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Sky High Insights: Campus Facility Management with Drones:This lightning talk will explore the integration of drone technology in university campus facility management. We will discuss how drone flights capture high-resolution images, enabling the creation of detailed 3D models of campus infrastructure. Leveraging advanced image processing and machine learning algorithms, these models facilitate enhanced data analysis for maintenance and planning.Key benefits include enhanced accuracy in monitoring facility conditions, proactive maintenance strategies, and optimized resource allocation. Through case studies, we will demonstrate how to prepare for drone flights and illustrate how the integration of drones with AI and machine learning can transform facility management, fostering smarter and more sustainable campus environments.Building accurate range maps for California’s 104 tree species:Biogeography is the study of the distribution of biota across space. In this way, it can inform every kind of ecological study. So, if we’re going to study biota across space, including predicting where those biota might be in the future or how they could respond to external pressures, we need a good estimate of where those biota are now. In essence, we need a good species range map. The last major effort to systematically map tree species ranges in California was done by Griffin and Critchfield (1972) of the U.S. Forest Service, over 50 years ago. Since then, thousands of studies have been completed with coordinates for trees, and many thousands more civilians have collected GPS points in public repositories for citizen science, advocacy, or enjoyment. After vetting for accuracy, this data can significantly enhance existing range maps. Also, recent high-quality vegetation mapping efforts by public agencies can provide both additional “presence” data to expand range maps beyond existing known boundaries and “absence” data in the sense that they can be used to subtract out unlikely range area within existing known boundaries.In this presentation, we’ll discuss the partially-automated GIS workflow we’ve developed for building the most accurate and comprehensive range maps for California’s 104 tree species, from creating the highest-quality-ever digitization of the Griffin and Critchfield (1972) range maps to collecting, processing, and incorporating hundreds of additional datasets to subtracting out non-range areas. We’ll also discuss how we’re using these state-of-the-art maps to assess the climate exposure, fire risk, and operational priority (seed demand) of each tree species to inform seed collection efforts for reforestation, as well as examples of how the actual map-building process can be used to address some fundamental questions in biogeographical theory.Hand-drawn historic maps: Utilization and conversion of unique features into Geographic Information Systems (GIS):The GIS Center at the University of California, Merced provides research services to faculty and is responsible for managing and maintaining a geospatial collection for our students and researchers. We support Geographic Information Systems (GIS) software for over 500 users yearly and provide workshops and consultations. GIS Center technical research staff have provided consulting services to researchers and direct project support. Through four case studies, we will detail our processes for converting historic maps into GIS products that contribute to research publications and data sets. Specifically, we will discuss the technical demands and research benefits of georeferencing and vectorizing digitized historic maps utilizing various methods including machine learning and heads up digitizing and sharing that data via ArcGIS Online and other cloud-based applications. We conclude with recommendations for others embarking upon this type of work.

The combination of electrophysiology and electrochemistry acquisition methods using a single carbon fiber microelectrode (CFM) in the brain has enabled more extensive analysis of neurochemical release, neural activity, and animal behavior. Predominantly, analog CMOS (Complementary Metal Oxide Semiconductor) switches are used for these interleaved applications to alternate the CFM output between electrophysiology and electrochemistry acquisition circuitry. However, one underlying issue with analog CMOS switches is the introduction of transient voltage artifacts in recorded electrophysiology signals resulting from CMOS charge injection. These injected artifacts attenuate electrophysiology data and delay reliable signal observation after every switch actuation from electrochemistry acquisition. Previously published attempts at interleaved electrophysiology and electrochemistry were able to recover reliable electrophysiology data within approximately 10-50 ms after switch actuation by employing various high-pass filtering methods to mitigate the observed voltage artifacts. However, high-pass filtering of this nature also attenuates valuable portions of the local-field potential (LFP) frequency range, thus limiting the extent of network-level insights that can be derived from in vivo measurements. This paper proposes a solution to overcome the limitation of charge injection artifacts that affect electrophysiological data while preserving important lower-frequency LFP bands. A voltage follower operational amplifier was integrated before the CMOS switch to increase current flow to the switch and dissipate any injected charge. This hardware addition resulted in a 16.98% decrease in electrophysiology acquisition delay compared to circuitry without a voltage follower. Additionally, single-term exponential modeling was implemented in post-processing to characterize and subtract remaining transient voltage artifacts in recorded electrophysiology data. As a result, electrophysiology data was reliably recovered 3.26 ± 0.22 ms after the beginning of the acquisition period (a 60% decrease from previous studies), while also minimizing LFP attenuation. Through these advancements, coupled electrophysiology and electrochemistry measurements can be conducted at higher scan rates while retaining data integrity for a more comprehensive analysis of neural activity and neurochemical release. [ABSTRACT FROM AUTHOR]

Background Deep brain stimulator (DBS)–related infection is a recognized complication that may significantly alter the course of DBS therapy. We describe the Mayo Clinic Rochester experience with DBS-related infections. Methods This was a retrospective study of all adults (≥18 years old) who underwent DBS-related procedures between 2000 and 2020 at the Mayo Clinic Rochester. Results There were 1087 patients who underwent 1896 procedures. Infection occurred in 57/1112 (5%) primary DBS implantations and 16/784 (2%) revision surgeries. The median time to infection (interquartile range) was 2.1 (0.9–6.9) months. The odds of infection were higher with longer operative length (P =.002), higher body mass index (BMI; P =.006), male sex (P =.041), and diabetes mellitus (P =.002). The association between infection and higher BMI (P =.002), male sex (P =.016), and diabetes mellitus (P =.003) remained significant in a subgroup analysis of primary implantations but not revision surgeries. Infection was superficial in 17 (23%) and deep in 56 (77%) cases. Commonly identified pathogens were Staphylococcus aureus (65%), coagulase-negative staphylococci (43%), and Cutibacterium acnes (45%). Three device management approaches were identified: 39 (53%) had complete device explantation, 20 (27%) had surgical intervention with device retention, and 14 (19%) had medical management alone. Treatment failure occurred in 16 (23%) patients. Time-to-event analysis showed fewer treatment failures with complete device explantation (P =.015). Only 1 individual had complications with brain abscess at failure. Conclusions Primary DBS implantations had higher rates of infection compared with revision surgeries. Complete device explantation was favored for deep infections. However, device salvage was commonly attempted and is a reasonable approach in select cases given the low rate of complications. [ABSTRACT FROM AUTHOR]