Search Results (94)

This study presents a computational analysis of industry-specific advertising message strategies through the theoretical lens of the FCB (Foote, Cone & Belding) grid framework. Leveraging the AiSAC (AI Analysis System for Ad Creation) system developed by the Korea Broadcast Advertising Corporation (KOBACO), we analyzed 27,000 Korean advertisements across five major industries using advanced machine learning techniques. Through Latent Dirichlet Allocation topic modeling with a coherence score of 0.78, we identified five distinct message strategies: emotional appeal, product features, visual techniques, setting and objects, and entertainment and promotion. Our computational analysis revealed that each industry exhibits a unique “message strategy fingerprint” that significantly discriminates between categories, with discriminant analysis achieving 62.7% classification accuracy. Time-series analysis using recurrent neural networks demonstrated a significant evolution in strategy preferences, with emotional appeal increasing by 44.3% over the study period (2015–2024). By mapping these empirical findings onto the FCB grid, the present study validated that industry positioning within the grid’s quadrants aligns with theoretical expectations: high-involvement/think (IT and Telecom), high-involvement/feel (Public Institutions), low-involvement/think (Food and Household Goods), and low-involvement/feel (Services). This study contributes to media science by demonstrating how computational methods can empirically validate the established theoretical frameworks in advertising, providing a data-driven approach to understanding message strategy patterns across industries. Full article

Aquatic ecosystems are essential for biodiversity and ecosystem services, but anthropogenic pressures threaten them. In this context, citizen science has emerged as an innovative strategy for biodiversity conservation and environmental monitoring. We conducted a scientometric analysis to identify patterns and gaps in the scientific literature on citizen science in aquatic ecology. We analyzed 185 articles published between 2003 and 2024 on the Web of Science and Scopus databases, with the highest number of publications on the topic (15.14%) in 2023. The United States, Australia, and the United Kingdom were the most productive and frequently studied countries. Studies focused on marine ecosystems (50.28%), while freshwater environments, such as rivers (12.99%), remain under-represented. Taxonomic groups such as fish (30.64%) and aquatic mammals (13.87%) were most commonly studied. The focus of monitoring was on ecology and species conservation. The projects adopted a contributory model of citizen engagement (92.97%), with a predominance of urban citizens (60.51%). Participants were trained through online platforms (25.75%) and in-person courses (21.56%), while communication methods involved sharing photos and videos (38.77%) and online uploads (23.79%). Therefore, expanding studies on freshwater ecosystems and rural and traditional communities, and integrating different levels of citizen participation, is essential. Full article

The SARS-CoV-2 main protease (Mpro), essential for viral replication, remains a prime target for antiviral drug design against COVID-19 and related coronaviruses. In this study, we present a systematic investigation into the molecular determinants of Mpro inhibition using an integrated approach combining large-scale data mining, cheminformatics, and quantum chemical calculations. A curated dataset comprising 963 high-resolution structures of Mpro–ligand complexes—348 covalent and 615 non-covalent inhibitors—was mined from the Protein Data Bank. Cheminformatics analysis revealed distinct physicochemical profiles for each inhibitor class: covalent inhibitors tend to exhibit higher hydrogen bonding capacity and sp³ character, while non-covalent inhibitors are enriched in aromatic rings and exhibit greater aromaticity and lipophilicity. A novel descriptor, Weighted Hydrogen Bond Count (WHBC), normalized for molecular size, revealed a notable inverse correlation with aromatic ring count, suggesting a compensatory relationship between hydrogen bonding and π-mediated interactions. To elucidate the energetic underpinnings of molecular recognition, 40 representative inhibitors (20 covalent, 20 non-covalent) were selected based on principal component analysis and aromatic ring content. Quantum mechanical calculations at the double-hybrid B2PLYP/def2-QZVP level quantified non-bonded interaction energies, revealing that covalent inhibitors derive binding strength primarily through hydrogen bonding (~63.8%), whereas non-covalent inhibitors depend predominantly on π–π stacking and CH–π interactions (~62.8%). Representative binding pocket analyses further substantiate these findings: the covalent inhibitor F2F-2020198-00X exhibited strong hydrogen bonds with residues such as Glu166 and His163, while the non-covalent inhibitor EDG-MED-10fcb19e-1 engaged in extensive π-mediated interactions with residues like His41, Met49, and Met165. The distinct interaction patterns led to the establishment of pharmacophore models, highlighting key recognition motifs for both covalent and non-covalent inhibitors. Our findings underscore the critical role of aromaticity and non-bonded π interactions in driving binding affinity, complementing or, in some cases, substituting for hydrogen bonding, and offer a robust framework for the rational design of next-generation Mpro inhibitors with improved selectivity and resistance profiles. Full article

