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The present study offers a comprehensive content analysis of the Forward-Looking on Green Human Resources Management (GHRM) research, providing insights into significant findings, determinants, challenges, and future trends of GHRM. The role of GHRM in developing green behaviour and improving environmental performance is becoming increasingly important, with evidence of positive effects on competitive advantage, company sustainability, and employee engagement. In addition, the study underscores the relevance of GHRM for organisational sustainability, focusing on different HRM practices such as recruitment, the Rewards System, and employee involvement. Furthermore, it identifies vital determinants of GHRM, such as integration of technology, effective green HRM policies, employee environmental awareness, top management support, and the promotion of a sustainable organisational culture. In parallel, challenges such as lack of awareness, need for practice change, insufficient training, absence of standard metrics, and cultural boundaries, are recognised. The study delineates promising trends for the future of GHRM, such as technological integration, a stronger focus on training and development, strategic integration of GHRM, broader application across different sectors, increased regulatory compliance, and an emphasis on green employee behaviour. Importantly, the study concludes by acknowledging the critical role of GHRM in promoting environmental sustainability within organisations while advancing employee engagement and performance, underlining the need for further research to solidify the business case for GHRM and contribute to a more sustainable future.

This panel dataset contains information collected from five distinct sources on the impact of democracy and political stability on economic growth in 15 emerging countries in the MENA region from 1983 to 2022. The dataset includes information about GDP per capita, inflation, trade, population growth, government expenditure, participatory democracy, deliberative democracy, egalitarian democracy, institutionalized autocracy, and political stability. Data analysis was carried out utilizing R statistical software to ensure the accuracy of the data by imputing missing data using the monotone REG approach, allowing future researchers to investigate the linkage between political factors and growth in various scenarios. Data are provided in two sheets, one containing the data before the missing value imputation and another after the monotone REG imputation. This dataset is a companion for an unpublished thesis titled “Democracy, Political Stability, and Economic Growth.”

Introduction. COVID-19 is the pandemic of the century with the unusual circumstances it generated. Subsequently, there has been medical and human scarcity of resources leading to the health system collapse, especially in third world countries. Objective. To support the white army in grasping the pandemic behavior, several studies have pointed to the existence of patient-related factors affecting COVID-19 patients’ mortality-risk. In the current study, Artificial Neural Network (ANN) has been employed to predict COVID-19 mortality. Material and methods. In particular, the modeling phase was done using a database of 684 samples collected from Mohamed Seddik Ben Yahia Hospital of Jijel, with antecedent diseases and blood biomarkers data of patients. Firstly, 18 parameters were selected in the input layer based on the literature recommendation and expert medical team consultation. Furthermore, the optimal inputs have been modeled using the ANN, and their performance was assessed through four performance measures (sensitivity, specificity, precision, and accuracy). Results. The comparative study proved the effectiveness of (18-12-2) model trained by Tansig transfer function, which displayed a higher performance in predicting COVID-19 mortality, compared to other models proposed in the literature. Afterward, the proposed optimal model was utilized to develop a GUI public interface by Matlab software. Conclusion. Finally, a reliable and easy-to-use graphical interface is generated in the current study dubbed “CoviSurv2021”. This latter will be very helpful for the medical staff to select priority patients who have upper urgency to be hospitalized, prioritize patients when the hospital is overcrowded, and gain time to provide the care needed.

In the last few decades, several contributions have used the Fiber Reinforced Polymer (FRP) for reinforcing slabs. However, previous studies disregarded the effect of spacing between the bands of the Carbon Fiber Reinforced Polymer (CFRP), which appears scientifically to be of great importance for enriching the literature. The principal objective of this paper is to ascertain the experimental data and results on the strengthened concrete slabs’ behavior when changing the spacing between the CFRP bands. To meet this objective, six slabs with 600 mm length, 500 mm width, and 50 mm thickness have been utilized. To begin with, we have put to test one reference slab without strengthening while the other slabs were strengthened with CFRP strips. Secondly, the strengthened slabs have been reinforced with three CFRP bands of 50 mm wide by varying either the spacing between them among 50 mm, 100 mm, and 150 mm, or the number of the CFRP layers. This research paper casts light on several points describing the strengthened concrete slabs’ behavior. It is worth mentioning that the slab breaking load increased when the spacing between the CFRP strips was small; and the bands were distributed close to the center.

