Lucian Blaga University of Sibiu

The rapid evolution of e-learning platforms, propelled by advancements in artificial intelligence (AI) and machine learning (ML), presents a transformative potential in education. This dynamic landscape necessitates an exploration of AI/ML integration in adaptive learning systems to enhance educational outcomes. This study aims to map the current utilization of AI/ML in e-learning for adaptive learning, elucidating the benefits and challenges of such integration and assessing its impact on student engagement, retention, and performance. A comprehensive literature review was conducted, focusing on articles published from 2010 onwards, to document the integration of AI/ML in e-learning. The review analyzed 63 articles, employing a systematic approach to evaluate the deployment of adaptive learning algorithms and their educational implications. Findings reveal that AI/ML algorithms are instrumental in personalizing learning experiences. These technologies have been shown to optimize learning paths, enhance engagement, and improve academic performance, with some studies reporting increased test scores. The integration of AI/ML in e-learning platforms significantly contributes to the personalization and effectiveness of the educational process. Despite challenges like data privacy and the complexity of AI/ML systems, the results underscore the potential of adaptive learning to revolutionize education by catering to individual learner needs.

In this study we assess the main determinants of banks’ profitability in EU27 over the period 2004-2011. We split the factors that influence bank profitability in two large groups: bank-specific (internal) factors and industry specific and macroeconomic (external) factors. We consider as proxy for banks profitability the return on average assets (ROAA) and the return on average equity (ROAE). The empirical findings are consistent with the expected results. Credit and liquidity risk, management efficiency, the diversification of business, the market concentration/competition and the economic growth have influence on bank profitability, both on ROAA and ROAE. An interesting and valuable result is the positive influence of competition on bank profitability in EU27.

Biomedicine represents one of the main study areas for dendrimers, which have proven to be valuable both in diagnostics and therapy, due to their capacity for improving solubility, absorption, bioavailability and targeted distribution. Molecular cytotoxicity constitutes a limiting characteristic, especially for cationic and higher-generation dendrimers. Antineoplastic research of dendrimers has been widely developed, and several types of poly(amidoamine) and poly(propylene imine) dendrimer complexes with doxorubicin, paclitaxel, imatinib, sunitinib, cisplatin, melphalan and methotrexate have shown an improvement in comparison with the drug molecule alone. The anti-inflammatory therapy focused on dendrimer complexes of ibuprofen, indomethacin, piroxicam, ketoprofen and diflunisal. In the context of the development of antibiotic-resistant bacterial strains, dendrimer complexes of fluoroquinolones, macrolides, beta-lactamines and aminoglycosides have shown promising effects. Regarding antiviral therapy, studies have been performed to develop dendrimer conjugates with tenofovir, maraviroc, zidovudine, oseltamivir and acyclovir, among others. Furthermore, cardiovascular therapy has strongly addressed dendrimers. Employed in imaging diagnostics, dendrimers reduce the dosage required to obtain images, thus improving the efficiency of radioisotopes. Dendrimers are macromolecular structures with multiple advantages that can suffer modifications depending on the chemical nature of the drug that has to be transported. The results obtained so far encourage the pursuit of new studies.

The authors have focused on organizational capabilities to achieve sustainable development goals (SDG) in the current study. In this regard, green knowledge management (GKM) and green innovation (specifically green technological and management innovation) are investigated. Moreover, it is also studied whether organizational green culture (OGC) strengthens organizational capabilities to innovate green and achieve sustainability goals via GKM. The researcher collected data from managers of different levels from manufacturing and service enterprises of all sizes and analyzed it through structural equation modeling. GKM strengthens organizational capabilities to achieve green innovation and SDG as per the findings. Moreover, green innovation has also been found to be a significant positive predictor of corporate sustainable development (CSD). It is also found that OGC strengthens the relationship between GKM and green innovation for achieving SDG. Furthermore, for all sizes of manufacturing and service organizations, GKM is found to be equally important.

