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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Rana Muhammad Adnan; Abolfazl Jaafari; Aadhityaa Mohanavelu; Ozgur Kisi; +1 Authors

    The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

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    Sustainability
    Other literature type . Article . 2021 . Peer-reviewed
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Article . 2021
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Other literature type . Article . 2021 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Karishma M. Qureshi; Bhavesh. G. Mewada; Saleh Y. Alghamdi; Naif Almakayeel; +2 Authors

    Business enterprises such as small and medium-sized enterprises (SMEs) play a significant role in economic development but struggle for sustainability. A business enterprise such as a manufacturing unit tries many technological innovations and strategic initiatives to accomplish sustainability in the manufacturing system. Lean manufacturing implementation is one such initiative that helps SMEs manufacture value-added products with increased profitability and waste minimization. However, lean implementation in SMEs is challenging. Hence, it is essential to follow a systematic framework and control the critical success factors (CSFs) in attempting lean implementation. The purpose of this research is to find, evaluate, and rank the CSFs of lean implementation of SMEs so that they may be controlled to accomplish successful lean implementation. The CSFs of lean implementation found by an in-depth assessment of the literature are modeled using the interpretative structural modeling (ISM) approach. MICMAC analysis is also used in classifying and understanding the significance of each lean implementation CSF. ISM and MICMAC provide the relationship modeling to reveal the inter-relationships of each lean implementation CSF. Subsequently, the ISM model is validated using the Delphi technique. The interpretative ranking process (IRP) has been applied to rank the CSFs of lean implementations. The results show that sustainability in a manufacturing system, financial capability, and employee involvement hold significant importance in lean implementations in manufacturing SMEs. Practicing managers may benefit from revisiting their lean implementation plans and respective aligned strategies. They will also be in a position to identify and focus on the scarce resources required for the subsequent lean implementations.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Farid S. Nassar; Ahmed O. Abbas; Abdulaziz A. Alaqil; Nancy N. Kamel;

    The negative impacts of high stocking density on the commercial poultry industry compromise sustainable birds’ productivity and welfare. Thus, we investigated the potential of colocynth seed (CC) supplementation in alleviating the negative impacts of high stocking density on broilers’ performance, immunity, inflammation, and redox status. A total of 648 one-day-old male Cobb 500 chicks were recruited and distributed into 2 × 2 factorial arrangements. The treatment groups were assigned based on stocking density as low stocking density (9 birds/m2; LSD) or high stocking density (19 birds/m2; HSD), and CC supplementation as without (0 g/kg feed; −CC) or with (1 g/kg feed; +CC) supplementation. Data were collected from week three to week five of age. Production performance was monitored and meat quality was assessed. Blood samples were collected to measure stress markers, humoral immune response, inflammatory cytokines, and antioxidant activity levels. The results indicated that HSD induced production performance reduction, immunosuppression, and imbalance redox status, along with elevation in inflammation and stress markers levels. Breast meat weight and yield were reduced in the HSD groups by 9 and 1%, respectively, compared to LSD groups. However, CC supplementation to HSD birds was able to slightly improve daily weight gain, body weight gain, and breast weight, showing no significant difference compared to the LSD-CC group, and significantly increased breast yield. Furthermore, CC supplementation significantly reduced inflammatory cytokines and stress markers levels. Under HSD, both cell-mediated and humeral immune responses were elevated with CC supplementation compared with the non-supplemented group. It can be concluded that HSD is a detrimental factor in the commercial poultry industry, which generates oxidative and inflammatory responses and, subsequently, immunosuppression and impaired performance. Nevertheless, dietary CC supplementation can be used as a natural antioxidant source to mitigate the negative impacts of HSD on broilers’ production performance, as well as physiological competency.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Noura Metawa; Mohamemd I. Alghamdi; Ibrahim M. El-Hasnony; Mohamed Elhoseny;

