Search results for: Majeda S. Hammoud
6 Anemia Among Pregnant Women in Kuwait: Findings from Kuwait Birth Cohort Study
Authors: Majeda Hammoud
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Background: Anemia during pregnancy increases the risk of delivery by cesarean section, low birth weight, preterm birth, perinatal mortality, stillbirth, and maternal mortality. In this study, we aimed to assess the prevalence of anemia in pregnant women and its associated factors in the Kuwait birth cohort study. Methods: The Kuwait birth cohort (N=1108) was a prospective cohort study in which pregnant women were recruited in the third trimester. Data were collected through personal interviews with mothers who attend antenatal care visits, including data on socio-economic status and lifestyle factors. Blood samples were taken after the recruitment to measure multiple laboratory indicators. Clinical data were extracted from the medical records by a clinician including data on comorbidities. Anemia was defined as having Hemoglobin (Hb) <110 g/L with further classification as mild (100-109 g/L), moderate (70-99 g/L), or severe (<70 g/L). Predictors of anemia were classified as underlying or direct factors, and logistic regression was used to investigate their association with anemia. Results: The mean Hb level in the study group was 115.21 g/L (95%CI: 114.56- 115.87 g/L), with significant differences between age groups (p=0.034). The prevalence of anemia was 28.16% (95%CI: 25.53-30.91%), with no significant difference by age group (p=0.164). Of all 1108 pregnant women, 8.75% had moderate anemia, and 19.40% had mild anemia, but no pregnant women had severe anemia. In multivariable analysis, getting pregnant while using contraception, adjusted odds ratio (AOR) 1.73(95%CI:1.01-2.96); p=0.046 and current use of supplements, AOR 0.50 (95%CI: 0.26-0.95); p=0.035 were significantly associated with anemia (underlying factors). From the direct factors group, only iron and ferritin levels were significantly associated with anemia (P<0.001). Conclusion: Although the severe form of anemia is low among pregnant women in Kuwait, mild and moderate anemia remains a significant health problem despite free access to antenatal care.Keywords: anemia, pregnancy, hemoglobin, ferritin
Procedia PDF Downloads 455 Gestational Vitamin D Levels Mitigate the Effect of Pre-pregnancy Obesity on Gestational Diabetes Mellitus: A Birth Cohort Study
Authors: Majeda S. Hammoud
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Background and Aim: Gestational diabetes mellitus (GDM) is a common pregnancy complication affecting around 14% of pregnancies globally that carries short and long-term consequences to the mother and her child. Pre-pregnancy overweight or obesity is the most consistently and strongly associated modifiable risk factor with GDM development. This analysis aimed to determine whether vitamin D status during pregnancy modulates the effect of pre-pregnancy obesity/overweight on GDM risk while stratifying by maternal age. Methods: Data from the Kuwait Birth Cohort (KBC) study were analyzed, which enrolled pregnant women in the second or third trimester of gestation. Pre-pregnancy body mass index (BMI; kg/m2) was categorized as under/normal weight (<25.0), overweight (25.0 to <30.0), and obesity (≥30.0). 25 hydroxyvitamin D levels were measured in blood samples that were collected at recruitment and categorized as deficiency (<50 nmol/L) and insufficiency/sufficiency (≥50 nmol/L). GDM status was ascertained according to international guidelines. Logistic regression was used to evaluate associations, and adjusted odds ratios (aOR) and 95% confidence intervals (CI) were estimated. Results: The analyzed study sample included a total of 982 pregnant women, with a mean (SD) age of 31.4 (5.2) years. The prevalence of GDM was estimated to be 17.3% (95% CI: 14.9-19.7), and the prevalence of pre-pregnancy overweight and obesity was 37.8% (95% CI: 34.8-40.8) and 28.8% (95% CI: 26.0-31.7), respectively. The prevalence of gestational vitamin D deficiency was estimated to be 55.3% (95% CI: 52.2-58.4). The association between pre-pregnancy overweight or obesity with GDM risk differed according to maternal age and gestational vitamin D status (Pinteraction[BMI × age × vitamin D = 0.047). Among pregnant women aged <35 years, prepregnancy obesity compared to under/normal weight was associated with increased GDM risk among women with gestational vitamin D deficiency (aOR: 3.65, 95% CI: 1.50-8.86, p = 0.004) and vitamin D insufficiency/sufficiency (aOR: 2.55, 95% CI: 1.16-5.61, p = 0.019). In contrast, among pregnant women aged ≥35 years, pre-pregnancy obesity compared to under/normal weight was associated with increased GDM risk among women with gestational vitamin D deficiency (aOR: 9.70, 95% CI: 2.01-46.69, p = 0.005), but not among women with vitamin D insufficiency/sufficiency (aOR: 1.46, 95% CI: 0.42-5.16, p = 0.553). Conclusion: The effect of pre-pregnancy obesity on GDM risk is modulated by maternal age and gestational vitamin D status, with the effect of pre-pregnancy obesity being more pronounced among older pregnant women (aged ≥35 years) with gestational vitamin D deficiency compared to those with vitamin D insufficiency/sufficiency. Whereas, among younger women (aged <35 years), the effect of pre-pregnancy obesity on GDM risk was not modulated by gestational vitamin D status. Therefore, vitamin D supplementation among pregnant women, specifically older women with pre-pregnancy obesity, may mitigate the effect of pre-pregnancy obesity on GDM risk.Keywords: gestational diabetes mellitus, vitamin D, obesity, body mass index
Procedia PDF Downloads 294 Modal Analysis of a Cantilever Beam Using an Inexpensive Smartphone Camera: Motion Magnification Technique
Authors: Hasan Hassoun, Jaafar Hallal, Denis Duhamel, Mohammad Hammoud, Ali Hage Diab
