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Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics
Crash injury severity for ride-hailing drivers: a questionnaire study in China
Rule-based design verification for mechanical parts with dynamic rule subset selection
An interview study exploring healthcare professionals’ experiences of supporting health behaviors in migrant women after childbirth with special emphasis on mHealth
Abstract Migrant health, including reproductive health, is a public health priority. The time after childbirth is considered an important period for health behavior change and mobile health (mHealth) interventions have shown promise in influencing health behaviors. Healthcare professionals have an important role in providing support for health behaviors and implementing mHealth tools in clinical care. This study therefore examined healthcare professionals’ experiences of health behavior promotion in migrant women and the potential for an mHealth intervention to improve health behaviors after childbirth. Twenty healthcare professionals in Sweden participated in individual semi-structured interviews. The informants had different professional backgrounds, ages, working experiences and all were females. Data was analyzed using thematic analysis and three main themes were generated. The first theme “Priorities and routines of health behavior promotion after childbirth” described a lack of priority for health behavior promotion after childbirth. The second theme “Social influences of health behaviors” described several factors that influenced possibilities for healthy behaviors after childbirth. In the third theme “mHealth in supporting health behaviors after childbirth”, informants stressed that a culturally appropriate smartphone app with reliable information had the potential to promote health behaviors after childbirth although further research is needed.
Effects of resilience training for mothers on maternal resilience and children’s pain in pediatric burn units in a randomized controlled trial
Abstract Mothers of children with burn injuries often experience psychological distress, affecting their well-being and children’s pain. This study evaluates the impact of resilience training on maternal resilience and child pain. This randomized clinical trial was conducted at Amir Al-Momenin Burn Hospital, Shiraz, Iran, with 50 mothers in 2021–2022. Participants were assigned to an intervention group (six-day resilience training) or a control group (standard care). Outcomes were measured at multiple time points using the Connor-Davidson Resilience Scale and the Visual Analog Scale. Data were analyzed using SPSS v.22. The analysis revealed significant time effects on child pain intensity (B = − 0.84, p < 0.001) and maternal resilience (B = 3.99, p < 0.001). Significant group effects revealed greater improvements in the intervention group for child pain intensity (B = 2.85, p < 0.001) and maternal resilience (B = − 3.05, p < 0.001). The intervention group showed significant improvement in maternal resilience over time compared to the control group (B= − 2.06, p = 0.001), with no significant difference in child pain intensity over time compared to the control group (B = − 0.05, p = 0.69). Resilience training enhances maternal resilience and children’s pain over time. However, its impact on child pain intensity is limited compared to standard care. Therefore, integrating resilience training for mothers into pediatric burn care is recommended.
Mapping the groundwater potential zones in mountainous areas of Southern China using GIS, AHP, and fuzzy AHP
Minimization of total costs for distribution systems with battery energy storage systems and renewable energy sources
Early acquisition of complex syntax in Mandarin-speaking infants
Abstract Although Mandarin is an S(ubject)V(erb)O(bject) language, other non-canonical sentences with the object marker ba are also possible, yet their comprehension in child Mandarin is underexplored. This study uses eye-tracking and the intermodal preferential looking paradigm, as well as the use of pseudo-verbs, to explore how 24 Mandarin infants (mean age: 17.5 months) and 48 adults process these structures. The results of our experiments show that both infants and adults looked longer at the target scenes for the three grammatical sentence types tested: SVO, SbaOV and O, SbaOV. While comprehension of SVO and SbaOV could be achieved with an agent-first parsing strategy, the fact that patient-first O, SbaOV constructions were also parsed by infants suggests access to grammatical, language-specific knowledge.
Metagenomic analysis of mosquitoes from Kangerlussuaq, Greenland reveals a unique virome
Abstract Climate change is dramatically affecting vector ecology in extreme environments such as the Arctic. However, little is known about the current status of viruses of arthropod vectors located in such northerly locations. As part of a field survey on the role of wildlife in international movement of zoonotic pathogens, we sampled mammalophilic mosquitoes near the settlement of Kangerlussuaq, Greenland in July 2022 and July 2023 to investigate their virome. The majority of mosquitoes were identified as either Aedes impiger or Aedes nigripes. Metagenomic analysis of RNA extracted from species pools detected a number of novel RNA viruses belonging to a range of different virus families, including Flaviviridae, Orthomyxoviridae, Bunyavirales, Totiviridae and Rhabdoviridae. However, the sequence identities when compared to previously published, were as low as 34% at the amino acid level. Furthermore, a comparison of virome diversity between Aedes species emphasises the uniqueness of both Aedes impiger and Aedes nigripes from this secluded ecosystem. It also highlights the need to better understand the viromes of potential pathogen vectors as the impacts of climate change are experienced in such northerly ecosystems.