    Recently, bitcoin-based blockchain technologies have received significant interest among investors. They have concentrated on the prediction of return and risk rates of the financial product. So, an automated tool to predict the return rate of bitcoin is needed for financial products. The recently designed machine learning and deep learning models pave the way for the return rate prediction process. In this aspect, this study develops an intelligent return rate predictive approach using deep learning for blockchain financial products (RRP-DLBFP). The proposed RRP-DLBFP technique involves designing a long short-term memory (LSTM) model for the predictive analysis of return rate. In addition, Adam optimizer is applied to optimally adjust the LSTM model’s hyperparameters, consequently increasing the predictive performance. The learning rate of the LSTM model is adjusted using the oppositional glowworm swarm optimization (OGSO) algorithm. The design of the OGSO algorithm to optimize the LSTM hyperparameters for bitcoin return rate prediction shows the novelty of the work. To ensure the supreme performance of the RRP-DLBFP technique, the Ethereum (ETH) return rate is chosen as the target, and the simulation results are investigated in different measures. The simulation outcomes highlighted the supremacy of the RRP-DLBFP technique over the current state of art techniques in terms of diverse evaluation parameters. For the MSE, the proposed RRP-DLBFP has 0.0435 and 0.0655 compared to an average of 0.6139 and 0.723 for compared methods in training and testing, respectively.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Sustainabilityarrow_drop_down
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    Other literature type . Article . 2021 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Esraa A. Elsherbiny; Mohamed Mortagi; Osama Youssf; Mohamed Abd Elrahman; +1 Authors

    Structural lightweight concrete is preferred over traditional concrete due to its ability to reduce the dead load, minimize the size of load-bearing structural members, and provide more economical solutions for foundation deteriorations. This research sheds light on sustainable lightweight concrete using waste crushed clay bricks (CCB) as a lightweight aggregate. To reduce micro-crack propagation of the developed concrete, two types of fiber were implemented and investigated. Steel fibers (SF) with amounts of 0.5% and 1.0% by volume of concrete, and polypropylene fibers (PPF) with amounts of 0.1% and 0.2% by volume of concrete, were employed. Five reinforced concrete beams were made and tested in order to precisely evaluate the structural behavior of the proposed lightweight CCB concrete. Additionally, ABAQUS software for nonlinear finite element analysis has been utilized to simulate the tested beams and compare the numerical model predictions with the experimental findings. The findings revealed that the addition of SF and PPF exhibited a notable influence on enhancing the mechanical characteristics of lightweight CCB concrete. Adding 0.2% PPF increased the ultimate load and deformation capacity at failure by approximately 16% and 24%, respectively. Furthermore, after 28 days, the addition of 0.5% and 1.0% SF enhanced the compressive strength by around 11.7% and 17.6%, respectively. Moreover, a significant level of consistency between the results obtained from the numerical model and the experimental findings was observed. In general, the use of SF and PPF in CCB concrete successfully produced high-quality lightweight concrete with interesting results for use in reinforced concrete beams.

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    Authors: Dania M. Allami; Mohamed T. Sorour; Medhat Moustafa; Ahmed Elreedy; +1 Authors

    Life cycle assessment (LCA) is a powerful tool to evaluate the environmental impacts of domestic wastewater treatment plant (WWTP) operations. It involves a thorough evaluation of the main characteristics or components of the environment, human health, and resources. However, the literature to date is still lacking analysis on the widely varied designs and operational conditions of full-scale WWTPs. The aim here was to integrate analyses such as LCA, greenhouse gas (GHG) emissions, and energy consumption, when considering the environmental impacts of a full-scale WWTP, which can provide practical outputs to aid decision-making on optimum designs and operational conditions. The Russtmiya domestic WWTP, located in Iraq, was considered as the case study. Three operational alternatives were proposed as solutions to improve the WWTP’s performance, as follows: (1) conventional activated sludge with sand filter (CAS), (2) conventional activated sludge with sand filter and nitrogen removal (CAS-N), and (3) membrane bioreactor (MBR). The operation of such alternatives was investigated through modeling and simulation using GPS-X 8.0.1 software. The energy consumption of each alternative was estimated via GPS-X, while the GHG emissions were estimated using three different methods according to the intergovernmental panel on climate change (IPCC), the United States Environmental Protection Agency (USEPA), and GPS-X software. The OpenLCA software (1.10.3) was used to measure all impact categories at both the midpoint and endpoint levels using various methods. As a conclusion, comparing the three proposed alternatives indicated that: (1) the MBR alternative provided the lowest energy consumption and moderate GHG emissions, and (2) the CAS alternative provided the best environmental performance, particularly in aspects such as ozone depletion, global warming, and climate change, where the lowest GHGs emission values had the major contribution.

