Al-Ahliyya Amman University
Recent publications
Carbon emissions are well-established as a major contributor to global warming and other climate change effects. This work experimentally explores the influence of energy consumption, economic development, urbanization, and energy consumption on carbon emission utilizing panel cointegration tests and pooled mean group (PMG-ARDL) approaches, drawing on panel data of the Chinese country from 1995 to 2020. We add urbanization to the model to determine its significance in the interplay between GDP growth, energy consumption, and carbon emissions. The results show that urbanization has no appreciable impact on environmental quality either immediately or in the long term. Energy usage, on the other hand, was proven to considerably increase environmental harm both immediately and over time. Further research indicated that environmental distortion is a long-term effect of economic expansion for the countries studied. The key to achieving a green and clean environment is in the hands of government officials and politicians, who must pay close attention to improving appropriate energy, urban planning, and pollution reduction without slowing economic growth.
Proton exchange membrane fuel cell (PEMFC) designs include multiple variable quantities with various nonlinear factors, which must be determined precisely to guarantee reliable modeling. The characteristic model of fuel cells (FCs) has an essential role in examining these cells' effective investigation. The FC design substantially influences simulation investigations of such methods, which has emerged in various applications. In this paper, a new identification method for the parameters' of the PEMFC is proposed based on using Gorilla Troops Optimizer (GTO). The optimized fitness function in the proposed method is used by the minimum value of the sum of squared errors (SSEs) of the current and estimated voltage cases. Various test cases are utilized to validate the effectiveness of the proposed method. After carrying many independent runs, the comparative algorithms are analyzed using SSEs, and the standard deviation measures. The high ability of the proposed method is investigated using steady-state and dynamic situations. The results showed that the proposed method got promising results and achieved better performance than other well-known comparative methods.
Salak is one of the fruits plants in Southeast Asia; there are at least 30 cultivars of salak. The size, shape, skin color, sweetness or even flesh color will be different depending on the cultivar. Thus, classification of salak based on their cultivar become a daily job for the fruit farmers. There are many techniques that can be used for fruit classification using computer vision technology. Deep learning is the most promising algorithm compared to another Machine Learning (ML) algorithm. This paper presents an image classification method on 4 types of salak (salak pondoh, salak gading, salak sideempuan and salak affinis) using a Convolutional Neural Network (CNN), VGG16 and ResNet50. The dataset consists of 1000 images which having 250 of images for each type of salak. Pre-processing on the dataset is required to standardize the dataset by resizing the image into 224 * 224 pixels, convert into jpg format and augmentation. Based on the accuracy result from the model, the best model for the salak classification is ResNet50 which gave an accuracy of 84% followed by VGG16 that gave an accuracy of 77% and CNN which gave 31%. KeywordsSalak classificationDeep learningCNNResNet50VGG16
The study examines the role of natural resources in improving environmental quality in South Asia. This research focuses primarily on the energy-environmental nexus, ignoring this important region regarding environmental quality proxies and estimation approaches. As a result, the study adopts a unique approach, examining the above mentioned effects using advanced panel data estimation methods for the period 1990–2018. The findings showed that natural resource abundance is positive, indicating its role in increasing environmental degradation in these countries. Moreover, using renewable energy negatively influences the ecological footprint, meaning that it can help reduce environmental degradation in South Asia. Furthermore, the environmental deterioration in South Asia is significantly affected by growth and population, indicating that these countries pursue economic development at the price of rising emissions that harm the environment. Overall, this research suggests that while natural resources, growing population, and economic growth both positively impact environmental quality, using renewable energy sources improves it over time. As a result, these countries need to rethink their plans and create a framework supporting long-term economic development and environmental protection.
