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Dynamics and triggers of misinformation on vaccines
The Covid-19 pandemic has sparked renewed attention to the risks of online misinformation, emphasizing its impact on individuals’ quality of life through the spread of health-related myths and misconceptions. In this study, we analyze 6 years (2016–2021) of Italian vaccine debate across diverse social media platforms (Facebook, Instagram, Twitter, YouTube), encompassing all major news sources–both questionable and reliable. We first use the symbolic transfer entropy analysis of news production time-series to dynamically determine which category of sources, questionable or reliable, causally drives the agenda on vaccines. Then, leveraging deep learning models capable to accurately classify vaccine-related content based on the conveyed stance and discussed topic, respectively, we evaluate the focus on various topics by news sources promoting opposing views and compare the resulting user engagement. Our study uncovers misinformation not as a parasite of the news ecosystem that merely opposes the perspectives offered by mainstream media, but as an autonomous force capable of even overwhelming the production of vaccine-related content from the latter. While the pervasiveness of misinformation is evident in the significantly higher engagement of questionable sources compared to reliable ones (up to 11 times higher in median value), our findings underscore the need for consistent and thorough pro-vax coverage to counter this imbalance. This is especially important for sensitive topics, where the risk of misinformation spreading and potentially exacerbating negative attitudes toward vaccines is higher. While reliable sources have successfully promoted vaccine efficacy, reducing anti-vax impact, gaps in pro-vax coverage on vaccine safety led to the highest engagement with anti-vax content.
Vestibular stimulation and space-time interaction affect the perception of time during whole-body rotations
Among the factors, such as emotions, that distort time perception, vestibular stimulation causes a contraction in subjective time. Unlike emotions, the intensity of vestibular stimulation can be easily and precisely modified, making it possible to study the quantitative relationship between stimulation and its effect on time perception. We hypothesized that the contraction of subjective time would increase with the vestibular stimulation magnitude. In the first experiment, participants sat on a rotatory chair and reproduced time intervals between the start and the end of whole-body passive rotations (40° or 80°; dynamic condition) or between two consecutive low-amplitude shakes (static condition). We also assessed reaction time under the same conditions to evaluate the attentional effect of the stimuli. As expected, duration reproduction in the 40° rotation was shorter than that observed in the static condition, but this effect was partly reversed for 80° rotations. In other words, vestibular stimulation shortens the perceived time interval, but this effect weakens with stronger stimulation. Attentional changes do not explain this unexpected result, as reaction time did not change between conditions. We hypothesized that the space-time interaction (i.e., spatially larger stimuli are perceived as lasting longer) could explain these findings. To assess this, in a second experiment participants were subjected to the same protocol but with three rotation amplitudes (30°, 60°, and 120°). The duration reproductions were systematically shorter for the lower amplitudes than for the higher amplitudes; so much so that for the highest amplitude (120°), the duration reproduction increased so that it did not differ from the static condition. Overall, the experiments show that whole-body rotation can contract subjective time, probably at the rather low level of the interval timing network, or dilate it, probably at a higher level via the space-time interaction.
Energy-exergy and environ-economic (4E) analysis of heat storage-based single-slope solar stills integrated with solar air heater
The energy-exergy and environ-economic (4E) analysis was conducted on a solar still with and without a hybrid thermal energy storage system (TESS) and a solar air heater. The proposed solar still was modified by integrating a rectangular aluminium box filled with paraffin wax and black gravel as the TESS and coupled with a solar air heater. Paraffin wax was selected due to its widespread availability and proven effectiveness in accelerating desalination, improving process uniformity, and maintaining optimal temperature levels. Throughout the experiments, meticulous data on mass loss, air velocity, and temperature were recorded for both conditions. The daily energy efficiency varies from 40.80% to 31.72%, showing a reduction rate with increased water depth. Estimates were made on the average exergy efficiency, losses, outflow, and inflow for the solar still. These were done for both setups. The analysis revealed that CO2 mitigation and credit were more favorable with the TESS. Furthermore, the Energy Payback Time (EPBT) for the hybrid heat storage-based single-slope solar still coupled with a solar air heater is 1.87 years. On the other hand, EPBT values for the hybrid heat storage single-slope solar still and the conventional single-slope solar still were 1.65 years and 0.95 years, respectively. Integrating a thermal energy storage system and solar air heater significantly improved the performance and sustainability of the solar still for desalination, making it a more efficient and environmentally friendly option for freshwater production.
