Search Results (659)

This paper uses panel data from 30 Chinese provinces (municipalities and autonomous regions) for the period 2007–2024. It examines the impact of the agglomeration of high-end talent on regional innovation efficiency and its underlying mechanisms, based on the theory of external economies of talent agglomeration. Additionally, it analyzes regional heterogeneity and heterogeneity across innovation actors. The study finds that the agglomeration of high-end talent exerts a significant positive effect on regional innovation efficiency, exhibiting a nonlinear inverted U-shaped relationship. These findings hold even after addressing endogeneity issues and conducting various robustness tests. Heterogeneity analysis indicates that the agglomeration of high-end talent has a more pronounced positive effect on regional innovation efficiency, particularly in the eastern and western regions and in universities and research institutions; however, the optimal agglomeration level in the western region is lower than that in the eastern region. The agglomeration of high-end talent in central regions and in enterprises above a certain scale fails to significantly enhance regional innovation efficiency. The agglomeration of high-end talent positively affects regional innovation efficiency in highly marketized regions, but such an effect is not observed in regions with low marketization. The results of mediation analysis suggest that high-end talent agglomeration fosters regional innovation efficiency by facilitating knowledge spillovers and collaborative industry–university–research activities. The above research not only confirms the positive impact of the agglomeration of high-end talent on regional innovation efficiency but also provides policy recommendations for local governments regarding talent development and regional mobility. It holds practical significance for achieving major strategic goals such as building a science and technology powerhouse, a talent powerhouse, and sustainable development. Full article

Modern healthcare systems, grounded in the logic of Western natural science, compartmentalize the mind and body, thereby privileging physical phenomena while excluding non-scientific or metaphysical understandings of illness. Within this context, Taiwan’s flourishing body–mind–spirit movements represent an important counter-discourse that challenges biomedical reductionism by reasserting the unity of corporeal and spiritual. Drawing on ethnographic research of the contemporary Taiwanese spiritual organization GW (pseudonym), this study examines how its teachings and practices articulate an alternative ontology of illness and healing. GW interprets certain ailments as manifestations of karmic or spiritual disturbances, and advocates meditative discipline, and bodily training as a means of restoring balance. The group’s framework situates the body not as a passive object of treatment but as an active site of transformation, reviving the Chinese tradition of self-cultivation. The analysis argues that GW exemplifies a modern revival of the tradition of self-cultivation within a scientifically oriented society. Full article

This paper presents an adaptive noise-aware bearing fault diagnosis framework that integrates Fast Fourier Transform (FFT)-windowed feature extraction, wavelet-based Signal-to-Noise Ratio (SNR) estimation, and Long Short-Term Memory (LSTM) classification to maintain high diagnostic accuracy under both clean and severely noisy operating conditions. The core novelty of the proposed framework lies in its adaptive model selection mechanism, which automatically selects the most appropriate LSTM classifier according to the estimated SNR, thereby improving diagnostic robustness across different noise environments. Experiments were conducted on two benchmark datasets, the Case Western Reserve University (CWRU) dataset and the Huazhong University of Science and Technology (HUST) bearing dataset, to evaluate the generalization capability of the proposed approach. Two preprocessing pipelines were examined: time-domain normalization before FFT and frequency-domain normalization after FFT. Vibration signals were segmented without overlap to ensure unbiased evaluation. The results demonstrate that both the choice of window function and the normalization strategy significantly influence classification accuracy and robustness. Under noise-free conditions, several window types achieved accuracies above 99%, with triangular and Hamming windows providing the best performance. The combination of triangular windowing and time-domain normalization achieved the highest accuracy of 99.69%. Furthermore, time-domain normalization combined with triangular windowing exhibited superior stability and noise resistance compared with frequency-domain normalization. Under noisy conditions, noise-augmented training was found to be essential for achieving robust generalization. Models trained with moderate noise levels (8–12 dB) provided the best trade-off between accuracy and robustness, whereas excessive noise during training degraded performance. To accommodate varying noise environments, a lightweight wavelet-based SNR estimator was used to categorize operating conditions into low-, medium-, and high-SNR regions and select the corresponding LSTM classifier. The proposed framework was successfully implemented on a ZedBoard FPGA (Field-Programmable Gate Array) development board using a System-on-Chip (SoC) architecture. Experimental results show that, with a sampling frequency of 48 kHz and a processing window of 2048 samples, the proposed system updates the diagnostic result every 42.7 ms, demonstrating its suitability for real-time industrial condition monitoring and intelligent predictive maintenance applications. Full article

