Search Results (1,340)

Sociotechnical systems (STSs) are generally assumed to be systems that incorporate humans and technology, strongly depending on a sustainable equilibrium between the following nondeterministic social context ingredients: social structures, roles, and rights, as well as the designers’ Holy Grail, the deterministic nature of the underlying technical system. The fact that the relevant social concepts are more mature than the supporting technologies qualifies the digital transformation of sociotechnical systems as a reengineering rather than an engineering endeavor. Preserving the social mission throughout the digital transformation process in varying social contexts is mandatory, making the digital twins (DT) methodology application a contemporary research hotspot. In this research, we combined continuous transformation STS theory principles, an observer-based system-of-sociotechnical-systems (SoSTS) architecture model, and digital twinning methods to address common STS context representation challenges. Additionally, based on model-driven systems engineering methodology and meta-object-facility principles, the research specifies the universal meta-concepts and meta-modeling templates, supporting the creation of arbitrary sociotechnical systems’ external context digital twins. Due to the inherent diversity, significantly influenced by geopolitical, economic, and cultural influencers, a higher education external context specialization illustrates the reusability potentials of the proposed universal meta-concepts. Substituting higher-education-related meta-concepts and meta-models with arbitrary domain-dependent specializations further fosters the proposed universal meta-concepts’ reusability. Full article

(1) Background: This article aims to understand the forms and elements through which the inhabitants of the city of Medellin have configured their subjectivity in the context of the application of neoliberal policies in the last two decades. In this way, we can approach the frameworks of understanding that constitute a fundamental part of the individuation processes in which the incorporation of their subjectivities is evidenced in neoliberal contexts that, in the historical process, have been converging with authoritarian, antidemocratic and neoconservative elements. (2) Method: A qualitative approach with a hermeneutic-interpretative paradigm was used. In-depth semi-structured interviews were conducted with 41 inhabitants of Medellín who were politically identified with right-wing or center-right positions. Data analysis included thematic coding to identify patterns of thought and points of view. (3) Results: Participants associate success with individual effort and see state intervention as an obstacle to development. They reject redistributive policies, arguing that they generate dependency. In addition, they justify authoritarian models of government in the name of security and progress, from a moral superiority, which is related to a negative and stigmatizing perception of progressive sectors and a negative view of the social rule of law and public policies with social sense. (4) Conclusions: The naturalization of merit as a guiding principle, the perception of themselves as morally superior based on religious values that grant a subjective place of certainty and goodness; the criminalization of expressions of political leftism, mobilizations and redistributive reforms and support for policies that establish authoritarianism and perpetuate exclusion and structural inequalities, closes roads to a participatory democracy that enables social and economic transformations. Full article

Aim: Pacifiers play a critical role in the early stages of craniofacial and palate development during infancy. While they provide comfort and aid in soothing, their use can also have significant impacts on the growth and function of the oral cavity. This study aimed to simulate and predict the behavior of six different types of pacifiers and their functional interaction with the tongue and palate, with the goal of understanding their potential effects on orofacial growth and development. Materials and Methods: Biomechanical analysis using Finite Element Analysis (FEA) mathematical models was employed to evaluate the behavior of six different commercial pacifiers in contact with the palate and tongue. Three-dimensional solid models of the palate and tongue were based on the mathematical framework from a 2007 publication. This allowed for a detailed investigation into how various pacifier designs interact with soft and hard oral tissues, particularly the implications on dental and skeletal development. Results: The findings of this study demonstrate that pacifiers exhibit different interactions with the oral cavity depending on their geometry. Anatomical–functional pacifiers, for instance, tend to exert lateral compressions near the palatine vault, which can influence the hard palate and contribute to changes in craniofacial growth. In contrast, other pacifiers apply compressive forces primarily in the anterior region of the palate, particularly in the premaxilla area. Furthermore, the deformation of the tongue varied significantly across different pacifier types: while some pacifiers caused the tongue to flatten, others allowed it to adapt more favorably by assuming a concave shape. These variations highlight the importance of selecting a pacifier that aligns with the natural development of both soft and hard oral tissues. Conclusions: The results of this study underscore the crucial role of pacifier geometry in shaping both the palate and the tongue. These findings suggest that pacifiers have a significant influence not only on facial bone growth but also on the stimulation of oral functions such as suction and feeding. The geometry of the pacifier affects the soft tissues (tongue and muscles) and hard tissues (palate and jaw) differently, which emphasizes the need for careful selection of pacifiers during infancy. Choosing the right pacifier is essential to avoid potential negative effects on craniofacial development and to ensure that the benefits of proper oral function are maintained. Therefore, healthcare professionals and parents should consider these biomechanical factors when introducing pacifiers to newborns. Full article

