bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of odorant‐binding proteins and functional analysis of antenna‐specific BhorOBP28 in Batocera horsfieldi (Hope)
Authors: Yi Shan‐Cheng , Chen Xin‐Hui , Wu Yu‐Hang , Wu Juan , Wang Jia‐Qing , Wang Man‐Qun 
Published: April 2024

AbstractBACKGROUNDThe important wood‐boring pest Batocera horsfieldi has evolved a sensitive olfactory system to locate host plants. Odorant‐binding proteins (OBPs) are thought to play key roles in olfactory recognition. Therefore, exploring the physiological function of OBPs could facilitate a better understanding of insect chemical communications.RESULTSIn this research, 36 BhorOBPs genes were identified via transcriptome sequencing of adults' antennae from B. horsfieldi, and most BhorOBPs were predominantly expressed in chemosensory body parts. Through fluorescence competitive binding and fluorescence quenching assays, the antenna‐specific BhorOBP28 was investigated and displayed strong binding affinities forming stable complexes with five volatiles, including (+)‐α‐Pinene, (+)‐Limonene, β‐Pinene, (−)‐Limonene, and (+)‐Longifolene, which could also elicit conformation changes when they were interacting with BhorOBP28. Batocera horsfieldi females exhibited a preference for (−)‐Limonene, and a repellent response to (+)‐Longifolene. Feeding dsOBP19 produced by a bacteria‐expressed system with a newly constructed vector could lead to the knockdown of BhorOBP28, and could further impair B. horsfieldi attraction to (−)‐Limonene and repellent activity of (+)‐Longifolene. The analysis of site‐directed mutagenesis revealed that Leu7, Leu72, and Phe121 play a vital role in selectively binding properties of BhorOBP28.CONCLUSIONBy modeling the molecular mechanism of olfactory recognition, these results demonstrate that BhorOBP28 is involved in the chemoreception of B. horsfieldi. The bacterial‐expressed dsRNA delivery system gains new insights into potential population management strategies. Through the olfactory process concluded that discovering novel behavioral regulation and environmentally friendly control options for B. horsfieldi in the future. © 2024 Society of Chemical Industry.
The Effects of D‐Allulose on the Gelatinization and Recrystallization Properties of Starches from Different Botanical Sources
Authors: Kwakye Alexandra Obenewaa , Fukada Kazuhiro , Ishii Toya , Ogawa Masahiro 
Published: April 2024

AbstractD‐allulose (Alu), a rare sugar, has proven to be a low‐caloric sugar with potential health benefits. Previous studies have reported that compared with sucrose (Suc), Alu suppresses an increase in gelatinization temperature and retards retrogradation in glutinous rice starch. This study investigates the effect of Alu on gelatinization, water activity, and recrystallization behavior of various starch sources (potato, wheat, tapioca, corn, normal rice, and glutinous rice). MicroDSC results show that compared with D‐glucose (Glc), D‐fructose (Fru), and Suc, Alu does not significantly increase the gelatinization temperatures of the starch suspensions. Alu decreases water activity in the same degree as Fru in wheat, tapioca, corn, normal rice, and glutinous rice starch gels but not potato starch gels. Alu has a stronger suppression effect on recrystallization of normal and glutinous rice compared to potato, wheat, and tapioca after 14‐day storage of 2% starch pastes at 4 °C. These findings suggest that Alu can be a better plasticizer than Suc, Glc, and Fru in most starch sources but retards recrystallization of only normal and glutinous rice starches.
Probing bad theories with the dualization algorithm. Part I
Authors: Giacomelli Simone , Hwang Chiung , Marino Fabio , Pasquetti Sara , Sacchi Matteo 
Published: April 2024

Abstract
Recently an algorithm to build SL(2, ℤ) duals, including mirror duals, of 3d $$ \mathcal{N} $$
N
= 4 quiver theories and their 4d $$ \mathcal{N} $$
N
= 1 uplift has been introduced. In this work we use this new tool to study the so-called bad theories. Our approach allows us to determine exactly indices/partition functions for generic values of fugacities/real mass and FI parameters revealing their surprising feature: the 4d index/3d partition function of a bad theory behaves as a sum of distributions rather than an ordinary function of the deformation parameters. We focus on the bad SQCD, with U(Nc) gauge group in 3d and USp(2Nc) in 4d, while in an upcoming paper we will consider linear quivers which, in the 3d case, have both unitary and special unitary bad nodes.
Lorentzian threads and generalized complexity
Authors: Cáceres Elena , Carrasco Rafael , Patil Vaishnavi 
Published: April 2024

Abstract
Recently, an infinite class of holographic generalized complexities was proposed. These gravitational observables display the behavior required to be duals of complexity, in particular, linear growth at late times and switchback effect. In this work, we aim to understand generalized complexities in the framework of Lorentzian threads. We reformulate the problem in terms of thread distributions and measures and present a program to calculate the infinite family of codimension-one observables. We also outline a path to understand, using threads, the more subtle case of codimension-zero observables.
Identification of superior and rare haplotypes to optimize branch number in soybean
Authors: Yu Hui , Bhat Javaid Akhter , Li Candong , Zhao Beifang , Bu Moran , Zhang Zhirui , Guo Tai , Feng Xianzhong 
Published: April 2024

Abstract
Key message
Using the integrated approach in the present study, we identified eleven significant SNPs, seven stable QTLs and 20 candidate genes associated with branch number in soybean.

