South Dakota School of Mines and Technology

The nature of dark matter remains unresolved in fundamental physics. Weakly Interacting Massive Particles (WIMPs), which could explain the nature of dark matter, can be captured by celestial bodies like the Sun or Earth, leading to enhanced self-annihilation into Standard Model particles including neutrinos detectable by neutrino telescopes such as the IceCube Neutrino Observatory. This article presents a search for muon neutrinos from the center of the Earth performed with 10 years of IceCube data using a track-like event selection. We considered a number of WIMP annihilation channels ( $\chi \chi \rightarrow \tau ^+\tau ^-$ χ χ → τ + τ - / $W^+W^-$ W + W - / $b\bar{b}$ b b ¯ ) and masses ranging from 10 GeV to 10 TeV. No significant excess over background due to a dark matter signal was found while the most significant result corresponds to the annihilation channel $\chi \chi \rightarrow b\bar{b}$ χ χ → b b ¯ for the mass $m_{\chi }=250$ m χ = 250 GeV with a post-trial significance of $1.06\sigma$ 1.06 σ . Our results are competitive with previous such searches and direct detection experiments. Our upper limits on the spin-independent WIMP scattering are world-leading among neutrino telescopes for WIMP masses $m_{\chi }>100$ m χ > 100 GeV.

This comprehensive review article explores the solid-state joining processes for developing structures of dissimilar materials such as titanium and aluminum alloys. These approaches are specifically invented to overcome numerous drawbacks associated with fusion-based manufacturing, particularly issues related to solidification and low mechanical properties. In a comparative background, solid-state processes offer advantages such as microstructural refinement, higher mechanical properties, reduced thermal stresses, improved microstructural control, broader material compatibility, and potentially smoother surface finishes. This work provides an in-depth analysis of the current state of knowledge and innovative advancements made for developing lightweight hybrid structures. Various methods, such as diffusion bonding, explosive welding, accumulative roll bonding, ultrasonic welding, rotational friction welding, and modern processes like friction stir welding, etc., are explored and reviewed in depth. The investigation extends to the impact of processing parameters, elucidation of the principles of different processes, analysis of the effects of process variables on structure–property relationships, underscored the significance of intermetallic phase evolution, and an exploration into resulting mechanical properties. Furthermore, the review addresses the challenges and opportunities associated with these techniques, highlighting their potential for broader implementation in manufacturing complex and lightweight components. These processes and techniques, recognized as profitable, find application in fabricating intricate parts, especially within the aviation, automotive, medical, and marine industries.

The XLZD collaboration is developing a two-phase xenon time projection chamber with an active mass of 60–80 t capable of probing the remaining weakly interacting massive particle-nucleon interaction parameter space down to the so-called neutrino fog. In this work we show that, based on the performance of currently operating detectors using the same technology and a realistic reduction of radioactivity in detector materials, such an experiment will also be able to competitively search for neutrinoless double beta decay in ¹³⁶Xe using a natural-abundance xenon target. XLZD can reach a 3σ discovery potential half-life of 5.7 × 10²⁷ years (and a 90% CL exclusion of 1.3 × 10²⁸ years) with 10 years of data taking, corresponding to a Majorana mass range of 7.3–31.3 meV (4.8–20.5 meV). XLZD will thus exclude the inverted neutrino mass ordering parameter space and will start to probe the normal ordering region for most of the nuclear matrix elements commonly considered by the community.