Background: Postoperative pain is an unpleasant experience for the patient and impairs postoperative functional outcomes. The current literature on the influence of preoperative predictors on postoperative pain outcomes remains limited. This study aimed to identify sociodemographic, clinical, psychological, and temperamental predictors of postoperative pain in patients undergoing surgery for degenerative disc disease (DDD). Methods: Eighty-one adults with DDD, qualified for neurosurgical intervention, were enrolled. All patients underwent neurological and psychiatric evaluations, as well as preoperative pain assessments using the Visual Analogue Scale (VAS) and the West Haven-Yale Multidimensional Pain Inventory (WHYMPI). Psychological assessments included the Perceived Stress Scale, Hospital Anxiety and Depression Scale, Somatic Symptom Scale, temperament, and personality inventories (e.g., FCB-TI, NEO-FFI), and cognitive tests (Trail Making Test, Digit Span Test). Postoperative pain was re-evaluated with the VAS 12 weeks after surgery. Data were analyzed using univariate and multivariate statistical methods. Results: Univariate analyses revealed significant differences between the defined groups regarding lack of improvement of pain 12 weeks after surgery compared to preoperative VAS, systolic blood pressure, and four scales from the WHYMPI. However, stepwise logistic regression identified only preoperative VAS score as an independent predictor of postoperative pain improvement. Receiver Operating Characteristic analysis and Youden’s index indicated a preoperative VAS cut-off score of 6 as the most predictive. Conclusions: A VAS score of 6 or more before surgery independently predicts the absence of chronic pain 12 weeks postoperatively for patients without neurological deficits. Moreover, given the complexity of this topic, further prospective, randomized controlled research is essential. Full article

Introduction: Asthma and chronic obstructive pulmonary disease (COPD) are chronic respiratory illnesses frequently accompanied by anxiety and depression. These psychological symptoms often go undetected due to their overlap with somatic complaints. According to the regulatory theory of temperament (RTT), biologically based temperament traits may influence emotional responses to chronic illness. This study examined whether RTT-defined temperament traits predict depression and anxiety severity in patients with asthma and/or COPD. Material and Methods: The study included 210 adult patients with asthma and/or COPD recruited from a university hospital and pulmonology clinics. Individuals with a prior history of mental illness were excluded. Participants completed three validated questionnaires: the Formal Characteristics of Behavior–Temperament Inventory (FCB-TI), the Beck Depression Inventory (BDI), and the State–Trait Anxiety Inventory (STAI). Additional demographic and clinical data were collected. Multiple linear regression was used to assess the predictive value of six temperament traits for depression, state anxiety, and trait anxiety. A significance threshold of α = 0.05 was used in all statistical tests. Results: Temperament structure significantly predicted all three mental health outcomes: depression (R² = 0.37), state anxiety (R² = 0.45), and trait anxiety (R² = 0.35). Briskness negatively correlated with all outcomes, while emotional reactivity showed a positive correlation. No significant associations were found for the remaining four traits. Socioeconomic and lifestyle factors were not significant predictors. Conclusions: Temperament traits, particularly briskness and emotional reactivity, significantly influence depression and anxiety severity in asthma and COPD. Temperament assessment may serve as a low-cost, telemedicine-compatible tool to identify at-risk patients and support integrated, personalized care. Full article

Amperometric biosensors (ABSs) and enzymatic biofuel cells (BFCs) share several fundamental principles in their functionality, despite serving different primary purposes. Both devices rely on biorecognition, redox reactions, electron transfer (ET), and advanced electrode materials, including innovative nanomaterials (NMs). ABSs and BFCs, utilizing microbial oxidoreductases in combination with electroactive NMs, are both efficient and cost-effective. In the current study, several laboratory prototypes of BFCs have been developed with bioanodes based on yeast flavocytochrome b₂ (Fcb₂) and alcohol oxidase (AO), and a cathode based on fungal laccase. For the first time, BFCs have been developed featuring anodes based on Fcb₂ co-immobilized with redox NMs on a glassy carbon electrode (GCE), and cathode-utilizing laccase combined with gold–cerium–platinum nanoparticles (nAuCePt). The most effective lactate BFC, which contains gold–hexacyanoferrate (AuHCF), exhibited a specific power density of 1.8 µW/cm². A series of BFCs were developed with an AO-containing anode and a laccase/nAuCePt/GCE cathode. The optimal configuration featured a bioanode architecture of AO/nCoPtCu/GCE, achieving a specific power density of 3.2 µW/cm². The constructed BFCs were tested using lactate-containing food product samples as fuels. Full article

