Explore the vast range of titles available.

Geographic information systems (GISs) based on WebGIS architectures have transformed geospatial data visualization and analysis, offering rapid access to critical information and enhancing decision making across sectors. This study conducted a bibliometric review of 358 publications using the Web of Science database. The analysis utilized tools, such as Bibliometrix (version R 4.3.0) and Biblioshiny (version 1.7.5), to study authors, journals, keywords, and collaborative networks in the field of information systems. This study identified two relevant clusters in the literature: (1) voluntary geographic information (VGI) and crowdsourcing, focusing on web integration for collaborative mapping through contributions from non-professionals and (2) GIS management for decision making, highlighting web-based architectures, open sources, and service-based approaches for storing, processing, monitoring, and sharing geo-referenced information. The journals, authors, and geographical distribution of the most important publications were identified. China, Italy, the United States, Germany, and India have excelled in the application of geospatial technologies in areas such as the environment, risk, sustainable development, and renewable energy. These results demonstrate the impact of web-based GISs on forest conservation, climate change, risk management, urban planning, education, public health, and disaster management. Future research should integrate AI, mobile applications, and geospatial data security in areas aligned with sustainable development goals (SDGs) and other global agendas.

Consumer-grade EEG devices have the potential for widespread brain-computer interface deployment but pose significant challenges for emotion recognition due to reduced spatial coverage and the variable signal quality encountered in uncontrolled deployment environments. While deep learning approaches have employed increasingly complex architectures, their efficacy in noisy consumer-grade signals and cross-system generalizability remains unexplored. We present a comprehensive systematic comparison of EEGNet architecture, which has become a benchmark model for consumer-grade EEG analysis versus traditional machine learning, examining when and why domain-specific feature engineering outperforms end-to-end learning in resource constrained scenarios. We conducted comprehensive within-dataset evaluation using the DREAMER dataset (23 subjects, Emotiv EPOC 14-channel) and challenging cross-dataset validation (DREAMER→SEED-VII transfer). Traditional ML employed domain-specific feature engineering (statistical, frequency-domain, and connectivity features) with random forest classification. Deep learning employed both optimized and enhanced EEGNet architectures, specifically designed for low channel consumer EEG systems. For cross-dataset validation, we implemented progressive domain adaptation combining anatomical channel mapping, CORAL adaptation, and TCA subspace learning. Statistical validation included 345 comprehensive evaluations with fivefold cross-validation × 3 seeds × 23 subjects, Wilcoxon signed-rank tests, and Cohen's d effect size calculations. Traditional ML achieved superior within-dataset performance (F1 = 0.945 ± 0.034 versus 0.567 for EEGNet architectures, < 0.000001, Cohen's d = 3.863, 67% improvement) across 345 evaluations. Cross-dataset validation demonstrated good performance (F1 = 0.619 versus 0.007) through systematic domain adaptation. Progressive improvements included anatomical channel mapping (5.8× improvement), CORAL domain adaptation (2.7× improvement), and TCA subspace learning (4.5× improvement). Feature analysis revealed inter-channel connectivity patterns contributed 61% of the discriminative power. Traditional ML demonstrated superior computational efficiency (95% faster training, 10× faster inference) and excellent stability (CV = 0.036). Fairness validation experiments supported the advantage of traditional ML in its ability to persist even with minimal feature engineering (F1 = 0.842 vs. 0.646 for enhanced EEGNet), and robustness analysis revealed that deep learning degrades more under consumer-grade noise conditions (17% vs. <1% degradation). These findings challenge the assumption that architectural complexity universally improves biosignal processing performance in consumer-grade applications. Through the comparison of traditional ML against the EEGNet consumer-grade architecture, we highlight the potential that domain-specific feature engineering and lightweight adaptation techniques can provide superior accuracy, stability, and practical deployment capabilities for consumer-grade EEG emotion recognition. While our empirical comparison focused on EEGNet, the underlying principles regarding data efficiency, noise robustness, and the value of domain expertise could extend to comparisons with other complex architectures facing similar constraints in further research. This comprehensive domain adaptation framework enables robust cross-system deployment, addressing critical gaps in real-world BCI applications.

