Search Results (45,745)

Detecting changes in coral and seagrass habitat composition from satellite imagery places exceptionally high demands on sensor design due to low underwater reflectance signals and variable water column conditions. Recent multispectral satellite-based attempts to assess such changes across large spatial extents illustrate this challenge through an inability to reliably distinguish live coral from algae, often resulting in broad confidence intervals. This study quantifies the radiometric sensitivity requirements for detecting 10% absolute changes in live coral and seagrass fractional cover from spaceborne imaging spectroscopy using representative parameters for an aquatic imaging spectrometer. The analysis combined representative benthic spectra with realistic, management-relevant co-occurrence scenarios informed by extensive regional knowledge and field measurements from Fiji, Australia, and the Solomon Islands to evaluate detection performance across depths from 0 to 30 m. We show that live coral is the most demanding of the benthic targets evaluated because of its low reflectance and spectral similarity to algal cover types, requiring SNRs of approximately 300–700 to detect 10% absolute changes in cover at depths up to 10 m. In contrast, the greater spectral separation between seagrass and adjacent sandy substrates allows detection of 10% absolute changes in cover to depths exceeding 20 m in clear water. These results highlight the importance of high radiometric sensitivity and contiguous spectral sampling for future aquatic imaging spectrometers intended to monitor benthic change. Approaches that increase effective SNR, such as ground motion compensation (GMC), can extend the depth and confidence with which changes in benthic composition are detected, supporting a transition from broad-area habitat mapping toward quantitative monitoring of benthic change from space. Full article

Cracks pose a significant threat to the structural integrity, durability, and service life of concrete; therefore, sustainable, autonomous repair solutions are paramount. In the last 25 years, bio-based self-healing, particularly microbially induced calcium carbonate precipitation (MICP), has become an attractive technology. Self-healing by bacteria has been studied extensively, but the use of other biomineralization agents, such as fungi and algae, has unique benefits, namely, hyphal crack-bridging and photosynthetic mineralization. In this paper, a thorough state-of-the-art review is presented that compares bacteria, fungi, and algae as biomineralization agents. The comparative methodology involves a structured review of the peer-reviewed literature on these agents (2000–2025), and compares them on a set of common performance criteria: (i) biochemical precipitation mechanisms (ureolytic, non-ureolytic, photosynthetic and hyphal bridging); (ii) quantitative crack-healing efficiency (maximum width of crack closed); (iii) mechanical performance recovery (restoration of compressive and tensile strength); (iv) long-term durability enhancement. Moreover, it critically evaluates implementation challenges, including biological viability in extreme cementitious media, encapsulation methods, and the levels of technological maturity for practical engineering applications. The findings of this synthesis outline key research gaps and offer a roadmap for creating hybrid, consortium-based self-healing systems to help engineers and researchers select the best bio-based concrete for a given structure and environment. Full article

This research project aimed to create a complete and representative picture of the facial heritage of the Canary Islands, by accommodating the interpretations of recent genome studies and explorations regarding the identity of the ancient Canarians, alongside facial anthropology and comparative analysis with a modern population. This project therefore represents an exciting combination of identity, migration, forensics and archaeology. Facial depictions were produced for fifty indigenous skulls housed at El Museo Canario of Gran Canaria, using the latest forensic technology along with well-established morphometrical standards. To our knowledge, this project represents the most extensive craniofacial analysis study of a single population from anywhere in the world. An exhibition at the El Museo Canario of Gran Canaria provided valuable public engagement in relation to anthropology and archaeology, while at the same time presenting the visualisation of people from the past. The research is timely and of global benefit within the wider cultural and social debate relating to identity, migration and nationality, demonstrating historical evidence for global migration as an ancient pattern rather than a recent phenomenon. Full article