Microglial depletion prevents visual deficits and retinal ganglion cell loss induced by early life stress in adult animals
Electrochemically induced Meerwein arylation as a green strategy for the synthesis of arylbenzoquinone derivatives under batch and flow conditions
A comparative analysis of nanocoated expanded polystyrene for sustainable infrastructure applications
Abstract Engineers increasingly face challenges due to the demand for sustainable infrastructure; thus, this research evaluates different road embankment techniques based on sustainability. It compares the environmental impacts and economic feasibility of three road embankment techniques: using traditional soil backfilling, using expanded polystyrene (EPS) geofoam blocks with geomembrane protection, and using EPS blocks coated with a newly developed nanocoating material. Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) methods are employed to measure the potential environmental loads and economic viability of a real-world twin-bay tunnel project. LCA has been performed with SimaPro software and using ReCiPe endpoint method. The findings indicate that EPS coated with nanocoating material has the lowest environmental impact and cost, with LCA single score of 1.06 MPt and cost reductions of about 14.5% and 27.48% compared to EPS with geomembrane and soil backfilling, respectively. Traditional soil backfilling has the highest environmental impact with a single score of 2.52 MPt. In comparison, EPS with geomembrane has a single score of 2.477 MPt offering a 15.17% cost reduction compared to soil backfilling. Sensitivity analysis concludes that the required amount of reinforced concrete for the tunnel significantly impacts the results. The outcomes support sustainable decision-making for infrastructure solutions.
1D hydrogen engine modeling to investigate air-fuel ratio, spark timing, and water injection effects on performance and emissions
Abstract This study presents a comprehensive 1D modeling and simulation of a hydrogen-fueled internal combustion engine, focusing on the impacts of air-fuel ratio, spark timing, and water injection on performance and emissions. Using a single-cylinder BMW F650 GS engine as a baseline, simulations were conducted in Ricardo WAVE to evaluate engine behavior under varying conditions. Results demonstrate that hydrogen fueling reduces CO emissions to negligible levels but increases NO x emissions under specific conditions due to elevated combustion temperatures. Water injection effectively mitigates NO x formation and enhances volumetric efficiency while slightly compromising power output at high hydrogen-to-water ratios. The findings highlight hydrogen’s potential as a sustainable fuel for internal combustion engines and underline the importance of optimizing operating parameters to balance performance, efficiency, and emissions. This research contributes valuable insights into the development of cleaner, hydrogen-powered transportation solutions.
Mulching and irrigation strategies for climate resilient apple cultivation in high-density orchards
Calculation method of impingement depth and multiple objective optimizations of nozzle layout for aviation gears considering windage
Abstract As the rotating speed of aviation gears becomes higher and higher, the influence of windage resistance on jet streamline must be considered in lubrication system design. To provide theoretical guidance for nozzle layout, an analytical model to calculate the windage impingement depth of gears is proposed. To obtain the best oil jet lubrication effect, the multi-objective optimization design method of oil jet streamline layout parameters with the largest impingement depth and the smallest impingement depth difference between two gears was proposed. CFD simulation analysis of flow field around gears are conducted to study the influence of jet nozzle layout parameters on the oil distribution and oil pressure. The results show that: the modulus and transmission ratio mainly affect the value range of oil jet streamline offset, and the correlation is positive. With the increase of inclination angle and initial offset, the impingement depth of the two gears is negatively correlated. The optimized oil jet streamline layout parameters of the case in the article are S = 0.53 mm, β = 4.6°, and the impingement depth difference between the two wheels of the gear pair after optimization is reduced by more than 50.3%. Calculation results are consistent with CFD, which validates the effectiveness and accuracy of the model. This research provides a design theory and method for the selection of oil lubrication parameters for aviation high-speed and heavy-load aviation gears.
Winding vibration caused by Lorentz force in shunt reactor and its control strategy
Construction and validation of a pain facial expressions dataset for critically ill children
Effects of overweight on serum 25-hydroxyvitamin D macro and microelements and hematological parameters in healthy adult client-owned cats
Feature fusion-enhanced t-SNE image atlas for geophysical features discovery
Abstract The discovery and identification of geophysical features from diverse gridded datasets play a pivotal role in understanding geological phenomena. Traditional tools tailored to identify specific signatures, such as lineaments in magnetic data, do not account for (1) the naturally occurring complexity of the causative geology which results from competing and overprinting processes and (2) often overlook important related patterns present in other forms of data (e.g., gradients in the associated gravity data). To address those limitations, we propose a two-step data-driven approach that integrates diverse gridded datasets and autonomously reveals inherent patterns without predefined assumptions in terms of feature geometry. Utilizing Haralick texture descriptors, we encode data patches from different geophysical datasets as points in a high-dimensional unified representation space, facilitating seamless data fusion. This representation is then nonlinearly projected into a two-dimensional space using t-distributed stochastic neighbor embedding (t-SNE), forming an interactive “t-SNE Atlas”. This atlas positions tiles from each dataset according to their position in the t-SNE while linking them back to their original geographical coordinates. Such a setup allows earth scientists to intuitively navigate through the data, exploring complex relationships between geophysical responses and geological structures, thus facilitating the discovery of new insights, the formulation of hypotheses, and the exploration of non-trivial connections. This is illustrated using magnetic and gravity data covering $$58,800 {\textrm{km}}^2$$ in the east Yilgarn Craton, Western Australia. Our methodology is adaptable and can be extended to include various other gridded datasets like gamma-ray spectrometry data, satellite imagery, and digital terrain models, thus broadening its applicability and enhancing geoscientific exploration. Our approach not only reveals subtle geophysical patterns but also offers practical benefits for exploration geologists. The atlas enables the identification of geological settings associated with mineral prospectivity and can serve as a pre-planning tool for pinpointing promising exploration sites, potentially accelerating discovery timelines.