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Institution

University of Jordan

EducationAmman, Jordan
About: University of Jordan is a education organization based out in Amman, Jordan. It is known for research contribution in the topics: Population & Health care. The organization has 7796 authors who have published 13764 publications receiving 213526 citations.


Papers
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Journal ArticleDOI
TL;DR: The findings of the present study highlight the high incidence of psychiatric disability and depression in amputees and showed the importance of sociodemographic factors in psychological adjustment to amputation.
Abstract: Objective This study aimed to assess the prevalence of anxiety and depression among Jordanian lower limb amputees with different clinical characteristics and sociodemographic data (gender, marital status, social support, income, type and level of amputation, and occupation). Methods Participants were 56 patients with unilateral lower limb amputation with mean duration (8.4 +/- 5.75 years). They were recruited from inpatient and outpatient clinics of Jordan University hospital, Royal Farah Rehabilitation Center, and Al-basheer hospital in Amman, Jordan. Participants responded to a questionnaire that included a battery of questions requesting brief information about sociodemographic variables and characteristics of amputation. The level of depression and anxiety in each participating patient was assessed by the Hospital Anxiety and Depression Scale (HADS). Results The prevalence of anxiety and depressive symptoms were 37% and 20%, respectively. Factors associated with high prevalence of psychological symptoms included female gender, lack of social support, unemployment, traumatic amputation, shorter time since amputation, and amputation below the knee. These findings were confirmed by a significant reduction of anxiety and depression scores in patients who received social support, patients with amputation due to disease, and patients with amputation above the knee. Presence of pain and use of prosthesis had no effect on the prevalence. Conclusions The findings of the present study highlight the high incidence of psychiatric disability and depression in amputees; it also showed the importance of sociodemographic factors in psychological adjustment to amputation. It is suggested that psychiatric evaluation and adequate rehabilitation should form a part of their overall management.

82 citations

Journal ArticleDOI
TL;DR: Peripheral Neuropathy is highly prevalent among Jordanian patients with type 2 diabetes mellitus and was significantly associated with duration of DM, dyslipidemia, diabetic retinopathy, cardiovascular disease, and unemployment.
Abstract: Peripheral neuropathy is one of the most common microvascular complication of diabetes mellitus. This study is conducted to determine the prevalence of diabetic peripheral neuropathy (DPN) and its associated factors among patients with type 2 diabetes mellitus in Jordan. A cross-sectional study was conducted at the National Center for Diabetes, Endocrinology and Genetics, Jordan. A total of 1003 patients with type 2 diabetes were recruited. Data were collected from participants during a face-to-face structured interview. DPN was assessed using the translated version of Michigan Neuropathy Screening Instrument (MNSI). The overall prevalence of DPN based on MNSI was 39.5%. The most frequently reported symptoms were numbness (32.3%) and pain with walking (29.7%), while the least reported symptoms were the history of amputation (1.3%) and loss of sensation in legs/feet while walking (3.8%). Logistic regression analysis revealed that unemployment, cardiovascular disease, dyslipidemia, diabetic retinopathy and long standing DM (diabetes of ≥ 5 years) were significantly associated with DPN. Peripheral Neuropathy is highly prevalent among Jordanian patients with type 2 diabetes mellitus. DPN was significantly associated with duration of DM, dyslipidemia, diabetic retinopathy, cardiovascular disease, and unemployment. Early detection and appropriate intervention are mandatory among high-risk groups.

82 citations

Journal Article
TL;DR: The early caries development seen in children from the lower socio-economic classes, because they are at high risk for caries in Jordan, reinforces the need for preventive programmes before eruption of the teeth.
Abstract: Objective To describe the prevalence of dental caries among Jordanian preschool children and risk factors for caries. Design Preschool children aged 1 to 5 years from randomly selected nurseries and kindergartens in Amman were surveyed in September 2001. A questionnaire to investigate factors that might have affected dental caries level was completed by parents. Dental caries was diagnosed as recommended by the World Health Organization. Results The mean dmft scores at 1, 2, 3, 4, and 5 years were 0.19, 1.15, 1.7, 2.13, and 3.22 respectively. Overall, 52% of children were caries-free. Caries level was significantly related to feeding practices, snacking habits, oral health practices and pattern of dental visiting as well as to socio-economic background, parents, education level and awareness. Conclusion The dental caries level was slightly higher than that of children in industrialised countries but lower than that of children in the neighbouring Arab countries. However, the early caries development seen in children from the lower socio-economic classes, because they are at high risk for caries in Jordan, reinforces the need for preventive programmes before eruption of the teeth. Access to dental care must be improved to enable any preventive strategies to be implemented.