Sacha inchi (P. volubilis L.), an ancient oilseed crop native to the Amazon, is gaining attention for its high nutritional value particularly due to its ω-3-, -6-, -9-rich oil. However, most research has focused mainly on oil characterization, neglecting the potential of its by-products, such as the Sacha inchi oil-press cake (i.e., the solid residue after oil extraction). This study explores the chemical composition of Sacha inchi oil press-cake powder, focusing on fatty acid and amino acid profiles, antinutrient factors, total phenolic content, antioxidant activity, and the bioactivity of its extracts on cellular models. Fatty acid analysis revealed a high proportion of polyunsaturated fatty acids, especially α-linolenic acid (42.52%), making it a valuable resource for health-promoting applications. The protein content was also significant (41.86%), with a balanced amino acid composition, including essential amino acids such as leucine, valine, and isoleucine, which are vital for muscle protein synthesis and energy metabolism, in food and/or feed applications. Antinutritional factors were detected, including saponins (1050.1 ± 1.1 mg/100 g), alkaloids (2.1 ± 0.5 mg/100 g), and tannins (6.2 ± 0.9 mg/100 g). While these phytotoxins could limit their use in food applications, their potential antimicrobial activity highlights promising pharmacological opportunities. Total phenolic content (TPC) and antioxidant activity (AO) were evaluated using two extract mixtures differing in composition and polarity, with the acetone/water/acetic acid solvent (80/19/1 v/v/v) showing the highest antioxidant properties. The extract obtained showed cytotoxic effects against Panc-1 cancer cells, highlighting its potential in nutraceutical and pharmaceutical applications. This study underscores the unexploited potential of Sacha inchi by-products, such as the oil press-cake, as a sustainable resource of bioactive compounds for functional products, supporting circular bio-economy strategies by plant-based waste and local biodiversity valorization.

Drugs that modulate serotonin (5-HT) synaptic concentrations impact neurogenesis and hippocampal (HPC)-dependent learning. The primary objective is to determine the extent to which psilocybin (PSOP) modulates neurogenesis and thereby affects acquisition and extinction of HPC-dependent trace fear conditioning. PSOP, the 5-HT 2A agonist 25I-NBMeO and the 5-HT 2A/C antagonist ketanserin were administered via an acute intraperitoneal injection to mice. Trace fear conditioning was measured as the amount of time spent immobile in the presence of the conditioned stimulus (CS, auditory tone), trace (silent interval) and post-trace interval over 10 trials. Extinction was determined by the number of trials required to resume mobility during CS, trace and post-trace when the shock was not delivered. Neurogenesis was determined by unbiased counts of cells in the dentate gyrus of the HPC birth-dated with BrdU co-expressing a neuronal marker. Mice treated with a range of doses of PSOP acquired a robust conditioned fear response. Mice injected with low doses of PSOP extinguished cued fear conditioning significantly more rapidly than high-dose PSOP or saline-treated mice. Injection of PSOP, 25I-NBMeO or ketanserin resulted in significant dose-dependent decreases in number of newborn neurons in hippocampus. At the low doses of PSOP that enhanced extinction, neurogenesis was not decreased, but rather tended toward an increase. Extinction of “fear conditioning” may be mediated by actions of the drugs at sites other than hippocampus such as the amygdala, which is known to mediate the perception of fear. Another caveat is that PSOP is not purely selective for 5-HT 2A receptors. PSOP facilitates extinction of the classically conditioned fear response, and this, and similar agents, should be explored as potential treatments for post-traumatic stress disorder and related conditions.

Olive growing has been intensified through the simplification of agricultural landscapes. In order to rethink the environmental drawbacks of these practices, conservation biological control techniques have been examined. In this work, Prays oleae and its natural enemy Chrysoperla carnea were monitored to account for the effects of the amount and diversity of different land-uses. We found that C. carnea showed an attraction to areas with high abundances of P. oleae but this predator did not display any affection by the different land-uses. Inversely, P. oleae abundance was lower in diverse landscapes and higher in simplified ones. Importantly, higher abundances of C. carnea were related to lower infestation levels of P. oleae in the late part of the season. These results corroborate the attraction of C. carnea to the olive moth, highlighting the potential of C. carnea as a biological control agent of this pest, assert that the promotion of land-use diversity can reduce P. oleae and confirm that landscapes dominated by olive groves can promote this pest. The present study aims at contributing to the discussion about the management of agricultural ecosystems by providing farmers with sustainable alternatives that do not have harmful effects on the environment and public health.

