Browse Articles

Lung ultrasonography to assess efficacy of intranasal and parenteral vaccinations for bovine respiratory disease (BRD) in dairy calves

Vaccination is used to control bovine respiratory disease (BRD). The aim of this study was to evaluate BRD vaccine efficacy through the lung lesions area in dairy calves, also discriminating the lung health status at vaccine administration. One hundred forty-nine dairy calves were enrolled and divided according to vaccine protocol and initial lung condition: healthy (H-CTR; n = 17) and diseased (D-CTR; n = 24) control group; healthy (H-INT; n = 28) and diseased (D-INT; n = 18) intranasal group, healthy (H-VAC; n = 31) and diseased (D-VAC; n = 31) intranasal and parenteral group. Intranasal vaccination was against bovine parainfluenza-3 and respiratory syncytial viruses, while parenteral vaccination was also against Mannheimia haemolytica. Animals were assessed by clinical and ultrasonographical examinations at 10, 17, 38, 52 days; ultrasonography and lung lesion scores (US and LLS), and total consolidation area (TC_A) were greater in CTR with increasing levels over time in both H-CTR (US: 1.45 at 10d vs. 3.8–4.4 thereafter; LLS: 3.5 at 10d vs. 12.4–13.3 thereafter; TC_A: 3.9 cm 2 at 10d vs. 9.8–15.4 cm 2 thereafter) and D-CTR groups (LLS: 12.1 at 10d vs. 13.0–15.7 thereafter; TC_A: 23.4 cm 2 at 10d vs. 34.9–49.4 cm 2 thereafter). However, TC_A was maintained in H-INT and reduced in D-INT (22.3 cm 2 at 10d vs. 14.3 cm 2 at 52d). The VAC had the lowest values in US, LLS and TC_A. The H-VAC preserved the initial condition for these parameters, while D-VAC showed a reduction in US (3.8 at 10d vs. 3.0 at 52d) and TC_A (18.4 cm 2 at 10d vs. 10.9 cm 2 at 52d). In conclusion, the combination of intranasal and parenteral vaccination reduced the progression of lung TC_A severity in both initially healthy and diseased female dairy calves.

Study on the influence of steel reinforcement on the bonding performance and crack width of UHPC-NSC interface

From image to trust: Cross-national pathways to brand evangelism in hospitality sector

This study investigates how frontline employee attributes foster customer brand evangelism in ASEAN hospitality, addressing whether symbolic brand image or relational trust better explains advocacy and under what conditions these mechanisms vary across cultures. A two-wave survey design was implemented with 428 hotel guests in Vietnam and Thailand. Using PLS-SEM and multi-group analysis, the model tested digital competence, proactive assistance, and relationship-building as antecedents of brand evangelism, mediated by brand image and customer trust, and moderated by loyalty program participation and visit frequency. Results reveal dual pathways: brand image and trust both mediate employee behaviors, with symbolic cues dominating in Vietnam and relational credibility prevailing in Thailand. Loyalty programs strengthened trust-based evangelism in Thailand, while visit frequency shaped image-based evangelism differently across contexts. These mechanisms explained substantial variance in evangelism, underscoring cultural contingencies in advocacy formation. This research advances brand evangelism theory by integrating symbolic and relational mediators, identifying boundary conditions, and demonstrating cultural contrasts. It provides a novel dual-process, cross-national framework that refines relationship marketing and social identity perspectives while offering actionable guidance for culturally adaptive hospitality strategies.

Evaluating ensemble learning approaches for horizontal gene transfer detection

Abstract Horizontal gene transfer (HGT) is widely recognized as a major driver of antimicrobial resistance (AMR) dissemination, with genomic islands (GIs) as one of the drivers facilitating the spread. Detecting GIs is essential for improving AMR surveillance. Numerous computational approaches have been developed for GIs detection, including recent advances in machine learning (ML). Several studies in other fields have shown that ML model performance depends on data representations. Combining multiple data representations in ensemble learning has been shown to improve performance in other genomics tasks. However, this approach has not yet been evaluated for GIs detection. To this end, we investigate the efficacy of integrating diverse data representations in ensemble learning for GIs detection, particularly for classification task. Then, we assess its applicability to localizing GIs, which are clusters of genes acquired through HGT, in a genomic sequence. We implemented a two-stage ensemble selection strategy to determine the optimal combination of data representations. Our ensemble selection strategy reveals that combining low-correlated data representations in an ensemble classifier yields a slightly higher Recall than individual representation for the classification task, but the improvement is not statistically significant. Nevertheless, the ensemble classifier could not localize GIs better, suggesting that the cross-task generalizability remains constrained. This finding presents an opportunity for future research to advance the field by redefining the problem formulation of GIs detection.