This study proposes a review on hyaluronic acid (HA) known as hyaluronan or hyaluronate and its derivates and their application in cosmetic formulations. HA is a glycosaminoglycan constituted from two disaccharides (N-acetylglucosamine and D-glucuronic acid), isolated initially from the vitreous humour of the eye, and subsequently discovered in different tissues or fluids (especially in the articular cartilage and the synovial fluid). It is ubiquitous in vertebrates, including humans, and it is involved in diverse biological processes, such as cell differentiation, embryological development, inflammation, wound healing, etc. HA has many qualities that recommend it over other substances used in skin regeneration, with moisturizing and anti-ageing effects. HA molecular weight influences its penetration into the skin and its biological activity. Considering that, nowadays, hyaluronic acid has a wide use and a multitude of applications (in ophthalmology, arthrology, pneumology, rhinology, aesthetic medicine, oncology, nutrition, and cosmetics), the present study describes the main aspects related to its use in cosmetology. The biological effect of HA on the skin level and its potential adverse effects are discussed. Some available cosmetic products containing HA have been identified from the brand portfolio of most known manufacturers and their composition was evaluated. Further, additional biological effects due to the other active ingredients (plant extracts, vitamins, amino acids, peptides, proteins, saccharides, probiotics, etc.) are presented, as well as a description of their possible toxic effects.

Anthocyanins are colored valuable biocompounds, of which extraction increases globally, although functional applications are restrained by their limited environmental stability. Temperature is a critical parameter of food industrial processing that impacts on the food matrix, particularly affecting heat-sensitive compounds such as anthocyanins. Due to the notable scientific progress in the field of thermal stability of anthocyanins, an analytical and synthetic integration of published data is required. This review focuses on the molecular mechanisms and the kinetic parameters of anthocyanin degradation during heating, both in extracts and real food matrices. Several kinetic models (Arrhenius, Eyring, Ball) of anthocyanin degradation were studied. Crude extracts deliver more thermally stable anthocyanins than purified ones. A different anthocyanin behavior pattern within real food products subjected to thermal processing has been observed due to interactions with some nutrients (proteins, polysaccharides). The most recent studies on the stabilization of anthocyanins by linkages to other molecules using classical and innovative methods are summarized. Ensuring appropriate thermal conditions for processing anthocyanin-rich food will allow a rational design for the future development of stable functional products, which retain these bioactive molecules and their functionalities to a great extent.

BACKGROUND: Sarma - cooked leaves rolled around a filling made from rice and/or minced meat, possibly vegetables and seasoning plants - represents one of the most widespread feasting dishes of the Middle Eastern and South-Eastern European cuisines. Although cabbage and grape vine sarma is well-known worldwide, the use of alternative plant leaves remains largely unexplored. The aim of this research was to document all of the botanical taxa whose leaves are used for preparing sarma in the folk cuisines of Turkey and the Balkans. METHODS: Field studies were conducted during broader ethnobotanical surveys, as well as during ad-hoc investigations between the years 2011 and 2014 that included diverse rural communities in Croatia, Bosnia and Herzegovina, Serbia, Kosovo, Albania, Macedonia, Bulgaria, Romania, and Turkey. Primary ethnobotanical and folkloric literatures in each country were also considered. RESULTS: Eighty-seven botanical taxa, mainly wild, belonging to 50 genera and 27 families, were found to represent the bio-cultural heritage of sarma in Turkey and the Balkans. The greatest plant biodiversity in sarma was found in Turkey and, to less extent, in Bulgaria and Romania. The most commonly used leaves for preparing sarma were those of cabbage (both fresh and lacto-fermented), grape vine, beet, dock, sorrel, horseradish, lime tree, bean, and spinach. In a few cases, the leaves of endemic species (Centaurea haradjianii, Rumex gracilescens, and R. olympicus in Turkey) were recorded. Other uncommon sarma preparations were based on lightly toxic taxa, such as potato leaves in NE Albania, leaves of Arum, Convolvulus, and Smilax species in Turkey, of Phytolacca americana in Macedonia, and of Tussilago farfara in diverse countries. Moreover, the use of leaves of the introduced species Reynoutria japonica in Romania, Colocasia esculenta in Turkey, and Phytolacca americana in Macedonia shows the dynamic nature of folk cuisines. CONCLUSION: The rich ethnobotanical diversity of sarma confirms the urgent need to record folk culinary plant knowledge. The results presented here can be implemented into initiatives aimed at re-evaluating folk cuisines and niche food markets based on local neglected ingredients, and possibly also to foster trajectories of the avant-garde cuisines inspired by ethnobotanical knowledge.

Social media allows customers and prospects to communicate directly to your brand representative or about yourbrand with their friends. However, the obvious question is: who are the people interacting online and howengaged are they in online activities? This paper aims to answer this question based on a study regarding theonline activities of 236 social media users, by identifying different types of users, a segmentation of these usersand a linear model to examine how different predictors related to social networking sites have a positive impacton the respondents’ perception of online advertisements. The answer can help discover how to engage withdifferent types of audiences in order to maximize the effect of the online marketing strategy.

