Land use change and forest management affect soil carbon stocks in the central hardwoods, U.S.

Most research addressing land use change and forest management effects on soil carbon (C) is conducted at large or localized scales, rather than intermediate scales where management is planned and implemented. We assessed effects of land use and forest management on soil C stocks, for the Central Hardwoods ecoregion of the U.S., using meta-analysis, soil survey and national forest inventory databases to examine baseline controls on soil C stocks and their responses to land use and forest management. Biotic and geologic factors drive baseline variation in soil C stocks across the ecoregion, with forest type and productivity being most important in surface horizons and parent material dominating at the whole profile level. Among forest management treatments, prescribed fire is most noteworthy, decreasing O horizons to an extent determined by place and practice (mean: −53 %). Coal mine reclamation is extensive in the region, and while there is no effect of forest vs. herbaceous reclamation, distinct overburden types have different effects on soil C stocks (mean: +183 %). Land use change effects on soil C are difficult to determine due to the preferential use of the most favorable soils for agriculture, the relegation of forests to the least productive soils, and the tendency for reforestation to occur on marginal soils. Overall, our results can help forest managers anticipate the C outcomes of typical burn prescriptions in this region of extensive prescribed fire, and help landowners and planners understand how parent material and soil properties influence soil C stocks under agriculture and mine reclamation

Geospatial analysis for promoting urban green space equity: Case study of Detroit, Michigan, USA

Urban green spaces play a vital role in promoting human health and well-being, enhancing urban ecosystems, and supporting urban sustainability and resilience. However, inequities in the distribution and accessibility to urban green spaces can disproportionately affect vulnerable and underserved communities. This study examines the distribution and accessibility of urban green spaces in Detroit, Michigan, using high-resolution geospatial data and geospatial analysis methods, including geographically weighted regression (GWR) and network-based analyses. The study aims to correlate urban green space access inequities with social and environmental justice indicators and offer strategies for urban planners to identify and address green space inequities using geospatial analysis. The case study identifies significant urban green space inequities, with 87 % (53 %) of buildings lacking a park or recreational area within a quarter-mile (half-mile) walking distance. GWR analysis further demonstrates that neighborhoods with higher social vulnerability scores tend to have significantly lower green space availability, although park areas appear to be equitably distributed in some parts of the city. These findings highlight critical areas in Detroit that can be prioritized for green space development to address these inequities and create healthier, more resilient urban environments. The methods presented can be applied to other cities to assist urban planners in identifying where resources can be most efficiently allocated to address current green space disparities, particularly in historically underserved areas

Preparation and Microwave Deicing Properties of Ferric Oxide-Modified Emulsified Asphalt

This study addresses the challenge of icy asphalt pavements in cold climates by proposing an innovative and eco-friendly deicing material. Traditional approaches, such as salt spraying and mechanical deicing, often lead to environmental concerns and increased resource usage. In response, this paper introduces a novel ferric oxide-modified emulsified asphalt (FO-EA), formulated by integrating ferric oxide (FO) powder with emulsified asphalt (EA). Experimental results, including segregation tests and fluorescence microscopy, confirm that 20% by weight of FO is evenly dispersed in the EA. Remarkably, FO-EA-coated asphalt demonstrates a 50% reduction in microwave deicing time compared to conventional asphalt, with a significant increase in the heating rate of 0.12°C/s. In addition, FO-EA surpasses standard asphalt in skid resistance and water seepage tests, meeting all specification requirements. Furthermore, its deicing efficacy remains robust after 500 abrasion resistance test cycles. Overall, FO-EA emerges as an efficient and sustainable solution for road deicing

Pilot plant study on manganese bioleaching using biomass decomposition products as a nutrient source and electrolysis for oxide precipitation

Manganese leaching was carried out on a small pilot scale with 110 kg of ore using manganese-reducing organisms and fermentative organisms with biomass (Typha latifolia) as the source of nutrition. This study was carried out without externally supplied chemical reagents and with minimal capital investment. The process involves fermentative organisms to ferment biomass from T. latifolia and generate organic acids. Manganese-reducing organisms and organic acids reduced and dissolved manganese from pyrolusite ore. Manganese was precipitated from the manganese-bearing solution using an electrolytic oxidation technique. A manganese concentration above 500 mg/L and negligible dissolved iron was achieved at a flow rate of 30 L/day, maintaining a pH range of 4 to 5, and a redox potential between 0.10 and 0.46 V. Manganese oxide was produced at a rate of 12 g/day, with a purity of 90 %. Amorphous manganese oxide was deposited on the cathode, while crystalline manganese oxide formed on the anode

