Journals
2025 EN
Beale Kevin · Bras Rafael L. · Romberg Justin
ABSTRACT Soil moisture is the linchpin of the surface hydrologic cycle, controlling the partitioning of water and energy fluxes at the surface. Without it, vegetation, and hence life on the solid Earth as we know it, would not exist. Understanding ecohydrology is understanding the availability of soil moisture to vegetation. Until recently, measuring soil moisture was difficult, expensive, intrusive, and local. NASA's Soil Moisture Active Passive (SMAP) mission changed that by providing global estimates at reasonable frequencies. Ecohydrology and many other hydrologic applications are best when high spatiotemporal resolution soil moisture datasets are available. The SMAP and SMAP‐Sentinel soil moisture products currently possess contrasting spatial and temporal resolutions, but their coincident nature presents an opportunity to learn how to enhance the spatial resolution of SMAP retrievals to obtain a global, high spatiotemporal resolution dataset. However, a challenge in learning from SMAP‐Sentinel data is the presence of missing pixels. In this work, we propose a low‐rank approach to both gap‐fill SMAP‐Sentinel and downscale SMAP and evaluate its performance globally on both held‐out SMAP‐Sentinel data and measurements from SMAPVEX validation datasets. The proposed method outperformed baselines globally on SMAP‐Sentinel data but had mixed performance against retrievals from airborne measurements. A procedure for filling in missing pixels in SMAP‐Sentinel measurements using the low‐rank models was found to outperform alternative interpolation methods. Overall, the results show that the proposed method can recover missing pixels in soil moisture measurements and can be used to compute estimates of high‐resolution SMAP‐Sentinel retrievals from low‐resolution SMAP data.
Journals
2025 EN
Ascanio Alfredo · Louis Brianna · Cannizzaro Andrew
+5 more
Abstract Periodical cicadas ( Magicicada spp.) emerge from the ground every 13‐ or 17‐year intervals across the eastern and midwestern continental United States. Due to their long generation times, these animals are vulnerable to rapid environmental change, which has contributed to decreased densities and even extinction of different Magicicada broods. We investigated trends in population density and emergence phenology of Brood X cicadas across three reproductive events (1987, 2004, and 2021) in southwestern Ohio, comparing habitats with different levels of anthropogenic disturbance or origin: old‐growth forest, rural woodlots, rural fencerows, and urban woodlots (added in 2021). Overall, we found that Magicicada cassini , M. septendecim, and M. septendecula were present in all studied sites, though the most abundant for the region was M. cassini . Our results revealed a generational decline in cicada density in old‐growth forest and rural woodlots, while fencerows, often considered heavily disturbed habitats, showed a doubling in density across generations. Phenological data showed consistent protandry (earlier male emergence), with an increased offset between sexes in the 2021 emergence compared to 1987. Emergence timing also varied across habitats, with rural woodlots showing the earliest emergence and urban woodlots and fencerows (mainly composed by edge habitat) showing the latest. These findings challenge assumptions that disturbed habitats universally reduce insect populations and suggest that treed fencerows may serve as important reproductive refuges under certain conditions. However, variance and delay in female emergence may indicate changing environmental cues or phenological mismatches, potentially reducing reproductive success. To aid conservation efforts, we recommend continued and expanded monitoring of future Brood X emergences, expansion of sampling in old‐growth forest sites, along with incentives to preserve and manage treed fencerows while also expanding existing tracts of forest.