The Cretaceous–Paleogene (K–Pg) boundary marks a pivotal moment in Earth's history; understanding this transition at a regional scale provides critical insights into sedimentary processes and lithological changes during this period. This study focuses on the lithological transitions at the Hell Creek–Ludlow contact in northwestern South Dakota to establish a regional lithostratigraphic framework and improve understanding of depositional changes during the K–Pg transition. Field investigations concentrated on stratigraphic measurements and sedimentological analyses. Results reveal consistent lithological transitions, with the Hell Creek Formation being dominated by clay-rich paleosols and floodplain deposits transitioning into the sandier, fluvial-dominated Ludlow Formation. The formational contact is interpreted as facies transition across all sites and marked by abrupt changes in grain size and sediment color. While lignite beds, including the “Z-coal”, serve as markers in some locations, their absence or variability underscores the limitations of relying solely on lithological criteria to define the K–Pg boundary. This study highlights regional variability in the Hell Creek–Ludlow transition and establishes a lithostratigraphic framework for northwestern South Dakota. The findings emphasize the need for complementary methods, such as palynostratigraphy, geochemistry, and magnetostratigraphy, to refine the geochronologic placement of the K–Pg boundary.

The translation of biomedical devices and drug research is an expensive and long process with a low probability of receiving FDA approval. Developing physiologically relevant in vitro models with human cells offers a solution to not only improving the odds of FDA approval but also to expand our ability to study complex in vivo systems in a simpler fashion. Animal models remain the standard for pre-clinical testing; however, the data from animal models is an unreliable extrapolation when anticipating a human response in clinical trials, thus contributing to the low rates of translation. In this review, we focus on in vitro vascular or angiogenic models because of the incremental role that the vascular system plays in the translation of biomedical research. The first section of this review discusses the most common angiogenic cytokines that are used in vitro to initiate angiogenesis, followed by angiogenic inhibitors where both initiators and inhibitors work to maintain vascular homeostasis. Next, we evaluate previously published in vitro models, where we evaluate capturing the physical environment for biomimetic in vitro modeling. These topics provide a foundation of parameters that must be considered to improve and achieve vascular biomimicry. Finally, we summarize these topics to suggest a path forward with the goal of engineering human in vitro models that emulate the in vivo environment and provide a platform for biomedical device and drug screening that produces data to support clinical translation.

Here we present a microfluidic model that allows for co-culture of human osteoblasts, chondrocytes, fibroblasts, and macrophages of both quiescent (M0) and pro-inflammatory (M1) phenotypes, maintaining initial viability of each cell type at 24 h of co-culture. We established healthy (M0-based) and diseased (M1-based) joint models within this system. An established disease model based on supplementation of IFN-γ and lipopolysaccharide in cell culture media was used to induce an M1 phenotype in macrophages to recapitulate inflammatory conditions found in Osteoarthritis. Cell viability was assessed using NucBlue™ Live and NucGreen™ Dead fluorescent stains, with mean viability of 83.9% ± 14% and 83.3% ± 12% for healthy and diseased models, respectively, compared with 93.3% ± 4% for cell in standard monoculture conditions. Cytotoxicity was assessed via a lactate dehydrogenase (LDH) assay and showed no measurable increase in lactate dehydrogenase release into the culture medium under co-culture conditions, indicating that neither model promotes a loss of cell membrane integrity due to cytotoxic effects. Cellular metabolic activity was assessed using a PrestoBlue™ assay and indicated increased cellular metabolic activity in co-culture, with levels 5.9 ± 3.2 times mean monolayer cell metabolic activity levels in the healthy joint model and 5.3 ± 3.4 times mean monolayer levels in the diseased model. Overall, these findings indicate that the multi-tissue nature of in vivo human joint conditions can be recapitulated by our microfluidic co-culture system at 24 h and thus this model serves as a promising tool for studying the pathophysiology of rheumatic diseases and testing potential therapeutics.

DNA metabolism consists of crucial processes occurring in all living cells. These processes include various transactions, such as DNA replication, genetic recombination, transposition, mutagenesis, and DNA repair. While it was initially assumed that these processes might occur in the cytoplasm of prokaryotic cells, subsequent reports indicated the importance of the cell membrane in various DNA transactions. Furthermore, newly identified factors play significant roles in regulating DNA-related cellular processes. One such factor is the Hfq protein, originally discovered as an RNA chaperone but later shown to be involved in several molecular mechanisms. These include DNA transactions and interaction with the cell membrane. Recent studies have suggested that Hfq plays a role in the regulation of DNA replication, mutagenesis, and recombination. In this narrative review, we will focus on the importance of membranes in DNA transactions and discuss the potential role of Hfq-mediated regulation of these processes in Escherichia coli, where the protein is the best characterized. Special attention is given to the affinity of this small protein for both DNA and membranes, which might help explain some of the findings from recent experiments.

