportunistic intestinal parasites. Rural areas, public toilets, and exposure to farm pigs were the univariate risk factors present in the 28 cases with opportunistic intestinal parasites. In logistic regression analysis, a CD4 count of ,100 cells/mm³ (OR = 4.60; 95% CI 1.70–12.20; P = 0.002), no ART (OR = 5.00; 95% CI 1.90–13.20; P , 0.001), and exposure to surface water (OR = 2.90; 95% CI 1.01–8.40; P = 0.048) were identified as the significant and independent determinants for the presence of opportunistic intestinal parasites. E. bieneusi and Cryptosporidium are becoming more prevalent in Kinshasa, Congo. Based on the findings, we recommend epidemiology surveillance and prevention by means of hygiene, the emphasis of sensitive PCR methods, and treating opportunistic intestinal parasites that may be acquired through fecal–oral transmission, surface water, normal immunity, rural area-based person–person and animal–human nfection, and transmission of HIV. Therapy, including ART and treatment with fumagillin, is needed.

Keywords: diarrhea, enterocytozoon bieneusi, cryptosporidium hominis, cryptosporidium parvum, risk factors, africans

Procedia PDF Downloads 126

Authors: Abrar Almutairi, Alyaa Farouk, Amal Gouda

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Background: Social capital is a factor that helps in bonding in a social network. The individual and the neighborhood social capital affect the health status of members of a particular society. In addition, to the influence of social health on the health of the population, social health has a significant effect on women, especially those with pregnancy. Study objective was to assess the impact of the social capital on the health status of pregnant women Design: A descriptive crosssectional correlational design was utilized in this study. Methods: A convenient sample of 210 pregnant women who attended the outpatient antenatal clinicsfor follow-up in King Fahad hospital (Ministry of National Guard Health Affairs/Riyadh) and King Abdullah bin Abdelaziz University Hospital (KAAUH, Ministry of Education /Riyadh) were included in the study. Data was collected using a self-administered questionnaire that was developed by the researchers based on the “World Bank Social Capital Assessment Tool” and SF-36 questionnaire (Short Form Health Survey). The questionnaire consists of 4 parts to collect information regarding socio-demographic data, obstetric and gynecological history, general scale of health status and social activity during pregnancy and the social capital of the study participants, with different types of questions such as multiple-choice questions, polar questions, and Likert scales. Data analysis was carried out by using Statistical Package for the Social Sciences version 23. Descriptive statistic as frequency, percentage, mean, and standard deviation was used to describe the sample characteristics, and the simple linear regression test was used to assess the relationship between the different variables, with level of significance P≤0.005. Result: This study revealed that only 31.1% of the study participants perceived that they have good general health status. About two thirds (62.8%) of the participants have moderate social capital, more than one ten (11.2٪) have high social capital and more than a quarter (26%) of them have low social capital. All dimensions of social capital except for empowerment and political action had positive significant correlations with the health status of pregnant women with P value ranging from 0.001 to 0.010in all dimensions. In general, the social capital showed high statistically significant association with the health status of the pregnant (P=0.002). Conclusion: Less than one third of the study participants had good perceived health status, and the majority of the study participants have moderate social capital, with only about one ten of them perceived that they have high social capital. Finally, neighborhood residency area, family size, sufficiency of income, past medical and surgical history and parity of the study participants were all significantly impacting the assessed health domains of the pregnant women.

Keywords: impact, social capital, health status, pregnant women

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Authors: Andrew Green, Jiaming Liu, Kellathur Srinivasan, Raymond Chua