Guinea pigs in intensive production generates an imperative necessity of physio-pathological bases for diagnosing their state of welfare, health, and production; those which are available for this species are referred to as laboratory or companion animal. The aim of this research is to determine changes in hematological and blood metabolites profiles in relation to age of Cavia porcellus reared in intensive system at 660 masl in humid tropic. For this purpose, forty 15-120 days old guinea pig in healthy conditions from the inti x Peru lines born in the humid tropic were used and the evaluation ages were 15-21, 22-35, 36-60 and 61-120 days. Blood samples were obtained by puncture of the cephalic vein; profiles of erythrocytes (RBC), total leucocytes (WBC), lymphocytes, granulocytes, hematocrit, hemoglobin, MCV, MCH and MCHC indices were determined. In serum, profiles of glucose, total protein (TP), albumin, total cholesterol (TC), triglycerides, total bilirubin (TB), and direct bilirubin (DB), alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were determined. Hemoglobin profile, MCH and MCHC indices increased as age increased (p < 0,05) and the erythrocytes, leucocytes, hematocrit, hemoglobin profiles and MCV, MCH, MCHC indices showed the narrower interval ranges in the 15-35and 61-120-days old guinea pigs. Profiles of TP, DB and AST showed increase with age (p < 0,05) and the DB, AST, ALT, and TC profiles showed the narrower interval range at 36-120 days old. The hematological and blood metabolites profiles of guinea pigs raised in intensive system in humid tropical conditions show significant changes with production age. . Los cuyes en producción intensiva generan la necesidad de bases fisiopatológicas para diagnosticar su estado de bienestar, salud y producción; las disponibles están referidas a esta especie como animal de laboratorio o de compañía. El objetivo de esta investigación es determinar los perfiles hematológicos y metabolitos sanguíneos en relación con la etapa de producción de cuyes en sistema de crianza intensivo a 660 msnm en trópico húmedo. Cuarenta cuyes clínicamente sanos de las líneas inti x Perú nacidos en trópico de 15-120 días de edad se distribuyeron en cuatro grupos etarios: 15-21, 22-35, 36-60 y 60-120 días. En sangre se determinó los perfiles de eritrocitos, leucocitos, linfocitos, granulocitos, hematocrito y hemoglobina e índices de MCV, MCH y MCHC y en suero sanguíneo los perfiles de glucosa, proteína total (PT), albumina, colesterol total (CT), triglicéridos, ALT, AST y bilirrubina directa (BD). El perfil de hemoglobina y los índices de MCH y MCHC incrementaron con la edad (p < 0,05) y los perfiles de eritrocitos, leucocitos, hemoglobina y hematocrito y los índices de MCV, MCH, MCHC mostraron una menor amplitud de intervalos en los cuyes de 15-35 y 61-120 días de edad. Los perfiles de PT, BD y AST incrementaron con la edad (p < 0, 05) y los perfiles de BD, AST, ALT y CT mostraron la menor amplitud de intervalo entre los 36-120 días de edad. Los perfiles hematológicos y de metabolitos sanguíneos en los cuyes criados en sistema de crianza intensivo en condiciones de trópico húmedos muestran cambios significativos con la edad de producción. Los cuyes en producción intensiva generan la necesidad de bases fisiopatológicas para diagnosticar su estado de bienestar, salud y producción; las disponibles están referidas a esta especie como animal de laboratorio o de compañía. El objetivo de esta investigación es determinar los perfiles hematológicos y metabolitos sanguíneos en relación con la etapa de producción de cuyes en sistema de crianza intensivo a 660 msnm en trópico húmedo. Cuarenta cuyes clínicamente sanos de las líneas inti x Perú nacidos en trópico de 15-120 días de edad se distribuyeron en cuatro grupos etarios: 15-21, 22-35, 36-60 y 60-120 días. En sangre se determinó los perfiles de eritrocitos, leucocitos, linfocitos, granulocitos, hematocrito y hemoglobina e índices de MCV, MCH y MCHC y en suero sanguíneo los perfiles de glucosa, proteína total (PT), albumina, colesterol total (CT), triglicéridos, ALT, AST y bilirrubina directa (BD). El perfil de hemoglobina y los índices de MCH y MCHC incrementaron con la edad (p < 0,05) y los perfiles de eritrocitos, leucocitos, hemoglobina y hematocrito y los índices de MCV, MCH, MCHC mostraron una menor amplitud de intervalos en los cuyes de 15-35 y 61-120 días de edad. Los perfiles de PT, BD y AST incrementaron con la edad (p < 0, 05) y los perfiles de BD, AST, ALT y CT mostraron la menor amplitud de intervalo entre los 36-120 días de edad. Los perfiles hematológicos y de metabolitos sanguíneos en los cuyes criados en sistema de crianza intensivo en condiciones de trópico húmedos muestran cambios significativos con la edad de producción.

