Search Results (161)

Three-dimensional (3D) microscopic imaging is indispensable for fundamental scientific research and clinical medical diagnosis. Given that conventional widefield optical microscopy and standard confocal microscopy fail to realize high-magnification, full-color, real-time stereoscopic imaging simultaneously, we herein propose a single-optical-path 3D microscopic framework enabled by liquid crystal polarization gratings (LCPGs). The LCPG integrated at the sample plane performs polarization-dependent beam splitting to generate paired left and right viewing channels. These two disparity-bearing view channels share a unified imaging optical path compatible with commercial upright microscopes, wherein an active liquid crystal cell modulates temporal view switching for sequential camera acquisition. We further construct a white-light microscopic platform supporting integrated reflection and transmission imaging modes. Two customized LCPGs with lattice periods of 72.6 μm and 56.9 μm are fabricated, offering angular view separations of 0.84° and 1.07°, respectively. Both gratings achieve ±1st-order diffraction efficiencies above 97% with polarization crosstalk not exceeding 0.8%. The developed system acquires paired left-right images with valid binocular disparity, which can be reconstructed into intuitive stereoscopic perceptions via a 3D display monitor. This LCPG-based optical architecture upgrades standard upright microscopes to compact dual-view stereoscopic imaging systems, while fully inheriting the native merits of white-light illumination and high-magnification microscopic observation. Full article

Stable and uniform pesticide application is essential for precision crop protection, input-use efficiency, and the reduction of off-target losses in large-scale farming systems. Large boom sprayers are important agricultural machines for high-efficiency crop protection, but their wide and flexible booms are highly sensitive to terrain-induced excitation, chassis motion, liquid sloshing, and hydraulic nonlinearities. These disturbances can cause roll, yaw, vertical oscillation, and boom-end height variation, thereby reducing spray uniformity, increasing drift risk, and threatening operational safety. Hybrid active–passive boom suspension systems have therefore become a key enabling technology for modern precision spraying. This review summarizes research progress in the structural design, dynamic modeling, sensing, and control of boom suspension systems for large-scale agricultural sprayers. Mainstream commercial machines commonly use double-pendulum active–passive suspension architectures, in which passive components attenuate high-frequency vibration and active subsystems improve low-frequency terrain-following performance. Recent studies have advanced electro-hydraulic actuation, disturbance compensation, adaptive control, multi-sensor fusion, and field evaluation methods; however, a unified framework for coupling boom dynamics, spray quality, sensing accuracy, and whole-machine operation remains incomplete. Key challenges include rigid–flexible–hydraulic coupling, underactuated control, uncertain parameters, external disturbances, and posture estimation errors caused by boom elastic deformation and sensor noise. Future research should emphasize rigid–flexible–fluid-coupled modeling, adaptive output-feedback control with disturbance and resonance suppression, terrain-preview and multi-source perception, and coordinated chassis–boom-spray control. These developments can support more stable, efficient, and environmentally responsible spraying operations in modern precision agriculture. Full article

Cooking liquid from Manila clam (Ruditapes philippinarum) is an underutilized byproduct rich in water-soluble taste compounds, representing a potential source of natural umami peptides. In this study, peptide fractions were separated from the cooking liquid. A total of 764 peptide sequences were identified from the most potent fraction, F3 (<3 kDa), by UPLC-ESI-Q-TOF-MS/MS. Machine learning prediction and molecular docking were further used for screening. Five candidate peptides were selected: TQDTVVALDA, KEY, YKD, RND, and GEAF. Sensory evaluation (on a 0–5 scale) and electronic tongue measurements independently confirmed that peptide YKD possessed the strongest taste profile, with an electronic tongue relative umami score of 8.81 ± 0.22. Furthermore, cell-based assays demonstrated that YKD effectively up-regulated the transcriptional expression of taste-related receptors, including GPRC6A, in STC-1 cells, revealing a multi-receptor synergetic mechanism for umami perception. In STC-1 cells, all peptides induced intracellular Ca²⁺ responses and showed no obvious cytotoxicity at 0.5–8.0 mmol/L. YKD produced the highest fluorescence response (0.59) at 1.0 mmol/L. Quantitative RT-PCR analysis suggested that YKD was associated with T1R1/T1R3-related expression, whereas TQDTVVALDA induced stronger CaSR expression. These findings elucidate the specific peptide sequence that engages multiple receptors to create complex tastes, providing a theoretical basis for converting seafood processing byproducts into natural flavor enhancers. Full article

