bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced Na‐Ion Electrochemical Performance through Cu Doping‐Mediated Sb2Se3 Phase Transformation into CuSbSe2 with Improved Kinetics
Authors: Ul Islam Shah Jahan , Majid Kowsar , Wahid Malik 
Published: November 2024

AbstractThis work investigates the influence of structural and electronic modification on the electrochemical performance of conversion and alloying materials. The CuSbSe2, a promising 2D layered conversion, and alloying material is being investigated with references to parent pristine Sb2Se3 and a doped version of later Sn0.2Sb1.8Se3 for their sodium‐ion battery performance. The CuSbSe2 with layered structure is well known to accommodate lattice distortions via inter‐layer movement, potentially mitigating distortions brought about by the Alkali ion (Na in this case) insertion. In contrast, the parent conversion‐cum‐alloying material Sb2Se3 with its one‐dimensional crystal structure leads to structural disintegration during battery operation. The Sn‐doped analog, Sn0.2Sb1.8Se3, comparatively exhibits enhanced kinetics owing to the reduced long‐range order. The 2D layered, CuSbSe2 despite exhibiting 2D long‐range order exhibits superior electrochemical performance owing to the favorable electronic and structural features. The CuSbSe2 exhibits a reversible capacity of 881 mAh g−1 compared to 516 mAh g−1 for Sn0.2Sb1.8Se3 and 429 mAh g−1 for Sb2Se3, with an improved Coulombic efficiency as well. The transient electrochemical investigations of Electrochemical Impedance Spectroscopy (EIS) and Galvanostatic intermittent titration techniques (GITT) reveal that better performance exhibited by CuSbSe2 may well be attributed to kinetics owing to enhanced diffusion coefficients in the intercalation and conversion regime.
Foams‐To‐Films: A Facile Approach Towards Space‐Confined CVD Growth of MoS2
Authors: Currie Taylor M. , Davalos Barrios Jesse , Lan Nguyen Moc , Tetard Laurene , Jurca Titel 
Published: November 2024

Abstract2D materials have rapidly become the building blocks for the next generation of semiconducting materials and devices, with chemical vapor deposition (CVD) emerging as a prefered method for their synthesis. However, the predictable and reproducible growth of high quality, large 2D monolayers remains challenging. An important facet is controlling the local environment at the surface of the substrate – here, space‐confinement techniques have emerged as promising candidates. We demonstrate that space‐confined CVD growth using microstructured MoOx grown on Ni foam is an appealing approach for rapid growth of high quality MoS2 monolayers; a very important subset of 2D materials. This method eschews the use of powders which can be more difficult to control. By incorporation of a porous barrier in the Ni foam support, the rate of delivery of both the Mo and S source to the substrate is dampened, leading to coverage of large, high quality, mono‐to‐few layer triangular domains as confirmed by Raman and photoluminescence (PL) spectroscopies together with atomic force microscopy (AFM) height measurements.
Light‐Induced Transformation of a Supramolecular Gel to a Stronger Covalent Polymeric Gel
Authors: Saleem Sabith K. , Pramod Thejus , Kuruva Pruthvi , Haridas Shyamkumar V. , Shanmugam Anusha , Thalakulam Madhu , Sureshan Kana M. 
Published: November 2024

AbstractA polymerizable diacetylene gelator, containing urea and urethane groups, that congeals various non‐polar solvents was synthesized. The gelator molecules self‐assemble forming non‐covalent polymers through intermolecular hydrogen bonding, as evidenced from FT‐IR and concentration‐dependent 1H NMR spectroscopy. The self‐assembly positions the diyne units of adjacent molecules at proximity and in a geometry suitable for their topochemical polymerization. UV irradiation of the gel resulted in topochemical polymerization, transforming the non‐covalent polymer to a covalent polymer, in situ, in the gel state. The polymerization was confirmed by characterizing the polydiacetylene (PDA) using UV‐Vis and Raman spectroscopy. Time‐dependent rheological studies revealed gradual strengthening of the gel with the duration of irradiation, suggesting that the degree of polymerization increases with the duration of irradiation. The PDA formed is a semiconductor, which might be useful for various applications.
An Investigation of the Structures of [(Glycine)(1‐Methyluracil)]M+ Complexes (M=H, Li, Na, K) in the Gas Phase by IRMPD Spectroscopy and Theoretical Methods
Authors: Atkinson Samuel C. , Fridgen Travis D. 
Published: November 2024