82 citations

Journal ArticleDOI
TL;DR: A comprehensive ensemble approach composed by optimized and diversified Artificial Neural Networks (ANNs) is proposed for improving the 24h-ahead solar PV power production predictions, which would allow balancing power supplies and demands across centralized grid networks through economic dispatch decisions between the energy sources that contribute to the energy mix.
Abstract: The use of data-driven ensemble approaches for the prediction of the solar Photovoltaic (PV) power production is promising due to their capability of handling the intermittent nature of the solar energy source. In this work, a comprehensive ensemble approach composed by optimized and diversified Artificial Neural Networks (ANNs) is proposed for improving the 24h-ahead solar PV power production predictions. The ANNs are optimized in terms of number of hidden neurons and diversified in terms of the diverse training datasets used to build the ANNs, by resorting to trial-and-error procedure and BAGGING techniques, respectively. In addition, the Bootstrap technique is embedded to the ensemble for quantifying the sources of uncertainty that affect the ensemble models' predictions in the form of Prediction Intervals (PIs). The effectiveness of the proposed ensemble approach is demonstrated by a real case study regarding a grid-connected solar PV system (231 kWac capacity) installed on the rooftop of the Faculty of Engineering at the Applied Science Private University (ASU), Amman, Jordan. The results show that the proposed approach outperforms three benchmark models, including smart persistence model and single optimized ANN model currently adopted by the PV system's owner for the prediction task, with a performance gain reaches up to 11%, 12%, and 9%, for RMSE, MAE, and WMAE standard performance metrics, respectively. Simultaneously, the proposed approach has shown superior in quantifying the uncertainty affecting the power predictions, by establishing slightly wider PIs that achieve the highest confidence level reaches up to 84% for a predefined confidence level of 80% compared to three other approaches of literature. These enhancements would, indeed, allow balancing power supplies and demands across centralized grid networks through economic dispatch decisions between the energy sources that contribute to the energy mix.

82 citations

Journal ArticleDOI
TL;DR: It is suggested that FT-IR spectroscopy may be applicable for detecting the presence of injured and viable but not culturable (VBNC) waterborne pathogens that are underestimated or not discernible using conventional microbial techniques.
Abstract: The effect of chlorine-induced bacterial injury on spectral features using Fourier transform infrared (FT-IR) absorbance spectroscopy was studied using a mixed bacterial culture of (1:1) ca. 500 CFU/mL each Escherichia coli ATCC 25922 and Pseudomonas aeruginosa ATCC 15442 in 0.9% saline. Bacterial cells were treated with 0, 0.3, or 1.0 ppm of initial free chlorine (21 degrees C, 1 h of contact time). Chlorine-injured and dead bacterial cells retained the ATR spectral properties of uninjured or live cells in the region of C-O-C stretching vibrations of polysaccharides, indicative of the cell wall peptidoglycan layer and lipopolysaccharide outer leaflet. This confirms the observations of others that extensive bacterial membrane damage is not a key factor in the inactivation of bacteria by chlorine. The bactericidal effect of chlorine caused changes in the spectral features of bacterial ester functional groups of lipids, structural proteins, and nucleic acids, with apparent denaturation reflected between 1800 and 1300 cm (-1) for injured bacterial cells. Three-dimensional principal component analysis (PCA) showed distinct segregation and clustering of chlorine-treated and untreated cells. Cells exposed to chlorine at 0.3 or 1.0 ppm could be distinguished from the untreated control 73 and 80% of the time, respectively, using soft independent modeling of class analogy (SIMCA) analysis. This study suggests that FT-IR spectroscopy may be applicable for detecting the presence of injured and viable but not culturable (VBNC) waterborne pathogens that are underestimated or not discernible using conventional microbial techniques.

82 citations


Authors

Showing all 7905 results

NameH-indexPapersCitations
Yousef Khader94586111094
Crispian Scully8691733404
Debra K. Moser8555827188
Pierre Thibault7733217741
Ali H. Nayfeh7161831111
Harold S. Margolis7119926719
Gerrit Hoogenboom6956024151
Shaher Momani6430113680
Robert McDonald6257717531
Kaarle Hämeri5817510969
James E. Maynard561419158
E. Richard Moxon5417610395
Liam G Heaney532348556
Stephen C. Hadler5214811458
Nicholas H. Oberlies522629683
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202334
2022163
20211,459
20201,313
20191,166
2018932