bluuebunny/crossref_metadata_2025_split huggingface dataset:
An efficient method of evaluating multiple concurrent management actions on invasive populations
Authors: Davis Amy J. , Farrar Randy , Jump Brad , Hall Parker , Guerrant Travis , Pepin Kim M. 
Published: April 2022

AbstractEvaluating the efficacy of management actions to control invasive species is crucial for maintaining funding and to provide feedback for the continual improvement of management efforts. However, it is often difficult to assess the efficacy of control methods due to limited resources for monitoring. Managers may view effort on monitoring as effort taken away from performing management actions. We developed a method to estimate invasive species abundance, evaluate management effectiveness, and evaluate population growth over time from a combination of removal activities (e.g., trapping, ground shooting) using only data collected during removal efforts (method of removal, date, location, number of animals removed, and effort). This dynamic approach allows for abundance estimation at discrete time points and the estimation of population growth between removal periods. To test this approach, we simulated over 1 million conditions, including varying the length of the study, the size of the area examined, the number of removal events, the capture rates, and the area impacted by removal efforts. Our estimates were unbiased (within 10% of truth) 81% of the time and were correlated with truth 91% of the time. This method performs well overall and, in particular, at monitoring trends in abundances over time. We applied this method to removal data from Mingo National Wildlife Refuge in Missouri from December 2015 to September 2019, where the management objective is elimination. Populations of feral swine on Mingo NWR have fluctuated over time but showed marked declines in the last 3–6 months of the time series corresponding to increased removal pressure. Our approach allows for the estimation of population growth across time (from both births and immigration) and therefore, provides a target removal rate (above that of the population growth) to ensure the population will decline. In Mingo NWR, the target monthly removal rate is 18% to cause a population decline. Our method provides advancement over traditional removal modeling approaches because it can be applied to evaluate management programs that use a broad range of removal techniques concurrently and whose management effort and spatial coverage vary across time.
A machine‐learning approach to predict success of a biocontrol for invasive Eurasian watermilfoil reduction
Authors: White Diana T. , Antoniou Thibaud M. , Martin Jonathan M. , Kmetz William , Twiss Michael R. 
Published: April 2022

AbstractMyriophyllum spicatum, more commonly known as Eurasian watermilfoil (EWM), is one of the most invasive aquatic plants in North America, causing negative ecological and economic impacts in ecosystems where it proliferates. Many control strategies have been developed and implemented to mitigate EWM growth and spread, although the results are mixed and there is no consensus on lake‐specific strategies. Here, we describe the development of a predictive model using a support vector technique, that predicts the success of biological pest control using Euhrychiopsis lecontei (the milfoil weevil), a milfoil specialist, to reduce EWM in lakes. Such a model is informed by lake characteristics (limnological and landscape) and augmentation strategies. To develop our predictive model, we performed a metadata analysis from 133 published peer‐reviewed literature and professional reports of milfoil weevil augmentation field experiments that contained information on lake characteristics. The predictive model's algorithm uses a support vector machine (SMV) to learn patterns among lake characteristics, along with the recorded augmentation strategy and the reported success of each study, where success is a measure of EWM change over a season and is recorded in a variety of ways (e.g., EWM biomass change, EWM percent change, EWM visual change, etc.,). Overall, the model results suggests that shallower lakes, more frequent weevil augmentations, and larger weevil overwintering habitat are the most important predictors for EWM reduction success by weevil augmentation. Although watermilfoil weevil augmentation is a promising mitigation strategy, it may not work for all lakes. However, in terms of suggesting weevil augmentation, our model is a valuable tool for lake stakeholders and resource managers, who can use it to determine whether milfoil weevil augmentation, which can be very costly due to the difficulties in finding and raising milfoil weevils, will be a useful and sustainable approach to control EWM in their lake community.
Fire‐driven vegetation type conversion in Southern California
Authors: Syphard Alexandra D. , Brennan Teresa J. , Rustigian‐Romsos Heather , Keeley Jon E. 
Published: April 2022