Sepiolite-based PDA-PAM hydrogels with enhanced interfacial adhesion capability

Elastic and dense connective tissues exhibit exceptional tensile strength and fatigue resistance, enabling them to withstand continuous stretching and cyclic loading. The endeavor to replicate these remarkable mechanical properties in artificial bionic robots or engineered tissues is still a challenge. Our study reveals that the toughness of the body\u27s elastic connective tissues is due to the orderly arrangement of collagen fibers. These fibers, 20 to 100 nanometers in diameter, act as a crucial buffer, reducing tension and fatigue impact. Inspired by that, we design and fabricate a sepiolite-based polydopamine-acrylamide (S-PDA-PAM) hydrogel, which mimics the structure of human tissue. The results demonstrate that, through mechanical training, the sepiolite composite hydrogel exhibits a higher adhesive fatigue threshold. Aligned sepiolite nanofibers reinforce and prevent polymer chain debonding, functioning as a rigid matrix. This structural reinforcement greatly increases the energy barrier against fatigue crack propagation, significantly raising the interfacial fatigue threshold. This boost in fatigue resistance gives the composite material exceptional mechanical resilience, similar to natural tissues

Data-driven identification of bandgaps in flexural metastructures using Component Mode Synthesis and FRF Based Substructuring

Metastructures, characterized by their periodic unit cells, are known for their ability to block the propagation of elastic waves within specific frequency ranges, known as “bandgaps”. To estimate the wave propagation characteristics of these systems, two primary approaches are employed: physics-based methods and data-driven techniques. Physics-based methods depend on the material properties and geometry of the unit cells, while data-driven approaches utilize experimental data, such as steady-state dynamic response data. This study assesses the effectiveness of data-driven techniques, particularly Component Mode Synthesis (CMS) and Frequency Response Function-Based Substructuring (FBS), in identifying bandgaps in metastructures composed of multiple unit cells. The focus is on metastructures consisting of 1D beams that exhibit flexural wave behavior. Within these structures, two significant challenges arise when using frequency response functions based on out-of-plane response data: the absence of rotational degrees of freedom (dofs) and the presence of rigid-body modes. Both factors critically impact the dispersion relationship and, by extension, the bandgap estimation. Traditionally, capturing rotational dynamics has been difficult due to limitations in direct experimental measurement, necessitating the inference of rotational dofs from translational measurements. Furthermore, rigid-body modes are estimated from experimental data. To overcome these challenges, we propose the estimation of rotational dofs by curve-fitting of translational dofs. In addition, this study explores a novel approach to the estimation of rigid body modes from the modal parameters acquired using the well-known Polymax algorithm. The discussed methodologies are also applied to derive dispersion relations for infinite metastructures

A Rhodamine-Based Ratiometric Fluorescent Sensor for Dual-Channel Visible and Near-Infrared Emission Detection of NAD(P)H in Living Cells and Fruit Fly Larvae

The detection and dynamic monitoring of intracellular NAD(P)H concentrations are crucial for comprehending cellular metabolism, redox biology, and their roles in various physiological and pathological processes. To address this need, we introduce sensor A, a near-infrared ratiometric fluorescent sensor for real-time, quantitative imaging of NAD(P)H fluctuations in live cells. Sensor A combines a 3-quinolinium electron-deficient acceptor with a near-infrared rhodamine dye, offering high sensitivity and specificity for NAD(P)H with superior photophysical properties. In its unbound state, sensor A emits strongly at 650 nm and weakly at 465 nm upon 400 nm excitation. Upon binding to NAD(P)H, it shows a fluorescence increase at 465 nm and a decrease at 650 nm, enabling accurate ratiometric measurements. Sensor A also exhibits ratiometric upconversion fluorescence when excited at 800 or 810 nm, offering additional flexibility for different experimental setups. The sensor’s response relies on the reduction of the 3-quinolinium acceptor by NAD(P)H, forming a 1,4-dihydroquinoline donor that enhances fluorescence at 465 nm and quenches the near-infrared emission at 650 nm through photoinduced electron transfer. This mechanism ensures high sensitivity and reliable quantification of NAD(P)H levels while minimizing interference from sensor concentration, excitation intensity, or environmental factors. Sensor A was validated in HeLa and MD-MB453 cells under various metabolic and pharmacological conditions, including glucose and maltose stimulation and treatments with chemotherapeutic agents. Co-localization with mitochondrial-specific dyes confirmed its mitochondrial targeting, enabling precise tracking of NAD(P)H fluctuations. In vivo imaging of Drosophila larvae under nutrient starvation or chemotherapeutic exposure revealed dose-dependent fluorescence responses, highlighting its potential for tracking NAD(P)H changes in live organisms. Sensor A represents a significant advancement in NAD(P)H imaging, providing a powerful tool for exploring cellular metabolism and redox biology in biomedical research