This review explicitly focuses on agricultural attachments and executing components that interact directly with soil and crops, rather than the tractor vehicle itself. Operating within complex and variable farmland media environments, the key components of agricultural machinery have long been constrained by bottlenecks such as high-energy draught resistance, severe solid–liquid interfacial adhesion, and intense abrasive wear. Bionic functional surfaces, based on the coupling of micro-geometric morphology and surface-interface physical chemistry, provide a scientific approach to overcoming traditional tribological limitations by reconstructing the contact mechanics and fluid dynamics boundaries at the interface. This paper presents a comprehensive review of the latest research progress regarding bionic functional surfaces in the fields of friction reduction, wear resistance, and anti-adhesion in agricultural machinery. The article systematically categorises typical biological prototypes, such as soil-burrowing animals, aquatic organisms, and plant leaves, alongside their multidimensional feature extraction methods. It provides an in-depth analysis of core interaction mechanisms, ranging from static air cushion effects and dynamic wetting evolution to active electro-osmotic soil detachment, interfacial stress redistribution, and microscopic wear debris capture. Furthermore, it evaluates the efficacy of cross-scale coupled numerical simulation technologies in resolving interfacial interactions. At the engineering application level, this review extensively discusses the field performance of bionic structures in typical operational scenarios, including draught reduction in tillage and land preparation, blockage prevention in seed-metering channels, and low-damage harvesting in agricultural machinery. Finally, countermeasures are proposed to address the fatigue degradation of bionic surfaces under alternating field loads and the barriers to the large-scale fabrication of large-sized components. The paper further highlights the development trend towards the deep integration of bionic tribology with digital twins and intelligent wear-state perception technologies, aiming to provide systematic underlying theoretical and technical references for the research and development of the next generation of intelligent agricultural equipment characterised by low energy consumption and a prolonged service life. Full article

The chemical composition and sensory profile of coffee are influenced by brewing method, namely extraction pressure, temperature, contact time, and equipment. This study compared coffee prepared with a traditional moka pot, a conventional espresso machine, and a novel Italian device (Kamira). Volatile compounds were analyzed by headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography–mass spectrometry (GC–MS), leading to the determination of furan (34–42%), pyrrole (4–10%), and pyrazine (13–14%) derivatives. The most abundant fatty acids were palmitic (36–37%), linoleic (40%), and oleic (11%) acids. Physicochemical parameters (total solids, pH, and refractive index) were also measured. Caffeine and chlorogenic acids were quantified by liquid chromatography (HPLC). Differences in chlorogenic acids and volatile compounds were associated with variations in bitterness, acidity, astringency, and aroma intensity. Finally, a trained panel performed sensory evaluation to evaluate the olfactory and flavor attributes of the three types of coffee brews. Significant differences emerged among brewing systems. Espresso showed the highest caffeine content (55.3 ± 4.1 mg/100 g) and total solids (2.61 ± 0.11 g/100 g), together with a stable crema and intense sensory attributes. Moka coffee exhibited a rich aromatic profile but limited crema. The Kamira device produced an abundant crema and a chemical profile partially comparable to espresso. These findings confirm that brewing technology markedly affects coffee composition and sensory perception. Full article

Cryptocurrencies have become increasingly in demand in Ukraine’s wartime economy, yet little is known about how entrepreneurs perceive them in terms of trust, business use, and reputation. This study examines trust dynamics in cryptocurrencies among Ukrainian small-to-medium enterprise (SME) entrepreneurs under wartime conditions, exploring their association with business behavior, investment decisions, and reputational perceptions. The analysis is based on a survey of 561 Ukrainian entrepreneurs. The results show a statistically significant increase in trust in cryptocurrencies during the war. Higher trust is associated with more intensive operational use of cryptocurrencies and greater importance in investment portfolios. Entrepreneurs who associate cryptocurrencies with traditional liquid assets are more likely to assign them a stronger investment role. The use of cryptocurrencies affects both cryptoassets’ reputations and entrepreneurs’ business reputations. Greater engagement with cryptocurrencies is associated with a higher likelihood of viewing their use as a reputational advantage. However, overall assessments remain cautious due to regulatory uncertainty, financial risks, and potential involvement in tax evasion or speculative activities. Different perceived value propositions of cryptocurrencies are also linked to distinct behavioral strategies. Overall, the findings suggest that, in wartime Ukraine, trust in cryptocurrencies is shaped by their practical usefulness during periods of financial disruption and by their implications for entrepreneurs’ reputations. Full article