The current study aims to explore the role of environmental taxes and regulations for the renewable energy consumption, focusing on reporting policy suggestions to overcome climate change issues and achieve environmental sustainability. The main objective of this paper is to examine the relation between renewable energy, environmental taxes, environmental technologies, and environmental regulations in 29 OECD countries during 1996–2018. More precisely, we inspect the impact of the environmental regulations and environmental technologies on the renewable energy consumption. The authors employ CIPS and CADF unit root tests, panel Westerlund co-integration test, FMOLS, and Quantile regression methods for the econometric analysis. The econometric analysis suggests that the environmental regulations impede the renewable energy consumption in OECD economies. The study suggests that environmental policy initiatives should focus on implementing environmental strategies to inspire cohesiveness between environmental regulations and the development of environmental technologies in order to promote the renewables industry in the developed countries.

This study explores how researchers' analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers' expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team's workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers' results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.

Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov’s methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov’s original analysis strategy, the valence–dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence–dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution. The stage 1 protocol for this Registered Report was accepted in principle on 5 November 2018. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.7611443.v1 . Jones et al. examine the generalizability of the valence–dominance model of social judgements of faces in 41 countries across 11 world regions. They find evidence of both generalizability and variation, depending on the analytical method.

BACKGROUND: Early and accurate diagnosis of endometriosis is crucial for the management of this benign, yet debilitating pathology. Despite the advances of modern medicine, there is no common ground regarding the pathophysiology of this disease as it continues to affect the quality of life of millions of women of reproductive age. The lack of specific symptoms often determines a belated diagnosis. The gold standard remains invasive, surgery followed by a histopathological exam. A biomarker or a panel of biomarkers is easy to measure, usually noninvasive, and could benefit the clinician in both diagnosing and monitoring the treatment response. Several studies have advanced the idea of biomarkers for endometriosis, thereby circumventing unnecessary invasive techniques. Our paper aims at harmonizing the results of these studies in the search of promising perspectives on early diagnosis. METHODS: We selected the papers from Google Academic, PubMed, and CrossRef and reviewed recent articles from the literature, aiming to evaluate the effectiveness of various putative serum and urinary biomarkers for endometriosis. RESULTS: The majority of studies focused on a panel of biomarkers, rather than a single biomarker and were unable to identify a single biomolecule or a panel of biomarkers with sufficient specificity and sensitivity in endometriosis. CONCLUSION: Noninvasive biomarkers, proteomics, genomics, and miRNA microarray may aid the diagnosis, but further research on larger datasets along with a better understanding of the pathophysiologic mechanisms are needed.

This paper is a synthetic overview of some of the threats, risks, and integrated water management elements in freshwater ecosystems. The paper provides some discussion of human needs and water conservation issues related to freshwater systems: (1) introduction and background; (2) water basics and natural cycles; (3) freshwater roles in human cultures and civilizations; (4) water as a biosphere cornerstone; (5) climate as a hydrospheric 'game changer' from the perspective of freshwater; (6) human-induced stressors' effects on freshwater ecosystem changes (pollution, habitat fragmentation, etc.); (7) freshwater ecosystems' biological resources in the context of unsustainable exploitation/overexploitation; (8) invasive species, parasites, and diseases in freshwater systems; (9) freshwater ecosystems' vegetation; (10) the relationship between human warfare and water. All of these issues and more create an extremely complex matrix of stressors that plays a driving role in changing freshwater ecosystems both qualitatively and quantitatively, as well as their capacity to offer sustainable products and services to human societies. Only internationally integrated policies, strategies, assessment, monitoring, management, protection, and conservation initiatives can diminish and hopefully stop the long-term deterioration of Earth's freshwater resources and their associated secondary resources.

In this paper we consider a particular case of a contractive self-mapping on a complete metric space, namely the F-contraction introduced by Wardowski (Fixed Point Theory Appl. 87, 2012, doi:10

Joseph Schumpeter’s economic thought is indissolubly linked to the study of entrepreneurship and innovation. In Business Cycles, the book planned to be ‘the crown of his work’, Schumpeter carefully crafted a theoretical framework in which both concepts are presented as the main engines of the cyclical economic evolution. This paper aims to offer a different view on this complex combination of economic theory, historical and statistical applied analyses which are today largely forgotten. Schumpeter’s theories of entrepreneurship and innovation are discussed within the general framework of his main intellectual legacy. Re-reading Schumpeter’s Business Cycles in the light of its scholarly reception, this study pays a special attention to some of the key reviews that critically addressed this book. The novelty of our approach lies in revealing the systematic emphasis placed upon the elements introduced by Schumpeter’s Business Cycles to his theories of innovation and entrepreneurship