AbstractOne consequence of global change causing widespread concern is the possibility of ecosystem conversions from one type to another. A classic example of this is vegetation type conversion (VTC) from native woody shrublands to invasive annual grasslands in the biodiversity hotspot of Southern California. Although the significance of this problem is well recognized, understanding where, how much, and why this change is occurring remains elusive owing to differences in results from studies conducted using different methods, spatial extents, and scales. Disagreement has arisen particularly over the relative importance of short‐interval fires in driving these changes. Chronosequence approaches that use space for time to estimate changes have produced different results than studies of changes at a site over time. Here we calculated the percentage woody and herbaceous cover across Southern California using air photos from ~1950 to 2019. We assessed the extent of woody cover change and the relative importance of fire history, topography, soil moisture, and distance to human infrastructure in explaining change across a hierarchy of spatial extents and regions. We found substantial net decline in woody cover and expansion of herbaceous vegetation across all regions, but the most dramatic changes occurred in the northern interior and southern coastal areas. Variables related to frequent, short‐interval fire were consistently top ranked as the explanation for shrub to grassland type conversion, but low soil moisture and topographic complexity were also strong correlates. Despite the consistent importance of fire, there was substantial geographical variation in the relative importance of drivers, and these differences resulted in different mapped predictions of VTC. This geographical variation is important to recognize for management decision‐making and, in addition to differences in methodological design, may also partly explain differences in previous study results. The overwhelming importance of short‐interval fire has management implications. It suggests that actions should be directed away from imposing fires to preventing fires. Prevention can be controlled through management actions that limit ignitions, fire spread, and the damage sustained in areas that do burn. This study also demonstrates significant potential for changing fire regimes to drive large‐scale, abrupt ecological change.
Optimizing management of invasions in an uncertain world using dynamic spatial models
Authors: Pepin Kim M. , Davis Amy J. , Epanchin‐Niell Rebecca S. , Gormley Andrew M. , Moore Joslin L. , Smyser Timothy J. , Shaffer H. Bradley , Kendall William L. , Shea Katriona , Runge Michael C. , McKee Sophie 
Published: April 2022

AbstractDispersal drives invasion dynamics of nonnative species and pathogens. Applying knowledge of dispersal to optimize the management of invasions can mean the difference between a failed and a successful control program and dramatically improve the return on investment of control efforts. A common approach to identifying optimal management solutions for invasions is to optimize dynamic spatial models that incorporate dispersal. Optimizing these spatial models can be very challenging because the interaction of time, space, and uncertainty rapidly amplifies the number of dimensions being considered. Addressing such problems requires advances in and the integration of techniques from multiple fields, including ecology, decision analysis, bioeconomics, natural resource management, and optimization. By synthesizing recent advances from these diverse fields, we provide a workflow for applying ecological theory to advance optimal management science and highlight priorities for optimizing the control of invasions. One of the striking gaps we identify is the extremely limited consideration of dispersal uncertainty in optimal management frameworks, even though dispersal estimates are highly uncertain and greatly influence invasion outcomes. In addition, optimization frameworks rarely consider multiple types of uncertainty (we describe five major types) and their interrelationships. Thus, feedbacks from management or other sources that could magnify uncertainty in dispersal are rarely considered. Incorporating uncertainty is crucial for improving transparency in decision risks and identifying optimal management strategies. We discuss gaps and solutions to the challenges of optimization using dynamic spatial models to increase the practical application of these important tools and improve the consistency and robustness of management recommendations for invasions.
Asymmetric Total Synthesis of All Rugulovasine Stereoisomers and Preliminary Evaluation of Their Biological Properties
Authors: Bartoccini Francesca , Regni Alessio , Retini Michele , Piersanti Giovanni 
Published: April 2022

