bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effect of viewing distance on empirical discriminability and the confidence–accuracy relationship for eyewitness identification
Authors: Lockamyeir Robert F. , Carlson Curt A. , Jones Alyssa R. , Carlson Maria A. , Weatherford Dawn R. 
Published: May 2020

SummaryThe distance from which an eyewitness views a perpetrator is a critical factor for eyewitness identification, but has received little research attention. We presented three mock‐crime videos to participants, varying distance to three perpetrators (3, 10, or 20 m). Across two experiments, increased distance reduced empirical discriminability in the form of a mirror effect, such that correct identifications decreased while false identifications increased. Moreover, high confidence identifications were associated with high accuracy at 3 m (Experiment 1 and 2) and 10 m (Experiment 2), but not at 20 m. We conclude that eyewitnesses may be less likely to identify a perpetrator viewed at a distance, and also more likely to falsely identify an innocent suspect. Furthermore, there may be certain boundary conditions associated with distance and the impact it has on the confidence–accuracy relationship. More research is needed to elucidate the effect of estimator variable manipulations on the confidence–accuracy relationship.
Yield and quality of intercropped wheat in jujube‐ and walnut‐based agroforestry systems in southern Xinjiang Province, China
Authors: Qiao Xu , Xiao Li , Gao Yonghong , Zhang Wen , Chen Xingwu , Sai Lihan , Lei Junjie , Xue Lihua , Zhang Yongqiang , Li Ailian 
Published: May 2020

AbstractAgroforestry is widely practiced in China and has the benefit of diversifying agricultural production and enhancing natural resource utilization; however, these systems create competition for light between trees and understory crops. We investigated the effects of shading by jujube (Zizyphus jujuba Mill.) and walnut (Juglans regia L.) trees on the yield and quality of intercropped wheat (Triticum aestivum L.) in agroforestry systems in southern Xinjiang Province, China. In the walnut–wheat intercropping system, mean daily photosynthetically active radiation (PAR) and net photosynthetic rates (Pn) in the understory were reduced by 72.4–79.7% and 45.8–49.6%, respectively, at the grain‐filling stage as compared to wheat grown in monoculture. Relative to monoculture wheat, the walnut‐based system resulted in significant reductions in the number of florets and spikelets per spike, grain‐filling rate, and grain yield and its components in intercropped wheat. In contrast, N and P concentrations, and protein and wet gluten contents of intercropped wheat were significantly increase. In the jujube–wheat intercropping system, mean daily PAR and Pn in the understory were reduced by 23.2–25.5% and 27.2–34.3% at the grain‐filling stage compared to monoculture wheat, but grain yield and its components, the number of florets and spikelets, N and P concentrations, and protein and wet gluten contents of wheat did not differ between the two systems. The jujube‐based agroforestry system was more sustainable than the walnut‐based system in our study region, but competition for light between walnut trees and intercrops may be alleviated by selective felling, pruning, and wider tree spacing.
Tailoring Component Interaction for Air‐Processed Efficient and Stable All‐Inorganic Perovskite Photovoltaic
Authors: Wang Xiaojuan , Ran Xueqin , Liu Xiaotao , Gu Hao , Zuo Shouwei , Hui Wei , Lu Hui , Sun Bo , Gao Xingyu , Zhang Jing , Xia Yingdong , Chen Yonghua , Huang Wei 
Published: May 2020

AbstractAll‐inorganic lead halide perovskites are promising candidates for optoelectronic applications. However, fundamental questions remain over the component interaction in the perovskite precursor solution due to the limitation of the most commonly used solvents of N,N‐dimethylformamide (DMF) and dimethyl sulfoxide (DMSO). Here, we report an interaction tailoring strategy for all‐inorganic CsPbI3−xBrx perovskites by involving the ionic liquid solvent methylammonium acetate (MAAc). C=O shows strong interaction with lead (Pb2+) and N−H⋅⋅⋅I hydrogen bond formation is observed. The interactions stabilize the perovskite precursor solution and allow production of the high‐quality perovskite films by retarding the crystallization. Without the necessity for antisolvent treatment, the one‐step air‐processing approach delivers photovoltaic cells regardless of humidity, with a high efficiency of 17.10 % along with long operation stability over 1500 h under continuous light illumination.
Tailor‐Made Amino Acids and Fluorinated Motifs as Prominent Traits in Modern Pharmaceuticals
Authors: Mei Haibo , Han Jianlin , White Sarah , Graham Daniel J. , Izawa Kunisuke , Sato Tatsunori , Fustero Santos , Meanwell Nicholas A. , Soloshonok Vadim A. 
Published: May 2020