Ecological niche modeling (ENM) is widely used to predict species distributions and support biodiversity conservation under environmental change, yet its application to Amazonian wetland plants has not been systematically synthesized. We conducted a systematic review following the PRISMA 2020 guidelines to evaluate methodological approaches, environmental predictors, model performance, and research gaps. Literature searches were performed in Web of Science, Scopus, and Consensus (as a complementary AI-assisted academic search platform), yielding 1789 records, of which 48 met the eligibility criteria. Correlative models predominated, with MaxEnt, Random Forest, and ensemble frameworks being the most frequently applied algorithms. Across studies, integrating hydrological and edaphic predictors consistently improved model performance and ecological realism compared with climate-only approaches. Future climate projections indicated greater vulnerability for habitat-specialist species, whereas western Amazonia and the Andean foothills were repeatedly identified as potential climatic refugia. Major limitations included geographically biased occurrence records, limited high-resolution environmental datasets, and the underrepresentation of several Amazonian wetland ecosystems. Overall, the evidence indicates that reliable ENMs for Amazonian wetlands require integrating climatic, hydrological, and edaphic drivers rather than relying solely on macroclimate. Future research should prioritize geographically representative sampling, improved environmental datasets, transparent workflows, and process-informed modeling to strengthen ecological forecasting and conservation planning under climate and land-use change. Full article

Mainland Portugal has a lichenological tradition spanning more than three centuries, yet it still lacks a modern, critically revised checklist of its lichen biota. This gap is particularly relevant given the increasing role of species checklists as authoritative references for DNA metabarcoding applications and the expansion of large biodiversity datasets, including those derived from citizen science initiatives. Here we present the first comprehensive checklist of lichens and lichenicolous fungi recorded from Mainland Portugal, based on the critical assessment of 43,718 bibliographic records drawn from 381 publications issued between 1788 and 2021. A total of 2012 species and infraspecific taxa are documented from a universe of 4440 taxonomic names, including synonyms. Nomenclature was updated in accordance with the ITALIC 8.0 database. Species distributions are provided by province, following the scheme adopted in Portuguese botanical floras, with additional information on substrates and altitudinal ranges where available. With over 2000 taxa recorded, Mainland Portugal can be considered a lichen-rich territory relative to its land area, comparing favourably with other European checklists. We discuss the factors underlying this diversity, with particular emphasis on the biogeographical position of Portugal at the south-western edge of the European continent. Full article

Background: Triple-Negative Breast Cancer (TNBC) remains the most aggressive oncological challenge within the African continent, characterized by high molecular heterogeneity, early onset in African women, and the absence of hormonal receptors. Multi-drug resistance (MDR), driven by ATP-binding cassette (ABC) efflux pumps and supported by the persistence of cancer stem cells (CSCs) within the tumor microenvironment, significantly compromises clinical outcomes and traditional treatment efficacy. Objective: This systematic review evaluates the ethnobotanical relevance, phytochemical diversity, and toxicity of some medicinal plants from the African pharmacopoeia specifically utilized or investigated for their activity against the TNBC phenotype. Methods: Following PRISMA guidelines, a systematic search was executed across PubMed, ScienceDirect, Scopus, Web of Science, and AJOL. The study focuses on original research published between 2011 and 2026 utilizing TNBC-specific models (such as MDA-MB-231, BT-20, HCC1937, or 4T1) and analyses the growth habits, parts used, and traditional administration modes of the selected African plant species, distributed across Western, Central, Southern, and Eastern Africa. Following a rigorous multi-reviewer screening process, a final set of 52 primary articles representing 30 distinct genera and 22 botanical families was selected for qualitative and quantitative synthesis. Results: This review identifies plant species actively used or studied in Africa for their anti-TNBC potential, with the most representative botanical families being Asteraceae (13%), Fabaceae (7%), and Annonaceae (7%). These species are traditionally administered through various methods, including decoction, infusion, and mastication, utilizing diverse plant parts such as leaves, stem and root barks. Significant cytotoxic activities against TNBC cell lines (notably MDA-MB-231) were recorded, with IC₅₀ values as low as 5.10 ± 0.28 µg/mL for Catharanthus roseus and 13.56 µg/mL for Nauclea pobeguinii. Furthermore, species such as Vernonia amygdalina and Curcuma longa demonstrated a capacity to enhance the effectiveness of conventional chemotherapy like Doxorubicin, suggesting a strong potential for chemosensitization and therapeutic synergy in managing resistant breast cancer phenotypes. Conclusions: Standardized African phytomedicines represent a promising frontier in overcoming TNBC chemoresistance. However, the lack of clinical trials and end-to-end drug development infrastructure on the continent remains a significant barrier. Transitioning to nano-formulated delivery systems and establishing regional drug discovery hubs under the ethical framework of the Nagoya Protocol are essential steps toward developing precise and equitable oncology treatments from Africa’s rich biodiversity. Full article

