Babeș-Bolyai University

Digitalization is a challenge of the current environment, and the digital transition has extended to the audit profession. It affects the technology used by clients and the pressure on auditors by audit regulations to apply and use computer-assisted audit techniques (CAATs). The results of specialized literature indicate that the application and use of CAATs in auditing practice are limited. Thus, the present research aimed to investigate the factors that could influence the use of CAATs by auditors, based on the Unified Theory of Acceptance and Use of Technology (UTAUT). The empirical investigation consisted of 112 questionnaires that were analyzed by external auditors. The research results indicated a positive influence on the behavioral intention to use CAATs, which was influenced by performance expectations and facilitating conditions. In contrast, effort expectations and social influence did not affect the behavioral intention to use CAATs. We conclude that management should have a greater involvement in encouraging the use and application of CAATs, including supporting the process with the necessary resources. This work augments the knowledge of the factors that influence the behavioral intention to use CAATs among auditors in Romania and can be a useful resource for practitioners. ■

The present chapter will discuss the role sociologists had in the modern evolution of Romanian society, politics, and debates around ideas, following three axes: activism, politics, and academia. We are interested in the role that sociology has played across different political regimes in shaping the discourse regarding social issues and inequalities, offering the intellectual groundwork for public policies, providing technical expertise to political elites, legitimising particular discourses over others (with regard to attitudes towards social issues, macroeconomic policy, etc.), as well as in adapting Western sociological discourses and ideas to the local context and its particularities.

In this work we will present a generalization of Covitz-Nadler’s contraction principle, as well as of the multi-valued graph contraction principle. The results of this paper extend and complement well-known fixed point theorems. Also, several stability properties are proved. In the last section, a Maia type theorem for a multi-valued nonlinear graph contraction is proved. An application to an integral inclusion of the Volterra type is given.

Surface Enhanced Raman Spectroscopy (SERS) is a highly specific, sensitive, and portable technique with great potential for on-site pesticide detection and monitoring. Endosulfan, an organochlorine pesticide known for its high toxicity, slow degradation, and bioaccumulation, has poor affinity for metallic SERS substrates. This study presents a label-free SERS detection method for endosulfan, using aggregating agents like potassium chloride (KCl), potassium hydroxide (KOH), potassium bromide (KBr), and sodium hydroxide (NaOH) to modify the behavior of Ag colloidal nanoparticles (NPs) and enhance the SERS signal of endosulfan molecules trapped within formed hot-spots. We analyzed the UV–Vis spectra, the hydrodynamic diameter, and zeta-potential of Ag NPs with the addition of these agents and endosulfan. Successful detection of both α- and ß- endosulfan isomers at μM concentrations in both ethanol and methanol was achieved with KOH-treated Ag NPs. The method was also applied to detect endosulfan in real water samples, along with simultaneous detection of λ-cyhalothrin, showcasing its capability to identify multiple analytes. The selectivity and specificity were confirmed using a mixture of endosulfan and thiabendazole, highlighting the crucial role of selecting the appropriate aggregating agent for each analyte. Overall, the findings emphasize the potential of aggregating agents to mediate the SERS enhancement of endosulfan, facilitating simple and rapid protocols for environmental pollutant detection, while shedding light on the intricate interplay between NP behavior, surface chemistry, and analyte interaction.

We analyze vertically stratified three-dimensional oceanic flows under the assumption of constant vorticity. More precisely, these flows are governed by the f-plane approximation for the divergence-free incompressible Euler equations at arbitrary off-equatorial latitudes. A discontinuous stratification gives rise to a freely moving impermeable interface, which separates the two fluid layers of different constant densities; the fluid domain is bounded by a flat ocean bed and a free surface. It turns out that the constant vorticity assumption enforces almost trivial bounded solutions: the vertical fluid velocity vanishes everywhere; the horizontal velocity components are simple harmonic oscillators with Coriolis frequency f and independent of the spatial variables; the pressure is hydrostatic apart from sinusoidal oscillations in time; both the surface and interface are flat. To enable larger classes of solutions, we discuss a forcing method, which yields a characterization of steady stratified purely zonal currents with nonzero constant vorticity. Finally, we discuss the related viscous problem, which has no nontrivial bounded solutions.