This study examines the influence of Economic Policy Uncertainty (EPU) on inflation dynamics in Japan from 2000 to 2024. Employing cointegration and ARDL modeling techniques, the research reveals a statistically significant long-term relationship, where heightened economic uncertainty corresponds with increased inflationary pressures in the Japanese economy. Increases in EPU are associated with substantial rises in inflation rates, highlighting the crucial role of policy stability in managing inflationary pressures. The error correction model further reveals the dynamic short-term effects, where both past inflation rates and changes in EPU influence current inflation levels. These findings underscore the importance of maintaining a predictable economic policy environment for mitigating inflation risks and fostering economic stability in Japan. The study contributes valuable insights for policymakers navigating the complexities of economic policy uncertainty and inflation management in Japan's unique economic challenges. [ABSTRACT FROM AUTHOR]

Estimating the bearing capacity of piles is an essential point when seeking for safe and economic geotechnical structures. However, the traditional methods employed in this estimation are time-consuming and costly. The current study aims at elaborating a new alternative model for predicting the pile-bearing capacity based on eleven new advanced machine-learning methods in order to overcome these limitations. The modeling phase used a database of 100 samples collected from different countries. Additionally, eight relevant factors were selected in the input layer based on the literature recommendations. The optimal inputs were modeled using the machine-learning methods and their performance was assessed through six performance measures using a K-fold cross-validation approach. The comparative study proved the effectiveness of the DNN model, which displayed a higher performance in predicting the pile-bearing capacity. This elaborated model provided the optimal prediction, i.e., the closest to the experimental values, compared to the other models and formulae proposed by previous studies. Finally, a reliable and easy-to-use graphical interface was generated, namely “BeaCa2021”. This will be very helpful for researchers and civil engineers when estimating the pile-bearing capacity, with the advantage of saving time and money.

هدفت هذه الدراسة إلى تسليط الضوء على أهمية الإستثمار الأجنبي المباشر من حيث أشكاله ومفهومه وأهميته في الاقتصاد، كما هدفت من ناحية أخرى غلى تبيان أثر الإستثمار الأجنبي المباشر على النمو الإقتصادي والخلق مناصب الشغل في الامارات العربية المتحدة خلال الفترة الممتدة من 1980 إلى 2012 . واعتمدت الدراسة الناتج المحلي الاجمالي كمتغير مستقل لقياس النمو الاقتصادي وكذلك مستوى التشغيل، في حين اعتبرت حجم تدفق الاستثمار الأجنبي المباشر كمتغير تابع . خلصت الدراسة إلى وجود علاقة وطيدة بين المتغير التابع والمتغيرات المستقلة، حيث لتزايد تدفق الاستثمار الاجنبي المباشر الاثر الكبير في زيادة نسبة النمو الاقتصادي و كذلك التخفيف من حدة البطالة وخلق مناصب شغل جديدة خلال فترة الدراسة. وقد أوصت الدراسة بضرورة القيام بأبحاث اخرى على نفس المنوال مع الاعتماد على بيانات وبرامج احصائية حديثة لتأكيد هذه النتائج أو الوصول إلى نتائج اخرى اكثر دقة ، كما أوصت أيضا بضرورة نقل تجربة الإمارات العربية المتحدة إلى البلدان الأخرى للاستفادة منها. The main objective of this study is to investigate the impact of Foreign Direct investment (FDI) on Economic Growth and Employment in United Arab Emirates (UAE), the study covering the period from 1980 to 2012. This study used Gross Domestic Product (GDP) as in dependent variable and also the employment level, whereas, the dependent variable is FDI. Based on descriptive analysis the study concludes that FDI dictate a positive relationship with GDP and so with the employment level. The study recommends making other research in the same field using more advanced statistical tool to get more accurate result and recommends transfer UAE experience in attracting FDI to other developing countries.