AbstractThe presence of ions in the complexation of molecules can profoundly affect the structure, resulting in changes to functionality and stability. These non‐covalent interactions drive many biological processes both necessary and inimical and require extensive research to understand and predict their effects. Protonated and alkali metalated complexes of glycine (Gly) and 1‐methyluracil (1‐mUra) were studied using infrared multiphoton dissociation (IRMPD) spectroscopy and density functional theory (DFT) calculations. The experimental and simulated vibrational spectra were compared to help elucidate the structure of each complex. The lowest energy structure for [(Gly)(1‐mUra)]H+ consists of amine protonated Gly bound to O4 of canonical 1‐mUra through a single ionic hydrogen bond with another, intraglycine ionic hydrogen bond between the protonated amine group and the carbonyl oxygen. For [(Gly)(1‐mUra)]Li+, [(Gly)(1‐mUra)]Na+ and [(Gly)(1‐mUra)]K+, the experimental spectra are most consistent with the metal cations binding in a trigonal planar geometry with 1‐mUra bound to the metal cation via the O4 carbonyl. In [(Gly)(1‐mUra)]Li+ and [(Gly)(1‐mUra)]Na+, the metal cation is bound to canonical Gly via the carbonyl oxygen and amine nitrogen, but in [(Gly)(1‐mUra)]K+, Gly is bound through both oxygens and contains an intraglycine hydrogen bond from the hydroxyl to the amine nitrogen. It was found that the B3LYP/6‐31+G(d,p) vibrational spectra are most consistent with the experimental spectra, but M062X was better than B3LYP at determining the lowest‐energy structures.
Evolutionary History and Ecology of Andrena (Foveoandrena) androfovea: A New Nearctic Mining Bee (Hymenoptera, Andrenidae) Species and Subgenus
Authors: Bossert Silas , Hung Keng‐Lou James , Neff John L. 
Published: November 2024

ABSTRACTWith about 1700 described species, the mining bee genus Andrena is a rapidly diversifying lineage and one of the most species‐rich groups of bees. Recent phylogenomic advances have greatly improved our understanding of the phylogeny of the genus, yet many species still await description, subgeneric assignments that are in line with their evolutionary history, as well as study of their morphology and behavior. Here we provide a comprehensive account of a newly discovered species, Andrena androfovea n. sp. We sequence the genome of the new species and include it in the presently most comprehensive phylogenomic analysis of Andrena using ultraconserved element (UCE) sequence data, comprising 264 samples and 249 species. Given the recovered phylogenetic position of the new species, we establish a new subgenus, Foveoandrena, provide a detailed morphological description, and discuss the antiquity and historical biogeography of the lineage in light of molecular divergence time estimates. Lastly, we study and document the foraging behavior of the new species with photos and video footage, and discuss the species' unusual host plant associations with Chamaesaracha and Quincula, both Solanaceae. Being likely oligolectic on these plants, we present the first documented case of an Andrena species being narrowly associated with members of this plant family. By integrating multiple lines of documentation, our study provides a particularly detailed account of species discovery and description.
An Updated Framework for Modeling White‐Tailed Deer (Odocoileus virginianus) Habitat Quality in Illinois, USA
Authors: Mori Jameson , Brown William , Skinner Daniel , Schlichting Peter , Novakofski Jan , Mateus‐Pinilla Nohra 
Published: November 2024