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    Authors: Ahmad K. Hegazy; Zahra S. Hussein; Nermen H. Mohamed; Gehan Safwat; +3 Authors

    Petroleum oil pollution is a worldwide problem that results from the continuous exploration, production, and consumption of oil and its products. Petroleum hydrocarbons are produced as a result of natural or anthropogenic practices, and their common source is anthropogenic activities, which impose adverse effects on the ecosystem’s nonliving and living components including humans. Phytoremediation of petroleum hydrocarbon-polluted soils is an evolving, low-cost, and effective alternative technology to most traditional remediation methods. The objective of this study is to evaluate the phytoremediation potentiality of Vinca rosea for crude oil-contaminated soil by understanding its properties and involvement in the enhanced degradation of crude oil. The remediation potentiality was determined by evaluating the total petroleum hydrocarbon degradation percentage (TPH%) and changes in the molecular type composition of saturated and aromatic hydrocarbon fractions. TPH% was estimated gravimetrically, and changes in the molecular type composition of saturated and aromatic fractions were measured using gas chromatography and high-performance liquid chromatography, respectively. Sulfur concentration was measured using X-ray fluorescence. Cadmium and lead quantification was measured using Inductively Coupled Plasma-Atomic Emission Spectrometry (ICP-AES). The results revealed that V. rosea enhanced total petroleum hydrocarbon (TPH) degradation and altered the molecular composition of the crude oil. The saturated hydrocarbons increased and the aromatic hydrocarbons decreased. The saturated hydrocarbon fraction in the crude oil showed a wider spectrum of n-paraffin peaks than the oil extracted from unplanted and V. rosea-planted soils. Polyaromatic hydrocarbon degradation was enhanced in the presence of V. rosea, which was reflected in the increase of monoaromatic and diaromatic constituents. This was parallel to the increased sulfur levels in planted soil. The determination of sulfur and heavy metal content in plant organs indicated that V. rosea can extract and accumulate high amounts from polluted soils. The ability of V. rosea to degrade TPH and alter the composition of crude petroleum oil by decreasing the toxicity of polyaromatic hydrocarbons in soil, as well as its capability to absorb and accumulate sulfur and heavy metals, supports the use of plant species for the phytoremediation of crude oil-polluted sites.

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    Authors: Saeed Mousa; Abdullah S. Alomari; Sabrina Vantadori; Waleed H. Alhazmi; +2 Authors

    Natural fibers (NFs) have recently been the center of attention among researchers due to their low cost, availability, ease of manufacture, and potential environmental friendliness as reinforcing agents in composites. The present work deals with the mechanical behavior of palm fiber-reinforced epoxy-based composites with different weight percentage (Wt.%) ratios, ranging from 6% to 31.6%. Glass and hybrid fiber-reinforced epoxy-based composites were also examined. The indirect tensile test, i.e., diametral tensile test (DTT) and the small punch test (SPT), were used in the present work to determine the mechanical properties of the epoxy reinforced with discontinuous random oriented short fibers. Furthermore, short glass fibers were used to compare with palm fiber-reinforced epoxy. In addition, morphology observations of epoxy residue clinging to the natural fibers were carried out using the optical microscope and Scanning Electron Microscopy (SEM). The results showed that the natural fiber has a better adhesion bonding between the palm fiber/epoxy than that of glass fiber/epoxy. Therefore, adding palm fibers improves epoxy’s mechanical properties compared with synthetic glass fibers. The composite with high Wt.% of NF showed the highest diametral tensile strength (DTS), 21.74 MPa, over other composites. The DTS of composites with medium and low Wt.% of NF was lower than that of the high Wt.% by 14% and 30%, respectively.

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    Authors: Touny, Ahmed S. El; Ibrahim, Ahmed H.; Mohamed, Hossam H.;

