bluuebunny/crossref_metadata_2025_split huggingface dataset:
Production of furfural and levulinic acid from purple Cameroon grass (Pennisetum purpureum cv. Morado) by a two-stage process
Authors: Ortiz-Cabrera Iván , Conde-Rivera Laura , Piñeros-Castro Yineth 
Published: December 2023

Abstract The purple Cameroon grass crop (P. purpureum cv. Morado) presents significant potential as a source of raw materials and renewable energy; it has rapid growth, high yield, and low fertilizer demand. During the conversion of lignocellulosic biomass, hemicellulose and cellulose can first be hydrolyzed into five and six-carbon sugars, and then the sugars are converted into furfural and levulinic acid (LA) respectively. In this work, the furfural and levunilic acid production was evaluated in a two-stage catalytic process with a tin catalyst supported on a sulfonated activated carbon. In the first stage, a furfural yield of 23.28% at 170 °C for 3 h. In the second stage, the effect of process temperature and time on LA production's yield and energy demand was evaluated; LA yield of 28.17% was obtained with an energy demand of 0.12 kWh/gLA at 180.47 °C for 1.78 h. These results demonstrate the possibility of obtaining furfural from Cameroon grass.
Graphical Abstract
Is Cannabis Use Associated with Motivation? A Review of Recent Acute and Non-Acute Studies
Authors: Skumlien Martine , Langley Christelle , Sahakian Barbara J. 
Published: December 2023

Abstract
Purpose of Review
Cannabis use has been anecdotally linked with reduced motivation, sometimes referred to as the ‘amotivational syndrome’. In this review, we evaluate research on the association between acute and non-acute cannabis use and motivation assessed with questionnaire or behavioural task-based measures, focusing on studies published in the last 5 years.

Recent Findings
Of the five non-acute studies which used behavioural tasks to assess motivation, three found that cannabis use was associated with higher willingness to expend effort for reward, while the other two found no differences between cannabis users and controls. Only two acute studies have been published to date, both of which found that cannabis reduced participants’ willingness to expend effort for reward compared with placebo. Most self-report survey studies did not find any differences in motivational outcomes between cannabis users and controls, though there was evidence of an association between apathy and cannabis dependence.

Summary
While cannabis may lower motivation acutely, recent non-acute studies do not support claims of an amotivational syndrome in people who use cannabis. However, there is some evidence of an association between cannabis use disorder and apathy.
MXene heterostructures based on Cr2C and Cr2N: evidence of strong interfacial interactions that induce an antiferromagnetic alignment
Authors: Gutierrez-Ojeda S. J. , Ponce-Pérez R. , Guerrero-Sánchez J. , Moreno-Armenta María G. 
Published: December 2023

AbstractIn the present work, Cr2C and Cr2N MXenes are stacked to conform 2D heterostructures. The structural, electronic, and magnetic properties were further investigated. Two stackings were treated; the first, Cr2C on top of Cr2N, and the second, Cr2N is on Cr2C. The most favorable configuration is Cr2C/Cr2N, with a vertical distance of 2.35 Å. The antiferromagnetic alignment evidences a possible bias exchange effect. Cr2C MXene preserves its ferromagnetic behavior and changes the top Cr layer polarization of Cr2N form the antiferromagnetic alignment with Cr2C. The bottom Cr layer of Cr2N conserves the intrinsic polarization as antiparallel. Electronic properties evidence a metallic behavior. Although the vertical distance in the MXene heterostructure is comparable with a van der Waals interaction, the 2D charge density maps and electron local function indicate a metallic interaction at the interface, meanwhile the charge density difference exhibits a charge transfer in the interface heterostructure. The new 2D heterostructure and the properties that emerge from it could be interesting to the spintronics community due to their applications in information storage devices.
Consumer Behaviour in a Circular System – How Values Promote and Hinder the Participation of Young Adults in the Swedish Deposit-Refund System for Beverage Packaging
Authors: Kremel Anna 
Published: December 2023