Tillage intensity reduction when coupled with higher yields and better equipment, has increased the potential to sequester carbon in farm fields. However, a few experiments have demonstrated that this is occurring. This studies objective was to investigate the macro-scale effects of crop tillage intensity decreases and yield increases and on soil organic carbon (SOC) storage in Nebraska (NE), Iowa (IA), Minnesota (MN), and South Dakota (SD) from 2000 to 2021. The analysis was based on grower surveys, state yields from 2000 to 2021, and over 12 million surface soil samples that were aggregated by state and year. The model used first order kinetics, and it consisted of three pools [non-harvested carbon (NHC), SOC, and atmospheric carbon dioxide (CO2)]. Annual NHC additions were estimated from the state-level crop yields and tillage intensity reductions were estimated from producer surveys. Across the four states and 21 years, there was an estimated decrease of 0.0339 soil mixing events per year, corn (Zea mays) and soybean (Glycine max) yields increased by 63 and 38%, respectively, and SOC increased at a rate of > 460 kg SOC-C/(ha × year). In addition, strong (p < 0.01) linear correlations between NHC additions and SOC gains indicate that soil at the state-scale soil was not approaching carbon saturation.

The push for sustainability in all facets of manufacturing has led to an increased interest in biomass as an alternative to non-renewable materials. Hemp bast fiber mats were produced from a bacterial retting process, named BFM, as the fiber reinforcement. The objective of this study was to evaluate the feasibility of laminating BFM with polylactic acid (PLA) for a composite panel product. Since both BFM and PLA are biodegradable, the resulting BFM-PLA composites will be 100% biodegradable. PLA pallets were processed into thin polymer sheets which served as the matrix. The BFM and PLA plates were laminated in five layers and compression-molded into composite panels. Experiments were conducted on the three BFM-to-PLA ratios (35/65, 45/55, and 50/50). Mechanical properties (tensile and bending properties) and physical properties (thickness swell and water absorption) were tested and compared to the currently commercial sheet molding compound (SMC) from fiber glass. The thermal behavior of the BFM/PLA composites was characterized using dynamic mechanical analysis (DMA) and differential scanning calorimetry (DSC). The developed BFM/PLA composite product is a sustainable alternative to existing synthetical fiber-reinforced polymer (FRP) that is biodegradable in landfill at the end of life.