Over the last six decades, the extensive use of antibiotics as growth promoters in animal nutrition has contributed to antimicrobial resistance and ultimately poses a risk to public and environmental health. Therefore, there is a growing interest in alternative strategies, such as plant extracts and essential oils, to address this issue. The aim of this study was to evaluate the effect of Morinda citrifolia leaf ethanolic extract (MCEE) on the intestinal health and performance of broiler chickens. A total of 360 Cobb 500 broilers were randomly distributed into groups C1, C2, S1, S2, and S3, with six replicates of 12 chickens each. C1 was fed the base diet (BD), and C2 was fed BD + 50 ppm zinc bacitracin (ZB). S1, S2, and S3 were supplemented with MCEE in daily doses of 5.62, 11.0, and 16.3 mg/kg BW, respectively, from 1 to 21 days of age. Hematological profiles and gut histology were assessed at 7, 14, and 21 days of age, while the abundance of microbiota in the ileum was measured at 21 and 28 days of age. Performance indices, including weight gain, feed intake, and feed conversion rate, were evaluated at 7, 21, and 33 days of age. Data were analyzed using a general factorial arrangement. The abundance of Escherichia coli and Staphylococcus aureus log (CFU/g) decreased in the three supplemented groups by 21 days of age, and these levels were maintained until 28 days of age. Additionally, in the three supplemented groups, the abundance of Lactobacillus sp. decreased by 21 days of age; however, it was re-established by 28 days of age. Villus height and crypt depth increased with age in the S2 group by 21 days of age. Performance indices improved during the fattening phase overall in chickens in group S2. In conclusion, a daily dose of 11.0 mg/kg BW MCEE in the diet improved performance indices by modulating gut microbiota and histology at 21 days in broiler chickens.

The growing need for secure and privacy-preserving identity management in industrial environments has exposed the limitations of traditional, centralized authentication systems. In this context, SIBERIA was developed as a modular solution that empowers users to control their own digital identities, while ensuring robust protection of critical services. The system is designed in alignment with European standards and regulations, including EBSI, eIDAS 2.0, and the GDPR. SIBERIA integrates a Self-Sovereign Identity (SSI) framework with a decentralized blockchain-based infrastructure for the issuance and verification of Verifiable Credentials (VCs). It incorporates multi-factor authentication by combining a voice biometric module, enhanced with spoofing-aware techniques to detect synthetic or replayed audio, and a behavioral biometrics module that provides continuous authentication by monitoring user interaction patterns. The system enables secure and user-centric identity management in industrial contexts, ensuring high resistance to impersonation and credential theft while maintaining regulatory compliance. SIBERIA demonstrates that it is possible to achieve both strong security and user autonomy in digital identity systems by leveraging decentralized technologies and advanced biometric verification methods.

In industrial environments there are critical devices, so their correct operation must be ensured. In particular, having a secure record of the different events related to these devices is essential. Thus, this record can be used in future forensic investigations in case of accidents or production failures. In this sense, blockchain technology can bring reliability to the event log. In this paper, ChronoEOS 2.0, an extension of ChronoEOS, is presented. This new version can record the events that occur in multiple industrial robotic arms by deploying a Smart Contract in the EOSIO blockchain so that all events are immutably recorded in the blockchain. Furthermore, the new version allows using a unique fingerprint of the robot before registering an event in the blockchain. This fingerprint depends only on the characteristics of the operation and configuration of the robot. For this reason, ChronoEOS 2.0 not only increase the ability of ChronoEOS in terms of handling multiple devices but also increases the security and reliability of the operations. Finally, in this study, we verify that the new improvements have little impact on the hosting resources (RAM and Network are not altered, while CPU consumption is slightly higher due to the device fingerprinting module).

Parkinson’s disease (PD) is a progressive neurodegenerative disorder for which there is no successful prevention or intervention. The pathological hallmark for PD involves the self-assembly of functional Alpha-Synuclein (αS) into non-functional amyloid structures. One of the potential therapeutic interventions against PD is the effective inhibition of αS aggregation. However, the bottleneck towards achieving this goal is the identification of αS domains/sequences that are essential for aggregation. Using a protein mimetic approach, we have identified αS sequences-based targets that are essential for aggregation and will have significant therapeutic implications. An extensive array of in vitro, ex vivo, and in vivo assays is utilized to validate αS sequences and their structural characteristics that are essential for aggregation and propagation of PD phenotypes. The study aids in developing significant mechanistic and therapeutic insights into various facets of αS aggregation, which will pave the way for effective treatments for PD. Inhibiting alpha-synuclein self-assembly into amyloid structures, associated with Parkinson’s disease, is a potential therapeutic intervention. Here, the authors identify the domains/sequences that are essential for alpha-synuclein aggregation and test the activity of foldamer-based antagonists to identify potential therapeutic targets.