ABSTRACTWhite‐tailed deer (Odocoileus virginianus) are a cervid species found mostly in the Americas. Managing white‐tailed deer requires understanding their relationship with the environment, which was characterized by Roseberry and Woolf (Wildlife Society Bulletin 1, 1998, 252) for all counties in Illinois, USA, who incorporated habitat quantity and quality in a deer habitat suitability index. However, this index was based on satellite imagery from 1996 and did not explore the smaller spatial scales used by deer. Our study addressed these gaps by developing a deer land cover utility (LCU) score for each TRS (township, range, and section), township, and county in Illinois based on the methodology outlined in Roseberry and Woolf (Wildlife Society Bulletin 1, 1998, 252) but using data from the National Land Cover Database (2001–2021). These deer LCU scores were validated against minimum deer population data using Bayesian regression with additional covariates relevant to hunting and deer density. These models performed well with Bayesian R2 values of 0.501 (TRS), 0.5 (township), and 0.969 (county). The regression coefficients for the deer LCU scores were statistically significant (95% credibility interval not containing 0) and positive at the TRS, township, and county levels, reflecting the expected relationship between minimum deer density and deer LCU. Predictions made by these regression models on new data were accurate, with the median absolute difference between the true and predicted values being 0.398 deer/km2 for TRS', 0.085 deer/km2 for townships, and 0.066 deer/km2 for counties. This deer LCU could be used in other studies about deer in Illinois or studies in which deer are a relevant factor such as investigations about deer disease or tick distribution. This modeling approach could also be adapted to different wild species, locations, and/or time periods for which land cover data is available.
The Effect of Grazing on Central Anatolian Steppe Vegetation: A Modeling Approach Using Functional Traits
Authors: Bahar Anıl , Tavşanoğlu Çağatay 
Published: November 2024

ABSTRACTGrazing is a major ecological driver that influences vegetation dynamics globally. We investigated the long‐term effects of different grazing regimes on the vegetation structure of the Central Anatolian steppes, a region characterized by its unique convergence of biogeographical influences and historical land use. We employed the spatially explicit FATELAND model to simulate vegetation dynamics over a 50‐year period under three distinct grazing scenarios: no grazing, moderate grazing, and overgrazing. Our simulations incorporated a range of plant functional traits to predict changes across five different vegetation types in Central Anatolia, including woodland steppes and treeless steppes. The simulations revealed that moderate grazing supports the diversity and abundance of various plant functional groups, excluding resprouter trees, which flourish under no grazing conditions. In contrast, overgrazing leads to significant reductions in the abundance of perennial forbs and both spiny and non‐spiny subshrubs, often resulting in a shift toward grassland dominated by resprouter gramineae or an annual herb‐dominated grassland, depending on the initial abundance of gramineae. Our findings highlight the critical role of grazing management in maintaining biodiversity and ecological stability in steppe ecosystems. While moderate grazing can enhance plant functional group diversity, overgrazing significantly threatens the ecological integrity of the Central Anatolian steppes. In conclusion, our modeling approach reveals that the grazing regime is a major driver in shaping the vegetation structure of Central Anatolian steppes. Grazing management strategies that are adjusted to the ecological characteristics and historical context of specific regions are required to prevent degradation and promote sustainable grassland vegetation.
Growth and Survival Outcomes for Immature Gopher Tortoises in Contrasting Habitats: A Test of Drone‐Based Habitat Assessment
Authors: Stemle Leyna R. , Sorfleet Julie M. , Moore Chelsea L. , Christie Jack T. , Searcy Christopher A. , Rothermel Betsie B. 
Published: November 2024