AbstractStructural analysis of modern pharmaceutical practices allows for the identification of two rapidly growing trends: the introduction of tailor‐made amino acids and the exploitation of fluorinated motifs. Curiously, the former represents one of the most ubiquitous classes of naturally occurring compounds, whereas the latter is the most xenobiotic and comprised virtually entirely of man‐made derivatives. Herein, 39 selected compounds, featuring both of these traits in the same molecule, are profiled. The total synthesis, source of the corresponding amino acids and fluorinated residues, and medicinal chemistry aspects and biological properties of the molecules are discussed.
Targeting the Water Network in Cyclin G‐Associated Kinase (GAK) with 4‐Anilino‐quin(az)oline Inhibitors
Authors: Asquith Christopher R. M. , Tizzard Graham J. , Bennett James M. , Wells Carrow I. , Elkins Jonathan M. , Willson Timothy M. , Poso Antti , Laitinen Tuomo 
Published: May 2020

AbstractWater networks within kinase inhibitor design and more widely within drug discovery are generally poorly understood. The successful targeting of these networks prospectively has great promise for all facets of inhibitor design, including potency and selectivity for the target. Herein, we describe the design and testing of a targeted library of 4‐anilinoquin(az)olines for use as inhibitors of cyclin G‐associated kinase (GAK). GAK cellular target engagement assays, ATP binding‐site modelling and extensive water mapping provide a clear route to access potent inhibitors for GAK and beyond.
Surface‐Initiated Redox Route to Hollow MnO2 Nanostructures
Authors: Bai Yaocai , Yao Xiaxi , Wang Xiaojing , Yin Yadong 
Published: May 2020

AbstractNanostructured MnO2 are gaining great research interest because of their wide applications ranging from optical and electronic devices to energy storage and catalysis. However, the formation of a well‐defined MnO2 coating on the surface of various colloidal objects has been challenging due to surface incompatibility. Here, we report a unique and robust surface‐initiated redox route to the controlled deposition of MnO2 on colloidal particles, which can be employed to produce high‐quality hollow MnO2 nanoshells and a variety of MnO2 coated nanocomposites. Colloidal resorcinol formaldehyde (RF) resin spheres serve as both reducing agents and sacrificial templates to initiate the controlled deposition of MnO2 on their surfaces. Further, the RF resin can also be coated on the surface of other colloidal nanostructures to allow overcoating of MnO2 through the redox reaction and produce nanocomposites such as SiO2@MnO2 and Au@MnO2. The size and thickness of the MnO2 nanoshells can be tuned precisely to induce resonant Mie scattering, leading to bright colorations that can shift reversibly in response to the changes in the refractive index of the surroundings.
Rare species of wood‐inhabiting fungi are not local
Authors: Dickie Ian A. , Wakelin Angela , Richardson Sarah J. 
Published: May 2020