This research offers a comprehensive review of the volatility spillover patterns in the Gulf Cooperation Council (GCC) stock market indexes covering daily data from 2/1/2004 to 5/11/2020. During this period, stock markets experienced fluctuations due to unexpected shocks, such as the international financial crisis, oil price shocks and, lately, the pandemic of COVID-19. The findings reveal a substantial increase in the connectedness of returns and volatilities in the GCC bloc during high stress periods with the COVID-19 era marking a historical high. That said, the results do not support significant changes in the directional patterns of volatility during the pandemic. © 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
To solve the problems of sluggish convergence at local minima, a combination of reptile search algorithms with differential evolution (CRSADE) has been developed. The conglomerated algorithm also includes a lens opposition-based learning method, which boosts population diversity and speeds up convergence. The differential evolution algorithm used in the developed CRSADE improves the exploration of the reptile search algorithm through its high ability to locate feasible regions with the best solution. This accelerates convergence by enhancing the end product of the algorithm. The proposed CRSADE helps in designing finite impulse response filters in which absolute error difference is utilized as a fitness function which is minimized by the proposed CRSADE to obtain optimal filter coefficients. To demonstrate its superiority and consistency, a comparison has been made between the developed method and other existing optimization algorithms. The developed filter satisfies the intended objective effectively with lower ripples in the pass band and higher attenuation in the stop band.
Background: Generic switching is a policy that has shown success in minimising pharmaceutical costs. It has also been used to mitigate recurrent and sudden drug shortages. Not all countries have policies that allow pharmacists to switch to generic drugs independently. In Jordan, only pharmacists at Ministry of Health hospitals automatically switch to generics if doctors had not already done INN prescribing. Objectives: This study targeted medical students to assess their experience with generic switching as patients, their knowledge of the subject as students, and their attitude towards it as future prescribers and policymakers. Methods: This is a descriptive, cross-sectional study conducted online. Eligibility criteria were being a fourth, fifth, or sixth-year medical school student enrolled at any of the six Jordanian universities. The questionnaire was developed by the researchers after a careful review of the relevant literature. Results: Three hundred and ninety students responded to the online questionnaire. Most participants were females (244, 62.6%), senior students in their final (6th) year (162, 41.5%) and with very good academic achievement (166, 42.6%). The highest knowledge scores concerned patient rights (0.73/1.00), followed by knowledge about monitoring after generic switching (0.66/1.00), and patients with known drug allergies (0.66/1.00). Almost half of the participants believe that pharmacists should not be given the right to do generic switching and only 16% stated that they would choose generic drugs if they needed treatment in the future. Multivariate linear regression analysis showed that significant predictors of knowledge were gender, GPA, and family income. No correlations were found between participants’ knowledge scores and their attitudes towards giving pharmacists the right to independently switch drugs, or whether they would accept a substitute from pharmacists rather than having to refer to the physician. Conclusion: Medical students in Jordan lack sufficient knowledge about generic switching. Students need to be more aware of the current policies and regulations of this practice, and the role of each healthcare worker involved in it. They also need to have a more positive attitude toward generic drugs and generic switching practice to facilitate its future implementation.
In this research, the performance of hot mix asphalts mixes (HMA) with RAP and RCA was evaluated, in terms of their Marshall stability, flow, and volumetric properties, to verify their applicability as a replacement for the natural aggregate in the flexible pavement surface layers of HMA mixtures. The experimental work was divided into two phases; the first phase investigated the crushed limestone, white hard-rock, and basalt aggregate materials with a nominal maximum aggregate size of 19 mm. The second phase studied the replacement of crushed limestone, by weight, with the RAP and RCA at different asphalt cement contents. The coarse and fine aggregate of the recycled materials were used at four percentages of 25%, 50%, 75%, and 100%, respectively. The experimental test results showed that replacing limestone with recycled aggregate materials affected the mechanical characteristics, mainly the volumetric properties of the HMA. Using RCA in the hot asphalt mixes violated the upper limit of 5% for the air voids property and increased the optimum asphalt content (OAC) up to 5.96% for mixes prepared with 50% RCA. The results also revealed that adding RAP aggregate to the limestone in the HMA improved their Marshall stability, and the highest value of 29.32 kN was recorded for the asphalt mixes prepared with 75% RAP at 3% asphalt content. The combination of RAP and RCA aggregates indicated that as the RCA proportion in the mix increased, lower load capacity was observed and higher OAC compared to the other asphalt mixes.
