Diverse Facets Research Articles

Adaptation of the Social and Emotional Loneliness Scale for Adults to Turkish Culture

This study addresses the pervasive human experience of loneliness, shifting from a traditional unidimensional perspective to a more nuanced, multidimensional understanding. The Social and Emotional Loneliness Scale for Adults (SELSA) was developed based on this conceptual shift, and this study focuses on adapting the scale to Turkish culture. Data from 197 Turkish adults (Mean age = 23 years, SD = 5.12) were analyzed using exploratory factor analysis, revealing a three-factor structure consistent with the original scale. The factors, namely social loneliness, romantic loneliness, and family loneliness, explained 23.7%, 17.5%, and 10.4% of the variance, respectively. One item was excluded from the scale due to the lack of contribution to any factor. Clear factor analysis results and high Cronbach’s alpha reliability coefficients (0.92, 0.93, and 0.90 for social, romantic, and family loneliness, respectively, and 0.90 for the total scale) indicate strong internal consistency. The findings not only affirm the applicability of SELSA in the Turkish context but also contribute to a nuanced understanding of loneliness. The multidimensional approach, supported by robust psychometric properties, offers a valuable tool for comprehensively assessing and addressing diverse facets of loneliness in Turkish young adults.

Understanding American Historical Change through Cultural Traditions, Physical Environment, & Literature: A Comparative Reflection in Global Community

This article embarks on a comprehensive exploration of the intricate interplay between cultural traditions, the physical landscape, and the realm of poetry or literature, particularly in their capacity as architects of public myths within societal consciousness. It endeavors to serve as a nuanced comparative reflection, offering valuable insights to English language and literature students. Leveraging the rich historical and cultural tapestry of America, it seeks to illuminate the multifaceted contexts underlying language and literature studies amidst the dynamic trends and formidable challenges of contemporary global society, where both tangible and virtual boundaries are increasingly contested. Rooted in an understanding spanning from the seventeenth century to the twentieth century, the author meticulously selects a myriad of historical records and literary masterpieces, each implicitly or explicitly portraying diverse facets of environmental dynamics and the notion of frontier. These meticulously curated depictions and conceptual frameworks from various sources constitute the cornerstone of the author's analytical approach, elucidating the intricate interconnectedness between American cultural ethos and its surrounding ecological milieu

Eutrophication modifies the relationships between multiple facets of macroinvertebrate beta diversity and geographic distance in freshwater lakes

AbstractAimUnderstanding the distance–decay relationship (DDR) has been considered important because it reflects a combination of several ecological processes such as dispersal limitation and environmental sorting. However, effects of human disturbances on DDR are poorly known, especially in freshwater lakes. This study is aimed to examine how anthropogenic eutrophication modified the relationships between three facets (taxonomic, functional and phylogenetic) of macroinvertebrate beta diversity and geographic and environmental distances across 30 freshwater lakes.LocationThe Yangtze River floodplain, China.MethodsWe used Mantel tests to examine the relationships between multiple facets of assemblage dissimilarities (overall beta diversity, replacement and richness difference components) and geographic and environmental distances. Distance‐based redundancy analysis (dbRDA) and associated variation partitioning procedures were applied to explore the relative contributions of environmental and spatial factors on the three facets of beta diversity.ResultsWe found that none of the three beta diversity facets was related to geographic distance, but all were significantly related to environmental distance, mainly mirroring eutrophication‐related variables. Based on the variation partitioning approach, the macroinvertebrate assemblages examined were almost exclusively structured by environmental factors associated with eutrophication, while spatial variables had a negligible effect. Nevertheless, the different facets of beta diversity did not decrease (i.e., no homogenization trend) in lake groups showing the highest eutrophication levels, implying complex influences of anthropogenic disturbances in driving homogenization or differentiation in assemblage compositional dissimilarity.Main ConclusionsOur findings suggested that the high degrees of eutrophication acted as an environmental filter to significantly modify the spatial distance–decay relationships, possibly via decreasing the importance of dispersal limitation in shaping macroinvertebrate assemblages in the studied lakes. Given the sensitivity of beta diversity patterns to eutrophication we found in this study, we recommend that the role of anthropogenic disturbances should be incorporated into research on general ecological patterns like the DDR.