Oat beverages are widely consumed as dairy alternatives; however, there is still limited understanding of how the source and structural organization of added lipids influence their physicochemical functionality and sensory perception. This study aimed to evaluate whether the type of lipid source used in commercial oat-based products can explain variability in lipid quality and consumer acceptability. Lipid fractions were extracted from 10 commercial oat-based products available on the Polish market, including 5 ready-to-drink beverages and 5 powdered products reconstituted with water. The extracted lipids were analyzed for fatty acid (FA) composition, positional distribution of FAs in triacylglycerols, melting behavior, and oxidative stability, complemented by sensory evaluation. Marked differences were observed among samples, primarily driven by the lipid source rather than product form. Products containing sunflower oil exhibited a favorable FA profile characterized by a high proportion of unsaturated FAs and relatively good oxidative stability. In contrast, oat-only formulations showed lower oxidative stability and reduced sensory performance, particularly in terms of taste and texture. The sample containing coconut fat demonstrated the highest oxidative stability (τ_max = 333.48 min) but the least favorable nutritional profile due to a predominance of saturated FAs (85.43% SFA). The highest overall sensory acceptance was recorded for sample L1 (overall desirability = 7.00). Overall, the findings demonstrate that lipid source is a key determinant of the nutritional, physicochemical, and sensory properties of oat beverages, while product format (liquid vs. powder) plays a secondary role. These results address the knowledge gap regarding the relationship between lipid origin and functional performance in plant-based beverages and highlight formulation strategy as a critical factor in product optimization. Full article

Both the productive efficiency and physical health of sika deer are strongly linked to their body conformation phenotypes. Breeding sika deer with excellent growth traits using molecular breeding technologies has become essential. Phenotypic data of 12 body conformation traits were measured for 613 sika deer across three age groups, including body traits and cephalic traits. Genetic typing was performed using the Sika Deer 100K SNP Liquid Chip, and genetic parameters were estimated through animal models to obtain the heritability and genetic correlation of traits within each age group. Single-trait and multi-trait GWASs were conducted, using GEMMA software to identify gene variants significantly associated with sika deer body conformation traits. Most of the 12 body conformation traits exhibited moderate to high heritability. The single-trait GWAS identified 49 SNPs (38 candidate genes), while multi-trait GWAS detected 134 SNPs (80 candidate genes), including 114 novel loci. A total of 163 SNPs and 196 candidate genes were identified, with 17 genes detected by both methods. These genes may be involved in pain perception, cell cycle regulation, immune response, and protein ubiquitination. Two significant KEGG pathways were enriched: steroid hormone biosynthesis and drug metabolism–cytochrome P450. Collectively, these detected loci and genes may serve as potential genetic resources for marker-assisted breeding, contributing to subsequent genetic improvement of body conformation in sika deer. Full article

Recent advances in large language models, tool-using agents, and financial machine learning are shifting financial automation from isolated prediction tasks to integrated decision systems that can perceive information, reason over objectives, and generate or execute actions. The paper develops an integrative framework for analysing agentic finance: financial market environments in which autonomous or semi-autonomous AI systems participate in information processing, decision support, monitoring, and execution workflows. The analysis proceeds in three steps. First, the paper proposes a four-layer architecture of financial AI agents covering data perception, reasoning engines, strategy generation, and execution with control. Second, it introduces the Agentic Financial Market Model (AFMM), a stylised agent-based representation linking agent design parameters such as autonomy depth, heterogeneity, execution coupling, infrastructure concentration, and supervisory observability to market-level outcomes including efficiency, liquidity resilience, volatility, and systemic risk. Third, it presents an illustrative empirical application based on event studies of AI-agent capability disclosures and heterogeneous market repricing. It argues that the systemic implications of AI in finance depend less on model intelligence alone than on how agent architectures are distributed, coupled, and governed across institutions. The empirical application is intentionally exploratory: it does not validate the full AFMM but shows how one observable expectations channel can be studied using public data. In the near term, the most plausible equilibrium is bounded autonomy, in which AI agents operate as supervised co-pilots, monitoring systems, and constrained execution modules embedded within human decision processes. Full article

Despite the success of artificial neural networks in solving numerous tasks, they face significant challenges, including difficulties in online adaptation and rapidly increasing energy consumption. As a biologically plausible alternative, spiking neural networks offer promising capabilities for efficient cognitive computing. Recently, a three-element spiking neuron model consisting of a threshold selector, a tunnel diode, and a capacitor was proposed. In this work, we experimentally validate this model using a threshold selector hardware emulator and demonstrate its dynamical equivalence to the biologically plausible Izhikevich neuron model. To evaluate the novel neuron’s applicability for cognitive computing, we implement a liquid state machine (LSM) reservoir architecture with spatially dependent random topology for synaptic weight distribution. Our simulations on the MNIST and Fashion-MNIST benchmarks demonstrate competitive classification accuracy (97.9% and 89.5%, respectively) while offering estimated energy efficiency and processing speed enhancements compared to existing FPGA-based and memristor-based spiking reservoir implementations. The developed reservoir is feasible for processing neuromorphic sensors output, including visual perception tasks. Full article