Converter-dominated power systems increasingly require flexible resources that can support frequency while preserving a physically interpretable energy trajectory. Thermal-energy-storage (TES)-based virtual energy storage systems (VESSs) can shift electrical demand within thermal-energy and comfort constraints, and have therefore attracted extensive interest. However, existing studies commonly coordinate requested or normalized power without fully connecting it to actuator execution and the electrical-to-thermal energy path. Command-level sharing cannot be directly equated with executed physical power, and controller storage cannot be combined with joule-valued hardware energy without dimensional separation. Therefore, this paper proposes a physically coupled and energy-traceable virtual asynchronous machine (VAM) control method for TES-based VESSs. First, a loss-resolved averaged model establishes the point-of-common-coupling (PCC)–converter–DC-link–actuator–TES physical chain and separates the hardware Hamiltonian from the dimensionless control Lyapunov function. Second, a neighbor-coupled marginal controller is embedded in a command–projection–execution chain so that frequency regulation and weighted sharing are evaluated using the executed service. Third, a constraint-handling mechanism combines directional headroom gating, actuator saturation and ramp limits, thermal comfort bounds, and request-inactive state reset to maintain executable trajectories under the declared constraints. Simulations under a sustained $120\mathrm{kW}$ disturbance show that primary-only control retains a $-0.08883\mathrm{Hz}$ steady-state offset, whereas the proposed nominal case restores frequency. In the constrained case, the 30 s terminal trend remains above the prescribed limit, while both terminal windows of the 60 s run satisfy the restoration criterion; the final-window mean error and dimensionless eligible-unit sharing spread are $-6.317\times {10}^{-5}\mathrm{Hz}$ and $6.564\times {10}^{-5}$, respectively. The model-internal electrical–thermal balance achieves a dimensionless relative RMS residual of $6.2361\times {10}^{-8}$. Because the PCC voltage/current pair is reconstructed from the same power source, this residual quantifies model-internal consistency rather than independent measured closure. These results demonstrate constrained frequency restoration, executed-power coordination, and energy traceability within the averaged-model scope. Full article

The spring floods that occurred in 2024 in western and northern Kazakhstan caused extensive damage. Our understanding of runoff formation processes under frozen-soil conditions remains limited. In this study, we apply a coupled hydrothermal model as a case study to explicitly simulate vertical heat and water transport, phase transitions, snow dynamics, and reduced infiltration capacity due to cryogenic pore blockage (ice-filled pores). The model is based on regular meteorological data from 65 stations in five regions covering the full hydrological cycle (August–May) of 2021 and 2024. A multilevel diagnostic check showed that soil temperature is reproduced with a median $R^2$ of 0.962 and NSE of 0.888, the frozen/thawed surface condition corresponds to WMO (World Meteorological Organization) standards on approximately 91% of days, and water balance agreement reaches 86.2% (56 out of 65 stations). The model reflects the regional variability of the 2024 flood. In the northern regions (Kostanay, North Kazakhstan), snowfall was above average, and modeled runoff increased compared to 2021 (for example, at the Sergeevka station, it increased by a factor of four). In the western regions, the trends were mixed: the strongest relative increase in runoff was recorded in the Atyrau region (+119%), whilst in the West Kazakhstan region, the increase was more modest (+19%), and in the Aktobe region, runoff increased by 60%. The key mechanism—the time lag between rapid snowmelt and delayed soil thaw—is clearly evident: peaks in snowmelt occur when the soil remains frozen, infiltration capacity decreases, and the runoff potential index (RPI) exceeds 1 for extended periods. Although the model does not simulate the river channel, its ability to diagnose runoff generation conditions at the slope scale offers a diagnostic framework for identifying runoff-conducive conditions in regions with limited data, rather than a physically validated tool for flood-prone area identification. The results show that the 2024 flood period was characterized by abnormally high water inflow and hydrothermal conditions consistent with a temporal mismatch between water supply and the recovery of soil infiltration capacity. Because the RPI is a diagnostic indicator constructed from water input and infiltration capacity, these results should be interpreted as evidence of conditions conducive to runoff generation rather than as an independent causal verification of the flood mechanism. Full article

Background: Endometriosis-associated ovarian cancers (EAOCs), encompassing clear cell (CC) and endometrioid carcinomas (EC), constitute distinct biological entities yet lack robust biomarkers for precise classification, prognostication, and therapeutic decision-making in women. Therefore, we aimed to describe novel biomarkers. Methods: In this study, we conducted an integrated transcriptomic analysis, powered by machine learning, to discover novel consensus biomarkers and delineate cancer hallmark signatures specific to EC and CC. Drawing on gene expression profiles from EAOC specimens, we merged differential expression analysis with LASSO regression and Random Forest classification to generate a reliable biomarker panel that effectively distinguishes EC from CC. Kaplan–Meier survival analyses and mutation analyses have been performed for selected biomarker genes. Results: Novel biomarkers, among others, the genes RPS28, EPAS1, ALKBH2, and DCLRE1A, uncover extensive transcriptional alterations tied to hypoxia signaling, oxidative stress, DNA repair, and metabolic reprogramming. Gene Ontology and pathway enrichment analyses revealed synchronized upregulation of epithelial–mesenchymal transition, TNF-α/NF-κB signaling, oxidative stress, hypoxia, and KRAS signaling pathways. Conclusions: Our work establishes novel exploratory transcriptomic candidates for innovative consensus biomarkers, yielding novel diagnostic and prognostic insights into EAOC and supporting further study of subtype-associated expression programs. The current study was designed primarily as an integrative computational investigation aimed at identifying candidate genes and molecular pathways distinguishing CC from EC. Full article