Introduction: It is estimated that about 20–35% of the Western population reports symptoms of food intolerances, which is a growing trend. Intolerance to histamine, a dose-dependent, non-allergic food hypersensitivity reaction, despite similar clinical manifestations, has mechanisms distinct from food allergies. Objectives: This narrative review aims to ascertain and synthesize the evidence on the role of nutrition, microbiota modulation, and food supplementation in histamine intolerance. Methods: The search was conducted between September and October 2025 in the PubMed and ScienceDirect databases, using terms related to “histamine intolerance” and considering the last 10 years. 43 scientific articles and 5 additional regulatory and guidance documents were included. Results: The clinical manifestations of histamine intolerance are heterogeneous and complex, and different responses may occur in the same individual with equal doses of histamine. In the literature, intestinal dysbiosis promotes a local and systemic increase in histamine, triggering symptoms in predisposed individuals. The low-histamine diet induced a significant reduction in cutaneous and gastrointestinal symptoms. The literature also shows that diamine oxidase enzyme supplementation is promising in the treatment of migraines and chronic urticaria, contributing to a reduction in the dose and frequency of drugs. In addition, vitamins C and B6, S-adenosylmethionine, and magnesium have been studied in therapy. Conclusions: Histamine intolerance represents a challenge in clinical practice due to its complexity, symptomatologic diversity, and the lack of consensus regarding diagnosis and treatment. Full article

To address the issues of rolling bearing fault vibration signals being susceptible to noise interference and the support vector machine (SVM) relying on manual parameter settings, this paper proposes a fault diagnosis method based on ICEEMDAN and AIHO−SVM. Firstly, the Hippopotamus Optimization Algorithm is improved by incorporating Chebyshev chaotic mapping, refraction opposite learning, dynamic weighting, adaptive step size, and guided learning strategies, thereby enhancing convergence accuracy and speed. Secondly, ICEEMDAN is employed to decompose vibration signals for noise reduction, and the effective intrinsic mode function (IMF) components are selected according to the mutual information criterion to reconstruct the signal. Nine time−domain statistical features are then extracted to construct the fault feature vector. Thirdly, AIHO is used to collaboratively optimize the penalty factor and kernel parameters of SVM, establishing an AIHO−SVM classification model. Finally, the proposed method is validated on bearing datasets from Case Western Reserve University and Huazhong University of Science and Technology. Experimental results show that the average diagnostic accuracies on the two datasets reach 99.07% and 99.09%, respectively, demonstrating the effectiveness of the proposed method for rolling bearing fault diagnosis. Full article

Contemporary cognitive science is predominantly grounded in physicalist assumptions that locate cognition and consciousness in neural and computational processes. While these approaches have yielded significant empirical advances, they often struggle to account for the qualitative and first-person structure of experience. This paper proposes an ethno-phenomenological perspective by engaging non-Western epistemic practices through the lens of embodied cognition and ontological pluralism. Rather than treating non-Western phenomenology as external to scientific inquiry, we analyze how it can inform cognitive dynamism and ontological enactment through sophisticated epistemic practices. Particularly, we analyze how by actively manipulating cognitive and informational structures, Śaiva-Śākta phenomenology may dynamically affect embodied subjectivity. From this perspective, certain methods like visualization and ritual enactment can be understood as systematic interventions that modulate attentional, mnemonic, and perceptual processes, thereby reconfiguring the experiential architecture of the self and world. We further examine how processes such as constructive imagination function as mechanisms of cognitive reorganization, enabling practitioners to inhabit multiple ontological configurations of subject–object relations. Drawing on predictive processing and enactive cognitive science, the paper argues that Śaiva-Śākta sādhanā may operationalize a form of embodied epistemology in which ontology is not merely represented but enacted. This supports a model of ontological pluralism in which divergent experiential worlds correspond to stabilized modes of cognition rather than competing metaphysical hypotheses. Within this framework, sādhanā is considered a methodological method for investigating consciousness beyond reductionist neurophysiological accounts, offering structured access to non-ordinary modes of experience. Conclusively, the paper proposes that certain non-Western traditions may provide not only philosophical insights but also alternative phenomenological pathways for exploring the informational dynamics of embodied cognition, thereby expanding the methodological and ontological horizons of cognitive science and philosophy of mind. Full article

