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Abstract Aim To assess the prevalence and compare the levels of intimate partner violence (IPV) before and during the pandemic and to identify the factors that associated with physical IPV among Jordanian pregnant women. Design A cross‐sectional, correlational design. Women were asked to report their experience with IPV twice: during and before the pandemic. Methods A convenience sampling technique was used to select pregnant women from National Woman's Health Care Center from 15 April to 1 September 2021. The Domestic Violence Questionnaire Screening Tool (DVQST) was used to assess the levels of IPV. Results The women (n = 232) who participated in the study experienced considerable levels of IPV before (69% control IPV, 59.90% psychological, 46.10% physical, 43.10% sexual) and during (75.90% control IPV, 64.20% psychological, 46.10% physical, 40.90% sexual) the pandemic. There were statistically significant (p ≤ 0.05) higher mean DVQST scores for control IPV and psychological IPV during the pandemic (control IPV mean = 9.78, psychological mean = 7.03) versus before the pandemic (control IPV mean = 8.95, psychological mean = 6.62). Woman's educational level, marriage duration, woman's employment status, and level of mutual understanding were inversely associated with physical IPV during the pandemic. Patient or Public Contribution IPV is a global public health problem and a major violation of human rights. The levels of control IPV and psychological IPV increased during the COVID‐19 pandemic, while the levels of physical and sexual IPV stayed the same. Antenatal screening for IPV is crucial to save women and their offspring from suffering this type of violence.

Abstract Background Resilience has a paramount role in dealing with different life stressors and has a great impact on mental health. Aim To assess the level of resilience among university students and explore the relation between resilience and a number of variables including psychological well-being, self-esteem and physical health. Methods A cross-sectional design was utilized. Data was collected from 676 university students. Students were required to complete a demographic sheet, Brief Resilience Scale, World Health Organization Well-Being Index, Rosenberg Self-Esteem Scale and a physical health survey. Results Overall, less than half of the participants have reported low levels of resilience (45.3%; n = 306). Regular sleep, perceived stress, WHO well-being index, self-esteem, and having a cumulative GPA of more than two, were factors that significantly predicted positive resilience in multivariate analysis. Conclusion Resilience is a necessary skill among university students that requires more academic attention. Factors predicting positive resilience should be considered when implementing mental health promotion programs.

To obtain efficient photovoltaic (PV) systems, optimum maximum power point tracking (MPPT) algorithms are inevitable. The efficiency of MPPT algorithms depends on two MPPT parameters, i. e., perturbation amplitude and perturbation period. The optimization of MPPT algorithms affect both the tracking speed and steady-state oscillation. In this paper, optimization methods of MPPT parameters are reviewed and classified into fixed and variable methods. The fixed MPPT parameters are constant during MPPT performance, and a trade-off should be made between the tracking speed and steady-state oscillation. However, the variable MPPT parameters will be changed to improve both the tracking speed and the steady-state oscillations. Moreover, some of them are simulated, compared, and discussed to evaluate the real contributions of the optimization methods to the MPPT efficiency. Furthermore, significant features of the optimization methods, i.e., noise immunity, robustness, and computation effort, are investigated.

Abstract Reservoir simulation is established as a good practice to make the best decision for a petroleum reservoir. The reservoir is characterized in terms of reservoir elements such as structural model, well data, rock and fluid properties. Then the reservoir model is enhanced through history matching and finally different prediction scenarios are tried to find the best plan for the reservoir understudy. The more accurate the reservoir is characterized, the faster and the more precisely the history match is finished and the more reliable predictions are obtained. The most important part of reservoir characterization is the rock typing, where the quality of CCAL (conventional core analysis) and SCAL (special core analysis) properties are evaluated and estimated for any simulation grid. The resulting oil in place must be confirmed by the OOIP (original oil in place) calculated based on average petro-physical parameters for any layer. To allocate different rock types to simulation grid, rock types should be assigned according to different ranges of rock differentiation parameter which has to be determined in any specific study. Based on our experience in Iranian carbonate reservoirs, most frequently irreducible water saturation is the rock differentiation parameter. In the oil zone, water saturation from log data is assumed to be the irreducible water saturation. Thus, the rock type is identified with no trouble. The problem arises in transition zone, where water saturation from log data is not equal to the irreducible water saturation of that rock. This study includes the observed variations in terms of water saturation data versus depth and how to assign rock types to the transition zone grids. The objective of the capillary-based method is to produce a water saturation map which honors laboratory data as well as the well log data and considers the depth so that it can handle the transition zone in a proper manner. In fact, novelty of this work is to explain how it is possible to consider log and capillary pressure data together so that the most accurate rock type is assigned to reservoir grids of the transition zone. Moreover, this method is consistent with equilibration method for initializing reservoir simulations. A procedure is presented for how to implement the capillary-based method in a stepwise manner. Once the proposed method is carried out, the initialized simulation model is consistent with all sources of data (core analysis and petro-physical data). In this procedure original oil in place calculated after the initialization for simulation is more accurate and can be cross-checked with volumetric calculation based on interpreted log data. Therefore, it is considered to facilitate subsequent stages of reservoir study, namely history match and prediction.

