Functional beverages enriched with herbal extracts are gaining popularity due to their potential health benefits. Tilia cordata flowers are known for their antioxidant and antimicrobial properties, making them a promising additive in food and beverage formulations. Our study aimed to develop ready-to-drink iced teas enriched with T. cordata flower extracts and to evaluate their antioxidant, antimicrobial, and sensory characteristics as functional food products. Fresh T. cordata flowers were analyzed for metal contents. Phenolic acid profiles in ethanolic and aqueous extracts were determined using HPLC-MS. Antioxidant activity was evaluated using DPPH radical scavenging, conjugated diene, and iron ion chelation assays. Antimicrobial effects were tested against Staphylococcus aureus, Bacillus cereus, and Listeria monocytogenes. Sensory analysis was conducted using AI-based facial expression recognition to assess consumer responses. Metal analysis revealed low concentrations of Mn, Zn, Cu, and Fe, with no detectable Pb, Cd, or Ni. Ethanolic extracts showed significantly higher levels of phenolic acids than aqueous extracts. Iced teas containing both types of extracts demonstrated strong antioxidant activity, with ethanolic formulations having the highest levels of phenols and flavonoids. Antimicrobial tests confirmed activity in both teas, with ethanolic extracts showing stronger effects. Sensory analysis indicated positive emotional responses and consumer acceptance for both formulations. Iced teas enriched with T. cordata extracts exhibited significant antioxidant and antimicrobial properties, confirming their potential as functional beverages. The use of AI-driven sensory evaluation proved effective in capturing consumer preferences, supporting its application in product development. These findings suggest commercial viability for industrial production.
Context. Detection and characterisation of Jovian analogues in precision radial velocity (RV) measurements is gaining momentum due to the constantly increasing observational baseline of Doppler surveys. The occurrence rate of Jovian-mass exoplanets is crucial to understanding the architecture of planetary systems. However, long-period RV signals in Doppler surveys could also be induced by stellar magnetic cycles, leading to misinterpretations of planetary candidates. Aims. We investigate long-term RV variability in the K-dwarf star GJ 1137 (HD 93083, HIP 52521), a known Saturn-mass exoplanet host, and assess the role of stellar activity in shaping the observed signals. Methods. We analyse 13 years of archival high-precision spectroscopic observations obtained with the High Accuracy Radial velocity Planet Searcher spectrograph (HARPS). We performed an extensive spectroscopic analysis of the stellar activity indicators and applied an RV modelling approach, incorporating Keplerian fits, Gaussian process regression as a proxy for stellar activity, and other stellar activity diagnostics. Furthermore, we refined the orbital parameters and the minimum mass of the known exoplanet GJ 1137 b and searched for additional planetary candidates in the system. Results. We detect a long-period RV signal that, if interpreted as planetary, would suggest the presence of a Jovian analogue companion. However, our spectroscopic activity analysis provides strong evidence that this variability is induced by the star's long-term magnetic cycle (P-cyc = 5870(-350)(+480) days) rather than by an orbiting planet. The signal is detected in both full width at half maximum (FWHM) of the cross-correlation function and the chromospheric activity index log R '(HK). We measure the stellar rotation period to P-rot = 32.3(-1.3)(+1.2) d and identify a significant short-period RV signal, which we attribute to a Super Earth with a period of 9.6412(-(11))(+(12)) d and a minimum mass of 5.12(-0.69)(+0.70) M-circle plus, making GJ 1137 a multiple-planet system.
In this study, double perovskites with the general formula LnMn0.5Fe0.5O3 (where Ln = Nd, Sm, Gd) were synthesized via the solution combustion method using glycine as fuel. The structural and morphological properties of the resulting materials were characterized by X-ray Powder Diffraction (XRPD), Scanning Electron Microscopy (SEM), and Energy Dispersive X-ray (EDX) spectroscopy. XRPD confirmed the formation of crystalline perovskite phases, while SEM and EDX analyses provided insights into particle morphology and elemental composition, consistent with the expected 2:1:1 atomic ratio of the constituent elements. A paraffin-impregnated graphite electrode (PIGE) modified with perovskite microcrystals was employed for electrochemical measurements. The electrocatalytic activity of the materials was evaluated using cyclic voltammetry (CV) and square-wave voltammetry (SWV), focusing on the oxidation of H2O2 and serotonin in phosphate buffer solution. All three perovskites exhibited catalytic activity toward both analytes, with comparable performance for hydrogen peroxide. However, SmMn0.5Fe0.5O3 and GdMn0.5Fe0.5O3 showed enhanced activity for serotonin oxidation compared to NdMn0.5Fe0.5O3. To rationalize these findings, crystallochemical calculations were performed to assess cell distortion, orthorhombic strain, and octahedral tilting, and their implications are discussed.
Biological invasions, driven by the spread of non-native species, have become a critical global issue because of their far-reaching ecological and socioeconomic impacts. Effective communication of the risks of biological invasions is essential for implementing robust policy and legislation and gaining public support for conservation efforts. However, current policies often suffer from fragmentation and ineffectiveness, largely due to inadequate risk communication and complex multi-level governance. To address this challenge, we develop a global framework designed to enhance clearer communication about biological invasion risks. The framework contextualizes key terms across three domains in invasion science: species invasiveness, risk analysis, and decision support tools. Using both diffusion-of-English and ecology-of-language paradigms, and following a three-step process involving preliminary consensus, AI querying, and ground-truthing with final consensus, we validate the framework in 70 non-English languages which, together with English, have official status in at least one country and collectively cover all 195 countries worldwide. Our findings reveal that while terminology for risk analysis is well established, terminology for species invasiveness and, especially, for decision support tools remains underdeveloped in many languages, hindering effective communication and policy implementation. Our framework underscores the importance of cultural and political neutrality. By promoting clearer risk communication among scientists, policymakers, and the public globally, we aim to reduce policy fragmentation and foster enhanced collaboration in risk mitigation. We recommend expanding multilingual decision support tools to include the full risk analysis process: risk identification, risk assessment, and risk management. This will support intergovernmental mitigation efforts and promote a unified global response to biological invasions.
A series of three ligands L1-L3 where L1 = N, N’-bis(3-methoxysalicylidene (propylen-2-ol)-1,3-diamine; L2 = N, N’-bis(3-ethoxy-salicylidene) (propylen-2-ol)-1,3-diamine); L3 = N, N’-bis(5-methylsalicylidene)(propylen-2-ol)-1,3-diamine are reported. Ligands were structurally characterized by NMR spectroscopy. The crystal structures of L2·2EtOH and L3 were determined by X-ray diffraction using aspheric Hirshfeld Atom Refinement model. Within the framework of quantum crystallography, HAR-derived geometries provide highly accurate hydrogen atom positions that serve as a reliable experimental basis for electron-density analysis. Both Schiff bases possess tautomeric character in their molecular structure, displaying ketoenamine/zwitterionic or enolimine forms stabilized by intra- or intermolecular hydrogen bonding. The nature and strength of these interactions were analyzed using electron-density based topological methods (QTAIM, Laplacian analysis) supported by complementary visualization tools (electron localization function ELF, reduced density gradient, RDG, deformation density maps and interaction region indicator, IRI), allowing detailed insight into proton localization and hydrogen-bond stabilization in the crystal state.
