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Closed-Loop Neuromorphic Deep Brain Stimulation using Deep Spiking Q-Networks
No full textCurrent open-loop deep brain stimulation (DBS) implants continuously apply electrical current to reduce motor symptoms in patients with Parkinson\u27s disease (PD). However, neural dynamics are patient-specific, and open-loop DBS systems are energy-inefficient as they can provide ineffective and unnecessary stimulus. Closed-loop DBS systems offer a more efficient and adaptive approach to delivering DBS. Advances in simulating biomarker responses across cortex-basal ganglia-thalamus (CBGT) networks has accelerated closed-loop DBS development. While deep learning shows promise for optimizing closed-loop stimulation, its high computational demands challenge the battery life of implanted DBS devices. Spiking neural networks (SNNs) offer an energy-efficient alternative to traditional neural networks. They benefit from the ability to take advantage of sparse activations of neurons and to transmit information as spikes. We propose a test bench for DBS parameter optimization by introducing a rat model of the CBGT network in a reinforcement learning (RL) environment and train a deep spiking Q network (DSQN) to validate an end-to-end spike model. This marks a step towards the first closed-loop benchmark with end-to-end spiking, from sensory inputs, to the model, to the stimulus outputs
Public support for puma reintroduction in the eastern United States
No full textPumas (Puma concolor) are among the species identified as having the potential to enhance ecosystem function. Previous research highlights sufficient ecological habitat to support pumas in the eastern United States; however, their reintroduction requires social and institutional support as well. To this end, we conducted research to assess attitudes about puma reintroduction among key constituencies like hunters, rural residents, and young people. We sampled 2756 respondents across seven states (Massachusetts, Maine, New Hampshire, New York, Pennsylvania, Vermont, and West Virginia). Ratios of strong support (for puma reintroduction) to strong opposition across states ranged from 4:1 to 13:1, and support outweighed opposition in every state. Our results contrasted with common assumptions that hunters, rural residents, and people who identify as politically conservative oppose carnivore conservation and reintroduction. We found marginal differences among categories of people, but overall little variation in support exhibited by different groups. People who identified very strongly as hunters were more supportive of reintroduction than those who did not identify as hunters at all. Taken together, the presence of quality habitat and support for puma restoration warrant further exploration. However, federal funding for state-based restoration efforts likely requires the inclusion of pumas in State Wildlife Action Plans (SWAPs), which are currently under a 10-year revision due to be published this year (2025)
Near-infrared fluorescent probe featuring a large Stokes shift for sensitive detection of NADH in diabetic models
No full textNicotinamide adenine dinucleotide (NADH) is a key metabolic and redox signaling molecule closely associated with metabolic disorders, including diabetes. Developing effective methods for monitoring NADH levels in cells and in vivo is critical for advancing early diagnostic strategies for such diseases. In this work, we report two novel fluorescent probes (A and B) for NADH detection, based on the conjugation of phenanthridinium and 1-methylquinolinium via a double bond. Upon reaction with NADH, the 1-methylquinolinium moiety undergoes specific reduction to form an electron-donating 2-hydroquinoline group, which initiates an intramolecular charge transfer (ICT) process, leading to significant fluorescence enhancement. Compared to Probe A, Probe B incorporates an additional N,N-diethylamine group on the phenanthridinium unit, acting as a second electron donor. This modification results in markedly improved sensing performance, including a rapid response time of 20 min, near-infrared fluorescence enhancement with large Stokes shift (130 nm), the lower detection limit, and excellent selectivity against interfering species. Probe B was effectively employed for visualization the NADH levels in both endogenous and exogenous cellular environments, as well as in diabetic cells. Furthermore, in vivo imaging studies in diabetic mice demonstrated its capability to monitor NADH fluctuations under pathological conditions. This study not only provides a novel design strategy for developing NADH fluorescent probes with large Stokes shifts, but also highlights the potential of Probe B as a powerful near-infrared fluorescent tool for real-time NADH imaging, offering promising applications in the early diagnosis and monitoring of diabetes
Analysis and modeling of paired droplet evaporation on heated substrates considering vapor-shielding and natural convection effects
No full textThis study investigates the evaporation characteristics of paired droplets on heated substrates, focusing on the effects of droplet spacing and substrate temperature. Paired deionized (DI) water droplets are deposited on a copper substrate using a multi-syringe pump, and their evaporation dynamics are analyzed through shadowgraph imaging and OpenCV-based image processing. The results show that the contact line remains pinned for approximately 90 % of the total evaporation time before depinning occurs, regardless of droplet spacing and substrate temperature. It is also found that the vapor-shielding effect decreases with increasing droplet spacing and substrate temperature due to enhanced natural convection, causing the evaporation time of paired droplets to converge toward that of a single droplet. Moreover, the results indicate that droplet spacing significantly affects the evaporation time than substrate temperature. A Rayleigh number-based model is suggested to predict the evaporation rate by combining the diffusion and natural convection effects, showing good agreement with the experimental data with a maximum relative error of less than 5 %
