Search Results (17,165)

Drought severely constrains grassland stability and forage productivity. Allium mongolicum Regel, a dominant species in desert steppes, exhibits high drought tolerance, yet its multi-level adaptive responses remain incompletely understood. Here, drought stress of different intensities (15%, 30%, 45%, and 60% PEG-6000) was simulated, and root phenotypes, physiological traits, and time-series transcriptomic profiles were integrated to characterize its drought-responsive patterns. The results revealed a biphasic phenotypic response: mild to moderate drought (15–30% PEG) promoted root elongation and surface expansion, consistent with a growth-prioritized response pattern, whereas severe drought (60% PEG) suppressed elongation and induced compensatory thickening, suggesting a shift toward a more structural defense-oriented response. Physiological analyses showed progressive MDA accumulation accompanied by increased SOD and POD activities and proline content, indicating enhanced antioxidant and osmotic regulation under stress. Time-series transcriptomics suggested a three-phase transcriptional adjustment pattern, including early alarm, intermediate acclimation, and late compensation. Early-stage DEGs were mainly enriched in photosystem regulation and ROS-related pathways, while intermediate stages were associated with translational control and protein folding. At the late stage, genes involved in mitochondrial metabolism and amino acid catabolism were prominently represented, implying increased respiratory activity under prolonged drought. WGCNA further identified two key modules associated with these shifts: the steelblue module, negatively correlated with root growth traits, and the darkturquoise module, positively correlated with growth-related traits and antioxidant activities. Collectively, these results outline a multi-level adaptive framework for drought responses in A. mongolicum and provide insights into how desert plants may balance growth and defense under water-limited conditions. Full article

The analysis of Synthetic Aperture Radar (SAR) imagery is essential to modern remote sensing, with applications in disaster management, agricultural monitoring, and military surveillance. A significant challenge is that the complex and noisy nature of SAR data severely limits the performance of traditional machine learning (TML) methods, leading to high error rates. In contrast, deep learning (DL) has recently proven highly effective at addressing these limitations. This study provides a comprehensive review of recent DL advances applied to SAR image despeckling, segmentation, classification, and detection. It evaluates widely adopted models, examines the potential of underutilized ones like GANs and GNNs, and compiles available datasets to support researchers. This review concludes by outlining key challenges and proposing future research directions to guide continued progress in SAR image analysis. Full article

Bone metastasis is among the most common complications of advanced malignant tumors and severely affects prognosis in patients. Nuclear medicine, particularly bone-targeted radiopharmaceuticals, plays a unique and pivotal role in the diagnosis and treatment of bone metastases. This review systematically outlines the evolutionary trajectory of bone-targeted radiopharmaceuticals. It revisits functional bone imaging agents based on Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET), as well as recently developed therapeutic radiopharmaceuticals for bone metastases. Building on this foundation, this article focuses on the advanced paradigm of “theranostics” in nuclear medicine, encompassing strategies for theranostic radionuclide pairing and the development of single-radionuclide theranostic agents, aiming to achieve individualized and precise dosimetry. Moreover, this review emphasizes bone-targeting molecular scaffolds, such as bisphosphonates, and highlights their potential and direction for optimization through rational drug design, with the goal of developing a new generation of highly effective and low-toxicity theranostic platforms. This work aims to provide systematic insights for enhancing the precise management of bone metastases. Full article

In the past few decades, we have seen increasing specialization within developmental science, with researchers focusing on narrowly defined research areas in child development. This specialization has yielded deep insights and methodological advances across many developmental areas. However, it has also led to siloes of expertise. In this article, we review findings on how motor, visual, auditory, olfactory and gustatory experiences affect early cognitive development. We identify some common themes across these domains, such as the role of predictive processing in early development. We argue for the importance of adopting a dynamic systems approach and considering the variabilities both within the individual and in the larger cultural environments. Finally, we conclude by outlining several avenues for future research that seek to advance integrative approaches within developmental science. Full article

Index matrices are an extension of the ordinary matrices with explicitly assigned index sets on both their rows and columns, forming an advanced mathematical structure used for specialized data modeling and problem-solving. In the present paper, a new operator, called “Inverse” operator, is defined over hierarchical index matrices with a description of its software implementation. This operator has no analogue in the classical theory of matrices. Its application allows various restructuring of datasets with multiple criteria, in order to outline data stratifications in the best possible way serving the particular decision maker’s needs. As an illustrative example for the new operator, a dataset of the recorded blood donors in Bulgaria is provided, with discussions of the different stratifications and perspectives in which the dataset can be rearranged using the “Inverse” operator. Full article