Applications of Learning Analytics in Latin America

Learning analytics (LA) is a key research domain within educational technology. This field harnesses data analysis, unlocking tangible advantages for educators and learners. Despite extensive research, geographical disparities in adoption remain, with certain regions still in developing stages. Within this scenario, Latin America has been adopting LA to address specific educational challenges, including reducing quality disparities and dropout rates. However, the region confronts limitations for adoption, such as infrastructure, a lack of widespread data literacy, and regulatory constraints, all of which impede broader implementation. In this context, this special issue, titled “Applications of Learning Analytics in Latin America,” intends to present a comprehensive perspective on LA’s deployment across the continent, highlighting its current state and potential growth. In this editorial, we curate a selection of relevant papers, each delving into diverse facets of LA’s application within Latin American contexts. These papers exemplify practical implementations and discuss the implications and possible future trajectories for LA research, especially tailored for the Latin American academic community.

Beyond likes & clicks: Empowering role of social media marketing in value creation

Social media is capturing the market in the modern era, when technology is permeating every aspect of life, to motivate marketers to appeal to diverse consumers. The rapid expansion of social media has brought about a substantial transformation in the communication system, giving rise to a distinct virtual realm. An assortment of social networking platforms are utilized for commercial purposes. Possible examples of such platforms are Google+, Facebook, LinkedIn, Twitter, and YouTube. This study aimed to ascertain the effect of various social media marketing platforms on post-purchase experience, customer value creation, purchase decision, and purchase perception. Utilizing quantitative methodology, the data collected via a questionnaire were compiled and analyzed. The respondents were sent a total of 183 questionnaires, of which 158 were utilized as the final sample for the study. The survey was constructed using a five-point Likert scale: strongly disagree = 1, neutral = 3, agree = 4, and strongly disagree = 5. The data were analyzed with the assistance of version SPSS 22 of the Statistical Package for the Social Sciences. The study’s findings indicate that social media marketing and consumer value creation are significantly related. The forthcoming focus is on equipping marketers with knowledge that substantiates the impact of social media marketing strategies on consumer value creation. Nevertheless, the fundamental objective of the research is to advance understanding of diverse facets pertaining to marketing via social media and its capacity to captivate and provide value to the customer base.

Detection of Forged Images Using a Combination of Passive Methods Based on Neural Networks

In the current era of social media, the proliferation of images sourced from unreliable origins underscores the pressing need for robust methods to detect forged content, particularly amidst the rapid evolution of image manipulation technologies. Existing literature delineates two primary approaches to image manipulation detection: active and passive. Active techniques intervene preemptively, embedding structures into images to facilitate subsequent authenticity verification, whereas passive methods analyze image content for traces of manipulation. This study presents a novel solution to image manipulation detection by leveraging a multi-stream neural network architecture. Our approach harnesses three convolutional neural networks (CNNs) operating on distinct data streams extracted from the original image. We have developed a solution based on two passive detection methodologies. The system utilizes two separate streams to extract specific data subsets, while a third stream processes the unaltered image. Each net independently processes its respective data stream, capturing diverse facets of the image. The outputs from these nets are then fused through concatenation to ascertain whether the image has undergone manipulation, yielding a comprehensive detection framework surpassing the efficacy of its constituent methods. Our work introduces a unique dataset derived from the fusion of four publicly available datasets, featuring organically manipulated images that closely resemble real-world scenarios. This dataset offers a more authentic representation than other state-of-the-art methods that use algorithmically generated datasets based on image patches. By encompassing genuine manipulation scenarios, our dataset enhances the model’s ability to generalize across varied manipulation techniques, thereby improving its performance in real-world settings. After training, the merged approach obtained an accuracy of 89.59% in the set of validation images, significantly higher than the model trained with only unaltered images, which obtained 78.64%, and the two other models trained using images with a feature selection method applied to enhance inconsistencies that obtained 68.02% for Error-Level Analysis images and 50.70% for the method using Discrete Wavelet Transform. Moreover, our proposed approach exhibits reduced accuracy variance compared to alternative models, underscoring its stability and robustness across diverse datasets. The approach outlined in this work needs to provide information about the specific location or type of tempering, which limits its practical applications.

