1 Decembrie 1918 University, Alba Iulia

The transition to clean and renewable energy sources is of prime importance in addressing environmental challenges related to the consumption of fossil fuels. Hydrogen, being a clean fuel with a high energy density, has huge potential, especially when it can be obtained through solar-driven PEC water splitting. Herein, MoS2 photocatalysts were synthesized by sulfurizing MoO3 thin films, using a CVD technique. The deposited MoO3 films by thermal evaporation at 450 degrees C were further sulfurized at 500 degrees C, 550 degrees C, and 600 degrees C. XRD results confirmed the successful conversion of MoO3 into MoS2. The optical properties showed a bandgap reduction from 2.50 eV to 1.30 eV, which leads to better absorption of light in the visible region.The photoelectrochemical experiment shows that the S-MoO3-600 degrees C thin film has the best performance, and the solar-to-hydrogen conversion efficiency reaches 0.11385% at an applied bias of 1.0 V versus Ag/AgCl, which is about 189 times higher than that of the pristine MoO3 thin film.

This paper introduces a new extended rectangular fuzzy b-metric-like space that generalizes the existing frameworks of the extended rectangular and fuzzy b-metric spaces. Within this setting, we establish several fixed-point theorems for Ciric-type and Banach-type contractions, accompanied by a series of corollaries, propositions, and conditions that further illustrate the proposed concept. These results unify and extend many known theorems in fuzzy metric theory. Moreover, we provided several non-trivial examples to validate of the main results. A flow diagram was provided to demonstrate the generalized structure. Additionally, we applied the fuzzy integral equation to establish the uniqueness and existence of our main result.

Linguistic interval-valued q-rung orthopair fuzzy (LIVq-ROF) sets offer a powerful framework for modeling uncertainty and vagueness in complex decision-making environments. This study leverages the expressive strength of LIVq-ROF sets to develop novel aggregation operators-specifically, the LIVq-ROF Choquet integral averaging and geometric operators-which are designed to capture interdependencies among attributes in multiple attribute group decision-making (MAGDM) scenarios. The theoretical properties of these operators are rigorously established. Building on this foundation, we propose a Choquet integral-based grey relational analysis (GRA) method tailored for MAGDM under uncertainty. The proposed model is applied to a real-world case study involving the selection of the optimal neural network model for predicting crop yields. Results demonstrate the model's effectiveness in identifying the best-performing alternative. A thorough sensitivity analysis and comparison with existing approaches confirm the robustness and superior performance of the proposed method.

Contemporary emergency systems operate at the intersection of climate volatility, digital interdependence, and cascading institutional disruptions. Despite growing research on resilience, adaptive governance, and digital transformation, these fields remain largely disconnected, leaving a theoretical gap in explaining how emergency systems perform under compound uncertainty. This integrative review synthesizes 32 peer-reviewed articles (post-2020) using structured narrative methodology and VOSviewer bibliometric analysis to map the field’s intellectual architecture and identify its structural gaps. The analysis reveals six thematic clusters organized around resilience as the central construct, yet characterized by three recurring disconnections: the weak integration between digital transformation and governance theory, the operational underdevelopment of polycentric governance frameworks, and the temporal separation between emergency response and climate adaptation. Drawing on this structural diagnosis, the study advances the Complex Adaptive Governance (CAG) model—a three-layer framework encompassing systemic architecture, adaptive mechanisms, and operational resilience—in which digital interoperability functions as a cross-cutting accelerator. The CAG model reconceptualizes resilience as a relational property of governance ecosystems, enhanced by digital interoperability, and offers design principles for climate-resilient emergency systems aligned with SDG 9, SDG 11, SDG 13, and SDG 16.

A robust audit services market is essential for ensuring financial transparency, regulatory compliance, and investor confidence. As a dimension of organizational sustainability, the capacity of audit firms to remain competitive and resilient under market pressures is increasingly relevant. However, existing research has paid insufficient attention to the stability of audit firms and the survival dynamics of mid-sized players. The present study addresses this gap by examining the volatility of the U.S. audit services market and the sustained dominance of the Big Four firms over the 2019-2023 period. Based on data from Accounting Today's annual rankings, the study employs Kaplan-Meier survival analysis to assess the probability of audit firms remaining in the Top 100 over time. Furthermore, K-means clustering is used to identify structural factors contributing to firm exit, including revenue, number of employees, branches, and partners. The results indicate that, while the Big Four retained stable leadership, 19 firms exited the rankings, with revenue and number of specialists being the most influential exit factors. These findings provide insights for enhancing risk assessment, strategic planning, and regulatory design. Moreover, the study contributes to broader discussions on organizational sustainability and long-term competitiveness within the context of the U.S. audit sector, while offering insights that may be informative for understanding similar dynamics in other markets rather than aiming for direct global generalization.