Genetic algorithm-based coverage path planning for autonomous aircraft cabin cleaning by reconfigurable robot

Designing an optimal Coverage Path Planning (CPP) framework for autonomous aircraft cabin cleaning is a critical challenge due to the time-sensitive nature of aircraft turnaround operations. Conventional domestic cleaning robots struggle to adapt to the confined and irregular cabin layouts of commercial aircraft. To address this, the paper proposes a two-stage CPP approach utilizing the reconfigurable robot. In the first stage, the robot operates in its full-size configuration to efficiently clean open regions such as aisles and galleys, skipping hard-to-access seat rows to minimize total cleaning time. In the second stage, a Genetic Algorithm (GA)-based Traveling Salesman Problem (TSP) optimization process determines the optimal visiting sequence for the skipped areas, while simultaneously accounting for the robot’s reconfiguration energy model. This integrated framework explicitly models the trade-off between coverage efficiency, energy consumption, and reconfiguration cost, ensuring that the robot autonomously selects the most energy-optimal path under operational constraints. The experiments incorporating airline procedures and cabin geometry demonstrate that the proposed approach significantly outperforms conventional CPP strategies in both coverage time and energy usage. The results validate the feasibility of deploying reconfigurable robotic systems for real-world autonomous aircraft cabin cleaning during turnaround operations.

Dynamic cytokine profiles across the progression of Type 1 diabetes mellitus are associated with diabetic retinopathy development

Biotechnology-driven extraction and characterisation of Chitosan from the West African river prawn (Macrobrachium vollenhovenii) and American Cockroach (Periplaneta americana) using a modified approach

Chitosan is a natural biopolymer derived from the deacetylation of chitin, a structural polysaccharide abundantly found in the shells and exoskeletons of crustaceans, insects, and other arthropods. Its unique physicochemical properties have led to widespread applications in biomedical, pharmaceutical, agricultural, and industrial sectors. In Nigeria, abundant freshwater crustaceans and insects remain underutilized as sources of chitosan. This study evaluated the potential of West African river prawns ( Macrobrachium vollenhovenii ) and American cockroaches ( Periplaneta americana ) as local chitosan sources using a modified chemical extraction process. Exoskeletal materials were pretreated, demineralized, deproteinized, and subjected to autoclave assisted alkaline deacetylation (50% NaOH, 121 °C, 15 psi, 30 min). Chitin yields were 29.53% for prawns and 17.78% for cockroaches, while chitosan yields were 28.13% and 11.56%, respectively. Fourier Transform Infrared Spectroscopy confirmed characteristic functional groups of chitosan in both sources. The degree of deacetylation (DD) was 68.79% for prawn-derived chitosan and 81.21% for cockroach-derived chitosan, indicating effective conversion of N-acetyl. D-glucosamine to D-glucosamine units. These findings demonstrate that both species are viable alternative sources for chitosan production, with pressurized deacetylation enhancing yield and polymer quality. This approach provides a scalable, reproducible strategy for sustainable chitosan extraction in Nigeria, supporting potential applications in biotechnology, medicine, and industry.

Time domain electromagnetic survey in deep mine galleries for mineral exploration

Retraction: Evolutionary game analysis of low-carbon technology innovation diffusion under PPP mode in China

Acute effects of moderate intensity exercise on uric acid excretion in underexcretion hyperuricemia

Emotion beyond boundaries: How multimodal cues foster cross-cultural affective contagion in immersive livestreaming

Digital and intelligent media technologies are fundamentally reshaping the landscape of international communication. This study examines the multimodal emotional communication mechanisms and efficacy of immersive live streaming through a case analysis of American influencer IShowSpeed’s “China tour” broadcasts on Bilibili. Using network analysis to map user interactions, sentiment analysis to measure emotional responses, and epidemiological modeling to track emotion spread, this study investigates how emotions operate and spread in cross-cultural digital environments. Our findings reveal three interconnected mechanisms: (1) algorithm-driven decentralized network structures that facilitate rapid information diffusion, (2) multimodal sensory cues triggering high-arousal positive emotions, and (3) emotion-similarity-based multilevel contagion pathways enabling cascading effects. These mechanisms collectively constitute a nonlinear, affect-first communication paradigm that effectively orchestrates immersive experiences and emotional resonance across cultural boundaries, generating positive cascading effects among diverse audiences. This research contributes to the theorization of digital international communication by proposing an exploratory “algorithm-infrastructure, emotion-pathway, identification-outcome” framework derived from a single-case mechanism analysis, and by offering empirical insight into how cross-cultural engagement is shaped through the interaction of affective communication and platform dynamics.