ABSTRACTJuvenile growth rate is a critical demographic parameter, as it shortens the time to maturity and often dictates how long individuals remain vulnerable to predation. However, developing a mechanistic understanding of the factors determining growth rates can be difficult for wild populations. The gopher tortoise (Gopherus polyphemus) is an ecosystem engineer threatened by habitat loss and deficient management of pinelands in the southeastern United States. We investigated the factors governing immature gopher tortoise growth and explored the use of drone‐based imagery for habitat assessment by comparing predictive models based on ground‐based plant surveys versus drone‐derived data. From 2021 to 2022, we tracked and measured immature tortoises in native sandhill and human‐modified, ruderal habitat in south‐central Florida. Using quarterly, high‐resolution drone imagery, we quantified plant cover types and vegetation indices at each occupied burrow and measured the frequency of occurrence of forage species by hand. Annual growth rates of immature tortoises in ruderal habitat were higher than those in sandhill and were the highest published for this species. Models based on drone‐derived data were able to explain similar proportions of variation in growth as ground‐collected measures of forage, especially during the late dry season when both types of models were most predictive. Habitat differences in forage nitrogen content were also more pronounced during this season, when dominant ground cover in ruderal habitat (bahiagrass) had much higher nitrogen content than dominant ground cover in sandhill (wiregrass). Despite concerns about potential growth‐survival trade‐offs, tortoises in ruderal habitat did not exhibit lower apparent survival. Our findings indicate that habitat dominated by nutritious non‐native grass can provide a valuable supplement to native sandhill through the mechanism of increased growth rates due to higher forage quality. Finally, our study demonstrates that drone technology may facilitate management by providing less labor‐intensive ways to assess habitat quality for this and other imperiled herbivores.
Predicting the Impact of Climate Change on Corylus Species Distribution in China: Integrating Climatic, Topographic, and Anthropogenic Factors
Authors: Liu Yu , Chen Lin 
Published: November 2024

ABSTRACTThis study investigates the impact of climate change on the distribution of Corylus species in China using the MaxEnt model. Key environmental variables, such as Bio6 (mean temperature of the coldest month) and human footprint, emerged as significant determinants of habitat suitability. The study reveals substantial shifts in suitable habitats due to global warming and increased precipitation, with notable expansion towards higher latitudes. Species like Corylus heterophylla Fisch. ex Bess. and Corylus mandshurica Maxim. demonstrate resilience in extreme conditions, highlighting the importance of specific ecological traits for conservation. Future projections under various SSP scenarios predict continued habitat expansion, emphasizing the need for targeted conservation strategies to address the critical role of human activities. This research highlights the complex interplay between climatic, topographic, and anthropogenic factors in shaping Corylus habitats, advocating for integrated adaptive management approaches to ensure their sustainability amid ongoing climate change.
A Well‐Advanced High‐Throughput Test System for Electrocatalytic Screening Applications Under Industrial Relevant Conditions – A Perspective to Accelerate Electrolysis Research and Development
Authors: Dogan Deniz , Hecker Burkhard , Hou Xuehuai , Dessel Inka , Müller Andreas , Wasserschaff Guido , Köcher Simone S. , Karyofylli Violeta , Kungl Hans , Tempel Hermann , Eichel Rüdiger‐A. 
Published: November 2024

ABSTRACTElectrolysis is a dynamic research area in which both mature and new promising processes, such as alkaline water electrolysis and electrochemical CO2 reduction, are under enormous development pressure due to their high relevance for the energy sector. High‐throughput (HT) technologies are efficient screening platforms that can accelerate research activities and significantly shorten development times. Over the past 25 years, various HT platforms have found their way into electrochemical research. These typically have one or more major disadvantages: they are characterized by abstract experimental conditions, designed for a specific application or process, or generate insufficiently comparable data. In this publication, we present a newly developed HT test system that enables the parallel operation of 16 electrochemical bench‐scale flow cells under industry‐relevant test conditions. The specially developed modular flow cell can be operated variably in the fully automated system and allows research into the most common applications in electrochemistry for many different processes with a focus on all relevant variants of water electrolysis and electrochemical CO2 reduction. Both the HT system and the developed flow cell are designed to accelerate the generation of reliably reproducible data with high comparability in order to strengthen scientific exchange. The fully automated process control, online analysis and programmable feedback loops of the HT test system provide great potential for the design of experiment strategies. The implementation of Design of Experiment strategies will maximize the testing efficiency of this innovative research system.
Epilepsy in CHAD: Realities, constraints, and prospects
Authors: Sakadi Foksouna , Christian Madjirabe Ngardidjim , Lamine Toure Mohamed , Dakisia Kamis , Christelle Nderbe Melom , Doufene Diponbe , Foksia Lintel Anicet , Nguelngar Carlos Othon , Balanmo Anatole , Babing‐ne Kobada , Nalire Desire , Amara Cisse 
Published: November 2024