Abstract
Branch number is a key yield-related quantitative trait that directly affects the number of pods and seeds per soybean plant. In this study, an integrated approach with a genome-wide association study (GWAS) and haplotype and candidate gene analyses was used to determine the detailed genetic basis of branch number across a diverse set of soybean accessions. The GWAS revealed a total of eleven SNPs significantly associated with branch number across three environments using the five GWAS models. Based on the consistency of the SNP detection in multiple GWAS models and environments, seven genomic regions within the physical distance of ± 202.4 kb were delineated as stable QTLs. Of these QTLs, six QTLs were novel, viz., qBN7, qBN13, qBN16, qBN18, qBN19 and qBN20, whereas the remaining one, viz., qBN12, has been previously reported. Moreover, 11 haplotype blocks, viz., Hap4, Hap7, Hap12, Hap13A, Hap13B, Hap16, Hap17, Hap18, Hap19A, Hap19B and Hap20, were identified on nine different chromosomes. Haplotype allele number across the identified haplotype blocks varies from two to five, and different branch number phenotype is regulated by these alleles ranging from the lowest to highest through intermediate branching. Furthermore, 20 genes were identified underlying the genomic region of ± 202.4 kb of the identified SNPs as putative candidates; and six of them showed significant differential expression patterns among the soybean cultivars possessing contrasting branch number, which might be the potential candidates regulating branch number in soybean. The findings of this study can assist the soybean breeding programs for developing cultivars with desirable branch numbers.
Hyper-ambition and the Replication Crisis: Why Measures to Promote Research Integrity can Falter
Authors: Erden Yasemin J. 
Published: April 2024

AbstractThis paper introduces the concept of ‘hyper-ambition’ in academia as a contributing factor to what has been termed a ‘replication crisis’ across some sciences. The replication crisis is an umbrella term that covers a range of ‘questionable research practices’, from sloppy reporting to fraud. There are already many proposals to address questionable research practices, some of which focus on the values, norms, and motivations of researchers and institutes, and suggest measures to promote research integrity. Yet it is not easy to promote integrity in hyper-competitive academic environments that value high levels of ambition. I argue that in such contexts, it is as likely that a kind of hyper-ambition is fostered that (inadvertently or otherwise) prioritises individual success above all, including to the detriment of scientific quality. In addition, efforts to promote values like integrity falter because they rely on sufficient uniformity in motivations or tendencies. Codes and guidance promoting integrity are, however, likely to influence those for whom such values are not optional, while others simply find ways around them. To demonstrate this I offer a thought experiment in which we consider the imaginary working situations of two ordinary academics. I conclude that tackling questionable research practices in the light of the replication crisis requires robust ‘top down’ measures that expect and accommodate a broader range of academic values, motivations, and tendencies, while challenging those that help to promote hyper-ambition.
Neuropragmatism, the cybernetic revolution, and feeling at home in the world
Authors: Solymosi Tibor 
Published: April 2024

Abstract
In recent work, Mark Johnson has argued that a scientifically updated version of John Dewey’s pragmatism affords human beings the opportunity to feel at home in the world. This feeling at home, however, is not fully problematized, nor explored, nor resolved by Johnson. Rather, Johnson and his collaborators, Don Tucker (2021) and Jay Schulkin (2023), defend this updated pragmatism within the historical development of the sciences of life and mind from the twentieth century to the present day. A central theme in this defense is the affinity pragmatism has with neurophenomenology, especially the enactivism seen in 4E cognition. Another theme is the future orientation of pragmatism, especially as it is focused on developments in cybernetics and artificial intelligence. Given Johnson’s previous work on expanding the number of E’s to 7, and other pragmatist suggestions for more, I argue that neuropragmatism’s development of Dewey’s conception of experience as organism-environment transaction (symbolized by the diphthong, Œ) is critical for understanding what Johnson and Tucker call the cybernetic revolution as an enchanting and welcoming future instead of a disenchanting and alienating one.
Dynamic Analysis of Loneliness at Older Ages in Europe by Gender
Authors: Pagan Ricardo , Malo Miguel Angel 
Published: April 2024