AbstractThis study contributes to the understanding of how values promote and hinder circular consumer behaviour by examining and learning from the Swedish deposit-refund system for beverage cans and PET bottles. We have used the consumption value theory in our analysis, building on the concepts of circular economy, sustainable consumption and recycling. Data was collected from focus group interviews with young adults in order to identify and explore the ways that values promote and hinder participation. Functional values were found to be at the core of sustainable consumption as a result of financial incentives and the fact that consumers value convenience. The study also highlights the importance that young adults place on emotional values, in particular embarrassment, which hinders them from recycling. When it comes to sustainable consumption, young adults are driven by selfish behaviour, prioritising personal comfort. Social settings were also found to promote and hinder participation in the deposit-refund system. The study finds that an understanding of the reasons why different social groups and age groups approve or disapprove of participation in circular solutions may help design solutions to increase participation in circular solutions and circular economies. The results show that it is important to study the combinations of value dimensions to understand consumer behaviour in a circular system fully.
Probabilistic approach for robust design with orthogonal experimental methodology in case of target the best
Authors: Zheng Maosheng , Yu Jie 
Published: December 2023

AbstractThis paper aims to develop a probabilistic approach for robust design with orthogonal experimental methodology in case of target the best on basis of the probabilistic multi-objective optimization. In the treatment, the difference of the target value and the arithmetic mean value of performance indicators of the alternatives is taken one objective to be minimum, and the square root of mean squared error of actual value of performance indicators from the target value of the alternatives is taken as the second objective to be minimum, which contribute their partial preferable probabilities to the alternative individually. As an application example, the probabilistic method for multi-objective optimization is combined with orthogonal experimental methodology to conduct the optimum design, range analysis is used to total preferable probability subsequently, and ranking sequence of total preferable probability of alternatives is used to complete the optimization option.
Superlubricity of molybdenum disulfide film
Authors: Li Hongxuan , Ju Shifan , Ji Li , Liu Xiaohong , Zhou Huidi , Chen Jianmin , Zhao Xiaoqin 
Published: December 2023

AbstractSuperlubricity is an ideal state with zero contact friction between two frictional interfaces. It has become a hot research topic for many scientists in the past 20 years, and the field spans the complex hot research directions of physics, chemistry, mechanics, and materials. The concept of superlubricity was introduced in 1990, and the understanding of the process of realizing superlubricity is vital for controlling the tribological properties of materials and promoting the development of tribology. This review focuses on the fundamental properties of molybdenum disulfide (MoS2) films and the influence of the environment on affecting MoS2 films. As a result, some methods for realizing superlubricity by MoS2 films are proposed. The key to achieving superlubricity with MoS2 is summarized. Finally, an outlook on the application of MoS2 films is given.
Dominance and transitivity
Authors: Birnbaum Michael H. 
Published: December 2023

Abstract
This article describes a study of transitivity of preference and of transparent dominance with 220 participants who judged each choice problem 4 times. It shows how a true-and-error model with 2 error terms per choice problem can be applied to replicated data, to ask if violations of dominance or of transitivity are ‘real’ rather than due to random response errors. These models allow one to estimate the incidence of systematic violations and of error rates. The new data showed about 3% violations of transitivity, corrected for error. This incidence might be statistically significant, but a skeptic might dismiss it as too small to build a theory upon. Tests of dominance found violations with overall rates from 4% to 18%. As in previous research, violations of transparent dominance appeared almost exclusively among people who systematically prefer ‘safe’ gambles (with low ranges of outcomes) over ‘riskier’ gambles with higher expected values when the ‘safe’ gamble was dominated by the higher-ranged gamble. For those participants and choice problems, rates of violation were 28%–45%, corrected for error. It was theorized that these violations of dominance may be due to a subgroup of risk-averse participants using a strategy in this experiment to find ‘safe’ alternatives, without comparing outcomes between gambles.
Blood meal sources of mosquitoes (Diptera: Culicidae) in domestic and open green environments from two urbanisations of temperate Argentina
Authors: Melgarejo-Colmenares Karelly , Vezzani Darío , Gallego Alejandra , Cardo María V 
Published: December 2023