Introduction: Estrogen hormones and their metabolites are implicated in the maintenance of healthy pregnancy and adequate fetal development. Abnormal levels were related to increased risk of pregnancy complications, particularly preeclampsia. Our aims were (1) to develop a methodological platform for the comprehensive assessment of estrogen metabolome in pregnancy; (2) to collect healthy reference data for relevant elements of estrogen metabolome in each trimester; (3) to assess unconjugated fractions of the estrogen metabolome, (4) to assess the dominant metabolic pathways of estrogen compounds., Methods: We enrolled healthy pregnant mothers between gestational week 5-15 (on the confirmation of pregnancy; 79 samples), gestational weeks 19-27 (70 samples), and gestational week 34-39 (54 samples). A method employing liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed to assess estrone, 17-beta-estradiol, estriol levels, and their metabolites as conjugated and unconjugated forms. Descriptive statistics were used to characterize the level of compounds in each trimester., Results: Estrone, 17-beta-estradiol and estriol levels are dramatically increasing with the advancement of pregnancy. Measured levels were in a very wide range. 17-beta-estradiol is neither glucuronated nor sulphated. To the contrary, estriol and estrone are significantly conjugated; unconjugated fraction is <15% of total hormone levels in any trimester. Regarding metabolism, 4-methoxy-estradiol and 17-epiestriol were not detected., Conclusion: We concluded that (1) the levels of estrogen compounds and metabolites increase with advancing gestational age; (2) the wide ranges of levels challenge the establishment of a healthy reference range for clinical purposes; (3) 17-beta-estradiol is not conjugated significantly; (4) 4-methylation and 17-epimerization pathways of estrogens are negligible with our LC-MS/MS method., Competing Interests: Declaration of competing interest As the corresponding author of this submitted manuscript hereby I declare that there is NO conflict of interest regarding the present study and any of co-authors., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Hemoglobin A1c (HbA1c) is used to monitor glucose homeostasis and to identify risk for diabetes. As diabetic patients are frequently present with dyslipidaemia, low-grade inflammation and hyperuricemia, we tested whether HbA1c levels can be estimated having the information about lipid profile, uric acid (UA) and C-reactive protein (CRP) levels. We developed formulas to describe the association of these parameters with HbA1c levels., Methods: Data of 9599 male and 10,817 female patients, measured between 2008 and 2018, were analysed. Patients represented a general hospital patient population with overrepresentation of those with elevated HbA1c over 5.6%. The impact of gender, age, CRP, lipid profile and UA levels on HbA1c % on HbA1c levels was tested with multiple linear regression model. The magnitude of effects of individual factors was used to develop formulas to describe the association between HbA1c and other cardiometabolic parameters. With these formulas we estimated median HbA1c values in each age in both gender and compared them to measured HbA1c levels., Results: The developed formulas are as follow: HbA1c (estimated) in women = 0.752 + 0.237*log10(HDL/cholesterol) + 0.156*log10 (cholesterol) + 0.077*log10 (triglyceride) + 0.025*log10(CRP) +0.001*log10 (age) -0.026*log10(HDL/LDL) -0.063*log10 (uric acid)-0.075*log10 (LDL)-0.199*log10(HDL); HbA1c (estimated) in men = 1.146 + 0.08*log10 (triglyceride) + 0.046*log10(CRP) + 0.01*log10 (cholesterol) + 0.001*log10 (age) -0.014*log10(HDL)-0.018*log10(HDL/LDL)-0.025*log10(HDL/cholesterol) -0.068*log10 (LDL)-0.159*log10 (uric acid) Between 20 and 70 years of age, estimated HbA1c matched perfectly to measured HbA1c in., Conclusion: At population level, HbA1c levels can be estimated almost exactly based on lipid profile, CRP and uric acid levels in female patients between 20 and 70 years., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Vitamin D deficiency has been linked to a higher risk of prostate cancer. We tested the hypothesis that vitamin D levels would have an impact on prostate specific antigen (PSA) levels., Methods: From our laboratory database we selected 5136 male patients with simultaneously determined vitamin D and PSA levels. Subgroups of several age cohorts with different vitamin D levels were created and PSA 95 percentile values were assessed. The independent effect of vitamin D levels and age on PSA levels was determined with logistic regression., Results: PSA levels increased with age, while no difference was identified in PSA levels in different vitamin D subgroups., Conclusion: Vitamin D levels do not have an effect on PSA. Hence, there is no need to adjust PSA reference ranges and threshold values to vitamin D levels during the process of decision making., (Copyright © 2020 International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). All rights reserved.)