Journals
2025 EN
Nix Paul · Goldstein Adam · Oppenheimer Michael
ABSTRACT Numerous barriers interfere with achieving effective outcomes of climate adaptation and mitigation governance. In the United States, the politicization of climate change and the long‐standing susceptibility of long‐term projects to politicians' short‐term budgetary incentives both heighten the difficulties for effective climate change governance. U.S. quasi‐governmental organizations (QGOs) were traditionally created to address several of these barriers in non‐climate change domains. The properties of QGOs that allow these organizations to address governance barriers may also allow them to cope with shocks more easily than traditional government agencies. Green banks are an emerging and growing form of dedicated climate change governance in the United States. We use the organizational ambidexterity (OA) framework to evaluate the case of the quasi‐governmental Connecticut Green Bank (CGB)'s adaptation to a 2017 state‐instigated budget shock. The OA framework is useful for this case study given its emphasis on managerial response to organizational survival threats. We find that the CGB adapted financially to the shock, as a result of mission and financial drift away from Connecticut state control and policy. The CGB's adaptation to the shock hinged on its quasi‐governmental status—which allowed it to create a nonprofit organization, Inclusive Prosperity Capital (IPC), and pursue activities to render both entities financially and operationally self‐sufficient. We characterize the CGB's adaptive response as hybrid , structural ‐ cyclical , ambidexterity . Our study provides the first empirical description of ambidexterity in the quasi‐governmental space and builds evidence for the utility of applying hybrid ambidexterity theory in the climate change domain. The analysis carries implications for a wide array of public and private organizations that must adapt to survival threats by balancing activities that affect short‐ and long‐term viability within the context of their mission orientation.
Journals
2025 EN
Sanchez Dwight B.
Transitioning from leading undergraduate admissions to managing graduate and professional enrollment is more than a title change — it is a professional evolution. While my own journey spans 16 years and multiple institutions, this article is not only a reflection on my career path; it is alos a guide for enrollment managers across the spectrum. The lessons I learned along the way — from HBCUs to globally ranked universities — apply broadly, regardless of the size, mission, or student population of your institution. Importantly, many of the strategies I developed in the graduate space — such as building deeper relationships, adapting to longer decision cycles, and demonstrating return on investment — are equally applicable to undergraduate recruitment as today's students and families increasingly seek personalized engagement and clarity of value.
Journals
2025 EN
Saarela Svetlana · Healey Sean P. · Yang Zhiqiang
+7 more
ABSTRACT The hierarchical model‐based (HMB) statistical method is currently applied in connection with NASA's Global Ecosystem Dynamics Investigation (GEDI) mission for assessing forest aboveground biomass (AGB) in areas lacking a sufficiently large number of GEDI footprints for employing hybrid inference. This study focuses on variance estimation using a bootstrap procedure that separates the computations into parts, thus considerably reducing the computational time required and making bootstrapping a viable option in this context. The procedure we propose uses a theoretical decomposition of the HMB variance into two parts. Through this decomposition, each variance component can be estimated separately and simultaneously. For demonstrating the proposed procedure, we applied a square‐root‐transformed ordinary least squares (OLS) model, and parametric bootstrapping, in the first modeling step of HMB. In the second step, we applied a random forest model and pairwise bootstrapping. Monte Carlo simulations showed that the proposed variance estimator is approximately unbiased. The study was performed on an artificial copula‐generated population that mimics forest conditions in Oregon, USA, using a dataset comprising AGB, GEDI, and Landsat variables.
Journals
2025 EN
Biagioli Niccolò · Parfyonov Maksim · Meletti Stefano
+16 more
Abstract The ILAE Neuroimaging Task Force publishes educational case reports that highlight basic aspects of neuroimaging in epilepsy, consistent with ILAE's educational mission. In patients with drug‐resistant focal epilepsy who are candidates for surgical intervention, the identification of structural abnormalities is a strong predictor of favorable postoperative seizure outcomes. When conventional imaging is insufficient, the integration of multimodal neuroimaging data with structural, metabolic, and functional imaging modalities is often helpful. The following two illustrative cases from two different centers highlight the challenges and needs to integrate the information from multiple imaging modalities for a more accurate diagnosis and resection planning of drug‐resistant focal epilepsies. This approach can increase the number of patients eligible for surgery while minimizing the risk of postoperative deficits.
Journals
2025 EN
Cohen Nathan T. · Vezina L. Gilbert · Oluigbo Chima
+16 more
Abstract The ILAE Neuroimaging Task Force aims to publish educational case reports that highlight basic aspects of neuroimaging in epilepsy consistent with the ILAE's educational mission. Here, we describe a case series of three neonates with focal cortical dysplasia (FCD)‐related drug‐resistant epilepsy who underwent surgical intervention. The purpose of this series is to demonstrate the difficulties of identifying FCD in this age group and to highlight the potential added value of arterial spin labeling MRI for delineation of the epileptogenic zone. This series also supports the importance of the 2019 ILAE recommendations for structural imaging in epilepsy, the 2009 ILAE recommendations on imaging infants and children with recent‐onset epilepsy, and the 2022 ILAE consensus classification of FCD.
