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Background: Fathers of children and youth with special healthcare needs (FCYSHCN) are an overlooked population at risk for chronic stress. Mind-body practices offer a patient-centered approach to foster coping and resiliency, yet low engagement from fathers in existing programs suggests adaptation is needed. This multiphase study examines the feasibility of a synchronous, virtual mind-body intervention adapted for FCYSHCN., Methods: 31 FCYSHCN were recruited online via community partners and recruitment portals in an academic medical center in Boston, MA. Phase 1 consisted of individual interviews (N = 17) to determine fathers' stressors, coping strategies, program needs, and suggested adaptations to the intervention protocol. The Phase 2 single arm pilot feasibility trial (N = 14) consisted of eight weekly 60-minute group sessions delivered virtually. Primary feasibility metrics were attendance (benchmark: mean=6 sessions) and electronic survey completion at baseline and post-intervention. Acceptability was assessed using post-session ratings of program satisfaction (4-point Likert scale; scores ≥3 coded as helpful) and helpfulness (e.g., group structure). Exploratory outcomes included validated measures of stress coping, resiliency, parental stress, depression, anxiety, which were analyzed using paired-samples t-tests (alpha=.05) to generate effect sizes (η2)., Results: In Phase 1, FCYSHCN discussed primary stressors (e.g., perceived inadequacy as a father) and multifaceted impacts of these stressors on physical, cognitive, emotional, and social wellbeing. Fathers also described coping strategies deemed helpful (e.g., humor) and unhelpful (e.g., "shutting down" from others). Qualitative findings informed intervention modifications. In Phase 2, most FCYSHCN (79%) attended ≥ 6 intervention sessions (mean=7). Follow-up survey completion was high (86%). Session satisfaction was high, with 7/8 sessions rated as helpful by most fathers. Program components deemed most helpful were the group structure, virtual delivery, exposure to a variety of relaxation and meditation skills, and the length of sessions. Although we were not powered to observe pre-post change, stress coping improved (p = .02, η2 = 0.42) and confidence increased in applying relaxation (p = .04, η2 = 0.34) and assertiveness techniques (p = .05, η2 = 0.31)., Conclusions: The first mind-body resiliency program for FCYSHCN is feasible and acceptable. Further testing is warranted in randomized trials with diverse samples of fathers, an appropriate comparison arm, and longitudinal assessments of psychosocial and biobehavioral outcomes., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Deep learning models perform remarkably well on many classification tasks recently. The superior performance of deep neural networks relies on the large number of training data, which at the same time must have an equal class distribution in order to be efficient. However, in most real-world applications, the labeled data may be limited with high imbalance ratios among the classes, and thus, the learning process of most classification algorithms is adversely affected resulting in unstable predictions and low performance. Three main categories of approaches address the problem of imbalanced learning, i.e., data-level, algorithmic level, and hybrid methods, which combine the two aforementioned approaches. Data generative methods are typically based on generative adversarial networks, which require significant amounts of data, while model-level methods entail extensive domain expert knowledge to craft the learning objectives, thereby being less accessible for users without such knowledge. Moreover, the vast majority of these approaches are designed and applied to imaging applications, less to time series, and extremely rare to both of them. To address the above issues, we introduce GENDA, a generative neighborhood-based deep autoencoder, which is simple yet effective in its design and can be successfully applied to both image and time-series data. GENDA is based on learning latent representations that rely on the neighboring embedding space of the samples. Extensive experiments, conducted on a variety of widely-used real datasets demonstrate the efficacy of the proposed method., Impact Statement—: Imbalanced data classification is an actual and important issue in many real-world learning applications hampering most classification tasks. Fraud detection, biomedical imaging categorizing healthy people versus patients, and object detection are some indicative domains with an economic, social and technological impact, which are greatly affected by inherent imbalanced data distribution. However, the majority of the existing algorithms that address the imbalanced classification problem are designed with a particular application in mind, and thus they can be used with specific datasets and even hyperparameters. The generative model introduced in this paper overcomes this limitation and produces improved results for a large class of imaging and time series data even under severe imbalance ratios, making it quite competitive.

This paper investigates a specific case of one of the most popular fluid dynamic simulations, the incompressible flow around an airfoil (NACA 0012 here) at a high Reynolds number ( 6 × 10 6 ). OpenFOAM software was used to study the effect of domain size and four common choices of boundary conditions on airfoil lift, drag, surface friction, and pressure. We also examine the relation between boundary conditions and the velocity, pressure, and vorticity distributions throughout the domain. In addition to the common boundary conditions, we implement the "point vortex" boundary condition that was introduced many years ago but is now rarely used. We also applied the point vortex condition for the outlet pressure instead of using the traditional Neumann condition. With the airfoil generating significant lift at incidence angles of 5 ∘ , 10 ∘ , and 14 ∘ , we confirm a previous finding that the boundary conditions combine with domain size to produce an induced (pressure) drag. The change in the pressure drag with domain size is significant for the commonly-used boundary conditions but is much smaller for the point vortex alternative. The point vortex boundary condition increases the execution time, but this is more than offset by the reduction in domain size needed to achieve a specified accuracy in the lift and drag. This study also estimates the error in total drag and lift due to domain size and shows it can be almost eliminated using the point vortex boundary condition. We also used the impulse form of the momentum equations to study the relation between drag and lift and spurious vorticity, which is generated as a result of using non-exact boundary conditions. These equations reveal that the spurious vorticity throughout the domain is associated with cancelling circulation around the domain boundaries., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2024.)

One strategy to reduce CO 2 emissions from cement production is to reduce the amount of Portland cement produced by replacing it with supplementary cementitious materials (SCMs). Biochar is a potential SCM that is an eco-friendly and stable porous pyrolytic material. However, the effects of biochar addition on the performances of Portland cement composites are not fully understood. This meta-analysis investigated the impact of biochar addition on the 7- and 28-day compressive strength of Portland cement composites based on 606 paired observations. Biochar feedstock type, pyrolysis conditions, pre-treatments and modifications, biochar dosage, and curing type all influenced the compressive strength of Portland cement composites. Biochars obtained from plant-based feedstocks (except rice and hardwood) improved the 28-day compressive strength of Portland cement composites by 3-13%. Biochars produced at pyrolysis temperatures higher than 450 °C, with a heating rate of around 10 C min -1 , increased the 28-day compressive strength more effectively. Furthermore, the addition of biochar with small particle sizes increased the compressive strength of Portland cement composites by 2-7% compared to those without biochar addition. Biochar dosage of < 2.5% of the binder weight enhanced both compressive strengths, and common curing methods maintained the effect of biochar addition. However, when mixing the cement, adding fine and coarse aggregates such as sand and gravel affects the concrete and mortar's compressive strength, diminishing the effect of biochar addition and making the biochar effect nonsignificant. We concluded that appropriate biochar addition could maintain or enhance the mechanical performance of Portland cement composites, and future research should explore the mechanisms of biochar effects on the performance of cement composites., Supplementary Information: The online version contains supplementary material available at 10.1007/s42773-024-00309-2., Competing Interests: Competing interestsThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© The Author(s) 2024.)