An experimental program is conducted to investigate the torsional behavior of reinforced concrete beams transversely reinforced with different configurations of continuous stirrups using circular and rectangular schemes. All test specimens have a typical cross-sectional area of 250 × 250 mm, and a length of 1600 mm. The specimens are divided into four groups: two control specimens without transverse reinforcement, seven specimens with transverse reinforcement spaced at 200 mm utilizing four types of transverse reinforcement arrangement, seven specimens with transverse reinforcement spaced at 150 mm using four types of transverse reinforcement arrangement, and seven specimens with transverse reinforcement spaced at 100 mm using four types of transverse reinforcement arrangement. Test results have shown that the use of continuous spiral and rectangular transverse reinforcement has enhanced the ultimate torsional capacity up to 17% compared to the traditional stirrups. The ultimate torsional capacity is predicted using the ACI318-14 equation and compared to the experimental values. It is found that the ACI318-14 torsion equations are applicable and conservative for predicting the ultimate torsional capacity of RC beams with continuous rectangular and spiral reinforcement.
Oligometastatic prostate cancer (omPCa) is a novel intermediate disease state characterized by a limited volume of metastatic cells and specific locations. Accurate staging is paramount to unmask oligometastatic disease, as provided by prostate-specific membrane antigen-positron emission tomography. Driven by the results of prospective trials employing conventional and/or modern staging modalities, the treatment landscape of omPCa has rapidly evolved over the last years. Several treatment-related questions comprising the concept of precision strikes are under development. For example, beyond systemic therapy, cohort studies have found that cytoreductive radical prostatectomy (CRP) can confer a survival benefit in select patients with omPCa. More importantly, CRP has been consistently shown to improve long-term local symptoms when the tumor progresses across disease states due to resistance to systemic therapies. Metastasis-directed treatments have also emerged as a promising treatment option due to the visibility of oligometastatic disease and new technologies as well as treatment strategies to target the novel PCa colonies. Whether metastases are present at primary cancer diagnosis or detected upon biochemical recurrence after treatment with curative intent, targeted yet decisive elimination of disseminated tumor cell hotspots is thought to improve survival outcomes. One such strategy is salvage lymph node dissection in oligorecurrent PCa which can alter the natural history of progressive PCa. In this review, we will highlight how refinements in modern staging modalities change the classification and treatment of (oligo-)metastatic PCa. Further, we will also discuss the current role and future directions of precision surgery in omPCa.
Recently, orthogonal Orbital Angular Momentum (OAM) modes of electromagnetic waves have been widely applied to achieve high spectral efficiency in the radio and microwave regimes. This study investigates utilizing multimodal OAM carrying waves in communications between a central unit and distributed receiving units. Accommodated by a planner grid-array of antenna elements and backed by appropriate pre-coding, the central unit can transmit to each receiving unit multi-OAM modes. A receiving unit comprises a simple circular array. Pre-coding at the transmitting unit is a two-fold process: preventing user-to-user interference and enforcing any predetermined combination of OAM modes to reach its destination. Accordingly, the parallel transmission of multiple channels to each receiver is possible. Channels aimed at the same receiver are distinguished by different modes, but the same group of modes can be simultaneously used upon transmission to other receivers. The numerical results show that significant increase in the transmission capacity is achieved. For instance, in a system including 6 receivers, 25 channels are delivered in parallel to each receiver while maintaining an acceptable low bit-error rate. Results are judged by considering the theoretical single-user quadrature phase shift keying modulation performance as a benchmark for comparison. This study also examines channel perturbations when interfering modes exist. In addition, it overcomes many typical limitations with the utilization of OAM-based solutions in radio, such as the need for transmitter-receiver alignment. The proposed system also solves the problem of wave divergence at high OAM modes, thereby avoiding the exclusion of using these modes in transmission.