AbstractWood‐inhabiting fungal communities are a diverse and ecologically critical part of forest ecosystems, yet the spatial structure of fungal biodiversity in these ecosystems is largely unknown. Legislation allowed harvesting of deadwood from temperate rainforests on conservation lands in New Zealand following Cyclone Ita in 2014. Harvesting guidelines specified widely spread harvesting, on the assumption that rare fungal species may be highly spatially restricted, but were not based on quantitative assessment. We sampled fungi in and on logs of Dacrydium cupressinum (Podocarpaceae) a long‐lived, common, canopy tree in lowland New Zealand forests. DNA was extracted from 81 logs varying in decay state across a 40 km long region of West Coast (South Island) forests, and sequenced using general fungal primers for metabarcoding to identify OTUs (operational taxonomic units). We examined three axes of rarity: occupancy, dominance when present, and niche breadth (as spatial extent and decay state specialization). Low‐occupancy fungi were common, including a group of infrequently occurring but dominant when present fungi, the majority of which were Ascomycota. Despite this, there was an overall positive relationship between occupancy and dominance. Widespread, dominant fungi were most commonly Basidiomycota. Testing all fungal OTUs, there were no more fungi with maximum range sizes < 4 km than would be expected at random. Of the 351 low‐occupancy OTUs found two to four times, only 12 had maximum range sizes < 900 m, and there was no more spatial restriction at scales < 900 m than would be expected by random chance, although there was some evidence of niche breadth restriction based on decay state similarity. The results show that fungal communities in deadwood are highly diverse, and include many rare taxa. Nonetheless, the lack of fungal OTUs with spatial restriction at scales < 900 m suggests that spatially dispersed timber harvesting will not mitigate risks of harvesting to rare fungal biodiversity.
Habitat heterogeneity captured by 30‐m resolution satellite image texture predicts bird richness across the United States
Authors: Farwell Laura S. , Elsen Paul R. , Razenkova Elena , Pidgeon Anna M. , Radeloff Volker C. 
Published: May 2020

AbstractSpecies loss is occurring globally at unprecedented rates, and effective conservation planning requires an understanding of landscape characteristics that determine biodiversity patterns. Habitat heterogeneity is an important determinant of species diversity, but is difficult to measure across large areas using field‐based methods that are costly and logistically challenging. Satellite image texture analysis offers a cost‐effective alternative for quantifying habitat heterogeneity across broad spatial scales. We tested the ability of texture measures derived from 30‐m resolution Enhanced Vegetation Index (EVI) data to capture habitat heterogeneity and predict bird species richness across the conterminous United States. We used Landsat 8 satellite imagery from 2013–2017 to derive a suite of texture measures characterizing vegetation heterogeneity. Individual texture measures explained up to 21% of the variance in bird richness patterns in North American Breeding Bird Survey (BBS) data during the same time period. Texture measures were positively related to total breeding bird richness, but this relationship varied among forest, grassland, and shrubland habitat specialists. Multiple texture measures combined with mean EVI explained up to 41% of the variance in total bird richness, and models including EVI‐based texture measures explained up to 10% more variance than those that included only EVI. Models that also incorporated topographic and land cover metrics further improved predictive performance, explaining up to 51% of the variance in total bird richness. A texture measure contributed predictive power and characterized landscape features that EVI and forest cover alone could not, even though the latter two were overall more important variables. Our results highlight the potential of texture measures for mapping habitat heterogeneity and species richness patterns across broad spatial extents, especially when used in conjunction with vegetation indices or land cover data. By generating 30‐m resolution texture maps and modeling bird richness at a near‐continental scale, we expand on previous applications of image texture measures for modeling biodiversity that were either limited in spatial extent or based on coarse‐resolution imagery. Incorporating texture measures into broad‐scale biodiversity models may advance our understanding of mechanisms underlying species richness patterns and improve predictions of species responses to rapid global change.
The relationship between trophic level and body size in fishes depends on functional traits
Authors: Keppeler Friedrich W. , Montaña Carmen G. , Winemiller Kirk O. 
Published: May 2020