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Introduction: The size of Singapore’s online health product (HP) market (e-commerce) is largely unknown. However, it is recognized that a large majority comes from overseas and thus, unregulated. As buying HP from unauthorized sources significantly compromises public health safety, understanding e-commerce users’ demographics and their perceptions on online HP purchasing becomes a pivotal first step to form a basis for recommendations in Singapore’s pharmacovigilance efforts. Objective: To assess the prevalence of online HP purchasing behaviour among Singaporean e-commerce users. Methodology: This is a cross-sectional study targeting Singaporean e-commerce users recruited from various local websites and online forums. Participants were not randomized into study arms but instead stratified by random sampling method based on participants’ age. A self-administered anonymous questionnaire was used to explore participants' demographics, online HP purchasing behaviour, knowledge and attitude. The association of different variables with online HP purchasing behaviour was analysed using logistic regression statistics. Main outcome measures: Prevalence of HP e-commerce users in Singapore (%) and variables that contribute to the prevalence (adjusted prevalent ratio). Results: The study recruited 372 complete and valid responses. The prevalence of online HP consumers among e-commerce users in Singapore is estimated to be 55.9% (1.7 million consumers). Online purchasing of complementary HP (46.9%) was the most prevalent, followed by medical devices (21.6%) and Western medicine (20.5%). Multivariate analysis showed that age is an independent variable that correlates with the likelihood of buying HP online. The prevalence of HP e-commerce users is highest in the 35-44 age group (64.1%) and lowest among the 16-24 age group (36.4%). The most bought HP through the internet are vitamins and minerals (21.5%), non-herbal (15.9%), herbal (13.9%), weight loss (8.7%) and sports (8.4%) supplements. While the top 3 products are distributed equally between the genders, there is a skew towards female respondents (12.4% in females vs. 4.9% in males) for weight loss supplements and towards males (13.2% in males vs. 3.7% in females) for sports supplements. Even though online consumers are in the younger age brackets, our study found that up to 72.0% of HP bought online are bought for others (buyer’s family and/or friends). Multivariate analysis showed a statistically significant association between purchasing HP through online means and the perceptions that 'internet is safe' (adjusted Prevalence Ratio=1.15, CI 1.03-1.28), 'buying HP online is time saving' (PR=1.17, CI 1.01-1.36), and 'recognition of HP brand' (PR=1.21 CI 1.06-1.40). Conclusions: This study has provided prevalence data for online HP market in Singapore, and has allowed the country’s regulatory body to formulate a targeted pharmacovigilance approach to this growing problem.

Keywords: e-commerce, pharmaceuticals, pharmacovigilance, Singapore

Procedia PDF Downloads 364

Authors: Thaminda Liyanage, Anuga Liyanage, Chamila Kurukulasuriya, Sidath Bandara

Abstract:

Background: The burden of chronic kidney disease (CKD) is growing rapidly around the world, particularly in Asia. Over the last two decades Sri Lanka has experienced an epidemic of CKD with ever growing number of patients pursuing medical care due to CKD and its complications, specially in the “Mahaweli” river basin in north central region of the island nation. This was apparently a new form of CKD which was not attributable to conventional risk factors such as diabetes mellitus, hypertension or infection and widely termed as “CKD-unknown” or “CKDu”. In the past decade a number of small scale studies were conducted to determine the aetiology, prevalence and complications of CKDu in North Central region. These hospital-based studies did not provide an accurate estimate of the problem as merely 10% or less of the people with CKD are aware of their diagnosis even in developed countries with better access to medical care. Interestingly, similar observations were made on the changing epidemiology of obesity in the region but no formal study was conducted to date to determine the magnitude of obesity burden. Moreover, if increasing obesity in the region is associated with CKD epidemic is yet to be explored. Methods: We will conduct an area wide cross sectional survey among all adult residents of the “Mahaweli” development project area 5, in the North Central Province of Sri Lanka. We will collect relevant medical history, anthropometric measurements, blood and urine for hematological and biochemical analysis. We expect a participation rate of 75%-85% of all eligible participants. Participation in the study is voluntary, there will be no incentives provided for participation. Every analysis will be conducted in a central laboratory and data will be stored securely. We will calculate the prevalence of obesity and chronic kidney disease, overall and by stage using total number of participants as the denominator and report per 1000 population. The association of obesity and CKD will be assessed with regression models and will be adjusted for potential confounding factors and stratified by potential effect modifiers where appropriate. Results: This study will provide accurate information on the prevalence of obesity and CKD in the region. Furthermore, this will explore the association between obesity and CKD, although causation may not be confirmed. Conclusion: Obesity and CKD are increasingly recognized as major public health problems in Sri Lanka. Clearly, documenting the magnitude of the problem is the essential first step. Our study will provide this vital information enabling the government to plan a coordinated response to tackle both obesity and CKD in the region.