Smart government is viewed as the highest modernization stage of public agencies. Governments seek to employ disruptive technologies to substantially transform government-citizen relationships, enhance citizens’ experiences, transform public decision making, emphasize citizen engagement in the democratic decision-making process, provide more agile and resilient government structures, create substantial public value and generally improve quality of life. Despite its numerous potential advantages, smart government is still in its early phases of development. Examining issues related to the usage behavior of smart government services has received little attention. Outcomes of the usage of online technologies in general, and electronic public services in particular, have been largely overlooked. Accordingly, this study aims at developing and empirically validating an integrated model of smart government usage by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) through the incorporation of a set of determinants and outcomes of smart government usage following an extensive review of extant literature. The data were obtained from 414 smart government clients in the United Arab Emirates through an online questionnaire and analyzed using structural equation modeling (SEM). The results of this study indicated that, among all significant antecedents of smart government usage, performance expectancy has the strongest impact, whilst facilitating conditions has the weakest influence. It has been also reported that personalization has no significant effect on smart government usage. The results further revealed that the strongest impact of smart government usage is on information transparency. Implications for theory and practice are also offered.
Advances in recent techniques for scientific data collection in the era of big data allow for the systematic accumulation of large quantities of data at various data-capturing sites. Similarly, exponential growth in the development of different data analysis approaches has been reported in the literature, amongst which the K-means algorithm remains the most popular and straightforward clustering algorithm. The broad applicability of the algorithm in many clustering application areas can be attributed to its implementation simplicity and low computational complexity. However, the K-means algorithm has many challenges that negatively affect its clustering performance. In the algorithm’s initialization process, users must specify the number of clusters in a given dataset apriori while the initial cluster centers are randomly selected. Furthermore, the algorithm's performance is susceptible to the selection of this initial cluster and for large datasets, determining the optimal number of clusters to start with becomes complex and is a very challenging task. Moreover, the random selection of the initial cluster centers sometimes results in minimal local convergence due to its greedy nature. A further limitation is that certain data object features are used in determining their similarity by using the Euclidean distance metric as a similarity measure, but this limits the algorithm’s robustness in detecting other cluster shapes and poses a great challenge in detecting overlapping clusters. Many research efforts have been conducted and reported in literature with regard to improving the K-means algorithm’s performance and robustness. The current work presents an overview and taxonomy of the K-means clustering algorithm and its variants. The history of the K-means, current trends, open issues and challenges, and recommended future research perspectives are also discussed.
Background There is lack of consensus about the effectiveness of neoadjuvant platinum-based chemotherapy in patients with micropapillary variant urothelial carcinoma (MVUC) prior to radical cystectomy. We studied the association between neoadjuvant chemotherapy (NAC) and pathologic response (PR) among patients with micropapillary versus non-variant bladder urothelial carcinoma (UC). Methods We queried the National Cancer Database to identify patients with localized UC and MVUC from 2004 to 2017. We restricted our analysis to patients who underwent radical cystectomy with or without NAC. We compared clinical, demographic, and pathologic characteristics associated with NAC. We used multivariable logistic regression and propensity score matching to examine the association between NAC and the occurrence of a pathologic complete response (pT0) and pathologic lymph node positivity (pN+). Kaplan Meier analyses and Cox proportional hazards models were used to assess overall survival (OS). We performed analyses among subsets of patients with clinical stage II (cT2) disease, as well as the entire cohort (cT2-T4). Results We identified 18,761 patients, including 18,027 with non-variant UC and 734 patients with MVUC. Multivariable analysis revealed that NAC use was associated with greater odds of pT0 (9.64[7.62–12.82], P<0.001), and the association did not differ significantly between MVUC and non-variant UC. In a propensity matched analysis of patients with MVUC, NAC use was associated with higher odds of pT0 (OR 4.93 [2.43–13.18] P<0.001), lower odds of pN+ (OR 0.52 [0.26–0.92] P=0.047) and pathologic upstaging (OR 0.63 [0.34–0.97] P=0.042) in all stages. Similar findings were observed with cT2 disease. No significant association was seen between NAC and OS with MVUC (HR 0.89 [0.46–1.10] P=0.63), including the subset of patients with cT2 (HR 0.83 [0.49–1.06] P=0.58). Conclusions NAC is associated with similar pathologic and nodal responses in patients with localized MVUC and non-variant UC. Improvements in pathologic findings did not translate into OS in this retrospective hospital-based registry study.