AbstractPredators typically are larger than their prey, and consequently, trophic level should increase with body size. Whereas this relationship has helped in developing predictions about food web structure and dynamics in mesocosms and simple communities, a trophic‐level–body‐size relationship may not exist for all kinds of communities or taxa, especially those with many non‐carnivorous species. Moreover, functional traits associated with trophic level generally have not been considered. Herein, we examine the correlation between trophic level and body size in fishes and how this relationship may vary in relation to functional traits (body dimensions, mouth size and orientation, tooth shape, gill rakers, and gut length) and trophic guilds (carnivorous vs. non‐carnivorous). We analyzed data from morphological measurements and dietary analyses performed on thousands of specimens from freshwater and estuarine habitats across three zoogeographic regions (Neartic, Neotropical, and Afrotropical). A positive relationship between trophic level and body size was only found for carnivorous fishes. No relationship was found when all species were analyzed together, rejecting the idea that trophic level is positively related with body size in fishes generally. This result was consistent even when using either body mass or standard length as the measure of body size, and trophic level for either species (average values) or individual specimens as the response variable. At the intraspecific level, trophic level varied consistently with size for one third of the species, among which only 40% had positive relationships. Body depth, tooth shape, and mouth width were all associated with the trophic‐level–body‐size relationship. Overall, predators with conical or triangular serrated teeth, large mouths, and elongated/and/or fusiform bodies tend to have positive trophic‐level–body‐size relationships, whereas primarily non‐carnivorous species with unicuspid or multicuspid teeth, deep bodies and small to medium sized mouth gapes tended to have negative relationships. Given the diverse ecological strategies encompassed by fishes, trophic level and food web patterns and processes should not be inferred based solely on body size. Research that integrates multiple functional traits with trophic ecology will improve understanding and predictions about food web structure and dynamics.
Formation of Polar Compounds During Deep‐frying—Determination by 1H NMR and ESR
Authors: Li Xiaodan , Li Jinwei , Wang Yong , Liu Yuanfa 
Published: May 2020

AbstractThe present study aims to elucidate the factors influencing the generation of polar compounds in oils during deep‐frying. Oils with different fatty acid compositions, including palm oil (PO), refined palm kernel oil (RPKO), and refined coconut oil (RCO), are applied in successive frying processes. 1H NMR spectra reveal that heated PO has a higher percentage of allyl acyl group and is more prone to formation of non‐polar dimeric triglycerides as compared to other types of oils. In addition, electron spin resonance (ESR) spectra indicate that alkyl radicals are more predominant than alkoxy radicals in heated PO. In contrast, RPKO and RCO are inclined to generation of alkoxy radicals during the thermal treatment. The results reveal that oils with high unsaturated fatty acid content are more prone to generation and oxidation of non‐polar dimeric triglycerides.Practical Applications: The change in free radical profile and concentration is one of the indicators of lipid oxidation and polymerization. Alterations in the levels of alkyl and alkoxyl radicals, revealed by ESR, can be used to illustrate the formation of polar compounds in deep‐fried oils with different fatty acid compositions. The percentage of allyl acyl group, revealed by 1H NMR, can be used to predict the generation of polar compounds. Therefore, this study provides useful information for the development of different methods to reduce polar compound formation in oils during thermal processing depending on the fatty acid composition of different deep‐fried oils.
Performance of laterally elongated pillar array columns in capillary electrochromatography mode
Authors: Baca Martyna , Kryj Agata , Naghdi Elahe , Gelin Pierre , Sukas Sertan , Laha Priya , Terryn Herman , Ottevaere Heidi , De Malsche Wim 
Published: May 2020

AbstractIn the present study, cylindrical and laterally elongated pillar array columns were investigated for use in capillary electrochromatography. Minimal theoretical plate heights of H = 1.90 and 1.46 μm (in absence of sidewall effect) were obtained for coumarin C440 under unretained conditions for cylindrical and rectangular (laterally elongated, aspect ratio 4) pillar array columns, respectively. By comparing dispersion at the entire channel width to that at the central zone only, it appears that sidewall related dispersion significantly contributes to overall dispersion. A 40% reduction of the plate height was observed by taking into account only the central channel zone.A kinetic plot analysis was performed to evaluate the potential of the studied geometries by considering a maximum operating voltage of 20 kV as limiting parameter. It was demonstrated that rectangular radially elongated pillars produce a higher efficiency than cylindrical pillars and other microfabricated column structures for microchip capillary electrochromatography previously studied.
Miniaturized liquid chromatography applied to the analysis of residues and contaminants in food: A review
Authors: Mejía‐Carmona Karen , Maciel Edvaldo Vasconcelos Soares , Lanças Fernando Mauro 
Published: May 2020