Sharing images of children on social media: British motherhood influencers and the privacy paradox
This study examines the extent to which popular British motherhood influencers infringe on their children’s privacy by posting images of them online. We conducted a content analysis of 5,253 Instagram posts from ten UK-based influencers, supplemented by self-reported data from these influencers. This represents the first comprehensive analysis of actual sharing practices in the British motherhood influencer industry, linking observed behavior with self-reported perceptions. Children appeared in over 75% of the posts (3,917), though the proportion of posts containing embarrassing, intimate, or revealing content was relatively low (11.5%). Notably, sponsorships and product advertisements were present in 46.4% of posts featuring children, indicating that children’s images are frequently used for financial gain. Despite this, post popularity did not vary based on the inclusion of children, as posts featuring children did not receive more likes than those without. Influencers reported strong trust in online safety on Instagram, and reported indifference or willingness to sharenting suggesting that sharing images of their children may be a deliberate strategy rather than an accidental act. Half of the influencers did not accurately estimate their past sharenting behavior. This study extends the existing body of knowledge on sharenting behaviour and the privacy paradox by establishing a foundation of parents’ real-world posting habits and connecting them to their beliefs about publicly sharing their children’s images in the UK context. The findings do not strongly support the privacy paradox in this sample.
Combining Distibene, Diazoolefins, and Visible Light: Synthesis and Reactivity of Inorganic Rings
Integrating life cycle assessment into supply chain optimization
Integrating Supply Chain Optimization (SCO) with Life Cycle Assessment (LCA) is essential for creating supply chains that are both economically efficient and environmentally sustainable. While SCO focuses on optimizing network structures and decisions related to product and service delivery, LCA systematically assesses the environmental impacts across the entire supply chain. The existing literature treats SCO and LCA as separate, sequential steps, often leading to inconsistencies in scope and challenges in data transfer and rescaling. Our research presents a novel Supply Chain Life Cycle Optimization (SCLCO) model that integrates SCO and LCA. Our SCLCO model is based on LCA data structures, incorporates multi-time period, closed-loop SCO decisions (e.g. reverse chain management, inventory control, network design), and is capable of considering the three pillars of sustainability: environmental, economic, and social. It includes harmonizing principles, terminology, and notation, thereby bridging the gap between the SCO and LCA communities through a generalized formulation. Computational experiments on a selected SCO model from Operations Research literature validate the SCLCO and demonstrate its effectiveness in providing valuable insights to both SCO and LCA practitioners and researchers. The results emphasize that the simultaneous execution of SCO and LCA in SCLCO minimizes the risk of overlooking decision impacts and facilitates data transfer from existing LCA databases.
Short-term impact of low air pressure on plants’ functional traits
Lower atmospheric pressure affects biologically relevant physical parameters such as gas partial pressure and concentration, leading to increased water vapor diffusivity and greater soil water content loss through evapotranspiration. This might impact plant photosynthetic activity, resource allocation, water relations, and growth. However, the direct impact of low air pressure on plant physiology is largely unknown. This study examined the effects of low air pressure, alone and combined with two water inputs, on different functional traits of three plant species transplanted from montane grasslands at 1,500 m a.s.l. during the first four weeks of their early phenological stage: Trifolium pratense, Hieracium pilosella, and Brachypodium rupestre. Using the terraXcube Ecotron facility which can simulate different climatic conditions, we isolated the effect of air pressure from those of other, related environmental factors (temperature, humidity, and solar radiation) by simulating three different elevations with corresponding air pressures: 1,500 m a.s.l. (85 kPa, control scenario), 2,500 m a.s.l. (75 kPa), and 4,000 m a.s.l. (62 kPa) and we used two different water regimes to observe the combined effect of low air pressure and the impact of varying water inputs on plants. In T. pratense and H. pilosella, we observed an increase in stomatal conductance but a reduction in aboveground biomass at the lowest pressure compared to the control scenario after four weeks of incubation. Contrastingly, B. rupestre showed an interactive effect of air pressure and water treatment on chlorophyll and biomass nitrogen content, which were reduced under higher soil water conditions at 85kPa. This study serves as an initial step in isolating the specific impact of air pressure on plant physiology, demonstrating the potential of the facility for future research. The mixed response patterns across species highlight that atmospheric pressure could be a driving factor to consider when assessing plant responses along elevational gradient.