Purpose After meaning-centered group psychotherapy for cancer survivors (MCGP-CS), depressive symptoms tend to decrease. An enhanced sense of meaning may play a mediating role in this decrease. The aim of this study was to assess whether personal meaning mediates the relationship between MCGP-CS and depressive symptoms. Methods Cancer survivors (n = 114) were randomly allocated to MCGP-CS or care as usual (CAU). The assessments were scheduled at baseline, postintervention, and at 3- and 6-month follow-up. Mediation models were estimated based on structural equation modeling. We computed the indirect effect of MCGP-CS on depressive symptoms at the 3-month follow-up through personal meaning, and other meaning-related mediators, measured postintervention. Results A small but significant indirect effect of MCGP-CS on depressive symptoms at the 3-month follow-up was found through personal meaning postintervention (b = − 0.29, 95% bootstrap CI (− 0.63, − 0.03)). There were no significant indirect effects through the other meaning-related factors. Conclusions This study tentatively supports the MCGP-CS working model in that an enhanced sense of meaning as a result of MCGP-CS mediates a reduction in depressive symptoms. Personal meaning mediated a small effect of MCGP-CS on depressive symptoms. The longitudinal mediating effect of personal meaning occurred within a time period of 3 months after MCGP-CS. Relevance MCGP-CS is a psychological intervention that supports cancer survivors in regaining or enhancing a sense of meaning in their lives. This enhanced sense of meaning is a protective factor against depressive symptoms. Trial registration The RCT was registered in the Netherlands Trial Register (number NTR3571/NL3421) on August 10, 2012.

The analytic functions with natural boundaries have been only occasionally mentioned in literature. They were defined mainly by lacunary power series of Hadamard type, except for the modular function which is the result of a laborious construction. The case of infinite Blaschke products which cannot be analytically continued over the unit circle is also known, yet the authors have no knowledge about any study devoted to these functions. The purpose of this article is to take a closer look upon these functions, to find new techniques of generating them and to bring this topic into the mainstream study of analytic functions. A special attention is devoted to the theory of Blaschke products, which is completed with new results related to their boundary behavior, making possible the study of the Blaschke products with natural boundary. We apply to them the same method of study as for ordinary infinite Blaschke products obtaining mirror functions with respect to the unit circle. The working tool is that of the fundamental domains, which are easily revealed by the technique of continuation over a curve, or lifting of a curve, having its origins in the differential geometry. Graphic illustrations contribute to a better understanding of the theoretical endeavors.

In this paper, we provide an overview of Human-Computer Interaction (HCI) in the context of Artificial Intelligence (AI), focusing on Machine Learning (ML), Deep Learning (DL), Artificial Neural Networks (ANN), and applications of these techniques in the field of Healthcare. This review highlights the critical role of the human factor in AI-driven systems with discussions on AI ethics and expectations. Artificial Intelligence techniques, including ML and DL enhance gesture and speech recognition in HCI, while ANN models are particularly effective for hand gesture recognition. In Human-Computer Interaction, AI techniques bring value and understanding to Healthcare in real life. Despite the benefits that Artificial Intelligence brings to HCI, challenges remain. The future promises new applications and perspectives in HCI, where AI with ML, DL, and ANN have an effective impact.

This study focuses on the development of bioactive packaging materials by incorporating grape pomace and copper particles into polylactic acid (PLA) composites. The goal is to increase the shelf life of packaged foods while benefiting the health of consumers through the use of these active materials. 6 recipes of composite materials based on polylactic acid and Proviplast 2624 plasticizer were obtained. The additives added were: grape pomace, added at 0.5%, 1% and 1.5%, and copper particles, formed using PEG 600 + CuSO₄, added at 2%, 5% and 8%. Material characterization techniques: FTIR Spectroscopy, used to study the chemical structure. Differential scanning calorimetry (DSC): examined thermal transitions such as glass transition and melting temperatures. Thermogravimetric analysis (TGA) and differential thermogravimetry (DTG): evaluated thermal stability and degradation temperatures. Scanning electron microscopy (SEM) and atomic force microscopy (AFM): analyzed the surface morphology and structure. Mechanical tests: evaluated tensile strength, elongation at break and flexibility. Thermal property analyzes revealed that the additives acted as plasticizers, reducing the intermolecular forces between PLA chains, which decreased the glass transition temperature (Tg), cold crystallization temperature (Tcc) and melting temperature (Tm). The addition of grape pomace and copper particles decreased the degradation temperature of PLA composites, indicating a slight reduction in thermal stability. The transformation temperatures changed and the nature of the thermal transitions (exothermic or endothermic) varied with additive concentrations. Mechanical properties indicated a reduction in tensile strength with increasing additive concentration. Elongation at break and longitudinal modulus of elasticity increased significantly, especially with grape pomace, improving the flexibility of PLA. These changes indicate that the material can absorb more energy before breaking, making it more ductile and more suitable for flexible packaging applications. Increased flexibility and improved thermal resistance ensure that these materials can withstand the demands of packaging, handling and shipping. The combination of improved flexibility, thermal resistance and moderate tensile strength makes these PLA-based composites incorporated with grape pomace or copper particles, enhance the aspect of sustainability by recycling agricultural waste, making the material both ecological and functional, making it a viable option for active food packaging.