Keywords: BMI, Chronic Kidney Disease, obesity, Sri Lanka

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Authors: Angela U. Makolo

Abstract:

Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: Mounir Baccar, Imen Jmal

Abstract:

Because of the rise in energy costs, thermal storage systems designed for the heating and cooling of buildings are becoming increasingly important. Energy storage can not only reduce the time or rate mismatch between energy supply and demand but also plays an important role in energy conservation. One of the most preferable storage techniques is the Latent Heat Thermal Energy Storage (LHTES) by Phase Change Materials (PCM) due to its important energy storage density and isothermal storage process. This paper presents a numerical study of the solidification of a PCM (paraffin RT27) in a rectangular thermal storage exchanger for air conditioning systems taking into account the presence of natural convection. Resolution of continuity, momentum and thermal energy equations are treated by the finite volume method. The main objective of this numerical approach is to study the effect of natural convection on the PCM solidification time and the impact of fins number on heat transfer enhancement. It also aims at investigating the temporal evolution of PCM solidification, as well as the longitudinal profiles of the HTF circling in the duct. The present research undertakes the study of two cases: the first one treats the solidification of PCM in a PCM-air heat exchanger without fins, while the second focuses on the solidification of PCM in a heat exchanger of the same type with the addition of fins (3 fins, 5 fins, and 9 fins). Without fins, the stratification of the PCM from colder to hotter during the heat transfer process has been noted. This behavior prevents the formation of thermo-convective cells in PCM area and then makes transferring almost conductive. In the presence of fins, energy extraction from PCM to airflow occurs at a faster rate, which contributes to the reduction of the discharging time and the increase of the outlet air temperature (HTF). However, for a great number of fins (9 fins), the enhancement of the solidification process is not significant because of the effect of confinement of PCM liquid spaces for the development of thermo-convective flow. Hence, it can be concluded that the effect of natural convection is not very significant for a high number of fins. In the optimum case, using 3 fins, the increasing temperature of the HTF exceeds approximately 10°C during the first 30 minutes. When solidification progresses from the surfaces of the PCM-container and propagates to the central liquid phase, an insulating layer will be created in the vicinity of the container surfaces and the fins, causing a low heat exchange rate between PCM and air. As the solid PCM layer gets thicker, a progressive regression of the field of movements is induced in the liquid phase, thus leading to the inhibition of heat extraction process. After about 2 hours, 68% of the PCM became solid, and heat transfer was almost dominated by conduction mechanism.

Keywords: heat transfer enhancement, front solidification, PCM, natural convection

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Authors: Silvia Portarena, Chiara Anselmi, Chiara Baldacchini, Enrico Brugnoli

Abstract:

Extra virgin olive oil (EVOO) is a complex matrix mainly composed by fatty acid and other minor compounds, among which carotenoids are well known for their antioxidative function that is a key mechanism of protection against cancer, cardiovascular diseases, and macular degeneration in humans. EVOO composition in terms of such constituents is generally the result of a complex combination of genetic, agronomical and environmental factors. To selectively improve the quality of EVOOs, the role of each factor on its biochemical composition need to be investigated. By selecting fruits from four different cultivars similarly grown and harvested, it was demonstrated that Raman spectroscopy, combined with chemometric analysis, is able to discriminate the different cultivars, also as a function of the harvest date, based on the relative content and composition of fatty acid and carotenoids. In particular, a correct classification up to 94.4% of samples, according to the cultivar and the maturation stage, was obtained. Moreover, by using gas chromatography and high-performance liquid chromatography as reference techniques, the Raman spectral features further allowed to build models, based on partial least squares regression, that were able to predict the relative amount of the main fatty acids and the main carotenoids in EVOO, with high coefficients of determination. Besides genetic factors, climatic parameters, such as light exposition, distance from the sea, temperature, and amount of precipitations could have a strong influence on EVOO composition of both major and minor compounds. This suggests that the Raman spectra could act as a specific fingerprint for the geographical discrimination and authentication of EVOO. To understand the influence of environment on EVOO Raman spectra, samples from seven regions along the Italian coasts were selected and analyzed. In particular, it was used a dual approach combining Raman spectroscopy and isotope ratio mass spectrometry (IRMS) with principal component and linear discriminant analysis. A correct classification of 82% EVOO based on their regional geographical origin was obtained. Raman spectra were obtained by Super Labram spectrometer equipped with an Argon laser (514.5 nm wavelenght). Analyses of stable isotope content ratio were performed using an isotope ratio mass spectrometer connected to an elemental analyzer and to a pyrolysis system. These studies demonstrate that RR spectroscopy is a valuable and useful technique for the analysis of EVOO. In combination with statistical analysis, it makes possible the assessment of specific samples’ content and allows for classifying oils according to their geographical and varietal origin.

Keywords: authentication, chemometrics, olive oil, raman spectroscopy

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