AbstractIn this article, we analyse loneliness trajectories for older people aged 50 or more in selected European countries by gender. We also focus on the relationship between disability and loneliness trajectories. We use three waves of the longitudinal SHARE database. Loneliness trajectories are non-linear, increasing with age for both genders, and have the same shape irrespective of disability status but with different levels of loneliness. Loneliness persistence increases with disability and disability severity, especially for women. Worsening (improving) disability increases (decreases) the risk of loneliness persistence. We build rankings of the country's effects on loneliness persistence by gender. Mediterranean and Eastern European countries have the highest persistence rates, while the lowest rates are in Northern countries.
Synergistic Interaction Effect of Artemisia cina n-hexane Extract and Tagetes lucida Ethyl Acetate Extract on Haemonchus Contortus
Authors: Santiago-Figueroa Itzel , González-Cortazar Manases , Estrada-Flores Julieta Gertrudis , Cuéllar-Ordaz Jorge Alfredo , López-Arellano María Eugenia , González-Reyes Francisco Javier , Olmedo-Juárez Agustín , Higuera-Piedrahita Rosa Isabel 
Published: April 2024

Abstract
Purpose
We analysed the possible synergistic activity among active extracts from Artemisia cina and Tagetes lucida combinations on Haemonchus contortus, a nematode parasitising sheep.

Methods
The work was carried out in vitro on eggs and infective larvae (L3) of H. contortus. The results were analysed with SAS 9.1, applying the ANOVA and Tukey test, and the lethal concentration (LC) values LC50 and LC90 were determined with regression analysis, employing Proc Probit of SAS 9.1. Additionally, the lethal concentration (LC) was calculated with LC50 and LC90 to determine the synergistic effect.

Results
The results demonstrated a high efficacy of the two plants studied on both nematode eggs and L3 larvae as well as of their combinations. The highest egg hatching inhibition was obtained with a 50/50 combination, and the best larvae mortality was obtained with 25% A. cina and 75% T. lucida at 10 mg/mL. Additionally, this combination showed a synergistic effect.

Conclusion
The two plant species studied here can be applied as natural anthelmintic alternatives due to their high bioactive effect and synergistic response.
The impact of education costs on income inequality
Authors: Chang Fa-Hsiang 
Published: April 2024

AbstractReducing education costs is a crucial policy element with broad support in the U.S. However, is lowering the cost of learning a panacea for eliminating income inequality? In this paper, I theoretically examine the relationship between income inequality and the cost of education by building a three-stage overlapping generation model with two sectors and two education systems. In contrast to conventional studies treating education as a unified concept or in hierarchical order, I consider two types of education, each targeting the training of workers for different roles in production. Workers who decide to spend time learning and improving creativity skills can work to produce intermediate goods used in current production and illuminate future production technology. Coders who produce industrial robots are one example of workers who receive this type of education. The other type of education only improves workers’ efficiency and helps them become experts in positions. For instance, office clerks who receive computer training can become more productive in dealing with their daily tasks. I pick a reasonable set of parameters, and the simulation result implies that reducing the cost of practical training may end up enlarging income inequality. The key is whether the effect resulting from the wage gap between jobs (wageeffect) dominates the effect of changing the share of workers in jobs (compositioneffect). Reducing the cost of learning creativity encourages marginal experts to learn creativity and marginal basic workers to receive training, leading to declining wage gaps and income inequality.
Academic integrity graphic novel mini-cases
Authors: Fischbach Sarah 
Published: April 2024

AbstractAcademic integrity is a crucial aspect of the educational process, often receiving insufficient attention until a violation occurs. Researchers emphasize the importance of students comprehending academic integrity to foster ethical professionalism. However, there is a lack of resources available to effectively support these conversations. This study aims to assess academic integrity efficacy and the multi-dimensional ethical scale (MES) through the use of a graphic novel mini-case study. The analysis reveals a significant relationship between academic integrity efficacy, MES dimensions (moral equity, relativism and contractualism), and the case studies among undergraduate participants. The combination of quantitative and qualitative findings provides valuable insights into how graphic novel mini-cases can engage in academic integrity discussions with undergraduate students. The graphic novel mini-cases, along with their limitations and potential for future research, are provided.
Short-term trends of air quality and pollutant concentrations in Nigeria from 2018–2022 using tropospheric sentinel-5P and 3A/B satellite data
Authors: Omokpariola Daniel O. , Nduka John N. , Omokpariola Patrick L. 
Published: April 2024