Global patterns and determinants of multiple facets of plant diversity

AbstractAimCombining different biodiversity dimensions can reveal new diversity patterns disclosing the relative roles of historical, environmental and anthropogenic factors in shaping global seed plant diversity.LocationGlobal.Time periodPresent.Major taxa studiedVascular plants.MethodsWe collated a database encompassing taxonomic (249,000 species), functional and phylogenetic information (34,694 species) of seed plants across different regions of the world. Species richness in each region was weighted accounting for their phylogenetic and functional distinctiveness, obtaining a new metric—μ‐diversity—which was modelled to disentangle the relative roles of historical factors such as climate variability since the Last Glacial Maximum (LGM), environmental features (e.g. actual evapotranspiration—AET) and anthropogenic factors (past and current).ResultsHigher μ‐diversity was observed in Papuasia, South East Asia, Australia and Central America, whereas the lowest values were primarily located in the Northern Hemisphere. Climate variability and AET were the most important determinants of μ‐diversity and individual diversity facets, whereas the importance of past human impacts (i.e. the onset of pastoralism) equated or exceeded those of the present ones.Main conclusionsOur integrative approach proved more sensitive in describing species diversity patterns. Few areas on Earth host high and unique proportions of multiple diversity facets and individual diversity facets contribute differently to μ‐diversity across continents. Historical climate stability and water‐energy dynamics strongly affect species diversity, but we also observed that past land‐use legacy may have influenced current plant diversity, which is under intense anthropogenic pressure, especially in Asia as well as in Central and South America.

Diverse Facets of Sustainability in Slums

Slums are considered to be informal settlements with dire living conditions that are occupied illegally causing serious impediment to the growth and development of any place. Therefore it is important to transform these areas into potential zones, that adds a positive impact to the process of urban development. Slums are characterized by defective physical, social and economical environment that exacerbated the living condition of the people residing there. In order to devise a holistic approach to address the situation it is necessary to understand the various elements of slums to attain sustainability. This paper looks into those varying aspects of sustainability in slums and identifies the diverse factors contributing to the attainment of the same. KEYWORDS: environmental impact, informal settlements, social equity, sustainability, urban development

Algae-Mediated Removal of Prevalent Genotoxic Antibiotics: Molecular Perspective on Algae-Bacteria Consortia and Bioreactor-Based Strategies.

Antibiotic pollution poses a potential risk of genotoxicity, as antibiotics released into the environment can induce DNA damage and mutagenesis in various organisms. This pollution, stemming from pharmaceutical manufacturing, agriculture, and improper disposal, can disrupt aquatic ecosystems and potentially impact human health through the consumption of contaminated water and food. The removal of genotoxic antibiotics using algae-mediated approaches has gained considerable attention due to its potential for mitigating the environmental and health risks associated with these compounds. The paper provides an in-depth examination of the molecular aspects concerning algae and bioreactor-driven methodologies utilized for the elimination of deleterious antibiotics. The molecular analysis encompasses diverse facets, encompassing the discernment and profiling of algae species proficient in antibiotic degradation, the explication of enzymatic degradation pathways, and the refinement of bioreactor configurations to augment removal efficacy. Emphasizing the significance of investigating algal approaches for mitigating antibiotic pollution, this paper underscores their potential as a sustainable solution, safeguarding both the environment and human health.

Taxonomic and functional-trait metrics track recovery of demersal fish and shrimp communities following system collapse

