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Abstract This study analyzes the effect of environmental, social, and governance (ESG) performance on banking stability in the digital era for a selected group of European banking institutions. Unlike many research, this paper incorporates the digital environment in which the European banking system operates into its investigation to capture the relationship between ESG scores, digitization, and bank stability from 2005 to 2022. This study uses a regime-switching model to investigate the non-linear hypothesis of the relationship, an aspect that has received insufficient attention in previous research. The empirical results confirm the non-linearity between ESG performance and banking stability in the digital era, identifying three ESG performance regimes. Moreover, higher ESG scores are associated with a lower risk of bank failure, aligning with stakeholder theory. Finally, European banks with weak ESG scores fail to avoid the fragility caused by investments in technological infrastructure. Overall, our results suggest that critics and proponents of banks’ commitment to social responsibility are, to some extent, right. Indeed, low or moderate ESG performance (Regimes 1 and 2) aligns with the classical perspective, while high ESG engagement (Regime 3) is consistent with the stakeholder view. Consequently, European banks need to adopt a digital strategy based on improving sustainability to leverage the positive impact of digitization and ESG performance on bank stability. On the policymakers’ side, they need to strengthen the legal infrastructure to support digitization and engagement in social responsibility activities.

Abstract After precipitation, reference evapotranspiration (ETO) plays a crucial role in the hydrological cycle as it quantifies water loss. ETO significantly impacts the water balance and holds great importance at the basin level because of the spatial distribution of managing water resources. Large scale teleconnection indices (LSTIs) play a vital role by influencing climatic variables and can be pivotal in determining ETO and its predictive variables. This study aimed to model and forecast annual ETO in Iran’s basins by utilizing LSTIs and employing various machine learning models (MLMs) such as least squares support vector machine, generalized regression neural network, multi-linear regression (MLR), and multi-layer perceptron (MLP). Initially, climate data from 122 synoptic stations covering six and 30, main and sub basins were collected, and annual ETO values were computed using the Food and Agriculture Organization 56 (PMF 56) Penman–Monteith equation. The correlations between these values and 37 LSTIs were examined within lead times ranging from 7 to 12 months. Through a stepwise approach, the most influential predictor indices (LSTIs) were selected as input datasets for the MLMs. The findings revealed the significant influence of factors such as carbon dioxide (CO2), Atlantic multidecadal oscillation, Atlantic Meridional Mode, and East Atlantic on annual ETO. Overall, all MLMs performed well in terms of the Scatter Index during both training and testing phases across all sub-basins. Furthermore, the MLP and MLR models displayed superior performance compared to other models in the training and testing evaluations based on various assessment metrics.

In this study, V2O5, 5ZnO/10V2O5, and ZnO, 10ZnO/10V2O5 nanocomposites were synthesized by the sol–gel method. The sol–gel technique is an important process for the fabrication of advanced oxide materials with desirable catalytic, optical, and structural properties. The varieties and flexibilities of sol–gel techniques help in preparing materials with extremely specific properties. For the presented samples, three types of phases were assessed. The average crystalline size of V2O5, 5ZnO/10V2O5 and ZnO, 10ZnO/10V2O5 nanocomposites were found to be 25, 26, 14.5, and 15.5 nm, respectively. SEM images showed three different shapes of semi-tube, semi-spherical, and semi-flower. The pure samples of V2O5 and ZnO showed semi-tube shapes. 5ZnO/10V2O5 shows a spherical shape with average dimeter of 0.6 µm. Strong dependence of the direct optical band gap was observed on different compositions that varied within the range of (2.33–2.73 eV). Conversely, the indirect values varied within the range of 2.119–2.35 eV. On the other hand, 10ZnO/10V2O5 has semi flower shape with different layers. Optical parameters, such as optical band gap, extension coefficient, tails of localized states, and refractive index, were gauged for these nanocomposites. In addition, the mean refractive index of ZnO is lower than that of V2O5, with differences observed between 5ZnO/10V2O5 and 10ZnO/10V2O5 nanocomposites.

Abstract Given the existing uncertainty regarding the effectiveness and safety of switching from low-molecular-weight heparin (LMWH) to direct oral anticoagulants (DOACs) in patients with cancer-associated venous thrombosis (CAT), we conducted a comprehensive population-based cohort study utilizing electronic health database in Hong Kong. A total of 4356 patients with CAT between 2010 and 2022 were included, with 1700 (39.0%) patients switching to DOAC treatment. Compared to continuous LMWH treatment, switching to DOACs was associated with a significantly lower risk of hospitalization due to venous thromboembolism (HR: 0.49 [95% CI = 0.35–0.68]) and all-cause mortality (HR: 0.67 [95% CI = 0.61–0.74]), with no significant difference in major bleeding (HR: 1.04 [95% CI = 0.83–1.31]) within six months. These findings provide reassurance regarding the effectiveness and safety of switching from LMWH to DOACs among patients with CAT, including vulnerable patient groups.

