Logistics service facilities such as warehouses and distribution centers are integral components of supply chains, providing essential services including transportation, storage, and consolidation of goods. The strategic location choice of these facilities represents a critical decision firms make to optimize logistics operations and overall supply chain performance. As key nodes serving as both origins and destinations of shipments, logistics service facilities directly influence the efficiency and cost-effectiveness of supply chains. Moreover, their location decisions contribute disproportionately to freight traffic generation and associated negative externalities within regional transportation networks. This study aims to model warehouse location choice in the Greater Golden Horseshoe (GGH), Canada. The novel contribution of our research is to differentiate between single-establishment and multi-establishment firms in the location choice of warehouses to investigate intra-firm interactions. Intra-firm interactions are modeled through explanatory variables and a panel mixed logit model specification. The model incorporates intra- and inter-industry interactions and land use and transportation infrastructure characteristics as explanatory variables. We find that substantial intra-firm interactions for multi-establishment warehouses tend to minimize the distance to other establishments belonging to the same firm, while preferring to locate farther from other warehouses belonging to the same firm. We find clustering effects in GGH where warehouses prefer locations closer to each other. These findings provide insights for freight transportation planning and evidence-based policy making.
Single atom catalysts are characterized by atomic dispersion of an active transition metal on a support by creating a stable bond between the two providing resistance to deactivation such as sintering or coking. Single atoms can achieve stability at high temperatures under oxidizing conditions but reducing conditions or steam can cause the single atoms to migrate forming nanoparticles, significantly impacting stability of the catalyst. In the context of bio-derived fuels such as upgrading ethanol to sustainable aviation fuel, Cu catalysts have garnered interest due to their ability to dehydrate alcohols, but deactivation poses a challenge due to the low melting temperature of Cu and the presence of steam/hydrogen during reaction. We demonstrate the synthesis of single atom Cu catalysts that provide hydrothermal stability under conditions encountered during biomass upgrading. Using a facile PVP sol-gel method achieves atomically dispersed Cu (~5wt%) capable of surviving under aggressive hydrothermal and reducing conditions. We used CO oxidation as a probe reaction to distinguish single site ionic Cu from metallic Cu or Cu oxide nanoparticles which demonstrate lower reactivity. Using XAS and operando DRIFTS during CO oxidation we confirm that the fresh catalyst contains single atom Cu2+ species which remain unchanged after aging.
Optical time projection chambers (OTPCs) are well suited for applications that require the highest spatial resolution for particle track reconstruction. The MIGDAL experiment uses a glass GEM-based OTPC and observes a systematic excess in both the intensity and width of particle tracks in its optical readout, when compared with charge readout simulations. One hypothesis is that scintillation light produced inside a GEM hole during the avalanche propagates through the GEM substrate and exits neighboring holes. We present lab measurements testing this hypothesized optical broadening effect in three types of GEM substrates: glass, ceramic, and FR4. Our observations quantify this optical broadening and demonstrate it to be strongest in glass GEMs. Additionally, we use Geant4 simulations to both reproduce our observations and quantify optical broadening effects in realistic charge avalanches. Applying our glass GEM effects to simulated particle tracks yields increases of track intensity and widths by up to approximately 26% and 31%, respectively. This may explain the larger-than-expected track intensities and widths observed in the MIGDAL OTPC. This effect may be relevant to GEM-based OTPCs, with its magnitude depending on the GEM structure and detector-specific optical configuration.
Cognitive control is fundamental to goal-directed behavior, and its protracted maturation is a hallmark of adolescent brain development. In adulthood, the inferior frontal junction (IFJ) is functionally characterized as a critical region for updating task representations to guide the implementation of cognitive control. Yet, how its domain-general control functions emerge and mature across development remains largely underexplored. Specifically, it is unclear whether IFJ’s capacity for cognitive control enhances uniformly as a single construct, or if this region matures asynchronously for distinct control processes like inhibition, switching, and working memory. To address this gap, we conducted a combined systematic review and coordinate-based neuroimaging meta-analysis. Applying multilevel kernel density analyses to fMRI studies of inhibition, switching, and working memory in youth and adults, we synthesized data from 72 contrasts (779 foci; N = 1913). The results revealed a staggered developmental trajectory for IFJ recruitment during visually cued cognitive control paradigms. While adults showed consistent convergence of activation in IFJ across all three domains, youth exhibited robust bilateral IFJ convergence exclusively during inhibitory control tasks. This suggests inhibition may be a developmentally foundational process localized to this region earlier in the lifespan. Furthermore, adults demonstrated hemispheric specialization absent in youth: left IFJ was uniquely sensitive to switching and working memory in adults, but not in youth. Together, these findings support a model where IFJ does not mature as a static, monolithic node, but rather acts as a dynamic hub that integrates fractionated cognitive processes at different stages of development.
The rising concentration of atmospheric CO2 significantly contributes to global temperature increases, prompting the need for efficient carbon capture materials. Alkali metal oxides, known for their intrinsic surface basicity and low cost, are promising candidates for CO2 adsorption. However, the strong binding of CO2 to bulk alkali oxides necessitates high energy input for its controlled desorption as a concentrated stream fit for sequestration. This study investigates the interaction of CO2 with potassium oxide (K2O) bulk surfaces and clusters of varying sizes, from monomer to tetramer, using density functional theory modeling to assess how cluster size affects adsorption strength. Our models indicate that CO2 adsorption is weaker on very small K2O clusters compared to bulk K2O. Empirical thermogravimetric and differential scanning calorimetry measurements corroborate that larger K2O clusters exhibit stronger CO2 adsorption. The cooperative electronic and geometric effects responsible for strong CO2 binding on continuous surfaces may be disrupted on highly constrained active surfaces, facilitating controlled desorption with reduced energy input. Additionally, K2O clusters supported on gamma-alumina were evaluated to examine the impact of metal oxide supports. The incorporation of gamma-alumina significantly enhanced CO2 binding energies, underscoring the critical role of supports in the adsorption chemistry of dispersed active clusters.