    A construction project is a dynamic and complex process that involves the identification and accurate fulfillment of the predetermined needs and requirements of the clients by the project team. There are many challenges and constraints that prevent the achievement of these predetermined and various requirements effectively and successfully, so the project team must face and overcome these challenges by identifying all the factors that help the project’s success. However, it is still unclear how to measure success for Egyptian construction projects. Despite the fact that several lists of literature-based factors have been compiled, the individual factors appear to be tabulated rather than grouped according to some criteria to aid in the analysis of their interactions and potential consequences. As such, the objective presented in this paper was to identify and prioritize integrated sustainable critical success factors (ISCSFs) that influence the performance of Egyptian construction projects to ensure successful construction projects. Critical success factors were identified and grouped into 2 major categories—(1) internal related factors and (2) external related factors—and 10 subcategories—(1) company-related factors thus, 100 factors were identified, filtered and developed. In the third stage, a questionnaire was created based on the significant factors identified. As a result, the 40 most important factors influencing the success of performance of construction projects have been identified, which are integrated between all factors (internal and external) and take into account the three pillars of sustainability (economic, social and environmental) as a decision-making tool to evaluate and improve project performance. and (10) industry-related factors in three distinct stages. In total, 140 factors were gathered from the literature review in the first stage. In the second stage, a brainstorming session was held in order to reduce the number of those factors and focus on the most important ones that influence project success (6) support-related factors (financial, human resources, security and legal and administration) (4) resource/procurement-related factors (labors, materials, equipment and subcontractors) (7) stakeholder-related factors (clients, consultants, project managers and end-users) (8) innovation, learning and growth-related factors (3) project management related factors (5) human capital-related factors (9) country-related factors (2) project-related factors

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    Authors: Ahlam H. Tolba; Chrisogonus K. Onyekwere; Ahmed R. El-Saeed; Najwan Alsadat; +2 Authors

    A novel lifetime distribution has been defined and examined in this study. The odd Lindley–Pareto (OLiP) distribution is the name we give to the new distribution. The new density function can be written as an odd Lindley-G distribution with Pareto amplification. The moment-generating function and characteristic function, entropy and asymptotic behavior, order statistics and moments, mode, variance, skewness, and kurtosis are some of the aspects of the OLiP distribution that are discovered. Seven non-Bayesian estimation techniques and Bayesian estimation utilizing Markov chain Monte Carlo were compared for performance. Additionally, when the lifetime test is truncated after a predetermined period, single acceptance sampling plans (SASPs) are created for the newly suggested, OLiP distribution. The median lifetime of the OLiP distribution with pre-specified factors is taken as the truncation time. To guarantee that the specific life test is obtained at the defined risk to the user, the minimum sample size is required. For a particular consumer’s risk, the OLiP distribution’s parameters, and the truncation time, numerical results are obtained. The new distribution is illustrated using mortality rates of COVID-19 patients in Canada and vinyl chloride data in (g/L) from ground-water monitoring wells that are located in clean-up-gradient areas.

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    Authors: Rana Muhammad Adnan; Abolfazl Jaafari; Aadhityaa Mohanavelu; Ozgur Kisi; +1 Authors

    The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

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    Authors: Karishma M. Qureshi; Bhavesh. G. Mewada; Saleh Y. Alghamdi; Naif Almakayeel; +2 Authors

    Business enterprises such as small and medium-sized enterprises (SMEs) play a significant role in economic development but struggle for sustainability. A business enterprise such as a manufacturing unit tries many technological innovations and strategic initiatives to accomplish sustainability in the manufacturing system. Lean manufacturing implementation is one such initiative that helps SMEs manufacture value-added products with increased profitability and waste minimization. However, lean implementation in SMEs is challenging. Hence, it is essential to follow a systematic framework and control the critical success factors (CSFs) in attempting lean implementation. The purpose of this research is to find, evaluate, and rank the CSFs of lean implementation of SMEs so that they may be controlled to accomplish successful lean implementation. The CSFs of lean implementation found by an in-depth assessment of the literature are modeled using the interpretative structural modeling (ISM) approach. MICMAC analysis is also used in classifying and understanding the significance of each lean implementation CSF. ISM and MICMAC provide the relationship modeling to reveal the inter-relationships of each lean implementation CSF. Subsequently, the ISM model is validated using the Delphi technique. The interpretative ranking process (IRP) has been applied to rank the CSFs of lean implementations. The results show that sustainability in a manufacturing system, financial capability, and employee involvement hold significant importance in lean implementations in manufacturing SMEs. Practicing managers may benefit from revisiting their lean implementation plans and respective aligned strategies. They will also be in a position to identify and focus on the scarce resources required for the subsequent lean implementations.