Monitoring programs that integrate both structural and functional ecosystem components play integral roles in ecosystem management and conservation planning. In the early 1990’s, the marine ecosystem of the waters surrounding Newfoundland and Labrador (NL) underwent a regime shift. Several demersal and pelagic fish stocks collapsed simultaneously, and this had significant ecological and socioeconomic consequences. As this regime shift impacted numerous commercial and non-commercial species, assessments based on individual species would be insufficient. We explored a variety of metrics that capture different facets of diversity across multiple species to provide a more robust ecosystem assessment. These were species richness, evenness, community-weighted means of maximum body length and trophic level (i.e., the mean maximum body size or trophic level of the species present in a community), and functional dispersion (FDis). The objectives of this study were 1) to assess trends in community structure of the NL demersal community during the post-collapse period (1995-2018), 2) explore how the various community-level metrics differ or are redundant, and 3) investigate how these metrics are associated with important covariates. Several metrics were redundant and displayed strongly positive, temporal trends being consistent with expectations for a recovery encompassing the entire demersal community. In particular, unweighted community-weighted means of body length and trophic level displayed nearly equal temporal patterns, showing increasing trends throughout the study period which were most prominent in the northern study area and within a limited depth range at the upper shelf break. Corresponding biomass-weighted metrics were also correlated with each other but only showed similar increasing tendencies after the first decade. In contrast, species richness did not show any temporal increase. Evenness and biomass-weighted FDis showed similar temporal patterns, decreasing during the first decade followed by strong increases during subsequent years, patterns that were directly linked to variation in Northern shrimp and Atlantic cod biomass. This study demonstrates how a variety of community metrics can provide insight into different aspects of the post-collapse recovery of the demersal community and help us better understand the complexity of the changes the ecosystem is undergoing.

Exploring non-perturbative corrections in thermodynamics of static dirty black holes

This research delves into an extensive exploration of the thermodynamic characteristics exhibited by a contaminated black hole subject to a uniform electric field, within the theoretical framework of the Einstein-Nonlinear Electrodynamics (ENE)-dilaton theory. The investigation encompasses a thorough analysis of diverse thermodynamic facets, encompassing heat capacity, Helmholtz free energy, and internal energy. Through this comprehensive examination, valuable insights are provided into the distinctive behavior of the black hole when subjected to the influence of the electric field. Moreover, our study embarks on an exploration of the nuanced interplay between quantum effects and the thermodynamic profile, with a particular focus on scrutinizing the quantum-corrected entropy. This approach allows for a deeper understanding of the intricate relationship between quantum mechanics and the thermodynamic attributes exhibited by the system. By doing so, we aim to illuminate the non-perturbative corrections inherent in this intricate system, thereby contributing to a holistic comprehension of the altered thermodynamics characterizing dirty black holes within the confines of the specified theoretical framework. In essence, this research endeavors to uncover the subtleties of the modified thermodynamic landscape governing black holes tainted by external factors, specifically within the context of the ENE-dilaton theory. The outcomes of this study promise to extend our understanding of the intricate interactions within such complex systems, offering valuable insights into the non-perturbative corrections that manifest in their thermodynamic behavior.

Identification and characterization of a fungal cutinase-like enzyme CpCut1 from Cladosporium sp. P7 for polyurethane degradation.

Plastic degradation by biological systems emerges as a prospective avenue for addressing the pressing global concern of plastic waste accumulation. The intricate chemical compositions and diverse structural facets inherent to polyurethanes (PU) substantially increase the complexity associated with PU waste management. Despite the extensive research endeavors spanning over decades, most known enzymes exhibit a propensity for hydrolyzing waterborne PU dispersion (i.e., the commercial Impranil DLN-SD), with only a limited capacity for the degradation of bulky PU materials. Here, we report a novel cutinase (CpCut1) derived from Cladosporium sp. P7, which demonstrates remarkable efficiency in the degrading of various polyester-PU materials. After 12-h incubation at 55°C, CpCut1 was capable of degrading 40.5% and 20.6% of thermoplastic PU film and post-consumer foam, respectively, while achieving complete depolymerization of Impranil DLN-SD. Further analysis of the degradation intermediates suggested that the activity of CpCut1 primarily targeted the ester bonds within the PU soft segments. The versatile performance of CpCut1 against a spectrum of polyester-PU materials positions it as a promising candidate for the bio-recycling of waste plastics.IMPORTANCEPolyurethane (PU) has a complex chemical composition that frequently incorporates a variety of additives, which poses significant obstacles to biodegradability and recyclability. Recent advances have unveiled microbial degradation and enzymatic depolymerization as promising waste PU disposal strategies. In this study, we identified a gene encoding a cutinase from the PU-degrading fungus Cladosporium sp. P7, which allowed the expression, purification, and characterization of the recombinant enzyme CpCut1. Furthermore, this study identified the products derived from the CpCut1 catalyzed PU degradation and proposed its underlying mechanism. These findings highlight the potential of this newly discovered fungal cutinase as a remarkably efficient tool in the degradation of PU materials.