In the last few decades, several contributions have used the Fiber Reinforced Polymer (FRP) for reinforcing slabs. However, previous studies disregarded the effect of spacing between the bands of the Carbon Fiber Reinforced Polymer (CFRP), which appears scientifically to be of great importance for enriching the literature. The principal objective of this paper is to ascertain the experimental data and results on the strengthened concrete slabs' behavior when changing the spacing between the CFRP bands. To meet this objective, six slabs with 600 mm length, 500 mm width, and 50 mm thickness have been utilized. To begin with, we have put to test one reference slab without strengthening while the other slabs were strengthened with CFRP strips. Secondly, the strengthened slabs have been reinforced with three CFRP bands of 50 mm wide by varying either the spacing between them among 50 mm, 100 mm, and 150 mm, or the number of the CFRP layers. This research paper casts light on several points describing the strengthened concrete slabs' behavior. It is worth mentioning that the slab breaking load increased when the spacing between the CFRP strips was small; and the bands were distributed close to the center. [ABSTRACT FROM AUTHOR]

Estimating the bearing capacity of piles is an essential point when seeking for safe and economic geotechnical structures. However, the traditional methods employed in this estimation are time-consuming and costly. The current study aims at elaborating a new alternative model for predicting the pile-bearing capacity based on eleven new advanced machine-learning methods in order to overcome these limitations. The modeling phase used a database of 100 samples collected from different countries. Additionally, eight relevant factors were selected in the input layer based on the literature recommendations. The optimal inputs were modeled using the machine-learning methods and their performance was assessed through six performance measures using a K-fold cross-validation approach. The comparative study proved the effectiveness of the DNN model, which displayed a higher performance in predicting the pile-bearing capacity. This elaborated model provided the optimal prediction, i.e., the closest to the experimental values, compared to the other models and formulae proposed by previous studies. Finally, a reliable and easy-to-use graphical interface was generated, namely "BeaCa2021". This will be very helpful for researchers and civil engineers when estimating the pile-bearing capacity, with the advantage of saving time and money. [ABSTRACT FROM AUTHOR]

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As one of the most swiftly industrializing countries in the world, China is struggling with significant challenges facing its environment, in particular in its marine ecosystems. Hence, economic activities increasingly are influencing these ecosystems, requiring their study crucial for sustainable development. Therefore, it is paramount perceiving the potential implications of economic growth and foreign direct investment (FDI) for marine health. The study aims to explore the impact of economic growth and FDI on China's marine ecosystem during 1980–2019, examining the probable intersections of economic advancement, FDI, and marine sustainability, the study used a novel nonlinear Fourier Autoregressive Distributed Lags (FARDL) approach. Notably, the paper confirms the Fishing Grounds Load Capacity Curve (FGLCC) hypothesis, demonstrating a nonlinear affiliation among income levels and maritime conditions. Moreover, the results point out that FDI initially worsens marine conditions until a certain threshold is reached, marking a pivotal change in the influence of FDI from environmental degradation to improvement. In addition, the study underscores the critical need for policies that balance economic development with Chines' marine environmental sustainability, emphasizing the importance of intended regulatory and strategic interventions. These insights are vital for enhancing marine requirements and ensuring well-being and health of future generations, providing significant implications maritime policymakers in addressing marine environmental challenges amid economic development. [Display omitted] • Analyzes China's marine sustainability from 1980 to 2019 using the Fishing Grounds Load Capacity Factor. • Proposes and tests the Fishing Grounds Load Capacity Curve hypothesis. • Evaluates marine Pollution Haven and marine Pollution Halo hypotheses. • Provides evidence for FGLCC and marine Pollution Haven based on Fourier ARDL modelling. • Offers insights into balancing economic growth and marine ecosystem preservation in China through key policy levers. [ABSTRACT FROM AUTHOR]