AbstractThe humankind is pretty dependent on food to control several biological processes into the organism. As the world population increases, the demand for foodstuffs follows the same trend claiming for a high food production situation. For this reason, a substantial amount of chemicals is used in agriculture and livestock husbandries every year, enhancing the likelihood of contaminated foodstuffs being commercialized. This outlook becomes a public health concern; thus, the governmental regulatory agencies impose laws to control the residues and contaminants in food matrices. Currently, one of the most important analytical techniques to perform it is LC. Despite its already recognized effectiveness, it is often time consuming and requires significant volumes of reagents, which are transformed into toxic waste. In this context, miniaturized LC modes emerge as a greener and more effective analytical technique. They have remarkable advantages, including higher sensitivity, lower sample amount, solvent and stationary phase requirements, and more natural coupling to MS. In this review, most of the critical characteristics of them are discussed, focusing on the benchtop instruments and their related analytical columns. Additionally, a discussion regarding the last 10 years of publications reporting miniaturized LC application for the analysis of natural and industrial food samples is categorized. The main chemical classes as applied in the crops are highlighted, including pesticides, veterinary drugs, and mycotoxins.
Modeling of CO2 absorption capabilities of amino acid solutions using a computational scheme
Authors: Razavi Razieh , Bemani Amin , Baghban Alireza , Mohammadi Amir H. 
Published: May 2020

AbstractIn this communication, modeling of carbon dioxide absorption by various amino acid solutions is presented as a function of operational parameters using the Least‐Squares Support Vector Machine (LSSVM) algorithm integrated with three different evolutionary algorithms, namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Hybrid GA and PSO (HGAPSO). A databank containing 255 data of carbon dioxide absorption by amino acids of potassium taurate, potassium glycinate, potassium prolinate, and potassium lysinate at different temperatures, partial pressures, and concentrations was prepared from different sources to train and test the proposed algorithms. The models were applied to estimate carbon dioxide absorption by amino acid solutions in terms of temperature, molar concentration, equilibrium partial pressure, molecular weight, number of hydrogen bond donor, number of hydrogen bond acceptor, and number of rotatable bond. The R2 values of LSSVM optimized by HGAPSO, PSO, and GA are 0.9944, 0.9915, and 0.9891, respectively, and the various errors were determined close to zero. On the other hand, the visual comparison of models outputs and actual carbon dioxide adsorption data was used to clarify performances of the models. By comparison analysis, it was found that the LSSVM‐HGAPSO is the most accurate model for estimation of carbon dioxide loading. Also, comparison of our proposed models results with previously reported artificial neural network results indicates the impressive estimation capability of LSSVM algorithm. According to sensitivity analysis, it becomes obvious that pressure is the most effective parameter on carbon dioxide absorption.
Evaluating the performance of a sequencing batch reactor for sanitary wastewater treatment using artificial neural network
Authors: Yazdani Hamid , Khoshhal Abbas , Mousavi Nayereh S. 
Published: May 2020

AbstractIn this work, the performance of a sequencing batch reactor (SBR) was studied for treating sanitary wastewater of Yazd power plant, Iran. For this purpose, at the first, a pilot system was designed, installed, and started up. Then the effects of retention time, pH, temperature, influent chemical oxygen demand (COD) concentration, and air flow rate were investigated on the effluent concentration of COD. In SBR reactor used in the Yazd power plant, the microalga was not used for the wastewater treatment. In this case, the COD effluent output was, at the best conditions, approximately 92 mg/L. In the studied SBR system, we used the Chlorella vulgaris microalgae and microorganisms, simultaneously. In this case, the COD level reached 34 mg/L. An artificial neural network (ANN) was developed by applying Levenberg‐Marquardt training algorithm to predict the effluent concentration of COD. The optimum conditions were obtained at pH = 8, temperature of 30°C, influent COD concentration of 600 mg/L, and air flow rate of 50 L/min. ANN predicted results were in good agreement with the experimental data with a validation coefficient of determination (R2) and validation mean square error of 0.962 and 0.0015, respectively.