Body-centered encoding of passive tactile pattern memories

Abstract The human brain stores and retrieves tactile experiences, allowing object recognition by touch, the definition of haptic preferences, and the retrieval of past bodily experiences. However, little is known about the spatial code of tactile body memories, particularly whether encoding takes place in a body-centered (tactile) reference frame, not influenced by hand posture or visual cues, or whether it takes place in an external reference frame, where tactile information is integrated with proprioceptive and visual information. Here, we combined a passive tactile pattern memory task with the crossed-hands paradigm to investigate if tactile pattern retrieval accuracy is influenced by in-/congruent hand position during learning and retrieval (experiment 1) and/or the spatial context surrounding the hand (experiment 2). We hypothesized that significant effects of hand position and/or visual context on retrieval accuracy evidence external encoding, whereas the absence of such effects are more consistent with body-centered encoding. Our data is in accordance with the latter hypothesis, and do not support external encoding. The results can be considered plausible in light of clinical evidence where bodily sensations related to past memories are often confined to specific body locations rather than remapped to external space.

Political uncertainty and multi-scale systemic risk spillovers in the cryptocurrency market: A STVAR-based network topology approach

This study employs a smooth transition vector autoregressive model combined with a network topology approach to capture the nonlinear impact of political uncertainty on multi-scale systemic risk spillovers in cryptocurrency market. To reveal the risk characteristics at different time scales, we use wavelet packet decomposition to decompose the sequence into short-term, medium-term, and long-term components; We also use forecast error variance decomposition to quantify risk spillovers, in order to study the direction and intensity of risk spillovers between different cryptocurrencies. In terms of the responses of cryptocurrency systemic risks to political uncertainty shocks, we find significant asymmetries. The mid- and long-term risk components indicate that most cryptocurrencies exhibit a stronger response during periods of high political uncertainty than during low periods. Moreover, shocks during high political uncertainty periods enlarge the cross-cryptocurrency risk spillovers. Finally, Bitcoin, Ethereum and Monero are stable risk transmitters, while Peercoin and Namecoin are more vulnerable risk receivers. This paper provides some insights into the differential impact of political uncertainty on the stability and interconnectivity of various cryptocurrencies.

Prevalence and Risk Factors for Cytomegalovirus Retinitis Among People Living with HIV in Sub-Saharan Africa in the Antiretroviral Therapy Era: A Systematic Review and Meta-Analysis

Editorial Note: Comparing public support for nuclear and wind energy in Washington State

Integrating morphological and molecular characterization to reveal genetic diversity and breeding potential in Turkish local alfalfa (Medicago sativa L.) populations

Abstract Alfalfa (Medicago sativa L.) is one of the most important forage crops due to its high crude protein content, nitrogen fixation ability, and adaptability to diverse ecological conditions. This study aimed to evaluate the morphological, phenological, yield, quality, and molecular diversity of 60 local alfalfa populations, together with 4 control varieties (64 genotypes in total), collected as clones from the Lakes Region of Türkiye (Isparta, Burdur, Afyonkarahisar, and Konya) between 2011 and 2013. Twenty-seven agronomic, morphological, and quality traits were analyzed, revealing substantial phenotypic variation among genotypes in terms of growth habit, regrowth rate, dormancy level, forage yield, and quality. Heatmap, PCA-biplot, and correlation analyses identified five major morphological groups with distinct yield–quality relationships. Molecular clustering and PCoA analyses supported these groupings and revealed strong genetic differentiation shaped by eco-geographic isolation and local adaptation. The combined evaluation of morphological and molecular data demonstrated that several genotypes possess both high agronomic performance and distinct genetic structure. In particular, genotypes LC3, LC17, LC24, LC29, LC39, LC49, LC53, LC54, LC57, and LC60 were identified as the most promising candidates for synthetic variety development due to their superior yield, quality traits, and representation of different genetic clusters. Overall, the findings highlight the significant breeding potential of local alfalfa germplasm and provide a reliable framework for developing high-yielding and high-quality varieties adapted to regional conditions.