Amid intensifying global ESG regulations and the expanding influence of green finance, China’s digital economy policies have emerged as key institutional instruments for promoting corporate sustainability. Leveraging the implementation of the National Big Data Comprehensive Pilot Zone as a quasi-natural experiment, this study utilizes panel data of Chinese listed firms from 2009 to 2023 and applies multi-period Difference-in-Differences (DID) and Spatial DID models to rigorously identify the policy’s effects on corporate ESG performance. Empirical results indicate that the impact of digital economy policy is not exerted through a direct linear pathway but operates via three institutional mechanisms, enhanced information transparency, eased financing constraints, and expanded fiscal support, collectively constructing a logic of “institutional embedding–governance restructuring.” Moreover, disruptive technological innovation significantly amplifies the effects of the transparency and fiscal mechanisms, but exhibits no statistically significant moderating effect on the financing constraint pathway, suggesting a misalignment between innovation heterogeneity and financial responsiveness. Further heterogeneity analysis confirms that the policy effect is concentrated among firms characterized by robust governance structures, high levels of property rights marketization, and greater digital maturity. This study contributes to the literature by developing an integrated moderated mediation framework rooted in institutional theory, agency theory, and dynamic capabilities theory. The findings advance the theoretical understanding of ESG policy transmission by unpacking the micro-foundations of institutional response under digital policy regimes, while offering actionable insights into the strategic alignment of digital transformation and sustainability-oriented governance. Full article

Knowing the superior biochemical defense mechanisms of sessile organisms, it is not hard to believe the cure for any human sickness might be hidden in nature—we “just” have to identify it and make it safely available in the right dose to our organs and cells that are in need. For decades, green tea catechins (GTCs) have been a case in point. Because of their low redox potential and favorable positioning of hydroxyl groups, these flavonoid representatives (namely, catechin—C, epicatechin—EC, epicatechin gallate—ECG, epigallocatechin—EGC, epigallocatechin gallate—EGCG) are among the most potent plant-derived (and not only) antioxidants. The proven anti-inflammatory, neuroprotective, antimicrobial, and anticarcinogenic properties of these phytochemicals further contribute to their favorable pharmacological profile. Doubtlessly, GTCs hold the potential to “cope” with the majority of today‘s socially significant diseases, yet their mass use in clinical practice is still limited. Several factors related to the compounds’ membrane penetrability, chemical stability, and solubility overall determine their low bioavailability. Moreover, the antioxidant-to-pro-oxidant transitioning behavior of GTCs is highly conditional and, to a certain degree, unpredictable. The nanoparticulate delivery systems represent a logical approach to overcoming one or more of these therapeutic challenges. This review particularly focuses on the lipid-based nanotechnologies known to be a leading choice when it comes to drug permeation enhancement and not drug release modification nor drug stabilization solely. It is our goal to present the privileges of encapsulating green tea catechins in either vesicular or particulate lipid carriers with respect to the increasingly popular trends of advanced phytotherapy and functional nutrition. Full article