The accelerating urgency of global public health challenges, biodiversity loss, and climate change has driven rapid innovation in novel foods and alternative proteins, including cultured cells, fermentation-derived components, plant-based meats, insects, and algae, which promise nutritious, sustainable, and ethical dietary choices with lower environmental footprints. Although technologies have advanced, consumer perception and preferences remain key hindrances due to perceptual, cultural, and sensory challenges. This semi-systematic narrative literature review aims to incorporate interdisciplinary studies (2020–2025) that span sensory science, AI-driven marketing, behavioral economics, and policy analysis to explore consumer incentives, barriers, and intervention approaches associated with novel food categories. Of 1260 initial records, 310 duplicates were removed, 530 were excluded at title/abstract screening, 233 were excluded at full-text review, leaving 197 studies for the final synthesis. The focus is on understanding cultural contexts, cognitive biases, digital and social influences, and the global framing impacts that shape consumer adoption. Consumer perceptions and preferences are primarily influenced by health benefits, ethical concerns, and environmental sustainability; however, neophobia, sensory unfamiliarity, trust deficits, and price temper these factors. Preliminary evidence suggests that AI-generated personalization, transparent labeling, behavioral nudges, and social norms may be useful tools for overcoming resistance to change, though the effectiveness of AI-driven personalization in actual purchasing behavior is not yet firmly established. Cultural diversity affects acceptance routes, with culturally established insect consumption differing from Western neophobia. Future studies should integrate interdisciplinary methodologies, longitudinal cross-cultural analyses, and innovative technologies to enhance communication and product design. Full article

Accessibility in bus-based public transport is essential for inclusive and sustainable urban mobility, yet bus stops and stations are often overlooked compared with vehicle modernization and network planning. This study presents a bibliometric and thematic review of research (2020–2026) on accessibility in bus stop and station infrastructure across European cities. Literature indexed in the Web of Science Core Collection was analyzed using thematic synthesis supported by bibliometric network analysis. A total of 685 publications were examined to identify research trends, barriers, regional differences, assessment methods, and planning implications. The findings show that accessibility is a multidimensional concept shaped by physical design, information systems, user experience, first- and last-mile connectivity, and governance capacity. Persistent barriers include poor boarding interfaces, inadequate maintenance, weak wayfinding, safety concerns, and uneven implementation of accessibility standards. The reviewed studies suggest that evidence of stronger integration and higher user satisfaction is more frequently reported in Northern and some Western European contexts, whereas rural and smaller cities often face lower service accessibility. Emerging topics include real-time passenger information, crowding management, electric buses, and smart mobility technologies. The review concludes that bus stops and stations should be treated as strategic mobility assets. Integrated planning, participatory design, and territorially differentiated policy support are essential to advance inclusive bus-based public transport across Europe. Full article