AbstractUnderstanding the blood-feeding patterns of mosquitoes is essential for evaluating their potential as disease vectors, especially in urban areas where mosquitoes coexist with humans, domestic animals and wildlife. This study aimed to bridge a substantial gap in regional knowledge by identifying the blood meal sources of field-collected mosquitoes in domestic and open green environments from two urbanisations of temperate Argentina, the Área Metropolitana de Buenos Aires (AMBA) and Tandil, using molecular techniques. Female mosquitoes were collected from November 2019 to March 2020 and April–May 2021. A bipartite network analysis was performed for each environment and urbanisation. A total of 103 blood meals from Aedes (2 species) and Culex (7 species) were identified. Among these, five mammal and 18 bird species were recognised as hosts. Aedes mosquitoes exclusively fed on mammals, while Culex mosquitoes exhibited a broader host range including both birds and mammals. In AMBA, the open green environments were composed by more mosquito species than the domestic environments, while both presented similar numbers of vertebrate species. In contrast, in open green environments from Tandil only blood-fed Aedes albifasciatus were collected. For open green environments of AMBA and domestic environments of Tandil, results suggested some degree of host selection. For the three main vectors of diseases in the region, Aedes aegypti, Ae. albifasciatus and Culex pipiens molestus, we present the first molecular evidence of human blood meals in South America. Epidemiological significance of the present findings is discussed.
Consistency of the Troposphere Wet Delay From Water Vapor Radiometer and Co‐Located GPS Station
Authors: Jiang Jun , Song Shuli , Zhou Weili , Liu Qinghui , Chen Houcai , Jiang Yongchen , Zhou Tianyu , Ali Tarig A. , Li Wei 
Published: December 2023

AbstractThe tropospheric delay acquired by the Global Navigation Position System (GPS) Precise Point Positioning (PPP) is continuous and steady, less affected by rainfall. The Water Vapor Radiometer (WVR) can provide real‐time meteorological parameters but is more sensitive to high‐frequency information in troposphere. To explore the use of WVR‐retrieved tropospheric delay and assist other geodetic techniques for atmospheric correction, the tropospheric delay from WVR and co‐located GPS at Shanghai, Beijing, Kunming, and Urumqi stations in China are compared. For the inconsistent values of WVR‐PPP zenith wet delay, the variations of the tropospheric delay from WVR and GPS before and after the rainfall were statistically analyzed. The results suggest that, for the rain rate ranging from 0.1 to 50 mm/hr, the impact of rainfall on WVR could last from 10 min before to 30 min after the rainfall. With filtering WVR data based on meteorological parameters and rain rate, the zenith wet delay between WVR and PPP at Shanghai shows good consistency, the root mean square (RMS) is 6.11 mm, correlation is 0.997, and the RMS in the other three stations ranges from 16.35 to 25.16 mm (correlation ranges in 0.794–0.951). The analysis indicates that the tropospheric delay of WVR is reliable to be applied to space geodetic techniques correction in real‐time with filtering to reduce the effect of rainfall, water vapor, and liquid water variability.
High‐Resolution Maps of Near‐Surface Permafrost for Three Watersheds on the Seward Peninsula, Alaska Derived From Machine Learning
Authors: Thaler E. A. , Uhleman S. , Rowland J. C. , Schwenk J. , Wang C. , Dafflon B. , Bennett K. E. 
Published: December 2023