Edible insects are increasingly recognized as sustainable and nutrient-dense ingredients with potential applications across diverse food systems. While their use in solid foods has been widely explored, the incorporation of insect-derived ingredients into beverages remains fragmented and insufficiently conceptualized. This narrative review critically examines the current state of insect-based beverages, integrating technological, nutritional, cultural, and market-oriented perspectives. Rather than adopting a fully systematic review methodology, this article synthesizes representative scientific literature, traditional practices, and emerging commercial examples to explore how edible insects are being positioned within two distinct yet complementary pathways: (i) functional beverages targeting nutrition, gut health, sports performance, immunity, and meal replacement, and (ii) experiential beverages driven by culinary storytelling, tradition, ritual, and sensory innovation, such as insect-infused beers and spirits. Relevant sources were identified through searches of major scientific databases using combinations of keywords such as edible insects, entomophagy, insect-based beverages, functional beverages, and insect protein, with emphasis on peer-reviewed literature published mainly over the past two decades, complemented by representative examples of traditional practices and emerging commercial products. The review discusses the nutritional and biofunctional potential of insect-derived proteins, lipids, and chitin-related components, with particular emphasis on their behavior in liquid matrices, including solubility, stability, flavor impact, and processing constraints. Technological challenges associated with beverage formulations are critically assessed. In parallel, consumer perception is examined through the lens of neophobia, sensory expectations, and the role of cultural framing and gastronomy in facilitating acceptance. By bridging food science, beverage technology, and food culture, this review identifies key knowledge gaps and research priorities for advancing insect-based beverages beyond niche applications. It argues that future development in this field will depend not only on technological optimization and a regulatory framework, but also on the deliberate design of products that integrate functionality with meaningful culinary and cultural narratives. Full article

Underwater micro-bubble detection entails multiple challenges, including diminutive target sizes, sparse pixel information, pronounced specular highlights and water scattering, indistinct bubble boundaries, and adhesion or overlap between instances. To address these issues, we propose HSMD-YOLO, an improved detector tailored for high-resolution micro-bubble detection and built upon YOLOv11. The model incorporates three novel components: the Scale Switch Block (SSB), a scale-transformation module that suppresses artifacts and background noise, thereby stabilizing edges in thin-walled bubble regions and enhancing sensitivity to geometric contours; the Global Local Refine Block (GLRB), which achieves efficient global relationship modeling with an asymptotic linear complexity ($O\left(N\right)$) in spatial dimensions while further refining local features, thereby strengthening boundary perception and improving bubble–background separability; and the Bidirectional Exponential Moving Attention Fusion (BEMAF), which accommodates the multi-scale nature of bubbles by employing a parallel multi-kernel architecture to extract spatial features across scales, coupled with a multi-stage EMA based attention mechanism to enhance detection robustness under weak boundaries and complex backgrounds. Experiments conducted on an Side-Illuminated Light Field Bubble Database (SILB-DB) and a public gas–liquid two-phase flow dataset (GTFD) demonstrate that HSMD-YOLO achieves mAP@50 scores of 0.911 and 0.854, respectively, surpassing mainstream detection methods. Ablation studies indicate that SSB, GLRB, and BEMAF contribute performance gains of 1.3%, 2.0%, and 0.4%, respectively, thereby corroborating the effectiveness of each module for micro-scale object detection. Full article

This study examines the False Reality Bias in treasury management, a cognitive distortion through which small and medium-sized enterprises (SMEs) infer financial stability from salient bank balances while overlooking pending obligations and cash-flow timing. Using a firm-level dataset of 50 Spanish meat-processing SMEs, the analysis develops two behavioral-finance indicators: the Liquidity Misperception Index (PEL), capturing the divergence between salient liquidity cues and effective short-term obligations, and the Liquidity Misconfidence Index (ICEL), measuring managerial overconfidence in liquidity assessments. Results show that 41% of firms overestimate liquidity (average PEL = 1.21), while 40% exhibit excessive confidence (ICEL > 1.3), both significantly associated with liquidity distress. Econometric estimates indicate that firms with PEL values above 1.2 are 4.48 times more likely to experience liquidity crises, even after controlling for bank balance levels. Predictive models are used in an exploratory capacity, achieving classification accuracies above 80% and supporting the robustness of the behavioral signals identified. In addition, AI-assisted cash-flow simulations reduce liquidity misperception by 34.7% (p < 0.01). Overall, the findings provide micro-level evidence that cognitive biases systematically distort SME treasury decisions but can be partially corrected through targeted decision-support tools, offering practical insights for managers, advisors, and policymakers. Full article

