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Additive Manufacturing of Polymer-Metal Systems
No full text{"value":"Modern additive polymer deposition is rapidly advancing across multiple industries. As manufacturing processes evolve, Additive Manufacturing (AM)—particularly AM using polymer direct deposition—has emerged as an affordable, precise, and efficient method for producing complex geometries and customized designs at high production rates [2][3]. Historically, AM has been limited to individual material classes such as metals, ceramics, or polymers, restricting the development of hybrid structures that integrate multiple material types [2].With the advancement of high-performance metals, the demand for stronger and more durable AM parts in applications such as weapons systems, automotive components, and fracture-resistant structures has increased [3]. The electronics industry has further expanded the potential of hybrid materials by introducing polymer deposition onto metal substrates, enabling novel metal-polymer hybrid designs [2].
At a fundamental level, chemical bonds at the polymer-metal interface are weak and generally ineffective for long-term adhesion [3]. This study explores methods to improve the “bonding” of inherently incompatible polymer and metal interfaces, seeking a mechanically robust alternative to traditional adhesive-based joining techniques [2]. While metals and polymers each exhibit distinct mechanical properties, conventional adhesives such as epoxy often result in weak interfacial bonds, susceptible to shear and normal forces, which limit the structural reliability of hybrid components [3].
To address this challenge, this research investigates mechanical interlocking as an alternative joining mechanism [2]. This method involves modifying the metal substrate interface to incorporate irregular surface textures or micro-sized extruded features, which physically interlock with the deposited polymer [3]. In this study, hourglass-shaped arrays, consisting of approximately 400 microstructures per 30 × 20 mm metal substrate, were examined as the primary interlocking geometry [2].
During polymer deposition using the Prusa i3 MK3S+ 3D printer, the warm polymer infiltrates the textured metal surface, effectively forming an interconnected mechanical bond [3]. The resulting structure mimics a Velcro-like effect, where the polymer is physically locked into place by the metal\u27s textured features, significantly enhancing adhesion strength compared to a smooth epoxy-metal interface [2].
This research provides insight into optimized polymer-metal bonding strategies by combining additive manufacturing, surface engineering, and mechanical interlocking [3]. The findings contribute to the development of high-performance hybrid structures with enhanced durability, load-bearing capacity, and resistance to mechanical stresses, paving the way for next-generation polymer-metal applications in aerospace, defense, and automotive engineering [2][3].
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Machine Learning-Enhanced Spectroscopy Techniques for Rapid MSW Feedstock Characterization
No full text{"value":"Municipal Solid Waste (MSW) gasification is a promising waste-to-energy pathway to support clean energy production and reduce environmental impact but suffers from feedstock variability. Existing off-site lab-based characterization methods are slow, costly, and unsuitable for real-time control. This dissertation presents a novel framework that integrates Laser-Induced Breakdown Spectroscopy (LIBS) with machine learning (ML) to enable rapid, in-situ prediction of key feedstock properties critical to gasification operation and performance. A custom LIBS system was developed featuring a Q-switched Nd:YAG laser operating at 1,064 nm with a pulse energy of 330 mJ. A total of 725 LIBS spectra were collected from various feedstock materials and four RDF (Refuse-Derived Fuel) samples. Each sample was paired with laboratory-measured values for higher heating value (HHV), fixed carbon, ash, volatile matter, ash softening temperature, chlorine content, and major ash-forming elements (e.g., Al, Na, Si, P, S, Ca, K, Mg, Fe). Feature selection was performed using a hybrid approach combining statistical correlation and domain expertise. Multiple ML models were trained and evaluated using 5-fold cross-validation. An ensemble model consists of Random Forest (RF), Support Vector Regression (SVR), and Artificial Neural Networks (ANN) emerged as the top performer, offering improved generalization and lower error rates compared to individual models.Final testing on a held-out dataset confirmed strong predictive accuracy with ML model R² up to 0.98, and Relative Root Mean Squared Error (RRMSE) below 15% for most parameters. Notably, the model predicted total sulfur, chlorine content and ash softening temperature—despite the lack of a robust LIBS spectral lines—by leveraging higher-order spectral correlations and robust feature selection.
To facilitate industrial application of this concept, a standalone software interface was developed. The software automates data input/output, preprocessing, quality control, drift correction, prediction, and output logging, enabling near-real-time feedstock monitoring in operational settings. This LIBS-ML system offers a scalable and practical tool for real-time MSW characterization, supporting data-driven process optimization and feed-forward control in waste-to-energy systems.