AbstractPermafrost soils are a critical component of the global carbon cycle and are locally important because they regulate the hydrologic flux from uplands to rivers. Furthermore, degradation of permafrost soils causes land surface subsidence, damaging infrastructure that is crucial for local communities. Regional and hemispherical maps of permafrost are too coarse to resolve distributions at a scale relevant to assessments of infrastructure stability or to illuminate geomorphic impacts of permafrost thaw. Here we train machine learning models to generate meter‐scale maps of near‐surface permafrost for three watersheds in the discontinuous permafrost region. The models were trained using ground truth determinations of near‐surface permafrost presence from measurements of soil temperature and electrical resistivity. We trained three classifiers: extremely randomized trees (ERTr), support vector machines (SVM), and an artificial neural network (ANN). Model uncertainty was determined using k‐fold cross validation, and the modeled extents of near‐surface permafrost were compared to the observed extents at each site. At‐a‐site near‐surface permafrost distributions predicted by the ERTr produced the highest accuracy (70%–90%). However, the transferability of the ERTr to the sites outside of the training data set was poor, with accuracies ranging from 50% to 77%. The SVM and ANN models had lower accuracies for at‐a‐site prediction (70%–83%), yet they had greater accuracy when transferred to the non‐training site (62%–78%). These models demonstrate the potential for integrating high‐resolution spatial data and machine learning models to develop maps of near‐surface permafrost extent at resolutions fine enough to assess infrastructure vulnerability and landscape morphology influenced by permafrost thaw.
Participatory Modeling for Analyzing Interactions Between High‐Priority Sustainable Development Goals to Promote Local Sustainability
Authors: Bandari Reihaneh , Moallemi Enayat A. , Szetey Katrina , Flanagan‐Smith Claire , Hadjikakou Michalis , Marcos‐Martinez Raymundo , Kharrazi Ali , Trogrlić Robert Šakić , Bryan Brett A. 
Published: December 2023

AbstractAchieving the Sustainable Development Goals (SDGs) is challenging given the complex interactions between different SDGs and their spillover effects. We developed a system dynamics model—the Local Environmental and Socio‐Economic Model (LESEM)—to analyze and quantify context‐based SDG interactions at the local scale using a participatory model co‐design process with local stakeholders. The LESEM was developed for the Goulburn‐Murray Irrigation District in Victoria, Australia, to assist policymakers in analyzing local issues with a more integrated and holistic approach to sustainable development at the local scale. The process of participatory systems dynamics modeling facilitates integrated and strategic decision‐making and can help local policymakers identify and quantify potential trade‐offs and synergies that benefit multiple SDGs, which eventually leads local communities toward sustainability. We present an illustrative application of the model that quantifies SDG interactions across four high‐priority SDGs, namely clean water and sanitation (SDG 6), zero hunger (SDG 2), economic growth (SDG 8), and life on land (SDG 15). We illustrate the use of the model in assessing key SDG indicator trajectories under a business‐as‐usual (BAU) scenario from 2010 to 2050. Under the BAU, agri‐food production increased despite a decline in water resource availability, with gains driven by intensification and increased agricultural productivity. This boosted local prosperity and reduced the amount of agricultural land required to meet future agri‐food demand, thereby reducing pressures on terrestrial ecosystems and creating the space for ecological restoration and carbon storage in soils and biomass. However, agricultural intensification impacted water quality through increases in algal blooms and river salinity.
Automated Seafloor Massive Sulfide Detection Through Integrated Image Segmentation and Geophysical Data Analysis: Revisiting the TAG Hydrothermal Field
Authors: Haroon Amir , Paasche Hendrik , Graber Sebastian , Petersen Sven , Attias Eric , Jegen Marion , Gehrmann Romina , Hölz Sebastian , Klischies Meike 
Published: December 2023