Generative AI is reshaping how workers form digital commerce entrepreneurial intentions, yet how AI-related fear of missing out (AI-FoMO) converts into proactive entrepreneurial behavior remains unclear. Drawing on social cognitive theory, this study tests a model in which AI-FoMO drives AI reliance, which in turn shapes two distinct cognitive routes: a tool-referenced route through perceived task automation (PTA) and an agent-referenced route through borrowed entrepreneurial competence (BEC), a newly proposed construct capturing how human–AI coupling reshapes workers’ self-perceived capability for solo digital entrepreneurship. We further test whether digital self-efficacy (DSE) moderates the conversion of these perceptions into intention. Survey data from 328 Korean workers were analyzed using PLS-SEM. AI-FoMO predicted AI reliance (β = 0.391), which shaped both PTA (β = 0.531) and BEC (β = 0.291); both routes predicted entrepreneurial intention, and both serial mediation paths were significant, with the PTA route approximately 2.6 times stronger than the BEC route. DSE moderated only the BEC route (β = 0.105, p = 0.025), not the PTA route (β = −0.077, p = 0.109), an asymmetry confirmed by a formal coefficient-difference test. The findings reframe AI-FoMO as a potential driver of approach-oriented entrepreneurial behavior, introduce BEC as an extension of vicarious experience to the human–AI context, and show that digital self-efficacy selectively regulates how AI-induced perceptions convert into entrepreneurial intention. Full article

Background/Objectives: This study investigated the effect of sprint intensity on spatiotemporal variables and joint kinematics during the maximal-velocity phase at each intensity level in experienced sprinters. Methods: Twenty experienced master sprinters (18 men and two women, age: 38.2 ± 12.1 years, height: 1.80 ± 0.06 m, body mass: 81.8 ± 8.8 kg, 100 m PB: 12.65 ± 1.06) performed nine 50 m sprints with increasing intensity each time (60–100%), during which step-by-step spatiotemporal parameters and joint kinematics during the maximal-velocity phase of each sprint were measured. Results: The main findings were that sprint times decreased significantly with each increase in intensity, together with a significant increase in maximal sprint velocity. The spatiotemporal parameters contact and flight times decreased, step frequency increased, while step length increased until 75% and decreased again after 90%. Joint angles of the ankle and knee changed, while those of the hip joint did not change at touchdown and toe-off with increasing intensity. All peak step-by-step angular joint velocities during the maximal-velocity phases increased with increasing sprint intensity. However, the changes in joint kinematics across joints did not occur at the same time between intensity levels. Conclusions: These findings highlight that spatiotemporal variables and joint kinematics do not follow a linear development as intensity increases; rather, they adopt distinct mechanical strategies at very high intensities to accommodate reduced time for force application and limb repositioning. Based on the findings it is suggested that training targeting rapid hip-extension mechanics, efficient limb repositioning, and the ability to maintain effective propulsion under shortened contact times may be particularly beneficial. Full article

Sustainability leadership is increasingly recognised as essential for addressing complex socio-ecological challenges, yet empirically grounded competency frameworks remain scarce, particularly those derived from interdisciplinary and intergenerational samples. Building on an extensive literature synthesis, this study developed an a priori framework comprising four dimensions: (1) Knowledge & Understanding, (2) Values, Motivation & Purpose, (3) Leadership Practices & Impact, and (4) Inner Development & Learning, operationalised into 20 core competency elements. A convergent parallel mixed-methods design was conducted at Kiel University, combining quantitative importance ratings from 301 participants with qualitative content analysis of open-ended responses from 312 participants across all faculties and status groups. Quantitative findings supported all 20 elements, with systemic, value-oriented, and collaborative competencies rated particularly highly. Qualitative findings supported all deductive competency domains, with K2 and K5 merged into one integrated category, and added 12 inductive categories, foregrounding relational, visionary, critical-systemic, and inner-directed capacities. Trust and empathy emerged as implicit foundations across several dimensions. The resulting framework is organised across four competency dimensions and three relational levels: I (the leader within), Us (in relation to others), and World (in relation to society and systems). It offers a theoretically and empirically grounded foundation for sustainability leadership development in higher education, organisations, and professional training. Full article