AbstractA unified enantioselective synthesis and the biological evaluation of all rugulovasine stereoisomers are reported. The syntheses are centered on the divergent and stereochemical modular combination of each enantiomer of 4‐amino Uhle's ketone and a methacrylate derivative to build the unsaturated oxaspirolactone moiety by the Dreiding‐Schmidt reaction, followed by Fukuyama alkylation to afford the required N‐methyl secondary amine in excellent yield. The modularity of this divergent approach, the diastereoselectivities of the reactions, and the late‐stage site‐selective methylation permit the rapid asymmetric syntheses of all rugulovasine stereoisomers, including the first total syntheses of optically pure (+)‐ and (−)‐rugulovasine B and their trideuteromethylated derivatives. All enantiopure stereoisomers of rugulovasine were tested for their binding affinities to dopamine, serotonin, and adrenergic neuroreceptors, revealing their preferred selectivity for the serotonin 1 A receptor.
Advances in the application of molecular sieves as catalysts for lignin depolymerization—HZSM‐5 as an example
Authors: Xu Jingyu , Jia Jiahai , Zhang Yunze , Wang Xing , Guo Yanzhu , Zhou Jinghui 
Published: April 2022

AbstractAt present, mankind faces the problem of increasingly serious global environmental crisis and growing shortage of petrochemical resources, making it more and more necessary to seek renewable substitute for petroleum. Biomass resources, which have received widespread attention and worldwide research, are the most common source of renewable carbon. Moreover, they are considered to be the major source of renewable green carbon today. Biomass resources contain three main aggregates, which are cellulose, hemicellulose, and lignin, as well as small amounts of other additional materials. Notably, the aromatic ring ethers linkage inside lignin molecules enables it to serve as a renewable and suitable feedstock for the production of aromatic chemicals and fuels. However, the recognition that lignin is the most difficult lignocellulosic biomass to degrade makes it much less valuable for practical applications. Therefore, in order to achieve high‐value conversion and utilization of lignin and replace non‐renewable fossil resources, the targeted conversion of lignin into chemicals and materials has become one of the major hot research areas. To this end, this article reviews research results on the use of molecular sieves (HZSM‐5) as catalysts for lignin degradation and conversion, providing an outlook on future research directions.
Effect of historical land‐use change on soil erosion in a Mediterranean catchment by integrating 137Cs measurements and WaTEM/SEDEM model
Authors: Lizaga Villuendas Ivan , Latorre Borja , Gaspar Leticia , Navas Ana 
Published: April 2022

AbstractSoil erosion is especially severe in areas affected by intermittent heavy rainfalls after dry periods, and human practices such as deforestation. Mediterranean mountain environments underwent conversion of rangelands into croplands during the previous centuries to increase agricultural production but this process was reversed after land abandonment in the middle of the twentieth century allowing the natural revegetation. To understand the effect of the past practices and the current agricultural management, we have combined the strength of empirical data and spatially distributed modelling in a medium‐sized catchment representative of agroforestry landscapes of NE Spain. We developed an ensemble technique composed of 137Cs‐derived soil redistribution rates as specific point values and as grid‐based setup calibration for the WaTEM/SEDEM. Thus, we overcame the point specific limitation of the 137Cs measurement and the need for calibration of spatially distributed models that allow a spatial interpretation of soil redistribution in the catchment. We implemented an automated routine model tool to increase the calculation speed and calibrate the model thus, allowing estimates of the main model parameters for simulating a variety of temporal scenarios. With this method a good fit between modelled and measured soil redistribution rates (R2 = 0.82) was obtained (Nash–Sutcliffe efficiency: 0.79). Estimates were also consistent with the previous apportions of sediment provenance obtained by the fingerprinting technique. An increase of 300% in sediment export was predicted for the past scenario when most of the catchment was cultivated, while a reduction of 40% occurred in the future scenario of land abandonment. A high influence of input resolution was found, wherein model efficiency was reduced when pixel‐size was increased. Our study demonstrates that spatially distributed models combined with 137Cs‐derived rates provide a powerful tool to understand the driving factors of erosion and delineate the hotspot areas that could suffer high erosion if submitted to certain management practices.
Reasons for satisfaction with the use of the 52‐mg levonorgestrel intrauterine system
Authors: Laporte Montas , Charles Charles M. , Metelus Sherly , Souza Rafael B. , Peloggia Alessandra , Bahamondes Luis 
Published: April 2022