AbstractAccessible seafloor minerals located near mid‐ocean ridges are noticed to mitigate the projected metal demands of the net‐zero energy transition, promoting growing interest in quantifying the global distributions of seafloor massive sulfides (SMS). Mineral potentials are commonly estimated using geophysical and geological data that lastly rely on additional confirmation studies using sparsely available, locally limited, seafloor imagery, grab samples, and coring data. This raises the challenge of linking in situ confirmation data to geophysical data acquired at disparate spatial scales to obtain quantitative mineral predictions. Although multivariate data sets for marine mineral research are incessantly acquired, robust, integrative data analysis requires cumbersome workflows and experienced interpreters. We introduce an automated two‐step machine learning approach that integrates the mound detection through image segmentation with geophysical data. SMS predictors are subsequently clustered into distinct classes to infer marine mineral potentials that help guide future exploration. The automated workflow employs a U‐Net convolutional neural network to identify mound structures in bathymetry data and distinguishes different mound classes through the classification of mound architectures and magnetic signatures. Finally, controlled source electromagnetic data are utilized together with in situ sampling data to reassess predictions of potential SMS volumes. Our study focuses on the Trans‐Atlantic Geotraverse area, which is among the most explored SMS areas worldwide and includes 15 known SMS sites. The automated workflow classifies 14 of the 15 known mounds as exploration targets of either high or medium priority. This reduces the exploration area to less than 7% of the original survey area from 49 to 3.1 km2.
Six Consecutive Seasons of High‐Resolution Mountain Snow Depth Maps From Satellite Stereo Imagery
Authors: Hu J. Michelle , Shean David , Bhushan Shashank 
Published: December 2023

AbstractFine‐scale seasonal snow depth observations can improve estimates of snow water equivalent at critical times of year. Airborne lidar is the current gold standard for snow depth measurement, but it involves high costs and relatively limited coverage. Using very‐high‐resolution satellite stereo images from WorldView‐2, WorldView‐3, and Pléiades‐HR 1A/1B, we produced a six‐year time series (2017–2022) of spatially continuous digital elevation models for an 874 km2 study area over Grand Mesa, Colorado. We generated high‐resolution stereo snow depth maps that capture intra‐ and interannual variability and span multiple anomalous years (58%–158% of median peak SNOTEL snow depth). Comparisons with near‐contemporaneous airborne lidar snow depth measurements showed good agreement, with median offset of −0.13 m, precision of 0.19 m and accuracy of 0.31 m. Our results suggest that satellite stereo can provide snow depth observations with the spatiotemporal coverage needed to improve operational forecast models and inform adaptive management strategies.
An Extended Triple Collocation Method With Maximized Correlation for Near Global‐Land Precipitation Fusion
Authors: Wei Linyong , Jiang Shanhu , Ren Liliang , Yuan Shanshui , Liu Yi , Yang Xiaoli , Wang Menghao , Zhang Linqi , Yu Huafei , Duan Zheng 
Published: December 2023

AbstractAn Extended Triple Collocation for maximized Correlation (ETCC) method was proposed with a unique correlation function, the purpose of which is to maximize the correlation between the merged product and unknown truth. The method was tested over quasi‐global land by combining three independent precipitation products. The performance of the ETCC‐merged product was then evaluated against three reference data sets and compared with the existing Triple Collocation (TC) merging. The merged product was found to be generally superior to each contributor. Moreover, the ETCC method is better able to improve the correlation of merged product compared with the TC approach. Other improvements are also shown in the absolute difference of the ETCC‐merged product, such as regional validation for central North America and mainland China. These demonstrate the effectiveness of the ETCC method, and accordingly, it can provide a promising solution for maximizing the correlation of merged product without the truth.
Modeling the Effects of Drift Orbit Bifurcation on the Magnetopause Shadowing Loss of Radiation Belt Electrons
Authors: Huang Jinbei , Lyu Xingzhi , Tu Weichao , Albert Jay M. , Lee Sang‐Yun 
Published: December 2023

AbstractLast closed drift shell (LCDS) has been identified as a crucial parameter for investigating the magnetopause shadowing loss of radiation belt electrons. However, drift orbit bifurcation (DOB) effects have not been physically incorporated into the LCDS calculation. Here we calculate event‐specific LCDS using different approaches to dealing with the DOB effects, that is, tracing field lines ignoring DOB, tracing test particles rejecting field lines with DOB, and tracing particles including field lines with DOB, and then incorporate them into a radial diffusion model to simulate the fast electron dropout observed by Van Allen Probes in May 2017. The model effectively captures the fast dropout at high L* and exhibits the best agreement with data when LCDS is calculated by tracing test particles with DOB more physically included. This study represents the first quantitative modeling of the DOB effects on radiation belt magnetopause shadowing loss via a more physical specification of LCDS.