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    Authors: Farid S. Nassar; Ahmed O. Abbas; Abdulaziz A. Alaqil; Nancy N. Kamel;

    The negative impacts of high stocking density on the commercial poultry industry compromise sustainable birds’ productivity and welfare. Thus, we investigated the potential of colocynth seed (CC) supplementation in alleviating the negative impacts of high stocking density on broilers’ performance, immunity, inflammation, and redox status. A total of 648 one-day-old male Cobb 500 chicks were recruited and distributed into 2 × 2 factorial arrangements. The treatment groups were assigned based on stocking density as low stocking density (9 birds/m2; LSD) or high stocking density (19 birds/m2; HSD), and CC supplementation as without (0 g/kg feed; −CC) or with (1 g/kg feed; +CC) supplementation. Data were collected from week three to week five of age. Production performance was monitored and meat quality was assessed. Blood samples were collected to measure stress markers, humoral immune response, inflammatory cytokines, and antioxidant activity levels. The results indicated that HSD induced production performance reduction, immunosuppression, and imbalance redox status, along with elevation in inflammation and stress markers levels. Breast meat weight and yield were reduced in the HSD groups by 9 and 1%, respectively, compared to LSD groups. However, CC supplementation to HSD birds was able to slightly improve daily weight gain, body weight gain, and breast weight, showing no significant difference compared to the LSD-CC group, and significantly increased breast yield. Furthermore, CC supplementation significantly reduced inflammatory cytokines and stress markers levels. Under HSD, both cell-mediated and humeral immune responses were elevated with CC supplementation compared with the non-supplemented group. It can be concluded that HSD is a detrimental factor in the commercial poultry industry, which generates oxidative and inflammatory responses and, subsequently, immunosuppression and impaired performance. Nevertheless, dietary CC supplementation can be used as a natural antioxidant source to mitigate the negative impacts of HSD on broilers’ production performance, as well as physiological competency.

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    Authors: Noura Metawa; Mohamemd I. Alghamdi; Ibrahim M. El-Hasnony; Mohamed Elhoseny;

    Recently, bitcoin-based blockchain technologies have received significant interest among investors. They have concentrated on the prediction of return and risk rates of the financial product. So, an automated tool to predict the return rate of bitcoin is needed for financial products. The recently designed machine learning and deep learning models pave the way for the return rate prediction process. In this aspect, this study develops an intelligent return rate predictive approach using deep learning for blockchain financial products (RRP-DLBFP). The proposed RRP-DLBFP technique involves designing a long short-term memory (LSTM) model for the predictive analysis of return rate. In addition, Adam optimizer is applied to optimally adjust the LSTM model’s hyperparameters, consequently increasing the predictive performance. The learning rate of the LSTM model is adjusted using the oppositional glowworm swarm optimization (OGSO) algorithm. The design of the OGSO algorithm to optimize the LSTM hyperparameters for bitcoin return rate prediction shows the novelty of the work. To ensure the supreme performance of the RRP-DLBFP technique, the Ethereum (ETH) return rate is chosen as the target, and the simulation results are investigated in different measures. The simulation outcomes highlighted the supremacy of the RRP-DLBFP technique over the current state of art techniques in terms of diverse evaluation parameters. For the MSE, the proposed RRP-DLBFP has 0.0435 and 0.0655 compared to an average of 0.6139 and 0.723 for compared methods in training and testing, respectively.

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    Authors: Esraa A. Elsherbiny; Mohamed Mortagi; Osama Youssf; Mohamed Abd Elrahman; +1 Authors

    Structural lightweight concrete is preferred over traditional concrete due to its ability to reduce the dead load, minimize the size of load-bearing structural members, and provide more economical solutions for foundation deteriorations. This research sheds light on sustainable lightweight concrete using waste crushed clay bricks (CCB) as a lightweight aggregate. To reduce micro-crack propagation of the developed concrete, two types of fiber were implemented and investigated. Steel fibers (SF) with amounts of 0.5% and 1.0% by volume of concrete, and polypropylene fibers (PPF) with amounts of 0.1% and 0.2% by volume of concrete, were employed. Five reinforced concrete beams were made and tested in order to precisely evaluate the structural behavior of the proposed lightweight CCB concrete. Additionally, ABAQUS software for nonlinear finite element analysis has been utilized to simulate the tested beams and compare the numerical model predictions with the experimental findings. The findings revealed that the addition of SF and PPF exhibited a notable influence on enhancing the mechanical characteristics of lightweight CCB concrete. Adding 0.2% PPF increased the ultimate load and deformation capacity at failure by approximately 16% and 24%, respectively. Furthermore, after 28 days, the addition of 0.5% and 1.0% SF enhanced the compressive strength by around 11.7% and 17.6%, respectively. Moreover, a significant level of consistency between the results obtained from the numerical model and the experimental findings was observed. In general, the use of SF and PPF in CCB concrete successfully produced high-quality lightweight concrete with interesting results for use in reinforced concrete beams.