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This paper aims to prove the accuracy of an inexpensive smartphone camera as a non-contact vibration sensor to recover the vibration modes of a vibrating structure such as a cantilever beam. A video of a vibrating beam is filmed using a smartphone camera and then processed by the motion magnification technique. Based on this method, the first two natural frequencies and their associated mode shapes are estimated experimentally and compared to the analytical ones. Results show a relative error of less than 4% between the experimental and analytical approaches for the first two natural frequencies of the beam. Also, for the first two-mode shapes, a Modal Assurance Criterion (MAC) value of above 0.9 between the two approaches is obtained. This slight error between the different techniques ensures the viability of a cheap smartphone camera as a non-contact vibration sensor, particularly for structures vibrating at relatively low natural frequencies.Keywords: modal analysis, motion magnification, smartphone camera, structural vibration, vibration modes
Procedia PDF Downloads 1413 Treatment of Septic Tank Effluent Using Moving Bed Biological Reactor
Authors: Fares Almomani, Majeda Khraisheh, Rahul Bhosale, Anand Kumar, Ujjal Gosh
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Septic tanks (STs) are very commonly used wastewater collection systems in the world especially in rural areas. In this study, the use of moving bed biological reactors (MBBR) for the treatment of septic tanks effluents (STE) was studied. The study was included treating septic tank effluent from one house hold using MBBRs. Significant ammonia removal rate was observed in all the reactors throughout the 180 days of operation suggesting that the MBBRs were successful in reducing the concentration of ammonia from septic tank effluent. The average ammonia removal rate at 25◦C for the reactor operated at hydraulic retention time of 5.7 hr (R1) was 0.540 kg-N/m3and for the reactor operated at hydraulic retention time of 13.3hr (R2) was 0.279 kg-N/m3. Ammonia removal rates were decreased to 0.3208 kg-N/m3 for R1 and 0.212 kg-N/m3 for R3 as the temperature of reactor was decreased to 8 ◦C. A strong correlation exists between theta model and the rates of ammonia removal for the reactors operated in continuous flow. The average ϴ values for the continuous flow reactors during the temperature change from 8°C to 20 °C were found to be 1.053±0.051. MBBR technology can be successfully used as a polishing treatment for septic tank effluent.Keywords: septic tanks, wastewater treatment, morphology, moving biological reactors, nitrification
Procedia PDF Downloads 3362 Synthesis of High-Antifouling Ultrafiltration Polysulfone Membranes Incorporating Low Concentrations of Graphene Oxide
Authors: Abdulqader Alkhouzaam, Hazim Qiblawey, Majeda Khraisheh
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Membrane treatment for desalination and wastewater treatment is one of the promising solutions to affordable clean water. It is a developing technology throughout the world and considered as the most effective and economical method available. However, the limitations of membranes’ mechanical and chemical properties restrict their industrial applications. Hence, developing novel membranes was the focus of most studies in the water treatment and desalination sector to find new materials that can improve the separation efficiency while reducing membrane fouling, which is the most important challenge in this field. Graphene oxide (GO) is one of the materials that have been recently investigated in the membrane water treatment sector. In this work, ultrafiltration polysulfone (PSF) membranes with high antifouling properties were synthesized by incorporating different loadings of GO. High-oxidation degree GO had been synthesized using a modified Hummers' method. The synthesized GO was characterized using different analytical techniques including elemental analysis, Fourier transform infrared spectroscopy - universal attenuated total reflectance sensor (FTIR-UATR), Raman spectroscopy, and CHNSO elemental analysis. CHNSO analysis showed a high oxidation degree of GO represented by its oxygen content (50 wt.%). Then, ultrafiltration PSF membranes incorporating GO were fabricated using the phase inversion technique. The prepared membranes were characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM) and showed a clear effect of GO on PSF physical structure and morphology. The water contact angle of the membranes was measured and showed better hydrophilicity of GO membranes compared to pure PSF caused by the hydrophilic nature of GO. Separation properties of the prepared membranes were investigated using a cross-flow membrane system. Antifouling properties were studied using bovine serum albumin (BSA) and humic acid (HA) as model foulants. It has been found that GO-based membranes exhibit higher antifouling properties compared to pure PSF. When using BSA, the flux recovery ratio (FRR %) increased from 65.4 ± 0.9 % for pure PSF to 84.0 ± 1.0 % with a loading of 0.05 wt.% GO in PSF. When using HA as model foulant, FRR increased from 87.8 ± 0.6 % to 93.1 ± 1.1 % with 0.02 wt.% of GO in PSF. The pure water permeability (PWP) decreased with loadings of GO from 181.7 L.m⁻².h⁻¹.bar⁻¹ of pure PSF to 181.1, and 157.6 L.m⁻².h⁻¹.bar⁻¹ with 0.02 and 0.05 wt.% GO respectively. It can be concluded from the obtained results that incorporating low loading of GO could enhance the antifouling properties of PSF hence improving its lifetime and reuse.Keywords: antifouling properties, GO based membranes, hydrophilicity, polysulfone, ultrafiltration
Procedia PDF Downloads 1381 Implementation of Correlation-Based Data Analysis as a Preliminary Stage for the Prediction of Geometric Dimensions Using Machine Learning in the Forming of Car Seat Rails
Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali
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When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis
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