Kynurenines and aerobic exercise capacity in chronic kidney disease: A cross-sectional and longitudinal study
Background The causes of reduced aerobic exercise capacity (ExCap) in chronic kidney disease (CKD) are multifactorial, possibly involving the accumulation of tryptophan (TRP) metabolites such as kynurenine (KYN) and kynurenic acid (KYNA), known as kynurenines. Their relationship to ExCap has yet to be studied in CKD. We hypothesised that aerobic ExCap would be negatively associated with plasma levels of TRP, KYN and KYNA in CKD. Methods We included 102 patients with non-dialysis CKD stages 2–5 (CKD 2–3, n = 54; CKD 4–5, n = 48) and 54 healthy controls, age- and sex-matched with the CKD 2–3 group. ExCap was assessed as peak workload during a maximal cycle ergometer test. Plasma KYN, KYNA and TRP were determined by high-performance liquid chromatography. Kidney function was evaluated by glomerular filtration rate (GFR) and estimated GFR. The CKD 2–3 group and healthy controls repeated tests after five years. The association between TRP, KYN, KYNA and ExCap in CKD was assessed using a generalised linear model. Results At baseline, there were significant differences between all groups in aerobic ExCap, KYN, KYNA, TRP and KYN/TRP. KYNA increased in CKD 2–3 during the follow-up period. In CKD 2–5, KYNA, KYN/TRP and KYNA/KYN were all significantly negatively associated with ExCap at baseline, whereas KYN and TRP were not. Kynurenines were significantly correlated with GFR (p < 0.001 for all). Including GFR in the statistical model, no kynurenines were independently associated with ExCap at baseline. At follow-up, the increase in KYN and KYN/TRP was related to a decrease in ExCap in CKD 2–3. After adjusting for GFR, increase in KYN/TRP remained an independent significant predictor of a decline in ExCap in CKD 2–3. Conclusion Aerobic ExCap was inversely associated with plasma levels of kynurenines in CKD at baseline and follow-up.
Modeling of chemo-radiotherapy targeting growing vascular tumors: A continuum-level approach
The aim of this study is to demonstrate the enhanced efficiency of combined therapeutic strategies for the treatment of growing tumors, based on computational experiments of a continuous-level modeling framework. In particular, the tumor growth is simulated within a host tissue and treated as a multiphase fluid, with each cellular species considered as a distinct fluid phase. Our model integrates the impact of chemical species on tumor dynamics, and we model –through reaction-diffusion equations– the spatio-temporal evolution of oxygen, vascular endothelial growth factor (VEGF) and chemotherapeutic agents. Simulations of a growing tumor exposed to external radiation showcase the rapid impact of radiotherapy on tumor suppression, however this effect diminishes over time. To enhance the therapeutic efficiency of radiotherapy, we investigate the combination of external radiation with the anti-VEGF drug bevacizumab and the cytotoxic drug docetaxel. Our simulations demonstrate that this synergistic approach integrates the immediate effectiveness of radiation therapy with the enduring tumor-suppressive capabilities of chemotherapy.
The Midas Touch by Iridium: A Second Near-Infrared Aggregation-Induced Emission-Active Metallo-Agent for Exceptional Phototheranostics of Breast Cancer
Effects of different tennis racket string tension on forehand stroke effect and racket dynamic impact
This study investigates the effect of varying tennis racket string tension on stroke effect and the dynamic response of the racket. Using the YSV dynamic acceleration signal acquisition system and a portable radar speed gun collect data on racket acceleration, stress-strain signals, and ball speed from 15 male athletes. Stroke accuracy and depth were assessed according to the International Tennis Number. The recorded stroke speeds were 108.87±13.57 km/h, 111.83±16.34 km/h, and 107.76±12.53 km/h for the low, medium, and high tension, respectively. A significantly higher ball speed was observed at 54lbs compared to both 48lbs and 60lbs (P <0.05). Control scores were 4.90±0.61,5.46±0.84, and 4.64±0.69 for the respective tensions. The control at 54lbs was significantly higher than at 60lbs (P<0.05). Deformation measurements were 18.53±4.90με, 16.31±4.42με, and 20.90±3.53με, with significantly lower deformation at 54lbs compared to 60lbs (P<0.05). The impact forces recorded were 381.81±48.51m/s2, 380.53±50.47m/s2, and 380.04±53.70m/s2, with no significant effect of string tension on impact force. Racket vibration frequencies were 44.14±0.48Hz, 44.08±0.35Hz, and 44.14±0.25Hz, with no significant difference among three string tensions. Rackets with three string tensions showed significantly higher vibration frequencies during the collision phase compared to before or after (P<0.01). In conclusion, string tension affect the stroke effect, racket strung at medium tension can optimize stroke effect while got milder dynamic impact, suggesting that racket strung at medium tension is recommended for tennis enthusiasts to enhance stroke performance and to decrease the risk of resonance damage in the forearm soft tissues.