The continuously enhanced generative capabilities of artificial intelligence (AI) are challenging the existing patent system. There are still some issues, such as whether AI can be considered an inventor, whether technical solutions generated by AI are patentable, and how ownership should be allocated. AI-generated technical solutions fall under the category of patentable subject matter. Specifically, if they meet the requirements of the “three criteria,” they can become the subject of patent rights. Regarding the issue of AI’s eligibility as an inventor, a parallel technical generation registration system for AI should be established, with the current inventor system maintained in parallel. Concerning patent ownership issues, the assignable subjects of patent rights should be limited to the binary subjects of users and investors. Contractual agreements should take precedence to ensure contractual freedom, and ownership should generally be attributed to the user if no agreement exists. Additionally, a specialized fast-track review and authorization mechanism should be designed for AI-generated technical solutions, given the unique nature of AI-generated solutions. Moreover, their protection periods should be appropriately shortened to ensure a balance of interests. Furthermore, a disclosure system should be built across the entire lifecycle to prevent and mitigate risks that may arise during the machine generation of technical solutions, patent applications, patent authorizations, and dissemination stages. Full article

This paper addresses the critical gap in the existing literature regarding the combined buoyancy–Marangoni convection of power-law fluids in three-dimensional porous media with complex evaporation surfaces. Previous studies have rarely investigated the convective heat transfer mechanisms in such systems, and there is a lack of effective methods to accurately track fractal evaporation surfaces, which are ubiquitous in natural and engineering porous media (e.g., geological formations, industrial heat exchangers). This research is significant because understanding heat transfer in these complex porous media is essential for optimizing energy systems, enhancing thermal management in industrial processes, and improving the efficiency of phase-change-based technologies. For this scientific issue, a general model is designed. There is a significant temperature difference on the left and right sides of the model, which drives the internal fluid movement through the temperature difference. The upper end of the model is designed as a complex evaporation surface, and there is flowing steam above it, thus forming a coupled flow field. The VOF fractal reconstruction method is adopted to approximate the shape of the complex evaporation surface, which is a major highlight of this study. Different from previous research, this method can more accurately reflect the flow and phase change on the upper surface of the porous medium. Through numerical simulation, the influence of the evaporation coefficient on the flow and heat transfer rate can be determined. Key findings from numerical simulations reveal the following: (1) Heat transfer rates decrease with increasing fractal dimension (surface complexity) and evaporation coefficient; (2) As the thermal Rayleigh number increases, the influence of the Marangoni number on heat transfer diminishes; (3) The coupling of buoyancy and Marangoni effects in porous media with complex evaporation surfaces significantly alters flow and heat transfer patterns compared to smooth-surfaced porous media. This study provides a robust numerical framework for analyzing non-Newtonian fluid convection in complex porous media, offering insights into optimizing thermal systems involving phase changes and irregular surfaces. The findings contribute to advancing heat transfer theory and have practical implications for industries such as energy storage, chemical engineering, and environmental remediation. Full article

Henri Lefebvre’s “right to the city” has rarely been examined through an intersectional feminist lens, leaving unnoticed the uneven burdens that urban design and policy place on women. This article bridges that gap by combining constitutional analysis, survey data (n = 736), in-depth interviews, and participatory observation to assess how Quito’s public spaces affect women’s safety and mobility. Quantitative results show that 81% of respondents endured sexual or offensive remarks, 69.8% endured obscene gestures, and 38% endured severe harassment in the month before the survey; 43% of these incidents occurred only days or weeks beforehand, underscoring their routine nature. Qualitative narratives reveal behavioral adaptations—altered routes, self-policing dress codes, and distrust of authorities—and identify poorly lit corridors and weak institutional presence as spatial amplifiers of violence. Analysis of Quito’s “Safe City” program exposes a gulf between its ambitious rhetoric and its narrow, transport-centered implementation. We conclude that constitutional guarantees of participation, appropriation, and urban life will remain aspirational until urban planning mainstreams gender-sensitive design, secures intersectoral resources, and embeds women’s substantive participation throughout policy cycles. A feminist reimagining of Quito’s public realm is therefore indispensable to transform the right to the city from legal principle into lived reality. Full article