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The (Non)Human Collapse: Evolution and Survival in Folk Horror
No full textFolk horror has often been framed as a genre obsessed with the return of the past—residual belief systems, haunted landscapes, and ancient gods disrupting modernity. But this paper argues that folk horror centers not on return but on survival through adaptation. Drawing on Mathias Clasen’s evolutionary model of horror, which links the genre’s endurance to ancestral fears like predation and contamination, I propose that folk horror’s staying power lies in its adaptability. Its landscapes, gods, and rituals don’t linger—they evolve. Rather than treating folklore as static or degenerative, I build on Alan Dundes and Gillian Bennett to show how folk horror reimagines myth and ritual as flexible systems that change under ecological and cultural pressure. I trace this across three main structures: (1) landscapes that assert sovereignty through selection and submission; (2) gods that are built, not inherited—mutating through ritual, belief, and bodily change; and (3) how animal and human bodies become entwined in a shared ecology of mutation and somatic adaptation. Through close readings of Adam Nevill’s The Ritual (2011), The Blood on Satan’s Claw (1971), Wake Wood (2009), Starve Acre (2023), and others, I argue that folk horror dramatizes a world where human life is no longer central—just another element in a system that survives by rewriting the rules. In these stories, horror isn’t about what returns; it’s about what adapts.</p
Exploring the Role of Facilitation and Functional Traits in Secondary Successional Processes of Arboreal Plants in a Temperate Rainforest
No full textEcological succession, the process by which communities change over time, is a fundamental process in plant ecology that remains underexplored in canopy ecosystems compared to ground-based ecosystems. This oversight is critical because epiphytic plants, especially non-vascular groups such as mosses, make significant contributions to global biodiversity and play essential roles in carbon, water, and nutrient cycling in high-diversity forests. To address this gap, I investigated secondary successional processes in epiphytic bryophytes within a temperate rainforest in Olympic National Park, Washington. I tested two hypotheses: 1) early-successional species facilitate the growth of late-successional species, and 2) species\u27 traits reflect their successional stage (e.g., early-successional species possess traits aiding establishment, while late-successional species possess traits promoting competitive dominance). In the summer of 2024, I resurveyed 144 paired permanent plots established in 2020. Each pair included one plot with all bryophytes removed and one with one of three early-successional "facilitator" species introduced. I compared species richness, abundance, and diversity between paired plots and analyzed plant traits (e.g., shoot length, sporophyte frequency) for 20 common species to determine their relationship with successional stages. Although I did not observe significant facilitation effects after four years, with both substrates averaging approximately five species, a 0.9 Shannon diversity index, and 22% cover, and exhibiting similar community compositions, I found that shoot length and lifeform differed significantly among species classified under the different successional stages (early, mid and late). Overall, this research contributes novel plant trait measurements for several species currently not represented in global trait databases, as well as an experimental approach to understanding fundamental secondary successional processes in this understudied group.</p
Strength and Persistence of the Illusion of Explanatory Depth
No full textPeople’s tendency to overestimate their understanding has been shown to be pervasive, especially in relation to causal knowledge. While this phenomenon, termed the illusion of explanatory depth (IOED), can be broken through the act of generating a causal explanation, there are still aspects about the boundaries of the IOED that have yet to be explored. Across two experiments, I investigated the strength and persistence of the IOED. In Experiment 1, I determined whether breaking an IOED can transfer to break the illusion of knowledge for similar items that were not explained. In Experiment 2, I used a 2-session design to determine if a broken IOED remains broken after a period of one week. Additionally, I assessed the quality of the explanations given by participants for both experiments to determine its influence on both the strength and/or persistence of the IOED. Results for Experiment 1 showed that a decrease in understanding ratings for explained devices led to an even greater decrease in ratings for unexplained devices, although explanation quality was not found to impact this transfer of knowledge reassessment. Results of Experiment 2 showed the IOED is largely retained over a period of one week for both devices that were previously explained and for completely new devices, and that the IOED can be broken a second time to a greater degree than the first IOED session. In addition, explanation quality was predictive of the retention of the broken illusion over time. These studies provide a better understanding of the IOED and its limits, which is imperative for successfully combating this metacognitive error.</p
Distinct bacterial succession and functional response to alginate in the South, Equatorial, and North Pacific Ocean
No full textThe availability of alginate, an abundant macroalgal polysaccharide, induces compositional and functional responses among marine microbes, but these dynamics have not been characterized across the Pacific Ocean. We investigated alginate‐induced compositional and functional shifts (e.g., heterotrophic production, glucose turnover, hydrolytic enzyme activities) of microbial communities in the South Subtropical, Equatorial, and Polar Frontal North Pacific in mesocosms. We observed that shifts in response to alginate were site‐specific. In the South Subtropical Pacific, prokaryotic cell counts, glucose turnover, and peptidase activities changed the most with alginate addition, along with the enrichment of the widest range of particle‐associated taxa (161 amplicon sequence variants; ASVs) belonging to Alteromonadaceae , Rhodobacteraceae , Phormidiaceae , and Pseudoalteromonadaceae . Some of these taxa were detected at other sites but only enriched in the South Pacific. In the Equatorial Pacific, glucose turnover and heterotrophic prokaryotic production increased most rapidly; a single Alteromonas taxon dominated (60% of the community) but remained low (<2%) elsewhere. In the North Pacific, the particle‐associated community response to alginate was gradual, with a more limited range of alginate‐enriched taxa (82 ASVs). Thus, alginate‐related ecological and biogeochemical shifts depend on a combination of factors that include the ability to utilize alginate, environmental conditions, and microbial interactions
Physical activity self-efficacy online intervention for adults with obesity: protocol for a feasibility study
No full textAbstract
Background
Even without weight loss, adults with obesity can greatly benefit from regular physical activity. The Physical Activity Self-efficacy (PAS) intervention is an online behavioral intervention newly developed to promote physical activity in adults with obesity by providing capability-enhancing learning opportunities. The objective of this manuscript is to describe the protocol for a feasibility study designed to investigate the feasibility and acceptability of implementing the PAS online intervention for adults with obesity recruited from a local weight management center in the United States of America (USA).