Structural, Exterior, and Interior Medium of Wood as a Holistic Museum Experience: A Case Study of OMM (Odunpazarı Modern Museum)

The fundamental research inquiry in this study revolves around wood materials’ diverse facets, including structural identities, contextual considerations, interior and external spatial applications, and their user experiences. To address this research, a comprehensive literature review, case study, and survey were conducted. The objective being to elucidate technical, functional, sensory, perceptual, and psychological impacts of wood in a sample structure where it is the primary material in the overarching user experience. The Odunpazarı Modern Museum (OMM), conceptualized by architect Kengo Kuma and inaugurated in 2019 in Eskişehir, stands as a testament to the historical significance of the timber trade in the region. The deliberate choice of wood as the primary construction material serves as a tribute to this historical narrative. The conspicuous incorporation of wooden lath materials into both the external and interior spaces signify a conscious reference to the region’s historical heritage and aligns with sustainability principles in design. Factors such as form characteristics, dimensional distinctions, spatial arrangements, and the extent of surface interactions collectively contribute to the compelling effect of this integrative approach. Within the confines of the museum, unconventional partitioning is implemented, and the strategic arrangement of masses results in multiple facades, even in the absence of overt wooden surfaces. The exterior impact of the wooden shell complements its interior application. For this reason, OMM enabled the understanding and explanation of all dimensions of the wooden material, including physical, technical, and psychosocial.

Rhizobia-legume symbiosis mediates direct and indirect interactions between plants, herbivores and their parasitoids

Microorganisms associated with plant roots significantly impact the quality and quantity of plant defences. However, the bottom-up effects of soil microbes on the aboveground multitrophic interactions remain largely under studied. To address this gap, we investigated the chemically-mediated effects of nitrogen-fixing rhizobia on legume-herbivore-parasitoid multitrophic interactions. To address this, we initially examined the cascading effects of the rhizobia bean association on herbivore caterpillars, their parasitoids, and subsequently investigated how rhizobia influence on plant volatiles and extrafloral nectar. Our goal was to understand how these plant-mediated effects can affect parasitoids. Lima bean plants (Phaseoulus lunatus) inoculated with rhizobia exhibited better growth, and the number of root nodules positively correlated with defensive cyanogenic compounds. Despite increase of these chemical defences, Spodoptera latifascia caterpillars preferred to feed and grew faster on rhizobia-inoculated plants. Moreover, the emission of plant volatiles after leaf damage showed distinct patterns between inoculation treatments, with inoculated plants producing more sesquiterpenes and benzyl nitrile than non-inoculated plants. Despite these differences, Euplectrus platyhypenae parasitoid wasps were similarly attracted to rhizobia- or no rhizobia-treated plants. Yet, the oviposition and offspring development of E. platyhypenae was better on caterpillars fed with rhizobia-inoculated plants. We additionally show that rhizobia-inoculated common bean plants (Phaseolus vulgaris) produced more extrafloral nectar, with higher hydrocarbon concentration, than non-inoculated plants. Consequently, parasitoids performed better when fed with extrafloral nectar from rhizobia-inoculated plants. While the overall effects of bean-rhizobia symbiosis on caterpillars were positive, rhizobia also indirectly benefited parasitoids through the caterpillar host, and directly through the improved production of high quality extrafloral nectar. This study underscores the importance of exploring diverse facets and chemical mechanisms that influence the dynamics between herbivores and predators. This knowledge is crucial for gaining a comprehensive understanding of the ecological implications of rhizobia symbiosis on these interactions.

The immediate effect of discrimination on mental health: A meta-analytic review of the causal evidence.