Zinc processing tailings (ZPTs) of the Kharzet Youcef processing complex, Setif, Algeria, are mainly stockpiled in tailing dumps without use, occupying significant surfaces and negatively influencing the human environment and health. Incorporating ZPTs into building materials manufacturing is an effective solution to meet the dual objectives of environmental protection and economic development. This study investigates the influence of firing temperature and integrating ZPTs as a partial replacement for clay on the physic-mechanical properties of fired clay bricks (FCBs). Microstructural, chemical, and mineralogical analyses of ZPTs and clay were carried out by SEM-EDS, XRF, and XRD, respectively. Seven mixtures were produced with various percentages of ZPTs added to clay (0%, 5%, 10%, 15%, 20%, 25%, and 30%) and were fired at two different temperatures (900 and 1000 °C) at a ramp rate of 5 °C. Physic-mechanical tests were carried out on different brick specimens, and the results obtained showed that the FCBs incorporated with 10% of ZPTs produced the highest flexural strength of 6.24 MPa, compressive resistance of 29.78 MPa, bulk density of 1.37 g/cm³, and water absorption of 15.1% at 900 °C. Therefore, the recycling of ZPTs for FCBs manufacturing is feasible and an effective alternative waste disposal solution for sustainable development while reducing negative environmental impacts. Full article

Artificial enzymes or nanozymes (NZs) are gaining significant attention in biotechnology due to their stability and cost-effectiveness. NZs can offer several advantages over natural enzymes, such as enhanced stability under harsh conditions, longer shelf life, and reduced production costs. The booming interest in NZs is likely to continue as their potential applications expand. In our previous studies, we reported the “green” synthesis of copper hexacyanoferrate (gCuHCF) using the oxidoreductase flavocytochrome b₂ (Fcb₂). Organic–inorganic micro-nanoparticles were characterized in detail, including their structure, composition, catalytic activity, and electron-mediator properties. An SEM analysis revealed that gCuHCF possesses a flower-like structure well-suited for concentrating and stabilizing Fcb₂. As an effective peroxidase (PO) mimic, gCuHCF has been successfully employed for H₂O₂ detection in amperometric sensors and in several oxidase-based biosensors. In the current study, we demonstrated the uniqueness of gCuHCF that lies in its multifunctionality, serving as a PO mimic, a chemosensor for ammonium ions, a biosensor for L-lactate, and exhibiting perovskite-like properties. This exceptional ability of gCuHCF to enhance fluorescence under blue light irradiation is being reported for the first time. Using gCuHCF as a PO-like NZ, novel oxidase-based sensors were developed, including an optical biosensor for L-arginine analysis and electrochemical biosensors for methanol and glycerol determination. Thus, gCuHCF, synthesized via Fcb₂, presents a promising platform for the development of amperometric and optical biosensors, bioreactors, biofuel cells, solar cells, and other advanced devices. The innovative approach of utilizing biocatalysts for nanoparticle synthesis highlights a groundbreaking direction in materials science and biotechnology. Full article

The functionalization of carbon black (CB) represents a promising strategy to enhance its compatibility with polymers while addressing sustainability concerns. In this study, a solvent-free mechanochemical approach (ball milling) is proposed for the functionalization of oxidized carbon black (oCB) with post-consumed polylactic acid (PLA), overcoming the environmental drawbacks of conventional methods that mostly rely on toxic solvents and catalysts. The functionalized carbon black (f-CB) was characterized by Fourier transform infrared spectroscopy (FTIR), elemental analysis (EA), and thermogravimetric analysis (TGA) to confirm the successful modification. At the same time, the influence of f-CB as a nanofiller of residual PLA waste was evaluated using differential scanning calorimetry (DSC) and gel permeation chromatography (GPC), demonstrating its stabilization effect during melt extrusion by preserving the molecular weight of the starting polymer. On the other hand, the dynamic mechanical analysis (DMA) revealed that the addition of f-CB did not negatively affect the mechanical properties of the resulting composite. In conclusion, mechanochemistry was used as a sustainable and unique strategy for the upcycling of waste PLA into a PLA-based composite stabilized by CB functionalized with the waste PLA itself. Full article