RURAL ELECTRIFICATION FOR HEATING AND COOLING: CHALLENGES AND OPPORTUNITIES FOR EQUITABLE DEVELOPMENT IN THE RURAL NORTH
No full textAbstract
This study examines the opportunities and challenges of electrifying heating and cooling systems in rural northern communities, with a focus on equity and justice. Anchored in three community case studies—Baraga County, Michigan; Ashland and Iron Counties, Wisconsin; and Beltrami and Clearwater Counties, Minnesota—the research investigates socio-economic and infrastructural barriers to electrification in regions historically impacted by extractive industries. These case studies, selected for their shared histories of resource extraction and active participation of Tribal Nations, including the Keweenaw Bay Indian Community (KBIC) and the Red Lake Reservation, reveal significant disparities in energy access and affordability. Using a mixed-methods approach, including an online survey of household energy use, the study finds that rural northern communities face high energy burdens, with 26% of households spending over 10% of their income on energy costs. Heating remains heavily reliant on fossil fuels, with only 4.6% of households using heat pumps, while cooling demand is increasingly met by inefficient systems, such as window air conditioners. Tribal Nations members and low-income households bear a disproportionate share of these challenges, exacerbated by poor housing insulation and frequent power outages. These findings underscore the need for equitable electrification policies that address energy poverty, improve housing efficiency, and support renewable energy development in rural northern regions. By centering the sovereignty and priorities of Tribal Nations, as well as the unique needs and histories of rural communities with post-extractive legacies, this research contributes to supporting decision making for a transition to more sustainable energy systems that are responsive to the unique needs of vulnerable communities.
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INNOVATIONS IN BALANCED MIX DESIGN: ESTABLISHING GWP THRESHOLDS FOR VARIOUS NMAS AND EVALUATING SUPERPAVE VS. BMD IN HIGH CONTENT RUBBER ASPHALT
No full textTraditional volumetric asphalt mix design methods, such as Superpave, frequently struggle to address critical performance parameters, leading many agencies to seek more robust approaches. Balanced Mix Design (BMD) has emerged as a forward-looking alternative by directly measuring rutting and cracking resistance in the laboratory. In this study, BMD principles were applied to asphalt mixtures featuring three distinct NMAS mixes and two high content rubber mixes, introduced through both dry and semi-wet processes. Compared with conventional volumetric constraints, BMD provided greater flexibility in adjusting binder content and gradation to accommodate elevated crumb-rubber levels. The resulting mixtures satisfied both rutting and cracking thresholds more consistently than those designed under Superpave criteria, demonstrating BMD’s capability to integrate substantial recycled materials without compromising performance. The successful utilization of up to 24% crumb rubber underscores the potential for higher waste-tire reuse in asphalt pavements, contributing to circular economy targets. In parallel, Environmental Product Declarations (EPDs) were leveraged to calculate the Global Warming Potential (GWP) of each BMD-optimized mixture. By aligning GWP analyses with mechanical performance tests, the study introduces preliminary GWP threshold values tied to BMD criteria. This approach ensures that mixtures achieving balanced resistance to rutting and cracking also align with broader environmental objectives, such as reducing carbon footprints in infrastructure projects. The findings thus highlight BMD’s dual benefits: it not only optimizes mechanical performance but also accommodates sustainability imperatives, surpassing the limitations of purely volumetric methods. Taken as a whole, this research positions BMD as a versatile, future-oriented framework for the design of high-performing, low-impact asphalt pavements
Smoke Plume Dispersion Animation for the Pacific Palisades Fire and the Eaton Fire from January 8-13, 2025, in Southern California
No full textIn January 2025, wildfires erupted in Southern California, impacting the Pacific Palisades and Eaton areas of Los Angeles County. These fires heavily impacted areas physically, socially, and economically. With advancements in thermal sensing technology, remote sensing techniques have become critical for wildfire analysis. GIS is now essential for analyzing remote sensing data and helps in understanding fire behavior. Consequently, the wildfires in these regions were studied using methods to (1) assess damaged areas, (2) identify factors influencing wildfire vulnerability, (3) monitor real-time air quality and smoke dispersion, and (4) estimate burned areas. With the above objectives, geospatial data, including satellite imagery, Digital Elevation Models (DEM), Land Cover raster, air pollutant data, and smoke plume data, were collected. The DEM and Land Cover data were used to create a Fire Risk Index, helping predict vulnerable areas where fires may originate and spread. Air quality data from January 2025 helped demonstrate harmful environmental effects, while smoke dispersion data showed how remote sensing warrants real-time fire monitoring. Post-fire damage analysis specified on burned and structurally damaged areas to evaluate fire severity.