Plant specialized metabolites are valuable sources of pharmaceuticals, nutraceuticals, and industrial compounds. Transferring their biosynthetic pathways into microbial hosts remains a major challenge, particularly in photosynthetic microalgae. Here, we investigated the ability of the green microalga Chlamydomonas reinhardtii to functionally express Cannabis sativa polyketide biosynthetic enzymes involved in olivetolic acid synthesis, a key intermediate in cannabinoid biosynthesis. Nuclear transformants carrying the C. sativa tetraketide synthase (CsTKS) and olivetolic acid cyclase (CsOAC) genes were generated. Functional enzyme activity was confirmed by in vitro enzymatic assays using total protein extracts. In vitro olivetolic acid production was detected, verified, and quantified by high-performance liquid chromatography and liquid chromatography–tandem mass spectrometry using authentic standards. However, in vivo olivetolic acid and downstream metabolites were not detected in algal biomass. This indicated that functional enzyme expression did not result in productive intracellular pathway flux. Untargeted metabolomic profiling revealed extensive metabolic rewiring and strain-specific metabolic perturbations following pathway introduction. These findings suggest that heterologous pathway expression triggered broad physiological responses. This study demonstrates that plant polyketide enzymes remain catalytically active in C. reinhardtii; however, intrinsic metabolic and cellular constraints limit in vivo metabolite accumulation. These findings provide important insights into the biological barriers that limit the functional implementation of plant polyketide pathways in photosynthetic microalgae C. reinhardtii and identify key targets for future metabolic and cellular engineering. Full article

Recently, several studies have investigated the validity of General Relativity’s predictions. Gravitational waves provide an ideal probe for testing the theory in the strong-field regime. In this work, we consider a class of modified-gravity theories, specifically $f\left(R\right)$, and scrutinize their predictions for the gravitational-wave emission from the coalescence of two astrophysical compact objects. We also assess the impact of next-generation gravitational-wave detectors on the ability to test these extensions of General Relativity. Full article

The fennel shoot borer, Evergestis extimalis (Scopoli) (Lepidoptera: Crambidae: Glaphyriinae), is a widespread and economically significant pest across the Qinghai–Tibet Plateau. However, its geographic distribution, comprehensive genomic resources and the phylogenetic position have not been systematically examined. Our findings reveal a broad distribution for E. extimalis, spanning extensive regions across Asia, Europe, and North America. Furthermore, we present the first complete mitochondrial genome (mitogenome) of this species and conduct extensive phylogenetic analyses to clarify its evolutionary relationships within Crambidae. The circular mitogenome is 15,301 bp in length and exhibits typical lepidopteran organization, comprising 13 protein-coding genes (PCGs), 22 transfer RNAs (tRNAs), 2 ribosomal RNAs (rRNAs), and an AT-rich control region. Comparative analysis of E. junctalis revealed conserved gene arrangement and high structural similarity. Among the 13 PCGs, nad6 exhibited the highest nucleotide diversity, whereas cox1 was the most conserved. Most PCGs were under purifying selection (Ka/Ks < 1) except atp8, nad2, and nad6. The AT-rich region (367 bp) contained tandem repeat motifs characteristic of Pyraloidea. Phylogenetic reconstruction based on concatenated sequences of 13 PCGs and 2 rRNAs from 58 species strongly supported the monophyly of Crambidae and revealed Glaphyriinae as a sister group to Odontiinae. Our results confirm the basal divergence between the “PS clade” (Pyraustinae + Spilomelinae) and the “non-PS clade” (Glaphyriinae, Odontiinae, Crambinae, Scopariinae, Schoenobiinae, and Acentropinae) but reveal discordant relationships within the “CAMMSS clade” (Crambinae, Acentropinae, Midilinae, Musotiminae, Schoenobiinae, and Scopariinae) compared to earlier nuclear gene-based studies. This study fills a significant gap in Glaphyriinae mitogenomics and provides valuable genomic resources for future population genetics on this economically important pest. Full article