Methods
The study design is a prospective, double-blind, parallel-group individual randomized pilot trial. Thirty participants will be randomly assigned to the PAS group or usual care group to achieve a 1:1 group assignment. Recruitment of participants is scheduled to begin on 1 March 2024 at a local weight management center within a private healthcare system in the USA. There are six eligibility criteria for participation in this study (e.g., a body mass index ≥ 25.00 kg/m2). Eligibility verification and data collection will be conducted online. Three waves of data collection will take up to 14 weeks depending on participants’ progress in the study. The primary feasibility outcomes in the study will be: (a) participation rate, (b) engagement behavior, and (c) a preliminary effect size estimate for the effect of the PAS intervention on physical activity. Instruments designed to measure demographic information, anthropometric characteristics, self-efficacy, and acceptability will be included in the survey battery. A research-grade accelerometer will be used to measure free-living physical activity objectively. Data will be analyzed using descriptive statistics and inferential statistical models under an intention-to-treat approach.
Discussion
Results are intended to inform the preparation of a future definitive randomized controlled trial.
Trial registration
ClinicalTrials.gov, NCT05935111, registered 7 July 2023.
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Psychometrics of rating scales for externalizing disorders in Japanese outpatients: The ADHD Rating Scale and the Disruptive Behavior Disorders Rating Scale
No full textAbstractObjectivesThis study validated the Japanese version of the Attention‐Deficit/Hyperactivity Disorder‐Rating Scale‐5 (ADHD‐RS‐5) and the Disruptive Behavior Disorders Rating Scale. We extended the ADHD‐RS‐5 by adding the oppositional defiant disorder and conduct disorder subscales to compare the two rating scales psychometrically.MethodsWe examined the internal consistency, test‐retest reliability, construct validity and criterion validity of the two rating scales in 135 Japanese outpatients aged 6–18 years.ResultsThe internal consistency and test‐retest reliability were good for all the subscales of the two rating scales except for the conduct disorder subscale of the ADHD‐RS‐5 extended. Good construct validity was revealed by expected correlational patterns between subscales from the two rating scales and the Children Behavior Checklist. The criterion validity was good for all the subscales of the two rating scales rated by parents, while teacher‐ratings revealed substantially lower predictive ability for all the subscales. Agreement between parent‐ and teacher‐ratings of the two rating scales was generally moderate and using predictive ratings alone of both ratings showed the best predictive ability among the integration methods examined.ConclusionThe two rating scales have sound psychometric properties and will aid in screening and severity assessment of externalizing disorders in Japanese clinical settings.</jats:sec
A Deeper Understanding of Material Properties Through Computational Model Development.
No full textThe pace of materials development can be significantly increased by computational models that accurately capture the characteristics of experimental materials. While advances in computational architecture have enabled researchers to calculate the properties of pure materials with high fidelity, it is often disorder of the perfect crystal that gives rise to technologically relevant properties. This thesis aims to contribute a robust modeling framework for disordered materials by developing improved criteria to access metal oxide point defects, interfaces, and nanoparticles using theories that are efficient and easily generalizable. Insights into technologically relevant materials are developed, including discovery and assignment of spectroscopic signals to new defect geometries in doped SrTiO3, identification of ring-like atomic motifs in amorphous Al2O3 responsible for experimentally observed electronic properties, and combination molecular dynamics and density functional theory approaches to produce more realistic amorphous TiO2 nanoparticles and interfaces.</p