This study aims to examine the employee intention to leave their organizations and discover how employee training could affect employee turnover intention. Furthermore, this paper intends to determine the relationship between the variables to present the idea of the impact of training on the ability of organizations to retain their employees. The research hypotheses were tested using the data obtained through a questionnaire. The sample included 160 employees working in 20 Jordanian five-star hotels in Amman, Jordan. The collected data were analyzed using the Smart-PLS software, where all necessary statistical techniques were applied. The results showed that training significantly affects the employees’ intention to leave their jobs. Moreover, the findings indicated that innovative behavior positively mediates the relationship between training and turnover intention. This requires human resource managers in this category of hotels to enhance investment in training and continue to hold training programs that meet the real needs of employees in addition to providing an environment that stimulates and enhances the innovative behavior of employees in the hospitality sector.
Introduction: Despite recent developments in the landscape of urothelial carcinoma (UC) treatment, platinum combination chemotherapy still remains a milestone. Recently immunotherapeutic agents have gained ever-growing attractivity, particularly in the metastatic setting. Novel chemotherapeutic strategies and agents, such as antibody-drug conjugates (ADCs), and powerful combination regimens have been developed to overcome the resistance of most UC to current therapies. Areas covered: Herein, we review the current standard-of-care chemotherapy, the development of ADCs, the rationale for combining therapy regimens with chemotherapy in current trials, and future directions in UC management. Expert opinion: Immunotherapy has prompted a revolution in the treatment paradigm of UC. However, only a few patients experience a long-term response when treated with single-agent immunotherapies. Combination treatments are necessary to bypass resistance mechanisms and broaden the clinical utility of current options. Current evidence supports the intensification of standard-of-care chemotherapy with maintenance immunotherapy. However, the optimal sequence, combination, and duration must be determined to achieve individual longevity with acceptable health-related quality of life. In that regard, ADCs appear as a promising alternative for single and combination strategies in UC, as they specifically target the tumor cells, thereby, theoretically improving treatment efficacy and avoiding extensive off-target toxicities.
Purpose: Guidelines suggest less favorable cancer control outcomes for local tumor destruction in T1a renal cell carcinoma patients with tumor size 3.1-4 cm. We compared cancer-specific mortality between cryoablation vs heat-based thermal ablation in patients with tumor size 3.1-4 cm, as well as in patients with tumor size ≤3 cm. Materials and methods: Within the Surveillance, Epidemiology, and End Results database (2004-2018), we identified patients with clinical T1a stage renal cell carcinoma treated with cryoablation or heat-based thermal ablation. After up to 2:1 ratio propensity score matching between patients treated with cryoablation vs heat-based thermal ablation, we addressed cancer-specific mortality relying on competing risks regression models, adjusted for other-cause mortality and other covariates (age, tumor size, tumor grade, and histological subtype). Results: Of 1,468 assessable patients with tumor size 3.1-4 cm, 1,080 vs 388 were treated with cryoablation vs heat-based thermal ablation, respectively. After up to 2:1 propensity score matching that resulted in 757 cryoablations vs 388 heat-based thermal ablations, in multivariable competing risks regression models, heat-based thermal ablation was associated with higher cancer-specific mortality (HR:2.02, P < .001), relative to cryoablation. Of 4,468 assessable patients with tumor size ≤3 cm, 3,354 vs 1,114 were treated with cryoablation vs heat-based thermal ablation, respectively. After up to 2:1 propensity score matching that resulted in 2,217 cryoablations vs 1,114 heat-based thermal ablations, in multivariable competing risks regression models, heat-based thermal ablation was not associated with higher cancer-specific mortality (HR:1.13, P = .5) relative to cryoablation. Conclusions: Our findings corroborated that in cT1a patients with tumor size 3.1-4 cm, cancer-specific mortality is twofold higher after heat-based thermal ablation vs cryoablation. Conversely, in patients with tumor size ≤3 cm either ablation technique is equally valid. These findings should be considered at clinical decision making and informed consent.