AbstractEpilepsy is a significant public health problem. More than 50 million people worldwide live with epilepsy, and over three‐quarters of them are in low‐ and middle‐income countries. The situation in Chad regarding people with epilepsy is challenging to assess, starting from the shortage of scientific data, the inadequacy of technical facilities, the lack of human resources, and the inadequacy of government action. The Ministry of Health and Chadian Society of Neurology are looking forward to prioritizing epilepsy as well as improving the living conditions of persons with this disease.The epilepsy treatment issue is also problematic. Most of the patients are either off treatment or under‐medicated. Few antiseizure medications (ASMs) are available, notably carbamazepine, phenobarbital, and valproic acid. Epilepsy remains little‐known and does not seem to be a priority for decision‐makers. We describe the current situation in Chad, to improve the conditions under which epilepsy is treated.Plain Language SummaryEpilepsies is a chronic brain problem that is common in poorer settings. The daily lives of people with epilepsy are chaotic in Chad. The challenges are numerous, particularly those related to health infrastructures, due to the lack of adequate diagnostic means and the lack of neurologists. The cultural and language challenges, especially since epilepsy is still considered the devil's disease and the name differs according to the dialects. Stigmatization is also frequent and is often responsible for school dropout, refusal, or dismissal from work. Care and prevention are daily challenges that require government action. Social coverage is insufficient and almost absent in rural areas. It is urgent to prioritize epilepsy in future action plans and also to increase awareness of the conditions to overcome these challenges.
Research on the attenuation characteristics of seismic energy in multicoal seam mining and the warning method of rock burst
Authors: Mu Hongwei , Zhang Yongliang , Gao Mingzhong , Zhu Quanlin , Li Jingbo , Cao Jinfeng , Fan Wentao 
Published: November 2024

AbstractThe mechanism of rock burst induced by the superposition of dynamic and static loads in multicoal seam mining is unique. To investigate the propagation attenuation law of large‐energy microseismic events and the induced mechanism of rock burst under this condition, this study employs FLAC3D's dynamic module to simulate and analyze the influence of propagation distance, overburden structure in multicoal seam mining, and interlayer plastic zone on vibration wave attenuation. Results indicate that when coal seams are mined at close distances, vibration waves experience significant attenuation while passing through the plastic zone between two layers of coal. At equal attenuation distances, multicoal seam mining structures exhibit greater effects on vibration wave attenuation. Considering differences between rock‐burst induction mechanisms in close‐distance coal seam group mining versus single coal seam mining, a discriminant criterion for rock bursts induced by superimposed dynamic and static loads in multicoal seam mining is established along with a monitoring and early warning method suitable for such conditions.
Automated identification of earthen berms in Western US rangelands from LiDAR‐based digital elevation models
Authors: Xu Haiqing , Nichols Mary H. , Lapides Dana , Crompton Octavia 
Published: November 2024

AbstractEarthworks such as earthen berms have been constructed across the western US since the late 1800s to mitigate erosion in landscapes where water is both the dominant driver of erosion and the limiting resource for biota. Berms alter hydrologic, geomorphic and ecologic processes by intercepting runoff and altering patterns of water availability in the landscape. Understanding site‐specific changes in process dynamics requires accurate mapping of berm locations and knowledge of their condition. This paper presents an automated, object‐based framework for identifying earthen berms from 1 m LiDAR‐derived digital elevation models in the western US rangelands. Geomorphon, a computer vision tool, was used to classify landforms and identify berm‐like landforms, including summits and ridges. Ten geomorphic and geometric attributes associated with each potential berm object were used to develop a machine‐learning model for distinguishing berms from natural summits and ridges. The model was trained and applied to independent test sites to identify and map berms. The mapped berms were compared with manually identified reference berms for accuracy assessment. The identification results achieved 79% to 87% recall, 82% to 92% precision and 81% to 89% F‐measure. We also explored the influence of training sample selection on model performance and conducted an analysis of attribute relative importance. The automated framework has the potential to be scaled up to larger areas in semi‐arid environments.