In the anti-immigrant national context of the first Trump administration, what motivated Latine immigrants in Texas to pursue naturalization? Based on 31 Spanish and English semi-structured interviews conducted during 2017–2019, we examine how lawful permanent residents’ (LPRs’) perceptions of contemporary immigration policy and their social rights affect their motivations to naturalize. Surprisingly, we find that although fear of deportation was an extremely common motivation, it was rarely the residents’ primary motivation. When asked why they wanted to naturalize, our respondents expressed four primary motivations grounded in their claims for social rights: proactive (gain the right to vote, benefit the group), pragmatic (expedite family reunification, access better jobs, benefit the individual), defensive (protect against deportation), and emotional (formalize a sense of belonging). Although 60 percent of interview subjects mentioned some defensive motivations, citing the current national and state political climate as hostile to immigrants, it was the least common primary motivation for naturalization; that is, they named another motivation first as their most important reason for naturalizing. The need to naturalize to protect their social rights in a shifting political context is a strong subtext to subjects’ narratives about why they choose to become citizens. Defensive motivations undergird all other motivations, but the national hostile climate is moderated by relatively positive local interactions with law enforcement and the larger community. Full article

Aside from a few passages addressing animals or the environment, Confucian philosophy appears to lack an environmental ethics perspective. Li Zhehou’s (李澤厚) contemporary work in Confucian philosophy continues this lacuna by limiting his understanding of community to the human realm. Using the common liberal humanism that limits moral actions to the interpersonal human realm misses the importance of inclusive moralities such as animal rights and environmental ethics. I propose that if we return to the original shared common cultural roots of Confucian and Daoist philosophy that a Confucian understanding of the natural world can embrace the non-human environment within the scope of Confucian morality. Extricating ideas from the Yijing, the Shijing, Xunzi, Dong Zhongshu, Wang Chong, and later scholars, the concept of the mutual resonance and response (ganying 感應) between the natural world and humans developed into the unity of heaven and humanity (tianren heyi 天人合一). An inclusive Confucian depth ecology opens new ways of thinking that can be deployed to envision deeper dimensions for understanding the self’s inner life, its connections to the outer life of the self–other relationship, and its extension to a kin relationship with the environment. This paper explores how these old and new ways of thinking can change our behavior and change our moral interactions with others including the environment and thereby enhancing freedom as an achievement concept derived from graceful moral action. Full article

Gait recognition is a reliable biometric approach that uniquely identifies individuals based on their natural walking patterns. It is widely used to recognize individuals who are challenging to camouflage and do not require a person’s cooperation. The general face-based person recognition system often fails to determine the offender’s identity when they conceal their face by wearing helmets and masks to evade identification. In such cases, gait-based recognition is ideal for identifying offenders, and most existing work leverages a deep learning (DL) model. However, a single model often fails to capture a comprehensive selection of refined patterns in input data when external factors are present, such as variation in viewing angle, clothing, and carrying conditions. In response to this, this paper introduces a fusion-based multi-model gait recognition framework that leverages the potential of convolutional neural networks (CNNs) and a vision transformer (ViT) in an ensemble manner to enhance gait recognition performance. Here, CNNs capture spatiotemporal features, and ViT features multiple attention layers that focus on a particular region of the gait image. The first step in this framework is to obtain the Gait Energy Image (GEI) by averaging a height-normalized gait silhouette sequence over a gait cycle, which can handle the left–right gait symmetry of the gait. After that, the GEI image is fed through multiple pre-trained models and fine-tuned precisely to extract the depth spatiotemporal feature. Later, three separate fusion strategies are conducted, and the first one is decision-level fusion (DLF), which takes each model’s decision and employs majority voting for the final decision. The second is feature-level fusion (FLF), which combines the features from individual models through pointwise addition before performing gait recognition. Finally, a hybrid fusion combines DLF and FLF for gait recognition. The performance of the multi-model fusion-based framework was evaluated on three publicly available gait databases: CASIA-B, OU-ISIR D, and the OU-ISIR Large Population dataset. The experimental results demonstrate that the fusion-enhanced framework achieves superior performance. Full article