In France’s 2024 legislative elections, two-thirds of the candidates who qualified for the runoff withdrew from the competition. The media argued that this was a deliberate strategy to reduce the radical right’s chances of winning an absolute majority of seats. This kind of strategic behavior is based on rationality and collective action that hardly covers the full range of possibilities. This article seeks to identify the reasons why candidates pulled out before the second round of the national legislative elections in France. Our analysis uses semi-structured interviews with candidates who withdrew and identifies several explanations for their decision: electoral tactics driven by coercion, the long-term prospects of profile-raising benefits, voter pressure, disaffection with the campaign content, and the personal examples of other candidates. These results indicate that the decision to leave the race involved rationality, responsiveness to public preferences, emotions, and a learning process.

This study examines the impact of the Kahramanmaraş earthquake on the BIST100 index through the application of complex network analysis. The method begins by examining the correlation distance between the logarithmic returns of companies in the BIST100 index, which serves as the foundation for creating filtered weighted networks. This technique prioritizes robust financial connections while downplaying weaker ones, enabling a thorough examination of the network topological structure and identifying noteworthy financial interactions. The study employs a combination of global and local topological metrics, as well as structural entropy, to gain insights on the interconnections among markets in terms of public interest and the roles played by various entities. It demonstrates how exogenous shocks impact the network structure and reaction. Findings indicate initial notable alterations in the network framework, which were subsequently alleviated by the implementation of financial rules and market processes. This demonstrates the ability of financial markets to recover and maintain stability following a disaster. Results offer useful perspectives on the interplay between market dynamics and the resilience of the financial system in the presence of natural disasters.

The digital transition in the business world emerged as a necessity during the health crisis. Along with businesses transitioning into the innovative digital sphere, ethical issues also appeared. To switch to new technologies, companies must not only be aware of but also engage in digital practices and, last but not least, consider the importance of ethics. Talking about ethics in business is easy since we have a series of guidelines. It becomes more complicated when we face digital ethics and robots that do not have morals. Such a transition requires companies to rethink and innovate their business models and how they offer their customers value, while simultaneously considering digital ethical matters and even environmental and social aspects. This systematic literature review highlights—from the company's perspective—the key topics that characterize digitalization and the crucial role of ethics, describing the internal and external factors to consider in transition processes. The research results propose a series of guidelines but also open up new research opportunities to facilitate the digital transition in the business environment while respecting its ethical aspects. The main contribution of the research is to the specialist literature, deepening the topic and identifying some key aspects regarding the crucial role of ethics in the digital transition.

This research delves into the emerging paradigm of biocultural systems, focusing on the intricate social-ecological dynamics which created and maintained an ancient farming system, the European wood-pastures. Innovatively conceptualizing wood-pastures as biocultural systems, this study employs a network approach to unravel the complex interactions between human activities and the natural particularities within these environments. By using field surveys and interviews conducted in Transylvania, Romania, this research reconstructs the traditional social-ecological drivers behind the preservation of ancient wood-pastures and their Nature’s Contributions to People (NCP). It identifies key variables and their centrality within the biocultural network, emphasizing that the rich natural values of wood-pastures are inextricably linked to management features. We employ RLQ and fourth corner analyses to investigate the interconnections among biophysical context, biocultural features (i.e. human made and natural features), and NCP, revealing significant correlations and gradients between the broad biophysical setting and the wood-pasture NCP. The findings underscore the importance of maintaining traditional management practices and stewardship to conserve the biodiversity and cultural heritage of wood-pastures. We contribute to a deeper comprehension of biocultural systems and offer insights for effective management and governance of traditional farming landscapes in Europe and beyond.

In this article, we contribute to the analysis of protest participation on a gradient from non- to actual participation. Using survey data from six European countries, we take the analysis beyond a binary differentiation between participants and non-participants. We evidence a participation gradient underpinned by a combination of social and political variables and separate patterns that allow for distinctions between non-, potential, and actual protesters. We establish that some factors have a gradual, linear, relation to protest participation, increasing the likelihood of moving from non-participation to potential participation and from potential to actual participation. Second, we find evidence of a punctuated rather than a linear participation gradient in as far as a range of variables distinguish protesters and potential protesters from non-participants but do not differentiate them from each other. Our findings provide practical insights into mobilization pathways while also inviting further research into intervening factors influencing protest behavior.