Artificial intelligence has become increasingly embedded in digital marketing, reshaping how firms collect consumer data, personalize content, automate persuasion, and evaluate campaign performance. While these developments offer clear strategic benefits, they also raise important ethical questions concerning privacy, transparency, fairness, manipulation, and accountability within platform-mediated marketing environments. This article presents a structured thematic review of recent research on the ethics of AI-driven digital marketing. The review focuses on English-language peer-reviewed journal articles and high-quality conference proceedings published between January 2023 and September 2025. Searches were conducted across Scopus, ScienceDirect, SpringerLink, ACM Digital Library, IEEE Xplore, MDPI, PubMed, and selected academic repositories. After deduplication, screening, and full-text assessment, 91 studies were included in the final synthesis. Methodological quality was appraised using the Mixed Methods Appraisal Tool and Joanna Briggs Institute critical appraisal criteria, while the findings were examined through thematic synthesis. The review identifies five recurring ethical domains in the literature: data privacy and GDPR compliance, algorithmic transparency and explainable AI, algorithmic fairness in targeting and automated decision-making, dark patterns and deceptive interface design, and influencer or virtual influencer disclosure. The evidence suggests that privacy, consent, deceptive design, and transparency are the most extensively discussed areas, whereas the practical effectiveness of fairness interventions, explainability tools, and disclosure mechanisms remains more mixed and context-dependent. Across these themes, ethical risks appear not only as the result of individual corporate decisions but also as outcomes shaped by platform infrastructures, ranking systems, data access arrangements, and performance-oriented advertising metrics. The article contributes by organizing recent scholarship into a coherent thematic framework and by situating AI-driven digital marketing ethics within a broader platform-governance perspective. It argues that responsible implementation requires clearer distribution of accountability among businesses, platforms, regulators, and researchers. The review is limited by its focus on the 2023–2025 period, its English-language scope, and the methodological heterogeneity of the included studies, which prevents statistical meta-analysis. Full article

Green roofs have emerged as a critical nature-based solution for urban climate mitigation, offering potential for carbon sequestration alongside thermal regulation and stormwater management. This literature review synthesizes recent research (2020–2025) on green roof carbon dynamics, with emphasis on temperate climate zones and methodological approaches relevant to environmental impact assessment. We systematically analyzed 47 peer-reviewed studies published between 2020 and 2025 through comprehensive database searches, focusing on substrate composition effects, vegetation type performance, seasonal variation patterns, and Life Cycle Assessment methodologies. Key findings from extensive systems in maritime and temperate–arid climates reveal that substrate organic carbon typically dominates total carbon storage, significantly exceeding plant biomass contributions. Extensive green roofs demonstrate a wide range of annual carbon fluxes—from initial net emissions of +20.2 g C m⁻² yr⁻¹ during establishment phases to substantial net sequestration rates reaching up to −1762 g CO₂ m⁻² yr⁻¹ in mature systems—depending strongly on substrate age, vegetation type, and local climate conditions. Native grass and forb mixtures consistently outperform Sedum monocultures in long-term carbon storage through enhanced root biomass and substrate organic matter accumulation. Substrate depth, composition, and moisture retention capacity emerge as primary controls on carbon balance, with recycled waste materials showing promise for enhanced storage. Life cycle assessment studies indicate that indirect carbon savings from reduced building energy consumption frequently exceed direct biological sequestration by one to two orders of magnitude. However, significant methodological heterogeneity, limited long-term monitoring datasets, and geographic gaps—particularly for Central and Eastern European temperate zones—constrain robust comparative analysis and transferability of findings. This review identifies critical research priorities, including standardized carbon accounting frameworks, dynamic life cycle assessments incorporating temporal sequestration trajectories, multi-decadal monitoring programs, and region-specific validation studies for temperate continental climates similar to Romania’s Cfb/Dfb zones. Full article

This study proposes a novel friction-based beam-to-column shear connection designed to behave as a nominally pinned joint while avoiding any perforation of the connected members. The connection relies on frictional resistance to transfer shear forces, enabling full reversibility and preserving the integrity of the structural elements for future reuse. A comprehensive design methodology is first introduced, addressing key parameters such as clamping force, friction coefficient, and slip resistance. Subsequently, an extensive numerical investigation is carried out using refined finite-element models, i.e., considering multiple geometric configurations and loading conditions. The local behaviour of the connection is hence assessed in terms of stiffness, strength, and slip capacity. Results show that—with proper sizing—plastic deformation localises in the beam while the joint remains elastic and slip is limited, confirming the conservativeness of the approach. The joints behave as nominally pinned in terms of resistance while showing moderate stiffness. Derived findings highlight the feasibility of adopting friction-based, non-invasive connections as a viable alternative for circular steel construction, contributing to the ongoing transition toward more sustainable structural systems. Full article