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    Authors: Dania M. Allami; Mohamed T. Sorour; Medhat Moustafa; Ahmed Elreedy; +1 Authors

    Life cycle assessment (LCA) is a powerful tool to evaluate the environmental impacts of domestic wastewater treatment plant (WWTP) operations. It involves a thorough evaluation of the main characteristics or components of the environment, human health, and resources. However, the literature to date is still lacking analysis on the widely varied designs and operational conditions of full-scale WWTPs. The aim here was to integrate analyses such as LCA, greenhouse gas (GHG) emissions, and energy consumption, when considering the environmental impacts of a full-scale WWTP, which can provide practical outputs to aid decision-making on optimum designs and operational conditions. The Russtmiya domestic WWTP, located in Iraq, was considered as the case study. Three operational alternatives were proposed as solutions to improve the WWTP’s performance, as follows: (1) conventional activated sludge with sand filter (CAS), (2) conventional activated sludge with sand filter and nitrogen removal (CAS-N), and (3) membrane bioreactor (MBR). The operation of such alternatives was investigated through modeling and simulation using GPS-X 8.0.1 software. The energy consumption of each alternative was estimated via GPS-X, while the GHG emissions were estimated using three different methods according to the intergovernmental panel on climate change (IPCC), the United States Environmental Protection Agency (USEPA), and GPS-X software. The OpenLCA software (1.10.3) was used to measure all impact categories at both the midpoint and endpoint levels using various methods. As a conclusion, comparing the three proposed alternatives indicated that: (1) the MBR alternative provided the lowest energy consumption and moderate GHG emissions, and (2) the CAS alternative provided the best environmental performance, particularly in aspects such as ozone depletion, global warming, and climate change, where the lowest GHGs emission values had the major contribution.

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    Authors: Ahmad K. Hegazy; Zahra S. Hussein; Nermen H. Mohamed; Gehan Safwat; +3 Authors

    Petroleum oil pollution is a worldwide problem that results from the continuous exploration, production, and consumption of oil and its products. Petroleum hydrocarbons are produced as a result of natural or anthropogenic practices, and their common source is anthropogenic activities, which impose adverse effects on the ecosystem’s nonliving and living components including humans. Phytoremediation of petroleum hydrocarbon-polluted soils is an evolving, low-cost, and effective alternative technology to most traditional remediation methods. The objective of this study is to evaluate the phytoremediation potentiality of Vinca rosea for crude oil-contaminated soil by understanding its properties and involvement in the enhanced degradation of crude oil. The remediation potentiality was determined by evaluating the total petroleum hydrocarbon degradation percentage (TPH%) and changes in the molecular type composition of saturated and aromatic hydrocarbon fractions. TPH% was estimated gravimetrically, and changes in the molecular type composition of saturated and aromatic fractions were measured using gas chromatography and high-performance liquid chromatography, respectively. Sulfur concentration was measured using X-ray fluorescence. Cadmium and lead quantification was measured using Inductively Coupled Plasma-Atomic Emission Spectrometry (ICP-AES). The results revealed that V. rosea enhanced total petroleum hydrocarbon (TPH) degradation and altered the molecular composition of the crude oil. The saturated hydrocarbons increased and the aromatic hydrocarbons decreased. The saturated hydrocarbon fraction in the crude oil showed a wider spectrum of n-paraffin peaks than the oil extracted from unplanted and V. rosea-planted soils. Polyaromatic hydrocarbon degradation was enhanced in the presence of V. rosea, which was reflected in the increase of monoaromatic and diaromatic constituents. This was parallel to the increased sulfur levels in planted soil. The determination of sulfur and heavy metal content in plant organs indicated that V. rosea can extract and accumulate high amounts from polluted soils. The ability of V. rosea to degrade TPH and alter the composition of crude petroleum oil by decreasing the toxicity of polyaromatic hydrocarbons in soil, as well as its capability to absorb and accumulate sulfur and heavy metals, supports the use of plant species for the phytoremediation of crude oil-polluted sites.