Great Lakes Water Level Trends Using the Moving Statistics Method, with Implications for Climate Change and Cities

Increasing magnitudes of precipitation and evaporation are predicted for future climate change. Knowing whether these trends are occurring can help water managers plan with respect to future erosion, flooding, and design changes for shoreline infrastructure. Data from all the Laurentian Great Lakes (Erie, Michigan-Huron, Ontario, St. Clair, and Superior) were analyzed here to determine whether these trends are being realized. The MovingStatistics Method is used here using the moving average and moving standard deviation. It was found that Lakes Erie and St. Clair had the highest moving average trend of 0.5 mm/month, while Lake Ontario had the highest moving standard deviation trend (also 0.2 mm/month). Lake Superior had a decreasing moving average, while Lakes Erie, Michigan-Huron, and St. Clair had decreasing values of moving standard deviation. All lakes had moving average values greater than the measurement margin of error except Lake Superior. It is concluded that Great Lakes water levels have changed in the past and probably continue to change in the future. Property owners land managers can use these results to plan future budgets

Metal-rich lacustrine sediments from legacy mining perpetuate copper exposure to aquatic-riparian food webs

Historic copper mining left a legacy of metal-rich tailings resulting in ecological impacts along and within Torch Lake, an area of concern in the Keweenaw Peninsula, Michigan, USA. Given the toxicity of copper to invertebrates, this study assessed the influence of this legacy on present day nearshore aquatic and terrestrial ecosystems. We measured the metal (Co, Cu, Ni, Zn, Cd) and metalloid (As) concentrations in sediment, pore water, surface water, larval and adult insects, and two riparian spider taxa collected from Torch Lake and a nearby reference lake. Overall, elevated metal and metalloid concentrations, particularly Cu, were measured in all sediment samples and some surface and pore water samples collected from Torch Lake. For instance, Cu concentrations in the Torch Lake sediment were ∼200% higher than the reference lake and all measured concentrations exceeded predicted effects concentrations by at least ninefold. Within larval insect tissues, we observed 160% higher Cu concentrations than measured in the reference lake, and Cu was the only measured element above predicted effects concentrations in Torch Lake. Adult insects collected at both lakes had similar metal concentrations irrespective of exposure levels. Yet we found 100% higher copper concentrations in Torch Lake riparian spiders, demonstrating elevated exposure risk to insectivores across the aquatic-terrestrial boundary. Our results highlight that other metals in the mixture may not be as concerning to adjacent riparian ecosystems, but copper remains a contaminant of concern in Torch Lake 60 years after mining ceased

First-Principles Study of the Heterostructure, ZnSb Bilayer/h-BN Monolayer for Thermoelectric Applications

ZnSb is widely recognized as a promising thermoelectric material in its bulk form, and a ZnSb bilayer was recently synthesized from the bulk. In this study, we designed a vertical van der Waals heterostructure consisting of a ZnSb bilayer and an h-BN monolayer to investigate its electronic, elastic, transport, and thermoelectric properties. Based on density functional theory, the results show that the formation of this heterostructure significantly enhances electron mobility and reduces the bandgap compared to the ZnSb bilayer, thereby increasing its power factor. These findings highlight the potential of the h-BN monolayer–supported ZnSb bilayer heterostructure in thermoelectric applications, where maximizing energy conversion efficiency is essential