Results showed that steeper slopes are more vulnerable to fire spread than flatter slopes, although slope does not solely cause fires. Overall, the movement of fires is heavily driven by topography. The monitoring of wildfires showed that meteorological conditions and air quality data help dictate public health decisions and efficiently distribute resources. Post-fire assessment of structural damage and burned areas supports rehabilitation planning and a solid approach to assessing long-term damage
METHOD FOR ASSESSING GASOLINE POWERED INTERNAL COMBUSTION ENGINE EXHAUST ACCUMULATION WHEN IDLING IN ENCLOSED SPACE BY AUTOMATIC SHUT OFF
No full textAbout 120 fatalities/year are caused by Carbon Monoxide (CO) poisoning outside of the vehicle which can take place in the garage or attached house. A controlled test environment was created to mimic a garage with representative ventilation, volume, and instrumentation. Tests were performed with vehicles of varying engine displacement size using parameters tuned to replicate four scenarios of vehicle operation including vehicle start state, HVAC operation, and ambient temperature. A house model was built to model CO accumulation using realistic air exchange rates to simulate air transfer between the garage and attached house. Depletion of Oxygen (O2) in the garage resulted in high CO concentration tailpipe gases after Critical O2 occurred. Critical O2 was the O2 concentration when engine combustion degraded and toxic tailpipe gas creation increased. Two vehicle shut-off methods were developed and simulated to assess their effectiveness. Each shut-off method prevented any potentially fatal scenario
ULTRASOUND SHEAR WAVE ELASTOGRAPHY: DEVELOPMENT OF TISSUE MODELS AND INVESTIGATION OF SHEAR WAVE VARIABILITY
No full textUltrasound shear wave elastography (USWE) is an evolving and promising clinical tool for noninvasively measuring in vivo soft tissue biomechanical properties. Assumptions incorporated into the clinical workflow and technical limitations have created gaps between theoretical and clinically derived solutions. The heterogeneity of the fibrotic liver tissue, composition of the background, such as the presence of fatty liver tissue, and the preferred local orientation of the scarred fibrotic liver tissues embedded into the liver parenchyma, may contribute to the uncertainty in USWE measurements. This study aims to systematically investigate four cofounding factors (i.e., size, volume fraction, orientation of the fibrotic inclusions, fatty background) using computer simulations, to describe the multifaceted impact on shear wave speed (SWS) variability (i.e., SWS standard deviation [STD]). Additionally, a machine-learning-based approach will be used to establish a relationship between the simulated fibrotic liver tissue microstructure (i.e., spatial characteristics [SC]) and the calculated SWS variability.
Even though volume fraction and the SWS estimates (mean SWS and SWS-STD) were highly correlated, percent inclusion as a single predictive factor was not an accurate indicator of the SWS estimates. For this study, none of the individual SC features were able to predict the SWS estimates. Both SWS estimates provided unique information regarding the tissue model microstructure and should be considered when analyzing fibrotic liver tissue. Additionally, this study demonstrated that both fibrosis and fatty background impact the SWS-STD and that the SWS-STD distributions do not follow a Gaussian distribution. While the SWS-STD increased with fibrosis size and volume fraction, the SWS-STD decreased as the fatty background increased. The shape of the distribution did not follow a consistent trend across fibrosis inclusion levels, fibrosis sizes, fibrosis orientations, and percent fatty background for either SWS estimates. This study provided evidence that the current clinical guidelines, regarding cut-off values for the different METAVIR Fibrosis stages, overestimate the fibrosis levels in the presence of steatosis (i.e., fatty liver tissue). These findings demonstrate that USWE numerical modeling is a promising area for research that holds the potential to close the gaps between the \u27true\u27 biological tissue response and the clinically measured findings