In the current context of environmental sustainability and reduced agricultural inputs, biostimulants represent one of the most efficient, eco-friendly and innovative strategies to preserve plants from biotic and abiotic stresses and to ensure sustainable agriculture. Ranging from benefic microorganisms, seaweed extracts, and humic acids to complex carbohydrates such as polysaccharides and oligosaccharides, these biostimulants are able to increase plant growth, photosynthetic efficiency, root development and nutrient uptake when they are applied during seed priming as foliar sprays or as liquid and solid soil amendments. The mechanisms underlying their effective action on plants are mainly related to the enhancement of antioxidant defenses and the regulation of hormonal pathways, particularly auxin homeostasis and transport. Several studies reported the relevance of biostimulant application in promoting root growth. In plants, roots play crucial roles, performing a variety of functions such as nutrients and water uptake, mediating stress perception and adaptation, influencing the rhizosphere microbiome, and providing structural support. The effectiveness and perception of polysaccharide-based biostimulants (PBs) are highly dependent on crucial factors, including the degree of depolymerization and the chemical modifications such as acetylation, methylation, sulfation, and oxidation. Furthermore, not all receptors and co-receptors involved in the recognition of PBs have yet been identified. However, there remain many gaps in our understanding regarding the interaction between biostimulants and roots, which is still far from fully elucidated. For these reasons, the present review provides a comprehensive overview of current research on biostimulants–root interactions, with a particular focus on polysaccharide-based biostimulants. It highlights the mechanisms involved in their recognition by plants roots, from perception to response, and the subsequent signaling cascades and the molecular pathways activated, with special emphasis on existing knowledge gaps and future research perspectives. Full article

Umami taste in lager beer not only determined body fullness and the backbone of aftertaste, but also affected the controllability and interpretability of flavor expression across the entire brewing process. Based on stage-wise sampling, peptidomic profiles were established on wort fermentation day 0, day 1, day 3, and day 9. A total of 25,592 peptides were identified by reversed-phase liquid chromatography–quadrupole time-of-flight mass spectrometry (RPLC-QTOF-MS). Molecular informatics screening was performed using UMPred-FRL (a feature representation learning-based meta-predictor for umami peptides) and TastePeptides-Meta (a one-stop platform for taste peptides and prediction models), yielding 7255 potential umami peptides. From these, 145 peptides were further selected for molecular docking. In addition, 6 representative umami peptides were selected for receptor-level validation and structural analysis. Mechanistically, the umami receptor taste receptor type 1 member 1/taste receptor type 1 member 3 (T1R1/T1R3) belonged to class C G protein-coupled receptor (GPCR) and relied on the extracellular Venus flytrap (VFT) domain for ligand capture. Ligand-induced VFT conformational convergence transmitted changes to the transmembrane region and triggered signal transduction. Docking and energy decomposition indicated that the ionic group primarily contributed to orientation and anchoring. Salt-bridge or hydrogen-bond networks were formed around Lys228, Arg240, Glu206, Asp210, Asn141, and Gln138, thereby reducing conformational freedom. Meanwhile, hydrophobic side chains obtained major binding gains within a hydrophobic microenvironment formed by Val135, Ile137, Leu165, Tyr166, Trp78, and His79. These results reflected a synergistic mode in which charge pairing enabled positioning and hydro-phobic complementarity promoted VFT closure. To experimentally confirm sensory relevance, 6 representative peptides were individually spiked into 4 brewing-stage beer samples, which produced a clear stratification pattern across stages. Notably, peptides with favorable docking-derived binding propensity did not necessarily enhance umami perception, and several longer peptides showed persistent negative sensory shifts, supporting that binding affinity alone could not be treated as a proxy for perceived umami in the beer matrix. At the node level, the cumulative abundance of umami peptides showed a significant positive correlation with umami scores, with a Pearson correlation coefficient of r = 0.963 and p = 0.037. This result indicated good linear consistency between umami peptide content and the upward shift in umami taste in lager beer. Umami peptide clusters were further proposed as a more appropriate functional unit, and an umami peptide cluster database spanning the full process was constructed. This database provided a reusable resource for process control and flavor prediction. Full article