Sulfate-reducing bacteria (SRB) exhibit versatile metabolic adaptability with significant flexibility influenced by pH fluctuations, which play a critical role in biogeochemical cycles. In this study, we used a model SRB, Oleidesulfovibrio alaskensis G20, to determine the temporal effects of pH variations (pH 6, 7, and 8) on both growth dynamics and metabolic gene expressions. The specific growth rate at pH 6 (0.014 h⁻¹) closely matched that at pH 7 (0.016 h⁻¹), while pH 8 exhibited a lower growth rate (0.010 h⁻¹). Lactate consumption peaked at pH 7 (0.35 mM lactate.h⁻¹) and declined at pH 8 (0.09 mM lactate.h⁻¹). Significant hydrogen production was evident under both acidic and alkaline conditions. Gene expression studies revealed that ATPases function as proton pumps, while hydrogenases mediate reversible proton-to-hydrogen conversion. Sulfate and energy metabolism act as electron acceptors and donors, while amino acid synthesis regulates basic and acidic amino acids to mitigate pH stress. Downregulation of FtsZ at pH 6 suggests impaired division, correlating with slightly longer lengths (~2 µm), while upregulation of divisome proteins at pH 8 suggests efficient division processes, aligning with shorter lengths (~1.8 µm). This study will facilitate the employment of O. alaskensis G20 in extreme pH environments, enhancing its effectiveness in optimizing bioremediation and anaerobic digestion processes. IMPORTANCE Sulfate-reducing bacteria (SRB) play essential roles in global sulfur and carbon cycling and are critical for bioremediation and anaerobic digestion processes. However, detailed studies on the genotypic and phenotypic responses of SRB under varying pH conditions are limited. This study addresses this gap by examining the pH-dependent genetic and metabolic adaptations of Oleidesulfovibrio alaskensis G20, revealing key mechanisms regulating hydrogenase and ATPase activities, cell division, and extracellular polymeric substance formation. These findings provide new insights into how SRB maintains pH homeostasis, showcasing their ability to survive and function in both acidic and alkaline environments. Furthermore, this study reveals critical genetic and phenotypic characteristics that will directly aid to engineer industrial effluent management systems, bioremediation, and dissolved heavy metal recovery. By elucidating the dynamic response of O. alaskensis G20 to varied pH environments, the research provides a foundation for enhancing the resilience and performance of SRB-based systems, paving the way for improved environmental and industrial applications.

The DeepCore subdetector of the IceCube Neutrino Observatory provides access to neutrinos with energies above approximately 5 GeV. Data taken between 2012 and 2021 (3387 days) are utilized for an atmospheric ν μ disappearance analysis that studied 150 257 neutrino-candidate events with reconstructed energies between 5 and 100 GeV. An advanced reconstruction based on a convolutional neural network is applied, providing increased signal efficiency and background suppression, resulting in a measurement with both significantly increased statistics compared to previous DeepCore oscillation results and high neutrino purity. For the normal neutrino mass ordering, the atmospheric neutrino oscillation parameters and their 1 σ errors are measured to be Δ m 32 2 = 2.40 − 0.04 + 0.05 × 10 − 3 eV 2 and sin 2 θ 23 = 0.54 − 0.03 + 0.04 . The results are the most precise to date using atmospheric neutrinos, and are compatible with measurements from other neutrino detectors including long-baseline accelerator experiments. Published by the American Physical Society 2025

The paper deals with a discrete‐time susceptible‐infected susceptible (SIS) networked epidemic model. In the model, nodes represent populations and the network links possible transmission pathways of the disease between populations. Our aim is to design a feedback controller so that the fraction of infected in each population node remains below a prespecified value for all time instants. To this end, we introduce a distributed control law at the node level. This control law can be realized by the population following announcements made by local policymakers to enhance nonpharmaceutical interventions such as hand‐washing, mask‐wearing, and social distancing. We show that with the controller in place not only do the fraction of infected in each population node stay below the prespecified level but also the state of the disease dynamics converges either to the disease‐free equilibrium or to a unique endemic equilibrium. It turns out that the endemic equilibrium is (element‐wise) smaller than the unique endemic equilibrium of the uncontrolled system. The theoretical findings are illustrated by numerical examples.

The instability of quick clay is a contributing factor for landslides within Scandinavia, Canada, and Russia. The addition of salts into quick clay is known to improve the remoulded shear strength and liquid limit. In this study, the mixing of salts recycled from waste incineration fly ash into remoulded quick clay was studied and compared with the incorporation of pure salts for applications in salt wells and for excavation applications. The salts were added as solutions at low concentrations and as solids at high concentrations and stored for 1, 28 or 90 days before testing. Nearly all samples with added salts had a liquid limit that exceeded the water content and a remoulded shear strength, which exceeded 0.5 kPa. The pure potassium chloride had the largest effect, followed by the recycled chloride mixture with the highest concentration of K⁺. While a change in the geotechnical properties was immediately evident upon the mixing, the effect on the shear strength increased further with increasing storage time. The findings imply that the recycled salts may be used to improve the geotechnical properties of excavated soft clays during the handling and transport to landfills as a viable and low-emission alternative to cementitious binders.