Bone marrow mesenchymal stem/stromal cells (BM-MSCs) are important components of bone marrow, possessing multipotent differentiation potential and the ability to support hematopoiesis. Exposure to ionizing radiation (IR) induces cellular damage in BM-MSCs, such as DNA lesions and mitochondrial dysfunction. Despite their relative radioresistance, most surviving BM-MSCs enter senescence post-irradiation. This senescent state disrupts the bone marrow niche, impairs stem cell proliferation and differentiation, and contributes to acute radiation syndrome (ARS) and myelosuppression. To clarify the impact of IR on BM-MSCs, this review systematically summarizes the general mechanisms of radiation-induced cellular senescence, examines the effects of different radiation types (e.g., gamma rays, X-rays, and heavy-ion radiation) and doses on BM-MSCs senescence, and outlines senotherapeutic strategies targeting BM-MSCs senescence. The analysis indicates that the senescence of BM-MSCs caused by IR is type- and dose-dependent. The review identifies key factors in IR-induced BM-MSCs senescence to guide targeted interventions, highlighting the need for future studies to elucidate the underlying mechanisms of IR-induced BM-MSCs senescence. Full article

The phosphatidylinositol-3-kinase (PI3K)/Akt signaling pathway is a central regulator of cellular metabolism, survival, and proliferation and is frequently dysregulated in cancer. Since the identification of protein kinase B (Akt) in 1996, extensive research has established its critical role in tumor initiation, progression, and therapeutic resistance, making Akt an attractive target for anticancer drug development. Although numerous inhibitors targeting the PI3K/Akt pathway have been developed, their clinical success has been limited due to inadequate isoform specificity and unfavorable toxicity profiles. These limitations have prompted increasing interest in identifying Akt-selective inhibitors from natural sources, particularly microbial metabolites. Recent in vitro and in vivo studies demonstrate that several microbial-derived compounds effectively modulate PI3K/Akt signaling and suppress key cancer hallmarks, including proliferation, angiogenesis, and metastatic potential. Nevertheless, further studies are required to define Akt isoform specificity, evaluate selectivity against closely related kinases, and validate therapeutic efficacy in relevant preclinical models, including patient-derived xenografts. In addition, the development of robust purification and optimization strategies remains essential to enable the reliable isolation and translational advancement of these bioactive metabolites. This review summarizes Akt structure, function, and key regulatory motifs relevant to pharmacological targeting and critically examines microbial-derived inhibitors of the PI3K/Akt pathway and their mechanisms of action. Representative compounds discussed include Bostrycin, Anthracycline analogs, Wentilactone A, Thiocoraline, Iturin A, SZ-685C, Isebromoamide B, Xyloketal B, and Demethoxyfumitremorgin C. Collectively, this review highlights the therapeutic potential of microbial natural products while outlining current challenges and future directions for developing selective Akt-targeted anticancer therapies. Full article

Over the last three decades, architecture has undergone a sustained digital transformation that has progressively displaced the ontology of the geometric generator, understood here as the primary artefact through which form is produced, controlled, and legitimized. This paper argues that, within one extended digital epoch, three successive regimes have reconfigured architectural agency. First, a digital model regime, in which computer-generated 3D models become the main generators of geometry. Second, a parametric code regime, in which scripted relations and numerical parameters supersede the individual model as the core design object, defining a space of possibilities rather than a single instance. Third, an emerging latent regime, in which diffusion and transformer systems produce high plausibility synthetic images as image-first generators and subsequently impose a post hoc image-to-geometry translation requirement. To make this shifting paradigm comparable across time, the paper uses the blob as a stable morphological reference and develops a comparative reading of four blobs, Kiesler’s Endless House, Greg Lynn’s Embryological House, Marc Fornes’ Vaulted Willow, and an author-generated GenAI blob curated from a traceable AI image archive, to show how the geometric generator migrates from object, to model, to code, to latent image-space. As a pre-digital hinge case, Kiesler is selected not only for anticipating blob-like continuity, but for clarifying a recurrent disciplinary tension, “ form first generators” that precede tectonic and programmatic rationalization. The central hypothesis is that GenAI introduces an ontological shift not primarily at the level of style, but at the level of architectural judgement and evidentiary legitimacy. The project can begin with a predictive image that is visually convincing yet tectonically underdetermined. To name this condition, the paper proposes the plausibility gap, the mismatch between visual plausibility and tectonic intelligibility, as an operational criterion for evaluating image-first workflows, and for specifying the verification tasks required to stabilize them as architecture. Selection establishes evidentiary legitimacy, while a friction map and Gap Index externalize the translation pressure required to turn predictive imagery into accountable geometry, making the plausibility gap operational rather than merely asserted. The paper concludes by outlining implications for authorship, pedagogy, and disciplinary judgement in emerging multi-agent design ecologies. Full article