The promotion of sustainable schools is an important criterion for the promotion of ecological protection and the transformation of today’s society into a more sustainable one. The early childhood environment is believed to provide the ideal foundation for fostering values and attitudes related to sustainable education and promoting pro-environmental behaviors. The main goal of this study is to explore educators’ perceptions and expectations regarding the role of sustainable schools in shaping the environmental awareness and behavior of young children. A pilot study was carried out in the context of quantitative research on Preschool Teachers of Primary Education. Research results indicate that a Sustainable School (SS), beyond the curriculum, must promote issues of environmental awareness, culture, equality, natural resource management, and human rights. Also, it was seen that a modern school should provide Educators with new training opportunities in teaching methods that are based on sustainability principles and promote sustainability skills. Students’ acquisition of environmental knowledge can positively influence pro-environmental behavior and increase the likelihood of engaging in sustainable practices to protect the environment. Full article

This article identifies the nature of Traditional Owners’ interests in Sea Country and addresses issues associated with all offshore energy projects—gas and wind. Exploring the impacts of offshore development on First Nations’ cultural heritage, the article proposes integration of free, prior and informed consent (FPIC) and the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), into the regulatory and legislative offshore environment. In the Australian context, this particularly regards administrative and regulatory reforms to overcome uncertainty arising from recent decisions in the Federal Court. The international focus on new energy has fast-tracked many processes that sideline First Nations’ rights, hitherto understood within the onshore minerals extraction regimes. The reforms proposed in this article recognise an international commitment to enact the principles contained in the UNDRIP and other relevant international law. Full article

Emotion recognition by wearable devices is essential for advancing emotion-aware human–computer interaction in real life. Earphones have the potential to naturally capture brain activity and its lateralization, which is associated with emotion. In this study, we newly introduced tympanic membrane temperature (TMT), previously used as an index of lateralized brain activation, for earphone-based emotion recognition. We developed custom earphones to measure bilateral TMT and conducted two experiments consisting of emotion induction by autobiographical recall and scenario imagination. Using features derived from the right–left TMT difference, we trained classifiers for both four-class discrete emotion and valence (positive vs. negative) classification tasks. The classifiers achieved 36.2% and 42.5% accuracy for four-class classification and 72.5% and 68.8% accuracy for binary classification, respectively, in the two experiments, confirmed by leave-one-participant-out cross-validation. Notably, consistent improvement in accuracy was specific to models utilizing right–left TMT and not observed in models utilizing the right–left wrist skin temperature. These findings suggest that lateralization in TMT provides unique information about emotional state, making it valuable for emotion recognition. With the ease of measurement by earphones, TMT has significant potential for real-world application of emotion recognition. Full article

Motor Imagery (MI) based Brain Computer Interfaces (BCIs) have promising applications in neurorehabilitation for individuals who have lost mobility and control over parts of their body due to brain injuries, such as stroke patients. Accurately classifying MI tasks is essential for effective BCI performance, but this task remains challenging due to the complex and non-stationary nature of EEG signals. This study aims to improve the classification of left and right-hand MI tasks by utilizing high-resolution time-frequency features extracted from EEG signals, enhanced with deep learning-based data augmentation techniques. We propose a novel deep learning framework named the Generalized Wavelet Transform-based Deep Convolutional Network (GDC-Net), which integrates multiple components. First, EEG signals recorded from the C3, C4, and Cz channels are transformed into detailed time-frequency representations using the Generalized Morse Wavelet Transform (GMWT). The selected features are then expanded using a Deep Convolutional Generative Adversarial Network (DCGAN) to generate additional synthetic data and address data scarcity. Finally, the augmented feature maps data are subsequently fed into a hybrid CNN-LSTM architecture, enabling both spatial and temporal feature learning for improved classification. The proposed approach is evaluated on the BCI Competition IV dataset 2b. Experimental results showed that the mean classification accuracy and Kappa value are 89.24% and 0.784, respectively, making them the highest compared to the state-of-the-art algorithms. The integration of GMWT and DCGAN significantly enhances feature quality and model generalization, thereby improving classification performance. These findings demonstrate that GDC-Net delivers superior MI classification performance by effectively capturing high-resolution time-frequency dynamics and enhancing data diversity. This approach holds strong potential for advancing MI-based BCI applications, especially in assistive and rehabilitation technologies. Full article