To advance crop type mapping in support of global food and water security, this study compared three spectral configurations: (A) the full 60-band DLR Earth Sensing Imaging Spectrometer (DESIS) hyperspectral narrowband (HNB) dataset, (B) a 14-band subset of DESIS-derived HNBs aligned with the planned Landsat 10 (formerly Landsat Next) spectral configuration (400–1000 nm), and (C) DESIS-based simulations of Landsat 10 superspectral broadbands. The analysis was conducted in California’s Central Valley, hereafter referred to as “the Central Valley”, during the peak growing month of August. DESIS imagery from August 2021, 2022, and 2023 was used sequentially for model development, testing, and independent validation. Over these three years, DESIS provided extensive hyperspectral coverage of much of the 4 million hectares in the Central Valley’s. Analyses were performed on Google Earth Engine using two pixel-based supervised classifiers, Random Forest (RF) and Support Vector Machine (SVM), to differentiate three major crop classes: row crops, grapes and tree crops, and winter wheat/fallow/other. The highest overall accuracy (86%) was achieved using SVM in combination with either the full DESIS hyperspectral dataset or the 14 DESIS narrowbands corresponding to Landsat 10. This finding aligns with earlier studies showing a small number of strategically positioned narrowbands can be optimal for crop type classification. Use of the narrowband datasets resulted in substantially higher accuracy (overall accuracy of 86%) compared to the simulated Landsat 10 broadbands (overall accuracy of 75%), supporting previous studies highlighting the utility of narrowbands. Despite the high accuracy using August imagery, the study indicates more granular crop type classification will require multi-temporal observations spanning the full phenological cycle (June–October), especially for a large number of crop classes. Acquiring task-based hyperspectral imagery over such large areas throughout the growing season remains operationally challenging. In contrast, Landsat 10 superspectral imagery could provide routine coverage across seasons and years that is practical and scalable for future large area crop type mapping and agricultural monitoring. Full article

High-latitude regions are witnessing unprecedented wildfires and accelerated warming. This study explored wildfire patterns and land changes within the high-latitude Indigenous Tłı̨chǫ territory in the Northwest Territories, Canada. It used the Two-Eyed Seeing approach, which combines Western science, or Scientific Ecological Knowledge (SEK), with Indigenous knowledge, or Traditional Ecological Knowledge (TEK). This method integrated Earth observation data with insights from Tłı̨chǫ Elders and officials. We analyzed spatiotemporal variations in burned areas, land surface temperature (LST), albedo, snow cover, soil moisture, and land-cover types. A listening and storytelling session with community Elders provided an in-depth Indigenous perspective. Our findings indicate a concerning shift in wildfire activity on Tłı̨chǫ land, primarily driven by the interplay between climate change and land-cover changes. Land-cover estimates over the past fifteen years indicate that nearly half of the forested areas on Tłı̨chǫ-owned land have been converted to other land-cover types, with shrublands increasing twofold and grasslands expanding tenfold. We observed significant increases in spring and summer LSTs (p < 0.05), alongside decreases in precipitation and snow cover (p < 0.05), consistent with the Elders’ observations. The decline in topsoil moisture, coupled with rising temperatures, has triggered a positive feedback loop in forested areas, intensifying future wildfire risk. The study’s implications extend beyond the Tłı̨chǫ territory, suggesting a broader significance for climate resilience and Indigenous stewardship. It highlights the significance of place-based, integrated research for understanding complex wildfire behavior and land-cover transformations. The study indicates that the Two-Eyed Seeing approach, which weaves local Indigenous knowledge with quantitative Earth observations, not only improves analytical precision but also provides a collaborative framework for developing targeted strategies to mitigate the effects of increasingly severe fire regimes and land-cover changes. Full article

Mental fatigue is an increasingly important concern among collegiate athletes whose academic–athletic roles require sustained cognitive effort, emotional regulation, and recovery across overlapping performance contexts. This structured narrative review synthesizes behavioral science, sport psychology, and athlete mental health literature to clarify how perceived stress, competitive anxiety, and psychological resilience may interact in the development and regulation of mental fatigue among collegiate athletes. Rather than treating mental fatigue as simple tiredness or an isolated performance symptom, this review conceptualizes it as a cognitive–emotional and psychobiological outcome shaped by stress appraisal, attentional load, effort regulation, and resource depletion. The main contribution of this review is to integrate previously separate lines of research into a collegiate-athlete-focused behavioral science framework in which perceived stress is positioned as an upstream appraisal-based condition, competitive anxiety as a proximal emotional mechanism, and psychological resilience as a dynamic regulatory resource that may buffer fatigue-related vulnerability. Tennis and Chinese/non-Western collegiate sport contexts are used as illustrative applications rather than exclusive empirical targets, highlighting how individual accountability, academic–athletic role demands, cultural expectations, and support structures may shape fatigue processes. This review also distinguishes established empirical evidence from theoretical inference and identifies key gaps in measurement heterogeneity, methodological transparency, longitudinal evidence, and culturally diverse collegiate athlete research. By refining the stress–anxiety–fatigue pathway and identifying resilience, recovery, and contextual support as important regulatory factors, this review provides a conceptual foundation for future empirical testing and for more targeted behavioral interventions to support collegiate athlete well-being and performance sustainability. Full article