Effective management of malignant weeds is critical to soybean growth. This study focuses on addressing the critical challenges of targeted spraying operations for malignant weeds such as Cirsium setosum, which severely threaten soybean yield in soybean fields. Specifically, this research aims to tackle key issues in plant protection operations, including the precise identification of weeds, the lightweight deployment of segmentation models, real-time requirements for spraying operations, and the generalization ability of models in diverse field environments. To address these challenges, this study proposes an improved weed instance segmentation model based on YOLOv8s-Seg, named FCB-YOLOv8s-Seg, for targeted spraying operations in soybean fields. The FCB-YOLOv8s-Seg model incorporates a lightweight backbone network to accelerate computations and reduce model size, with optimized Squeeze-and-Excitation Networks (SENet) and Bidirectional Feature Pyramid Network (BiFPN) modules integrated into the neck network to enhance weed recognition accuracy. Data collected from real soybean field scenes were used for model training and testing. The results of ablation experiments revealed that the FCB-YOLOv8s-Seg model achieved a mean average precision of 95.18% for bounding box prediction and 96.63% for segmentation, marking an increase of 5.08% and 7.43% over the original YOLOv8s-Seg model. While maintaining a balanced model scale, the object detection and segmentation accuracy of this model surpass other existing classic models such as YOLOv5s-Seg, Mask-RCNN, and YOLACT. The detection results in different scenes show that the FCB-YOLOv8s-Seg model performs well in fine-grained feature segmentation in complex scenes. Compared with several existing classical models, the FCB-YOLOv8s-Seg model demonstrates better performance. Additionally, field tests on plots with varying weed densities and operational speeds indicated an average segmentation rate of 91.30%, which is 6.38% higher than the original model. The proposed algorithm shows higher accuracy and performance in practical field instance segmentation tasks and is expected to provide strong technical support for promoting targeted spray operations. Full article

Whale blow, the vapor exhaled during respiration of cetaceans, provides valuable genetic information to monitor health status and population dynamics. However, obtaining samples of sufficient quality and quantity remains a challenge, particularly for small odontocetes. Here, we developed both field and laboratory protocols optimized for the genetic analysis of blow samples of short-finned pilot whales (Globicephala macrorhynchus). Blow collection was performed from a small research vessel at a slow speed using a hand-held carbon fiber pole equipped with a sterile Petri dish. Determination of the sex was conducted using up to five PCRs of multiplexed markers from a classical methodology (SRY + ZFX/ZFY genes) and a novel protocol (SRY + FCB17) optimized for highly degraded, fragmented and/or scarce DNA. A total of 47 blow samples of free-ranging pilot whales off the Canary Islands were collected. The presence of DNA was confirmed in 98% of the blow samples, which were further processed resulting in 32 of them with positive genetic sex determination applying the novel methodology (70%), compared to only 8 (19%) with the classical method. Results confirmed the success of sampling, DNA extraction and sex determination using multiplexed markers in blow samples of odontocetes. This protocol represents an important management tool to conduct future non-invasive health assessments of small cetaceans in the wild. Full article

We report the development of amperometric biosensors (ABSs) employing flavocytochrome b₂ (Fcb₂) coupled with nanoparticles (NPs) of noble metals on graphite electrode (GE) surfaces. Each NPs/GE configuration was evaluated for its ability to decompose hydrogen peroxide (H₂O₂), mimicking peroxidase (PO) activity. The most effective nanoPO (nPO) was selected for developing ABSs targeting L-lactate. Consequently, several Fcb₂/nPO-based ABSs with enhanced sensitivity to L-lactate were developed, demonstrating mediated ET between Fcb₂ and the GE surface. The positive effect of noble metal NPs on Fcb₂-based sensor sensitivity may be explained by the synergy between their dual roles as both PO mimetics and electron transfer mediators. Furthermore, our findings provide preliminary data that may prompt a re-evaluation of the mechanism of L-lactate oxidation in Fcb₂-mediated catalysis. Previously, it was believed that L-lactate oxidation via Fcb₂ catalysis did not produce H₂O₂, unlike catalysis via L-lactate oxidase. Our initial research revealed that the inclusion of nPO in Fcb₂-based ABSs significantly increased their sensitivity. Employing other PO mimetics in ABSs for L-lactate yielded similar results, reinforcing our hypothesis that trace amounts of H₂O₂ may be generated as a transient intermediate in this reaction. The presence of nPO enhances the L-lactate oxidation rate through H₂O₂ utilization, leading to signal amplification and heightened bioelectrode sensitivity. The proposed ABSs have been successfully tested on blood serum and fermented food samples, showing their promise for L-lactate monitoring in medicine and the food industry. Full article