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    Authors: Saeed Mousa; Abdullah S. Alomari; Sabrina Vantadori; Waleed H. Alhazmi; +2 Authors

    Natural fibers (NFs) have recently been the center of attention among researchers due to their low cost, availability, ease of manufacture, and potential environmental friendliness as reinforcing agents in composites. The present work deals with the mechanical behavior of palm fiber-reinforced epoxy-based composites with different weight percentage (Wt.%) ratios, ranging from 6% to 31.6%. Glass and hybrid fiber-reinforced epoxy-based composites were also examined. The indirect tensile test, i.e., diametral tensile test (DTT) and the small punch test (SPT), were used in the present work to determine the mechanical properties of the epoxy reinforced with discontinuous random oriented short fibers. Furthermore, short glass fibers were used to compare with palm fiber-reinforced epoxy. In addition, morphology observations of epoxy residue clinging to the natural fibers were carried out using the optical microscope and Scanning Electron Microscopy (SEM). The results showed that the natural fiber has a better adhesion bonding between the palm fiber/epoxy than that of glass fiber/epoxy. Therefore, adding palm fibers improves epoxy’s mechanical properties compared with synthetic glass fibers. The composite with high Wt.% of NF showed the highest diametral tensile strength (DTS), 21.74 MPa, over other composites. The DTS of composites with medium and low Wt.% of NF was lower than that of the high Wt.% by 14% and 30%, respectively.

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    Authors: Touny, Ahmed S. El; Ibrahim, Ahmed H.; Mohamed, Hossam H.;

    A construction project is a dynamic and complex process that involves the identification and accurate fulfillment of the predetermined needs and requirements of the clients by the project team. There are many challenges and constraints that prevent the achievement of these predetermined and various requirements effectively and successfully, so the project team must face and overcome these challenges by identifying all the factors that help the project’s success. However, it is still unclear how to measure success for Egyptian construction projects. Despite the fact that several lists of literature-based factors have been compiled, the individual factors appear to be tabulated rather than grouped according to some criteria to aid in the analysis of their interactions and potential consequences. As such, the objective presented in this paper was to identify and prioritize integrated sustainable critical success factors (ISCSFs) that influence the performance of Egyptian construction projects to ensure successful construction projects. Critical success factors were identified and grouped into 2 major categories—(1) internal related factors and (2) external related factors—and 10 subcategories—(1) company-related factors thus, 100 factors were identified, filtered and developed. In the third stage, a questionnaire was created based on the significant factors identified. As a result, the 40 most important factors influencing the success of performance of construction projects have been identified, which are integrated between all factors (internal and external) and take into account the three pillars of sustainability (economic, social and environmental) as a decision-making tool to evaluate and improve project performance. and (10) industry-related factors in three distinct stages. In total, 140 factors were gathered from the literature review in the first stage. In the second stage, a brainstorming session was held in order to reduce the number of those factors and focus on the most important ones that influence project success (6) support-related factors (financial, human resources, security and legal and administration) (4) resource/procurement-related factors (labors, materials, equipment and subcontractors) (7) stakeholder-related factors (clients, consultants, project managers and end-users) (8) innovation, learning and growth-related factors (3) project management related factors (5) human capital-related factors (9) country-related factors (2) project-related factors

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    Authors: Ahlam H. Tolba; Chrisogonus K. Onyekwere; Ahmed R. El-Saeed; Najwan Alsadat; +2 Authors

    A novel lifetime distribution has been defined and examined in this study. The odd Lindley–Pareto (OLiP) distribution is the name we give to the new distribution. The new density function can be written as an odd Lindley-G distribution with Pareto amplification. The moment-generating function and characteristic function, entropy and asymptotic behavior, order statistics and moments, mode, variance, skewness, and kurtosis are some of the aspects of the OLiP distribution that are discovered. Seven non-Bayesian estimation techniques and Bayesian estimation utilizing Markov chain Monte Carlo were compared for performance. Additionally, when the lifetime test is truncated after a predetermined period, single acceptance sampling plans (SASPs) are created for the newly suggested, OLiP distribution. The median lifetime of the OLiP distribution with pre-specified factors is taken as the truncation time. To guarantee that the specific life test is obtained at the defined risk to the user, the minimum sample size is required. For a particular consumer’s risk, the OLiP distribution’s parameters, and the truncation time, numerical results are obtained. The new distribution is illustrated using mortality rates of COVID-19 patients in Canada and vinyl chloride data in (g/L) from ground-water monitoring wells that are located in clean-up-gradient areas.

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