This meta-analysis synthesizes experimental studies on the immediate effects of discrimination on mental health, exploring the effects of different paradigms and discrimination types on diverse facets of mental health. We analyzed data from a systematic literature search (73 studies; 12,097 participants; 245 effect sizes) for randomized controlled trials with manipulation of discrimination as a predictor and mental health as an outcome using a three-level random-effects model. Experimentally manipulated discrimination led to poorer mental health (g = -0.30), also after controlling for publication year, region, education level, and methodological quality. Moderator analyses revealed stronger effects for pervasive (g = -0.55) compared to single-event manipulations (g = -0.25) and a trend toward weaker effects for samples with nonmarginalized (g = -0.16) compared to marginalized identities (g = -0.34). Gender and age did not moderate the effect. Discrimination had the largest effects on externalizing (g = -0.66) and distress-related outcomes (g = -0.41); heterosexism (g = -0.66), racism (g = -0.32), and sexism (g = -0.30) had the largest effects on mental health. Convenience sampling compromised generalizability to subgroups and the general population, downgrading methodological quality for all included studies. When interpreting the findings, selective samples (mostly young female adults with higher education), often limited ecological validity, and ethical restrictions of lab-induced discrimination need to be considered. These constraints likely led to conservative estimates of the mental health effects of discrimination in this meta-analysis. Future research should investigate more diverse samples, further explain the heterogeneity of findings, and explore protective factors of the effects of discrimination on mental health. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Ayurvedic Herbal Medicines: A Literature Review of Their Applications in Female Reproductive Health.

Ayurveda, an ancient holistic and personalized healing system originating from the Indian subcontinent, has been gaining increasing attention as a complementary and alternative medical practice for treating various health conditions, including those related to women's reproductive well-being. This comprehensive literature review examines a wide array of experimental and clinical studies exploring the diverse facets of Ayurvedic interventions in addressing issues such as menstrual irregularities, polycystic ovary syndrome (PCOS), infertility, and menopausal symptoms. The paper specifically focuses on discussing the available data regarding the efficacy of Tulsi (Ocimum tenuiflorum), ashwagandha (Withania somnifera), ginger (Zingiber officinale), cardamom (Elettaria cardamomum), turmeric (Curcuma longa), and Shatavari (Asparagus racemosus), which have traditionally been used in Ayurvedic medicine for centuries. The synthesis of literature not only highlights the potential benefits of these Ayurvedic interventions, but also critically assesses the methodological rigor of existing studies, identifying research gaps, and proposing directions for future investigations. While acknowledging the need for further rigorous research and clinical trials, the review emphasizes the benefits of collaborative and integrative healthcare. This review aims to serve as a valuable resource for healthcare practitioners, researchers, and individuals seeking holistic and natural alternatives for female reproductive health management.

A path to success: educational board diversity and its influence on MENA banks’ efficiency and stability

PurposeThis paper aims to examine how the diversity of educational levels within bank boards influences the efficiency and stability of banks operating in the Middle East and North Africa (MENA) region. Unlike previous studies, this analysis also investigates the role of board gender diversity in moderating the relationship between board educational level diversity and bank efficiency and financial stability in MENA.Design/methodology/approachIn this study, a sample of 77 banks in the MENA region spanning the years 2011 to 2018 is used. The relationship between the presence of highly educated directors on the board, bank efficiency and stability is assessed using the ordinary least squares method. Additionally, the authors use the Generalized Method of Moments technique to correct endogeneity problem.FindingsThis study establishes a positive association between the presence of directors with advanced educational backgrounds on bank boards and bank efficiency and stability. Furthermore, the inclusion of women on the board strengthens this relationship.Practical implicationsThese findings have important implications for policymakers and regulators in the MENA region, suggesting that promoting diversity policies that encourage the participation of highly educated directors on bank boards can contribute to enhanced efficiency and financial stability. Policymakers may also consider implementing quotas or guidelines to improve gender diversity in board appointments, thereby fostering bank performance in the region.Originality/valueThis study stands out for its innovation and distinctiveness, as it delves into the connection between board educational level diversity and bank efficiency in the MENA region. Notably, it surpasses previous research by investigating the moderating role of board gender diversity, thus offering valuable insights into the complex interplay between these two facets of board diversity. This contribution enriches the existing literature by providing novel perspectives on board composition dynamics and its influence on bank efficiency and stability.