This paper presents a comprehensive review of scientific papers and market reports analyzing the economic competitiveness of fuel cell electric buses (FCEBs) with respect to their conventional alternatives via the total cost of ownership (TCO) methodology. We discussed the variables and data taken into account and compared the resulting outcomes by year and geographical areas. It emerged that FCBs are not currently cost competitive. The decreasing trend in acquisition and fuel costs, however, indicates potential for future competitiveness. We find that the current TCO literature on FCEBs presents several areas of uncertainty and weakness. Potential improvements can be achieved by: (i) extending the geographic coverage to Asian and African developing countries; (ii) making use of real-world data instead of simulated data, in particular, concerning acquisition costs, hydrogen costs under different pathways, fuel efficiency, and maintenance costs; (iii) clarifying the role of infrastructural costs; (iv) exploring the existence of economies of scale at fleet level; (v) distinguishing among different bus sizes. Full article

Mesquite (Prosopis spp.) is one of the main plant representatives in regions with a dry climate, and is a fundamental part of the flora of the Mexican arid, with an indisputable importance from ecological, economic and industrial points of view. However, the restrictive factors of dry climates, as well as genetic variability, are sources of the great diversity of mesquite, so its taxonomy is not yet well defined. The present study seeks to determine the diversity of mesquite in the Mexican semi-desert based on the morphometric characterization of its leaves. Methods: Different leaf parameters such as the number, length and width of the leaflets were recorded in 31 well-marked sites in the area, to obtain measures of central tendency and dispersion, and to determine the differences and similarities between the sites, as well as the groups of homogeneous and heterogeneous taxa. Results: Five taxa were identified, of which there were two varieties (Prosopis glandulosa var. glandulosa and Prosopis reptans var. cinerascens), a pure or typical species (Prosopis laevigata) and two hybrids (Prosopis glandulosa var. glandulosa x Prosopis laevigata and Prosopis laevigata x Prosopis glandulosa var. glandulosa). The discriminant analysis indicated that five variables presented the highest percentage of separation or best separated the taxa, so the study was based on the phenogram with the combination of these five variables: (a) length of middle leaflets, (b) length of upper leaflets, (c) spacing of middle leaflets, (d) length/width relationship of middle leaflets and (e) length/width relationship of middle leaflets. Conclusions: Both the traditional taxonomic classification and the cluster and discriminant analyses reflected the same taxa (Prosopis glandulosa var. glandulosa, Prosopis laevigata and Prosopis reptans var. cinerascens) and the existence of hybridization between Prosopis glandulosa var. glandulosa and Prosopis laevigata. Full article

Argemone mexicana L. has been used in traditional Mexican medicine. Among its bioactive constituents, berberine (BER) has garnered attention for its cytotoxic properties against different tumor cell lines. This study investigates the in vitro toxicity against HEP-G2 (human hepatocellular carcinoma) and murine lymphoma (L5178Y-R) cells using the MTT assay of the methanol extract (AmexM), sub-partitions of A. mexicana, and BER. Selectivity indices (SIs) were determined by comparing their cytotoxic effects on VERO (monkey kidney epithelial) and PBMC (human peripheral blood mononuclear) non-tumoral cells. Additionally, the anti-hemolytic effect of these treatments was assessed using the AAPH method. The treatment with the most promising activity against tumor cells and anti-hemolytic efficacy underwent further evaluation for toxicity in Artemia salina and antioxidant activities using DPPH, ABTS, and FRAP assays. BER demonstrated an IC₅₀ = 56.86 µg/mL in HEP-G2 cells and IC₅₀ < 5.0 µg/mL in L5178Y-R cells, with SI values of 15.97 and >5.40 in VERO and PBMC cells, respectively. No significant hemolytic effects were observed, although AmexM and BER exhibited the highest anti-hemolytic activity. BER also demonstrated superior antioxidant efficacy, with lower toxicity in A. salina nauplii compared to the control. Additionally, BER significantly attenuated nitric oxide production. This study highlights the antiproliferative effects of A. mexicana, particularly BER, against HEP-G2 and L5178Y-R tumor cell lines, along with its selectivity towards normal cells. Furthermore, its anti-hemolytic and antioxidant potentials were demonstrated, suggesting that BER is a promising candidate for potent chemotherapeutic agents. Full article