Dirhodium–Palladium Dual-Catalyzed [1 + 1 + 3] Annulation to Heterocycles Using Primary Amines or H<sub>2</sub>O as the Heteroatom Sources
Retraction: Recombinant Pvs48/45 Antigen Expressed in E. coli Generates Antibodies that Block Malaria Transmission in Anopheles albimanus Mosquitoes
Helical Assemblies of Colloidal Nanocrystals with Long-Range Order and Their Fusion into Continuous Structures
A framework for assessing reliability of observer annotations of aerial wildlife imagery, with insights for deep learning applications
There is growing interest in using deep learning models to automate wildlife detection in aerial imaging surveys to increase efficiency, but human-generated annotations remain necessary for model training. However, even skilled observers may diverge in interpreting aerial imagery of complex environments, which may result in downstream instability of models. In this study, we present a framework for assessing annotation reliability by calculating agreement metrics for individual observers against an aggregated set of annotations generated by clustering multiple observers’ observations and selecting the mode classification. We also examined how image attributes like spatial resolution and texture influence observer agreement. To demonstrate the framework, we analyzed expert and volunteer annotations of twelve drone images of migratory waterfowl in New Mexico. Neither group reliably identified duck species: experts showed low agreement (43–56%) for several common species, and volunteers opted out of the task. When simplified into broad morphological categories, there was high agreement for cranes (99% among experts, 95% among volunteers) and ducks (93% among experts, 92% among volunteers), though agreement among volunteers was notably lower for classifying geese (75%) than among experts (94%). The aggregated annotation sets from the two groups were similar: the volunteer count of birds across all images was 91% of the expert count, with no statistically significant difference per image (t = 1.27, df = 338, p = 0.20). Bird locations matched 81% between groups and classifications matched 99.4%. Tiling images to reduce search area and maintaining a constant scale to keep size differences between classes consistent may increase observer agreement. Although our sample was limited, these findings indicate potential taxonomic limitations to aerial wildlife surveys and show that, in aggregate, volunteers can produce data comparable to experts’. This framework may assist other wildlife practitioners in evaluating the reliability of their input data for deep learning models.
Spontaneous Catalytic Reaction of a Surfactant in the Interfacial Microenvironment of Colloidal Gold Nanoparticles
Comparison of greenhouse gas emissions associated with the construction of timber, concrete, and steel check dams in Akita, Japan: An input-output analysis
To mitigate global warming, replacing concrete and steel with timber as the primary construction material for construction projects, such as check dams, is being promoted in Japan and other countries. Timber check dams have more limited installation sites than concrete or steel dams because of installation conditions such as locations less susceptible to debris flows and locations where there is constant running water. However, even when the installation conditions are met, engineers and contractors are reluctant to select timber as a construction material because of its high construction cost. In this study, an input-output table was used to compare the greenhouse gas (GHG) emissions associated with the construction of a timber check dam at the design stage with those associated with the construction of concrete and steel check dams to quantitatively evaluate the added value of timber utilization (in addition to its construction cost). The results revealed that replacing concrete and steel check dams with timber check dams could reduce GHG emissions by 61% and 34%, respectively. This study demonstrated the possibility of evaluating the GHG emissions associated with a construction project at the design stage. Moreover, it highlights the importance of considering the GHG emissions associated with construction materials when selecting the most appropriate materials for public works projects.
Triphenylphosphine Oxide-Derived Anolyte for Application in Nonaqueous Redox Flow Battery
A novel broad-spectrum bacteriophage cocktail against methicillin-resistant Staphylococcus aureus: Isolation, characterization, and therapeutic potential in a mastitis mouse model
Bovine mastitis is a considerable challenge within the dairy industry, causing significant financial losses and threatening public health. The increased occurrence of methicillin-resistant Staphylococcus aureus (MRSA) has provoked difficulties in managing bovine mastitis. Bacteriophage therapy presents a novel treatment strategy to combat MRSA infections, emerging as a possible substitute for antibiotics. This study evaluated the therapeutic potency of a novel bacteriophage cocktail against MRSA mastitis. Two new bacteriophages (vB_SauR_SW21 and vB_SauR_SW25) with potent lytic activity against MRSA were isolated and characterized. The one-step growth curve displayed a rapid latent period (20–35 min) and substantial burst size (418 and 316 PFU/ cell). In silico analyses have confirmed the absence of antimicrobial resistance or virulence factor-encoding genes within their genomes. According to the results, combining these phages augmented their host range and virulence. The phage cocktail significantly reduced bacterial burden in a BALB/c mastitis model, demonstrating efficacy comparable to antibiotic treatment. Moreover, its administration led to decreased concentrations of IL-1β and TNF-α compared to the negative control group. The bacteriophage cocktail (SW21-SW25) exhibits a promising profile for therapeutic applications and may represent a novel substitute to antibiotics for managing MRSA bovine mastitis.