Uncovering PPAR-γ agonists: An integrated computational approach driven by machine learning

Peroxisome proliferator-activated receptor gamma (PPAR-γ) serves as a nuclear receptor with a pivotal function in governing diverse facets of metabolic processes. In diabetes, the prime physiological role of PPAR-γ is to enhance insulin sensitivity and regulate glucose metabolism. Although PPAR-γ agonists such as Thiazolidinediones are effective in addressing diabetes complications, it is vital to be mindful that they are associated with substantial side effects that could potentially give rise to health challenges. The recent surge in the discovery of selective modulators of PPAR-γ inspired us to formulate an integrated computational strategy by leveraging the promising capabilities of both machine learning and in silico drug design approaches. In pursuit of our objectives, the initial stage of our work involved constructing an advanced machine learning classification model, which was trained utilizing chemical information and physicochemical descriptors obtained from known PPAR-γ modulators. The subsequent application of machine learning-based virtual screening, using a library of 31,750 compounds, allowed us to identify 68 compounds having suitable characteristics for further investigation. A total of four compounds were identified and the most favorable configurations were complemented with docking scores ranging from −8.0 to −9.1 kcal/mol. Additionally, the compounds engaged in hydrogen bond interactions with essential conserved residues including His323, Leu330, Phe363, His449 and Tyr473 that describe the ligand binding site. The stability indices investigated herein for instance root-mean-square fluctuations in the backbone atoms indicated higher mobility in the region of orthosteric site in the presence of agonist with the deviation peaks in the range of 0.07–0.69 nm, signifying moderate conformational changes. The deviations at global level revealed that the average values lie in the range of 0.25–0.32 nm. In conclusion, our identified hits particularly, CHEMBL-3185642 and CHEMBL-3554847 presented outstanding results and highlighted the stable conformation within the orthosteric site of PPAR-γ to positively modulate the activity.

Diversity of an Odonata assemblage from a tropical dry forest in San Buenaventura, Jalisco, Mexico (Insecta, Odonata).

The patterns of richness, diversity, and abundance of an odonate assemblage from San Buenaventura, Jalisco are presented here. A total of 1087 specimens from seven families, 35 genera and 66 species were obtained through monthly samplings of five days each during a period of one year. Libellulidae was the most diverse family (28 species), followed by Coenagrionidae (21), Gomphidae (7), Aeshnidae (6), Calopterygidae (2), Lestidae (1) and Platystictidae (1). Argia was the most speciose genus. The highest species richness and Shannon diversity were found during August and September, whereas the highest abundance was observed in June and the highest Simpson diversity was recorded in September - all of which were associated with the rainy season. The highest values of phylogenetic diversity were found from June to October. The different diversity facets of this assemblage were positively correlated with precipitation and minimum temperature, whereas maximum temperature showed no influence. In addition, we found that this odonate diversity was higher than most Mexican localities with tropical dry forest (TDF) studied. We continue our efforts to describe the patterns of richness, diversity and abundance of some insect groups associated with the tropical dry forest ecosystem in Mexico, following a latitudinal gradient of the distribution of this ecosystem in the country. Our emphasis here was to evaluate the spatial and temporal patterns of richness and diversity of an Odonata assemblage from Jalisco, Mexico.

University Students’ Conceptualisation of AI Literacy: Theory and Empirical Evidence

This research endeavours to systematically investigate the multifaceted domain of AI literacy, given the pervasive impact of artificial intelligence on diverse facets of contemporary human existence. The inquiry is motivated by a fundamental question posed to educators: how best to cultivate AI literacies and competencies and how these proficiencies are structured and influenced. Employing a rigorous two-part methodology, the initial phase scrutinises 28 studies from the SCOPUS database, unveiling five distinct discourses germane to AI literacy. Subsequently, the second phase involves the administration of questionnaires to 73 students, whose responses undergo thematic analysis to discern patterns within the four domains delineated by Ng et al. The ensuing discourse underscores a pivotal revelation: despite formal adherence to established discourses, the conceptualisation of AI literacy necessitates a departure from conventional perspectives. Ethical principles, elucidated by students, emerge not merely as individual components but as integral facets of a broader societal literacy profile, thereby advocating a paradigm shift towards social reflection. This novel insight prompts a critical re-evaluation of AI literacy’s prevailing assumptions and conceptual frameworks, urging a transition towards models grounded in ecological or network dynamic interactionist principles.