Background Direct oral anticoagulants (DOACs) have demonstrated clinical benefits and better patient adherence over low-molecular-weight heparin (LMWH) in treating patients with cancer-associated venous thrombosis (CAT). We aimed to compare the cost-effectiveness of DOACs against LMWH in patients with CAT from the perspective of the Hong Kong healthcare system.Methods A Markov state-transition model was performed to estimate the incremental cost-effectiveness ratio (ICER) per quality-adjusted life years (QALYs) for DOACs and LMWH in a hypothetical cohort of 10,000 patients with CAT over a 5-year lifetime horizon. The model was primarily based on the health states of no event, recurrent venous thromboembolism, bleeding, and death. Transition probabilities, relative risks, and utilities were derived from the literature. Resource cost data were obtained from the Hong Kong Hospital Authority. Deterministic and probabilistic sensitivity analyses tested the robustness of the results.Results Relative to LMWH, DOACs were associated with increased QALYs (1.52 versus 1.50) at a lower medical cost of USD 2,232 versus 8,224 in five years. The cost of LMWH was the main contributor to the outcome. Out of 10,000 simulated cases, DOACs were dominant in 15.8% and cost-effective in 42.1%, at the willingness-to-pay threshold of USD 148,392 per additional QALY.Conclusions DOACs were associated with greater QALY improvements and lower overall costs compared to LMWH. Accounting for uncertainty, DOACs were between cost-effective and dominant in 57.9% of cases. DOACs are a cost-effective alternative to LMWH in the management of CAT in Hong Kong.

We are witnessing an explosion in the concept of the Internet of Things (IoT) as smart objects become more important in our daily lives to make it easier to achieve our goals. It is obvious that the application areas of IoT are extremely diverse. Indeed, several sectors will be deeply impacted by IoT applications. Of which, security in the Internet of Things (IoT) has become a major concern due to increasing vulnerabilities and threats. Connected devices, often with limited security capabilities, have become attractive targets for attackers. Vulnerabilities in IoT devices, whether resulting from unmodified default configurations, lack of regular updates, or insecure communication protocols, expose these systems to potential risks. Cryptography, as a discipline dedicated to securing communications, uses advanced mathematical techniques to guarantee the confidentiality of electronic exchanges by making the data incomprehensible to unauthorized persons.In this paper, we show an in-depth exploration of the generation of new S-boxes using the genetic algorithm. These new S-boxes are dynamically generated with the new genetic algorithm-based approach. This new method offers adaptive optimization, iteratively exploring the solution space to identify robust S-boxes, thereby strengthening the security of the encryption system. The study continues with the evaluation of these S-boxes through dedicated metrics, allowing an in-depth analysis of their performance in terms of resistance to cryptographic attacks and preservation of substitution properties. Finally, this evaluation extends to the incorporation of these newly generated S-boxes into the AES encryption algorithm, where different dimensions, such as cryptanalysis resistance, scene visibility, and other performance levels, will be examined.

Since 2005, the International Financial Reporting Standards (IFRS) mandatory adoption in the European Union has played a pivotal role to reduce financing costs which has influenced positively economic growth across member states. Thus, this study examines the effect of Cost of Capital on Economic Growth under IFRS mandatory adoption in 17 European countries between 1994 and 2021 using Pooled Mean Group Autoregressive Distributed Lag (PMG-ARDL) and System Generalized Method of Moments (GMM-system) methods. The findings reveal a positive correlation between the Cost of Capital and Economic Growth under IFRS adoption. Specifically, the model estimates indicate that the Cost of Capital contributes to a 0.58% increase in Economic Growth in the PMG-ARDL framework. Moreover, the GMM-system model underscores the significance of IFRS adoption in reducing the Cost of Capital, leading to a 0.52% increase in Economic Growth. These results provide insights into the benefits of adopting international accounting standards and highlight the importance of institutional and financial factors in shaping the economic impact of adopting accounting standards.

Clean water is a necessity for many organisms, especially human life. Due to many factors, there is a significant shortage of potable water. This has led to efforts involving recovering water from wastewater or the sea through different technologies. Recently, the desalination of seawater via the reverse osmosis system has shown to be a promising method for drinking water treatment and recovery. Such a technique relies on mathematical models based on many parameters, resulting in special PDEs to model the reverse osmosis system. This paper develops a numerical method to solve a reverse osmosis model. The governing PDE is converted into a Sylvester equation that is proved to be uniquely solvable, stable, consistent, and convergent. The numerical scheme developed is validated with experimental data from the literature, and some numerical simulations.

This study aimed to determine the efficiency and productivity of the production factors in the case of public transport in Sfax – the second most important agglomeration in Tunisia–. The analysis of factor productivity enabled identifying the shortcomings in the supply of this service and advocating certain strategies to boost supply. We use an estimation of the trans-logarithmic costs function with different restrictions while relying on the foundations of the microeconomic theory. We relied on annual statistical data from the Regional Transport Company in Sfax over the period preceding the COVID 19 crisis spanning from 1985 to 2018. The estimation results showed the presence of scale diseconomies, the gain in productivity over the years is too slow. The technical progress of public transport in Sfax is very low and the technical efficiency is also very limited. The results revealed that there is a decline in productivity growth due to a growing inefficiency throughout the study period.

Iraq, one of the main oil exporting nations, is extremely susceptible to changes in the price of oil. This article attempts to investigate how the price of oil affects the way the Iraqi economy performs, as indicated by a number of factors (economic growth and international financial markets). We will apply econometric techniques in both linear and non-linear frameworks to accomplish this goal. To represent NARDL non-linearities in the relationship between the aforementioned economic variables, we will first look for linear cointegrating correlations and/or estimate ARDL models. If necessary, we will next use threshold cointegration. Thus, we demonstrate that, independent of the regime we are in, the asymmetry associated with the shock's sign is confirmed over the span January 2006–December 2020. Regarding the asymmetry associated with the shock's magnitude, it is only confirmed under the "below oil price threshold regime." In the "above oil price threshold regime," yields respond in a way that is proportionate to the shock's magnitude. Additionally, we demonstrate that the asymmetry associated with the shock's sign is confirmed during times of negative industrial output growth, while the influence of shocks looks symmetrical during times of positive industrial production variation.