AbstractObjectivesTo assess the reasons to use, reasons they liked, satisfaction with, and possibilities of recommendation to other women of the levonorgestrel 52‐mg intrauterine system (LNG‐IUS) by users.Materials and MethodsA cross‐sectional study was conducted at the University of Campinas, Campinas, Brazil from January to July 2021. We enrolled users who came to the clinic, and we applied a pre‐tested structured questionnaire with open‐ended questions. We performed descriptive analyses of the variables, assessing the level of satisfaction with, and the reasons regarding the possibility of continuing to use, the IUS.ResultsOf the 517 enrolled women, 251 (48%) were aged 35 years or older (mean age 33.9 ± 9.0 years), 276 (53%) were white, 14 (3%) were adolescents, 155 (30%) were nulligravidas, and 307 (59.4%) reported experiencing amenorrhea in the last 90 days. Common reasons why women liked to use the LNG‐IUS included both the reduction of menstrual bleeding (419 women; 81%) and dysmenorrhea (290 women; 56.1%). Nine out of 10 users (517 women; 91%) were satisfied with the method, and the majority would recommend it to other women.ConclusionWe found a high satisfaction rate among LNG‐IUS users mainly due to the reduction of both menstrual bleeding and dysmenorrhea.
Improving thermal stability of sulfide solid electrolytes: An intrinsic theoretical paradigm
Authors: Wang Shuo , Wu Yujing , Li Hong , Chen Liquan , Wu Fan 
Published: April 2022

AbstractAll‐solid‐state batteries (ASSBs) have been widely acknowledged as the key next‐generation energy storage technology/device, due to their high safety and energy density. Among all solid electrolytes (SEs) that have been studied for ASSBs, sulfide SEs represent the most promising technical route due to their ultra‐high ionic conductivity and desirable mechanical property. However, few results have been reported to study the thermal stability/safety issue of sulfide SEs and ASSBs. Herein, we develop the first‐of‐its‐kind theoretical paradigm and a new conceptual parameter Th to quantitatively calculate/predict the essential thermal stability of sulfide SEs. This theoretical paradigm takes all types of parameters (e.g. crystal structure, localized polyhedra configuration, bond energy, bond type, bond number, normalization factor, and the energy correction factor) into consideration, and more importantly, can be simplified into one straightforward equation for its convenient application in any crystalline systems. To prove its functionality, the typical experimental strategies (stoichiometric ratio control and elemental doping) are adopted for typical sulfide SEs (Li7P3S11, Li3PS4) to improve their thermal stabilities, based on the predictions obtained from the derived theory and equation. Moreover, the potential doping elements to improve thermal stability of sulfide SEs are screened throughout the whole periodic table, and the theoretically predicted trends correspond well with experimental evidence. This work may represent the most critical breakthroughs in the research field of thermal stability for sulfide SEs, not only because it fills the gap of this field, but also due to its precise and quantitative prediction based on a complete consideration of all parameters that determine their thermal stabilities. The handy model developed herein can also be applied to any crystalline materials.image
Computed Tomography–Based Stiffness Measures of Trabecular Bone Microstructure: Cadaveric Validation and In Vivo Application
Authors: Guha Indranil , Zhang Xialiou , Rajapakse Chamith S. , Letuchy Elena M. , Chang Gregory , Janz Kathleen F. , Torner James C. , Levy Steven M. , Saha Punam K. 
Published: April 2022