Background and objectives: We examined the effect of disease-free interval (DFI) duration on cancer-specific mortality (CSM)-free survival, otherwise known as the effect of conditional survival, in surgically treated adrenocortical carcinoma (ACC) patients. Methods: Within the Surveillance, Epidemiology, and End Results database (2004-2018), 867 ACC patients treated with adrenalectomy were identified. Conditional survival estimates at 5-years were assessed based on DFI duration and according to stage at presentation. Separate Cox regression models were fitted at baseline and according to DFI. Results: Overall, 406 (47%), 285 (33%), and 176 (20%) patients were stage I-II, III and IV, respectively. In conditional survival analysis, providing a DFI of 24 months, 5-year CSM-free survival at initial diagnosis increased from 66% to 80% in stage I-II, from 35% to 66% in stage III, and from 14% to 36% in stage IV. In multivariable Cox regression models, stage III (hazard ratio [HR]: 2.38; p < 0.001) and IV (HR: 4.67; p < 0.001) independently predicted higher CSM, relative to stage I-II. The magnitude of this effect decreased over time, providing increasing DFI duration. Conclusions: In surgically treated ACC, survival probabilities increase with longer DFI duration. This improvement is more pronounced in stage III, followed by stages IV and I-II patients, in that order. Survival estimates accounting for DFI may prove valuable in patients counseling.
The Internet of Things (IoT) introduces innovative real-time applications that use sensors to collect data that exchange between things to things and things to humans through the network. In this aspect, security and privacy is the primary concern for researchers to protect these systems. This paper proposes a real-time authentication algorithm based on the one-time pad (OTP) principle. The keys are dynamically exchanged, and the data is encrypted via dynamic encryption, depending on random sensors' data. The key is generated and exchanged dynamically using the dynamic encryption technique, thus enhancing the users' data privacy and security. Moreover, a lightweight key generation, exchange, and authentication protocol are proposed for data collecting from smart home sensors. The proposed protocol guarantees security and privacy demand, which are the user's primary concern. The proposed protocol is developed for smart home applications with interfacing requirements, which makes the system real and applicable. The operation principle of the proposed protocol is illustrated sufficiently if there is any desynchronization or emergency.
In light of the technological advancement and green growth in G7 economies, this research investigates the trends in sustainable development goals (SDGs) as reflected through social and environmental dimensions. Data were collected from 2000 to 2019 with yearly observation for advanced panel estimations.The preliminary finding raises the issues of cross-sectional dependency and slope heterogeneity; thus, we have applied the cross-sectional autoregressive distributed lag(CS-ARDL) model.The long-run findings confirm that technological innovations and green growth encourage environmental sustainability. Moreover, economic growth, green technological innovations, and government effectiveness have significantly promoted social development through higher employment opportunities. Similar results are also observed in the short run; however, the influence is more substantial in the long run. These findings imply that green growth, eco-innovations, and institutional governance are core drivers of SDGs in the long run.
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487 members
Ashok K. Shakya
  • Faculty of Pharmacy and Medical Sciences
Manal Ahmad Abbas
  • Medical Laboratory Sciences
Omar Adwan
  • Faculty of Information Technology
Mohammad Alhaj
  • Computer Engineering
Khaldun Mohammad Al Azzam
  • Pharmaceutical Sciences
Amman, Jordan
Head of institution
Prof. Dr. Sadeq Hamed