Intestinal aging is characterized by a gradual decline in epithelial renewal capacity, barrier function, immune balance, and metabolic regulation, often accompanied by shifts in gut microbial composition. Polyamines, including putrescine, spermidine, and spermine, are vital microbial–host metabolites that support intestinal cell growth, autophagy, immune modulation, and mucosal repair. With advancing age, both host-derived and microbiota-mediated polyamine production declines, contributing to intestinal dysfunction and heightened vulnerability to inflammation and age-related disorders. This review explores the diet–microbiota–polyamine axis as a key biological framework influencing intestinal aging. It aims to integrate evidence on how dietary components and functional foods shape gut microbial ecology and, in turn, regulate microbial polyamine biosynthetic pathways that impact intestinal health. The review highlights major microbial contributors to polyamine metabolism, particularly lactic acid bacteria, and outlines mechanistic pathways linking polyamines to epithelial regeneration, inflammatory control, and gut barrier maintenance. It further discusses how age-associated dysbiosis disrupts these interactions and evaluates nutritional and microbial-based strategies such as fermented foods, prebiotics, and probiotics that may enhance polyamine availability and restore gut homeostasis. From the standpoint of food microbiology and human physiology, this synthesis underscores the translational potential of targeting microbial polyamine production through diet-based interventions. This article presents a narrative review synthesizing experimental, animal, and emerging human evidence on microbial and dietary polyamines in intestinal aging. In conclusion, modulating the diet–microbiota–polyamine axis represents a promising strategy to promote healthy intestinal aging, meriting deeper mechanistic exploration and validation through clinical studies. Full article

Point cloud technology, characterized by its high-precision 3D geometric acquisition in complex railway environments, has become a cornerstone for the intelligent detection, monitoring, and maintenance of railway infrastructure. This paper provides a systematic review of point cloud applications across critical railway scenarios, encompassing track geometry extraction, infrastructure component identification, tunnel and bridge modeling, clearance and encroachment analysis, and structural condition monitoring. We evaluate various mobile and stationary acquisition platforms alongside their typical data processing workflows. Furthermore, this review synthesizes cutting-edge advancements in processing algorithms, with a focus on feature extraction, semantic segmentation, and the transformative impact of deep learning and artificial intelligence on data fusion. Notably, the paper explores the synergy between point clouds and computational mechanics, specifically the construction of high-fidelity digital twins through multi-physics coupling to enable real-time simulation of structural stress distribution and damage evolution. We critically analyze persistent technical bottlenecks, such as acquisition efficiency, monitoring precision, data fragmentation, environmental interference, and the complexities of multi-modal data fusion. Finally, the paper outlines future research trajectories, focusing on autonomous intelligent sensing, multi-sensor integration, and the comprehensive digital transformation of railway infrastructure management, aiming to provide a robust theoretical framework and technical roadmap for the sustainable intelligentization of global railway systems. Full article

Amid the exponential growth of streaming data and rising demands for real-time decision-making, Online Convex Optimization (OCO) has emerged as a foundational framework for sequential data processing in dynamic environments. This survey presents a systematic review of recent evolutionary and adaptive OCO strategies, offering a detailed taxonomy that classifies algorithms according to their constraint-handling mechanisms and environmental feedback. The analysis first examines Constrained OCO, elucidating the trade-offs between computational efficiency and theoretical guarantees across projection-based methods, projection-free Frank–Wolfe variants, and general convex optimization approaches. It then explores the Unconstrained OCO landscape, emphasizing the shift from parameter-dependent methods to fully adaptive, parameter-free algorithms capable of handling unknown comparator norms and gradient scales. Furthermore, the study synthesizes state-of-the-art applications in power systems, network communication, and quantitative finance, bridging theoretical OCO models with robust engineering solutions. The paper concludes by outlining critical open challenges and future research directions, such as the integration of OCO with deep learning, non-convex optimization, and robustness against adversarial corruptions in data-intensive scenarios. Full article