Computer vision based indoor localization methods use either an infrastructure of static cameras to track mobile entities (e.g., people, robots) or cameras attached to the mobile entities. Methods in the first category employ object tracking, while the others map images from mobile cameras with images acquired during a configuration stage or extracted from 3D reconstructed models of the space. This paper offers an overview of the computer vision based indoor localization domain, presenting application areas, commercial tools, existing benchmarks, and other reviews. It provides a survey of indoor localization research solutions, proposing a new classification based on the configuration stage (use of known environment data), sensing devices, type of detected elements, and localization method. It groups 70 of the most recent and relevant image based indoor localization methods according to the proposed classification and discusses their advantages and drawbacks. It highlights localization methods that also offer orientation information, as this is required by an increasing number of applications of indoor localization (e.g., augmented reality).

Thiazole, a five-membered heteroaromatic ring, is an important scaffold of a large number of synthetic compounds. Its diverse pharmacological activity is reflected in many clinically approved thiazole-containing molecules, with an extensive range of biological activities, such as antibacterial, antifungal, antiviral, antihelmintic, antitumor, and anti-inflammatory effects. Due to its significance in the field of medicinal chemistry, numerous biologically active thiazole and bisthiazole derivatives have been reported in the scientific literature. The current review provides an overview of different methods for the synthesis of thiazole and bisthiazole derivatives and describes various compounds bearing a thiazole and bisthiazole moiety possessing antibacterial, antifungal, antiprotozoal, and antitumor activity, encouraging further research on the discovery of thiazole-containing drugs.

This paper presents a novel supervised convolutional neural network architecture, "DUCK-Net", capable of effectively learning and generalizing from small amounts of medical images to perform accurate segmentation tasks. Our model utilizes an encoder-decoder structure with a residual downsampling mechanism and a custom convolutional block to capture and process image information at multiple resolutions in the encoder segment. We employ data augmentation techniques to enrich the training set, thus increasing our model's performance. While our architecture is versatile and applicable to various segmentation tasks, in this study, we demonstrate its capabilities specifically for polyp segmentation in colonoscopy images. We evaluate the performance of our method on several popular benchmark datasets for polyp segmentation, Kvasir-SEG, CVC-ClinicDB, CVC-ColonDB, and ETIS-LARIBPOLYPDB showing that it achieves state-of-the-art results in terms of mean Dice coefficient, Jaccard index, Precision, Recall, and Accuracy. Our approach demonstrates strong generalization capabilities, achieving excellent performance even with limited training data.

This study aims to explore the direct impact of the digital orientation, Internet of Things (IoT) and digital platforms on the sustainable digital innovation in the context of the digital economy and frugal environment. This study also investigated the mediating role of the digital platforms in these relations. The study was based on the quantitative research design and data were collected from the 397 CEOs and managing directors of Small and Medium Enterprises in Pakistan. Correlation and structural equation modeling approaches were applied for the analysis and testing of the hypotheses. Results revealed that the digital orientation, IoT and digital platform are major antecedents of the sustainable digital innovation. Results also show that the digital platforms mediate between both digital orientation-sustainable digital innovation link and IoT-sustainable digital innovation link. The rapid pace of change in the technology has forced the business organizations to think out of box and align their operational mechanism accordingly. The need for the sustainable digital innovation is a major need of the current decade for meeting the increasing demands of the society in a sustainable way. Organizations, especially SMEs, should be able to deal with these challenges and rapid technological transformations through cost effective frugal business models. The frugal innovation is an important element of sustainable digital innovation enables SMEs to reduce resources usage and waste and to enhance sustainable economic activities. In this way, they can develop and gain advantages in this highly competitive digital environment. This is the first study showing the bright harmony of the digital orientation, IoT and digital platforms for achieving the sustainable digital innovation in the rapid evolving digital economy.

Abstract The intangible resources management (IRM) is a key area within organizations, not only in terms of theory, but also in practice. However, reality shows that organizations face unexpected challenges in developing and implementing strategies and processes of intangible resources management. This article seeks to contribute to the improvement of IRM at the organization level by building a model that describes the process followed by organizations seeking to implement an intangible resources management system. Our study emphasizes the need of three phases: the identification of critical intangible resources for creating value; the measurement of these resources through a set of indicators and, finally, the monitoring of the resources and intangible activities. However, the management, monitoring and reporting on intangible resources is very idiosyncratic and unique for each organization; there is not a universal recipe, each organization should develop its own process.