Friction surfacing (FS) is increasingly recognized as an advanced technique for coating similar and dissimilar materials, enabling superior joint quality through plastic deformation and grain refinement. This study investigates the deposition of AA6082-T651 alloy on a medium-carbon steel EN14B substrate using FS, with process parameters optimized, and the effect of axial load, rotational speed, and traverse speed on coating integrity. The optimal sample was subjected to heat treatment (HT) at 550 °C for 24, 36, and 48 h to further enhance mechanical properties. Comprehensive microstructural and mechanical analyses were performed on both heat-treated and non-heat-treated samples using optical microscopy (OM), field emission scanning electron microscopy (FESEM) with energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), microhardness testing, and micro-tensile techniques. The optimized sample was processed with a 6 kN axial load, a rotational speed of 2700 rpm, and a traverse speed of 400 mm/min, and demonstrated superior bond quality and enhanced mechanical properties. The highest interfacial hardness values, 138 HV0.1 were achieved for the sample annealed for 48 h, under an axial load of 6 kN. Annealing for 48 h significantly improved atomic bonding at the aluminum–steel interface, confirmed by the formation of Fe3Al intermetallic compounds detected via FESEM-EDS and XRD. These compounds were the primary reason for the enhancement in the mechanical properties of the FS deposit. Furthermore, the interrelationship between process and thermal parameters revealed that a peak temperature of 422 °C, heat input of 1.1 kJ/mm, and an axial load of 6 kN are critical for achieving optimal mechanical interlocking and superior coating quality. The findings highlight that optimized FS parameters and post-heat treatment are critical in achieving high-quality, durable coatings, with improved interfacial bonding and hardness, making the process suitable for structural applications.

This study addresses a significant gap in understanding the features of the south‐central Cascadia subduction zone, a region characterized by complex geologic, tectonic, and seismic transitions both offshore and onshore. Unlike other segments along this margin, this area lacks a 3‐D velocity model to delineate its structural and geological features on a fine scale. To address this void, we developed a high‐resolution 3‐D P‐wave velocity model using active source seismic data from ship‐borne seismic shots recorded on temporary and permanent onshore seismic stations and ocean‐bottom seismometers. Our model shows velocity variations across the region with distinct velocity‐depth profiles for the Siletz, Franciscan, and Klamath terranes in the overlying plate. We identified seaward dipping high‐velocity static backstops associated with the Siletz and Klamath terranes, situated near the shoreline and further inland, respectively. Regions of reduced crustal velocity are associated with crustal faults. Moreover, there is significant along‐strike depth variation in the subducting slab, which is about 4 km deeper near the thick, dense Siletz terrane and becomes shallower near the predominantly less‐dense Franciscan terrane. This highlights a sudden tectonic and geologic transition at the southern boundary of the Siletz terrane. Our velocity model also indicates slightly increased hydration, though still minimal, in both the oceanic crust and the upper mantle of the subducting plate compared to other parts of the margin.

The application of artificial intelligence (AI) and machine learning (ML) in medicine and healthcare has been extensively explored across various areas. AI and ML can revolutionize cardiovascular disease management by significantly enhancing diagnostic accuracy, disease prediction, workflow optimization, and resource utilization. This review summarizes current advancements in AI and ML concerning cardiovascular disease, including their clinical investigation and use in primary cardiac imaging techniques, common cardiovascular disease categories, clinical research, patient care, and outcome prediction. We analyze and discuss commonly used AI and ML models, algorithms, and methodologies, highlighting their roles in improving clinical outcomes while addressing current limitations and future clinical applications. Furthermore, this review emphasizes the transformative potential of AI and ML in cardiovascular practice by improving clinical decision making, reducing human error, enhancing patient monitoring and support, and creating more efficient healthcare workflows for complex cardiovascular conditions.