This review presents a comprehensive examination of the total fatigue life behaviour of high-strength steels (HSS) with particular emphasis on fatigue crack initiation in the very high cycle fatigue (VHCF) regime and crack propagation based on fracture mechanics. The discussion draws on recent advances in experimental techniques, microstructural characterisation, and analytical approaches by reviewing studies conducted over the past few years. Key factors influencing fatigue performance, including loading frequency, specimen geometry, microstructure, and environmental conditions, are critically evaluated. The review concludes by highlighting existing knowledge gaps and outlining directions for future research aimed at improving the understanding and optimisation of fatigue performance in current and next-generation HSS. Full article

Digital product passports outline information about a product’s lifecycle, circularity, and sustainability-related data. Sustainability data contains claims about carbon footprint, recycled material composition, ethical sourcing of production materials, etc. Also, upcoming regulatory directives require companies to disclose this type of information. However, current sustainability reporting practices face challenges, such as greenwashing, where companies make incorrect claims that are difficult to verify. There is also a challenge of disclosing sensitive production information when other stakeholders, such as consumers or other economic operators, wish to verify sustainability claims independently. Zero-knowledge proofs (ZKPs) provide a cryptographic system for verifying statements without revealing sensitive information. The goal of this research paper is to explore ZKP cryptography, trust models, and implementation concepts for extending DPP capability in privacy-aware reporting and verification of sustainability claims in products. To achieve this goal, first, formal representations of sustainability claims are provided. Then, a data matrix and trust model for generating proofs are developed. An interaction sequence is provided to show different components for various proof generation and verification scenarios for sustainability claims. Lastly, the paper provides a circuit template for the proof generation of an example claim and a credential structure for their input data validation. The proposed approach is assessed using a scenario-based evaluation to check the performance metrics for data credential verification and proof generation for verifying material composition in a product. Full article

This article outlines the central role of the human eye as a consistent and recurring aesthetic strategy in the cinematic oeuvre of Sergei Eisenstein via an investigation of three films—Strike (1925), Potemkin (1925), and the unfinished, two-part Ivan the Terrible (1945, 1958). It analyses seeing, being seen, and shut and open eyes, in conjunction with the use of the close-up, as crucial to Eisenstein’s visual vocabulary and argues for the need to think about the persistent focus on eyes and vision in terms of panoptic mechanisms of political surveillance and control. Meaning is generated from eye to eye, through configurations of looking and spying, revealing and concealing—formal and aesthetic strategies which condition the gaze of the spectator, creating sites of affect that provide continuity between the films. It furthermore contextualises Soviet montage and Eisenstein’s work in relation to European avant-gardes, specifically French Impressionism and German Expressionism, whose influence on the director’s filmography has received little scholarly attention. Full article

Photocatalytic reduction of CO₂ into valuable solar fuels represents a promising strategy to address both energy crises and carbon emissions. Bismuth-based semiconductors have emerged as attractive visible-light-driven photocatalysts due to their suitable band structures, layered architectures, and tunable morphologies. This review systematically summarizes recent advances in Bi-based photocatalysts for CO₂ photoreduction. First, the fundamental principles and key challenges of CO₂ photoreduction are outlined. Subsequently, the structural and electronic characteristics of typical Bi-based materials, including Bi₂O₃, Bi₂S₃, Bi₂MO₆ (M = W; Mo), BiVO₄, and BiOX (X = Cl; Br; I), are discussed. Emphasis is placed on design strategies to enhance photocatalytic performance, such as vacancy engineering, microstructure control, crystal facet engineering, heterojunction construction, cocatalyst loading, and their combinations. A comprehensive comparison of catalytic activities under various conditions is also provided. Finally, current limitations and future perspectives are highlighted, aiming to guide the rational design of efficient and stable Bi-based photocatalysts for CO₂ conversion. Full article