Correction: Translation, cross-cultural adaptation, validity and reliability of the inaugural Albanian Roland-Morris Disability Questionnaire in Albanian population with low back pain

Trajectories of antidepressant dispensing among privately insured transgender people in the United States

Abstract Psychiatric medication utilization studies rarely identify transgender and gender diverse (TGD) people, masking TGD health inequities. This study assessed antidepressant prescription fill patterns and their predictors among a privately insured TGD sample with newly dispensed anti-depressants after a recent depression or anxiety diagnosis from Merative MarketScan commercial insurance claims from 2007 to 2021. We measured trajectories of antidepressants utilization over 6-months using group-based trajectory modeling (GBTM), then identified demographic and clinical predictors of medication utilization group membership. Among 2499 TGD people with depression or anxiety, we found three anti-depressant dispensing trajectory groups (short-term [21.1%], decreasing [32.3%], and long-term [46.6%]). TGD people with previous chronic co-morbidities or emergency department visits had an increased probability of shorter-term antidepressant dispensing compared to long-term dispensing. TGD people under the age of 25 and those with previous psychotherapy treatment were less likely to have shorter-term anti-depressant dispensing than those with older ages (25–64) and those without prior psychotherapy. This study provides real-world evidence of distinct anti-depressant dispensing patterns and predictive factors associated with shorter-term dispensing among TGD people. Policymakers, providers, and advocacy groups can utilize findings to inform tailored strategies to improve sustained antidepressant use among TGD people living with mental health conditions.

Temporal and spatial patterns and determinants of traditional villages in Henan Province

Traditional villages are important carriers of China’s cultural heritage and reflect long-term interactions among history, environment, and human settlement. This study examines 1,035 officially recognized traditional villages in Henan Province to identify their spatiotemporal distribution patterns and associated factors. Using ArcGIS-based spatial analysis, GeoDetector, the spatial lag model, and historical literature review, we find that traditional villages show significant spatial clustering and clear regional inequality. High-density clusters occur in northern Henan (Anyang–Hebi), central Henan (Pingdingshan), and southern Henan (Xinyang), whereas eastern Henan remains sparsely distributed, partly due to the long-term impacts of Yellow River flooding. The evolution of village distribution can be divided into four major historical stages, and the dominant spatial orientation shifted from a southwest–northeast trend before the Ming period to a southwest–northeast trend thereafter. Descriptively, village concentration is associated with moderate elevation, proximity to water, lower GDP levels, and intermediate distance from county-level central cities. However, after spatial autocorrelation was controlled for, these variables were not statistically significant as independent predictors in the spatial lag model, suggesting that village distribution is shaped more by combined effects and spatial spillover than by single factors alone. These findings provide evidence for cluster-based heritage protection in Henan and offer broader lessons for historically layered inland regions facing rural transformation and urbanization pressures.

Solar-driven S-scheme magnetic CoFe2O4/CdO@bentonite heterostructure for concurrent Cr(VI) reduction and cefixime degradation: mechanistic insights, kinetics, and real wastewater validation

Abstract A novel solar-responsive magnetic CoFe 2 O 4 /CdO@bentonite (CF-CdO@B) heterostructure was rationally engineered. The incorporation of bentonite as a support matrix enabled improved dispersion, enhanced interfacial contact, and increased adsorption capacity, while the integration of CoFe 2 O 4 and CdO facilitated efficient charge separation. Comprehensive structural, optical, and electrochemical characterizations confirmed the successful formation of a tightly coupled heterointerface. Under sunlight irradiation, the optimized photocatalyst achieved rapid and complete removal of Cr(VI) and cefixime within 25 and 60 min, respectively. Kinetic analysis revealed pseudo-first-order behavior with significantly enhanced rate constants (0.6447 min -1 for Cr(VI) and 0.2686 min -1 for cefixime), outperforming the individual components by an order of magnitude. Mechanistic investigations demonstrated that the superior photocatalytic activity originates from an S-scheme charge transfer pathway. The catalyst exhibited excellent magnetic recoverability, structural stability, and reusability over multiple cycles. Importantly, its practical applicability was validated in complex real water matrices, achieving high cefixime removal efficiencies (94% in tap water, 91% in river water, and 85% in hospital wastewater) and complete Cr(VI) reduction even in industrial effluents. This study provides a robust and sustainable strategy for dual-function photocatalysis, offering new insights into S-scheme heterojunction design and highlighting the potential of CF-CdO@B as an efficient candidate for real-world wastewater remediation.