Journals
2025 EN
Chen Xiao · Archer John · Bernhardt Boris C.
+13 more
Abstract The ILAE Neuroimaging Task Force publishes educational case reports that highlight basic aspects of neuroimaging in epilepsy consistent with the ILAE's educational mission. Tuberous sclerosis complex (TSC) is a rare, complex, and multisystem autosomal dominant genetic disorder that arises from variations in the TSC1 or TSC2 genes. While characterized by a wide range of clinical manifestations, TSC commonly presents with epilepsy, which is a clinically challenging feature of the condition. Neuroimaging plays a pivotal role in the early diagnosis, screening, and long‐term monitoring of TSC patients. CT serves as the first‐line imaging tool in emergency settings; yet MRI is the primary diagnostic modality for TSC. In this report, we present two patients with TSC‐related epilepsy and analyze their neuroimaging findings. We also address the diagnostic and therapeutic challenges faced by TSC patients with epilepsy.
Journals
2025 EN
Celikel Resat · Aydogmus Omur · Yilmaz Musa
ABSTRACT In industrial robotics, it is crucial to ensure the completion of ongoing processes in the event of a power outage. In this study, a robotic system integrated with a solar panel production system was designed using the ABB RobotStudio program. The energy consumed by the robot during a single cycle was calculated within the same software. Additionally, the energy consumption of the motors in the belt and table system was estimated based on real‐world systems. To address power interruptions, a flywheel energy storage system (FESS) was designed to ensure the continuation of operations. The FESS is capable of supplying the required energy even at the initial start of the robotic system's mission. A notable aspect of this setup is that the drive systems of the motors operate at 800 V. When functioning as a generator, the FESS delivers this voltage to the DC link of the robotic system by acting as a boost converter. The FESS utilizes a high‐speed BLDC motor, and an LC filter is placed between the motor and the inverter. When the motor operates in generator mode, the filter components enable its use as a boost converter. During a single process cycle, the system's speed ranges between 4500 and 3700 r/s. The FESS system was simulated in the MATLAB/Simulink environment, and the results are presented in graphical form.
Journals
2025 EN
Mehrishi Pragya · Kropáček Jan
Abstract Glacier mass balance is a key indicator of climate change, with most glaciers worldwide exhibiting negative trends due to rising temperatures. However, Adishi Glacier in the Central Caucasus presents an anomaly published by earlier studies. This research uses Ice, Clouds and Land Elevation Satellite‐2 altimetry data (2018–2024) and the Shuttle Radar Topography Mission Digital Elevation Model to assess recent elevation changes and mass balance variations. ERA5 reanalysis data were used to examine potential climatic drivers. Results show persistent thinning in lower glacier regions, while the accumulation area demonstrates sustained elevation gains. The equilibrium line altitude shows a slight upward trend (+3.07 m/year), consistent with global patterns. Notably, Adishi Glacier exhibited a positive mass balance of 0.05 ± 0.17 m w.e. a −1 in 2021 and 0.03 ± 0.06 m w.e. a −1 in 2024, but the mean for 2018–2024 remains negative at −0.31 ± 0.09 m w.e. a −1 . This suggests that, despite short‐term gains, the anomaly is not sustained. Compared to the neighbouring glaciers—Bezengi, Khalde, Tsaneri North and South—which show continuous negative mass balances, Adishi's stability stands out. Regional warming (+0.19°C/year) based on ERA5 reanalysis contributes to ablation zone losses, but glacier hypsometry, with an extensive accumulation area above 4,000 m a.s.l., and orographic effect of snowfall on windward slopes support temporary gains. These favourable conditions, however, are insufficient to maintain a long‐term positive mass balance under ongoing climate change.