ABSTRACTOsteoporosis causes bone fragility and elevates fracture risk. Applications of finite element (FE) analysis (FEA) for assessment of trabecular bone (Tb) microstructural strength at whole‐body computed tomography (CT) imaging are limited due to challenges with Tb microstructural segmentation. We present a nonlinear FEA method for distal tibia CT scans evading binary segmentation of Tb microstructure, while accounting for bone microstructural distribution. First, the tibial axis in a CT scan was aligned with the FE loading axis. FE cubic mesh elements were modeled using image voxels, and CT intensity values were calibrated to ash density defining mechanical properties at individual elements. For FEA of an upright volume of interest (VOI), the bottom surface was fixed, and a constant displacement was applied at each vertex on the top surface simulating different loading conditions. The method was implemented and optimized using the ANSYS software. CT‐derived computational modulus values were repeat scan reproducible (intraclass correlation coefficient [ICC] ≥ 0.97) and highly correlated (r ≥ 0.86) with the micro‐CT (μCT)‐derived values. FEA‐derived von Mises stresses over the segmented Tb microregion were significantly higher (p < 1 × 10−11) than that over the marrow space. In vivo results showed that both shear and compressive modulus for males were higher (p < 0.01) than for females. Effect sizes for different modulus measures between males and females were moderate‐to‐high (≥0.55) and reduced to small‐to‐negligible (<0.40) when adjusted for pure lean mass. Among body size and composition attributes, pure lean mass and height showed highest (r ∈ [0.45 0.56]) and lowest (r ∈ [0.25 0.39]) linear correlation, respectively, with FE‐derived modulus measures. In summary, CT‐based nonlinear FEA provides an effective surrogate measure of Tb microstructural stiffness, and the relaxation of binary segmentation will extend the scope for FEA in human studies using in vivo imaging at relatively low‐resolution. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
Clinical manifestations, treatment options, and comorbidities in COVID‐19 relapse patients: A systematic review
Authors: Koupaei Maryam , Mohamadi Mohamad Hosein , Yashmi Ilya , Shahabi Amir Hossein , Shabani Amir Hosein , Heidary Mohsen , Khoshnood Saeed 
Published: April 2022

AbstractIntroductionInterest revolving around coronavirus disease 2019 (COVID‐19) reinfection is escalating rapidly. By definition, reinfection denotes severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), PCR redetection, and COVID‐19 recurrence within three months of the initial symptoms. The main aim of the current systematic review was to evaluate the features of COVID‐19 relapse patients.Materials and methodsFor this study, we used a string of terms developed by a skilled librarian and through a systematical search in PubMed, Web of Science, and Embase for eligible studies. Clinical surveys of any type were included from January 2019 to March 2021. Eligible studies consisted of two positive assessments separated by a negative result via RT‐PCR.ResultsFifty‐four studies included 207 cases of COVID‐19 reinfection. Children were less likely to have COVID‐19 relapse. However, the most patients were in the age group of 20–40 years. Asthenia (66.6%), headache (66.6%), and cough (54.7%) were prevalent symptoms in the first SARS‐CoV‐2 infection. Asthenia (62.9%), myalgia (62.9%), and headache (61.1%) were most frequent in the second one. The most common treatment options used in first COVID‐19 infection were lopinavir/ritonavir (80%), oxygen support (69.2%), and oseltamivir (66.6). However, for the treatment of second infection, mostly antibiotics (100%), dexamethasone (100%), and remdesivir (80%) were used. In addition, obesity (32.5%), kidney failure (30.7%), and hypertension (30.1%) were the most common comorbidities. Unfortunately, approximately 4.5% of patients died.ConclusionWe found the potency of COVID‐19 recurrence as an outstanding issue. This feature should be regarded in the COVID‐19 management. Furthermore, the first and second COVID‐19 are similar in clinical features. For clinically practical comparison of the symptoms severity between two epochs of infection, uniform data of both are required. We suggest that future studies undertake a homogenous approach to establish the clinical patterns of the reinfection phenomena.