After more than thirty years, the Directive 91/271/EEC on urban wastewater is currently under revision. In the new directive, the clear specification of the concept of domestic wastewater, with inclusion in this category of sewages from human excretions alone, reflects the particular attention recently paid to the pollution of anthropic origin, mainly accounted for by contaminants of emerging concern (CECs) such as pharmaceutical compounds and personal care products. To this aim, by explicitly introducing the term “quaternary treatment”, the new directive intends to emphasize the need to remove a broad spectrum of micropollutants from urban wastewater through specific treatment processes, which indeed are not currently routinely integrated into wastewater treatment plants, unless in the presence of peculiar pollution from industrial activity. This chapter gives an insight into the established technologies for urban wastewater depuration, evaluates their performance towards CEC removal, and highlights critical situations, such as the increased concentrations of some CECs along the treatment chain. To this purpose, more than one thousand CEC removal data in articles published since 2000, identified through Google Scholar and Scopus databases, were reviewed. The data covered various geographical regions, to consider the different technologies used in several countries, according to specific conditions of technological development and financial resources. Technologies used as secondary, tertiary, and quaternary treatment stages of urban wastewater were considered, highlighting, where possible, the specific contributions of each treatment to the overall removal. The heterogeneity in the removal data presentation (i.e. the aggregation of classes of CECs, rather than individual CEC, the grouping of removal efficiency within the same technology) prevented, in many cases, a complete interpretation of data. Nevertheless, careful extraction of removal data for selected CECs from the reviewed literature allowed us to gather information on the efficiency of secondary and tertiary/quaternary treatments through a meta-analysis approach, which is not biased by the high level of data heterogeneity. Our analysis suggests higher removal efficiency of combined anaerobic-anoxic–oxic stages towards CECs and a statistically significant impact of disinfection/oxidation process.

Access to the internet and online resources changes the concept of health and increases people’s autonomy. In this context, Health Literacy (HL) is a critical determinant of health-related choices. At World Health Organization (WHO) level, M-POHL (Action Network on Measuring Population and Organizational Health Literacy of WHO-Europe) created and validated on European population four questionnaires: digital HL (HLS19-DIGI), communication HL (with doctors from health care services - HLS19-COM-P-Q11 long version and HLS19-COM-P-Q6 short version), online navigation HL (HLS19-NAV), and vaccination HL (HLS19-VAC). Based on the expertise of the team, the present study aimed to report the study protocol for Romanian translation, culturally adapting and psychometric testing the following three M-POHL health literacy tools: HLS19-DIGI, HLS19-NAV, and HLS19-COM-P-Q11, HLS19-COM-P-Q6. We will conduct a qualitative descriptive study design in seven steps to translate and adapt the HLS19-DIGI, HLS19-NAV, and HLS19-COM-P-Q11, HLS19-COM-P-Q6 to the Romanian speakers. The study will begin with the translation of English (En)-Romanian (Ro) (2 researchers involved) (step 1), followed by the evaluation of the translation by a bilingual researcher independent of the two researchers who did the En-Ro translation (step 2), the translation of Ro-En (2 researchers but not those in step 1; step 3), the evaluation of the translation by a bilingual researcher independent of the two researchers who did the Ro-En translation (step 4), evaluation of the translation of the tool in an expert group (step 5), pilot testing on a sample of the target population (step 6) and full psychometric testing of the version resulting from step 6 (step 7).

We propose a deep learning method to model and generate synthetic aortic shapes based on representing shapes as the zero-level set of a neural signed distance field, conditioned by a family of trainable embedding vectors with encode the geometric features of each shape. The network is trained on a dataset of aortic root meshes reconstructed from CT images by making the neural field vanish on sampled surface points and enforcing its spatial gradient to have unit norm. Empirical results show that our model can represent aortic shapes with high fidelity. Moreover, by sampling from the learned embedding vectors, we can generate novel shapes that resemble real patient anatomies, which can be used for in-silico trials.

Background Individuals reporting self-injury are at greater risk of several adverse outcomes, including suicide. There is reason to be concerned how these individuals cope when stressful life events increase. This study aimed to investigate the trajectories of anxiety and depressive symptoms and the predictive value of self-injury history in individuals with psychiatric symptoms during the unique and stressful conditions of the COVID-19 pandemic. Methods In a longitudinal population cohort study (N = 1810) ranging from 2020 to 2022, anxiety (measured by Generalized Anxiety Disorder, GAD-7) and depressive symptoms (measured by Patient Health Questionnaire, PHQ-9) were self-reported monthly during 12 months. Latent growth curve models with and without self-reported self-injury history as predictors were conducted. Results Overall, anxiety and depressive symptoms decreased from baseline, but remained at moderate severity at follow-up. Individuals reporting suicidal or nonsuicidal self-injury reported significantly higher symptom severity at baseline. In addition, individuals reporting suicidal self-injury demonstrated a slower rate of decline in the symptom load over the course of 12 months. Conclusions Over the course of 12 months, anxiety and depressive symptoms decreased in individuals with psychiatric symptoms, but still indicate a psychiatric burden. Individuals with a history of self-injury could be more vulnerable in face of stressful conditions such as those experienced during the COVID-19 pandemic.