AbstractThis study presents a comprehensive analysis of atmospheric parameters in Nigeria, utilizing Sentinel-5P and 3A/B offline datasets from April 2018 to December 2022. The research evaluates the concentrations of pollutants such as Nitrogen Dioxide (NO2), Sulphur Dioxide (SO2), Ozone (O3), Formaldehyde (HCHO), Methane (CH4), Carbon Monoxide (CO), and Aerosol Indices (AI) across different periods. The data analysis employs multivariate techniques, including Factor Analysis, Pearson Correlation Coefficient, Scatter Plots, and Dendrogram Clustering, providing insights into the interrelationships and potential sources of pollution. Additionally, the study examines monthly trends, temperature variations, and their impacts on human health and climate. The findings reveal stable levels of NO2, SO2, O3, and HCHO with minimal fluctuations, while CH4 and CO exhibit slight variations, possibly influenced by emission reductions or atmospheric changes. Aerosol optical indices consistently indicate aerosol presence, influenced by local emissions and atmospheric processes. Multivariate analyses highlight shared patterns among atmospheric constituents, shedding light on potential common sources and chemical relationships. The Pearson correlation coefficients illustrate the strength and direction of linear relationships, offering valuable information on pollution dynamics. The study's visualizations, including scatter plots and dendrogram clustering, enhance the understanding of complex interactions. Overall, the research underscores the significance of continuous monitoring and research efforts for informed decision-making and environmental management in Nigeria.
Analysis of English Classroom Teaching Behavior Mode in Environmental Protection Field Based on Deep Learning
Authors: Li Yuanyuan 
Published: April 2024

AbstractLearning is to use algorithms to enable machines to learn rules from a large amount of historical data, so as to intelligently identify new samples or predict the future. Deep learning can promote students’ understanding of knowledge, conduct in-depth processing of new knowledge, integrate it with the original knowledge, and apply it to new situations, solve intelligent audio–visual listening from the perspective of deep learning, and focus on cultivating students’ in-depth learning ability and individual differences in innovative thinking. As the main position of ecological education, schools should effectively strengthen the publicity and education of ecological ideas and low-carbon concepts, and integrate them into education and teaching to effectively improve students’ awareness of environmental protection. This study aims to explore the effectiveness of flipped classroom teaching model based on deep learning. Therefore, from the perspective of deep learning, this paper combs the theory of deep learning, constructs a new model of smart classroom, and provides ideas and directions for model reform. In this study, the flipped classroom teaching model based on deep learning was applied to English teaching, and an 8-week teaching experiment was conducted. In addition, this paper believes that it is of great practical significance to carry out environmental protection education with the help of English teaching.
Machine Learning Algorithms for Power System Sign Classification and a Multivariate Stacked LSTM Model for Predicting the Electricity Imbalance Volume
Authors: Bâra Adela , Oprea Simona-Vasilica 
Published: April 2024

AbstractThe energy transition to a cleaner environment has been a concern for many researchers and policy makers, as well as communities and non-governmental organizations. The effects of climate change are evident, temperatures everywhere in the world are getting higher and violent weather phenomena are more frequent, requiring clear and firm pro-environmental measures. Thus, we will discuss the energy transition and the support provided by artificial intelligence (AI) applications to achieve a cleaner and healthier environment. The focus will be on applications driving the energy transition, the significant role of AI, and collective efforts to improve societal interactions and living standards. The price of electricity is included in almost all goods and services and should be affordable for the sustainable development of economies. Therefore, it is important to model, anticipate and understand the trend of electricity markets. The electricity price includes an imbalance component which is the difference between notifications and real-time operation. Ideally it is zero, but in real operation such differences are normal due to load variation, lack of renewable energy sources (RES) accurate prediction, unplanted outages, etc. Therefore, additional energy has to be produced or some generating units are required to reduce generation to balance the power system. Usually, this activity is performed on the balancing market (BM) by the transmission system operator (TSO) that gathers offers from generators to gradually reduce or increase the output. Therefore, the prediction of the imbalance volume along with the prices for deficit and surplus is of paramount importance for producers’ decision makers to create offers on the BM. The main goal is to predict the imbalance volume and minimize the costs that such imbalance may cause. In this chapter, we propose a method to predict the imbalance volume based on the classification of the imbalance sign that is inserted into the dataset for predicting the imbalance volume. The imbalance sign is predicted using several classifiers and the output of the classification is added to the input dataset. The rest of the exogenous variables are shifted to the values from previous day d − 1. Therefore, the input variables are either predicted (like the imbalance sign) or are known from d − 1. Several metrics, such as mean average percentage error (MAPE), determination coefficient R2 and mean average error (MAE) are calculated to assess the proposed method of combining classification machine learning (ML) algorithms and recurrent neural networks (RNN) that memorize variations, namely long short-term memory (LSTM) model.
Klimabewusste Verordnung von Inhalativa – Umsetzung in der hausärztlichen Praxis
Authors: Schmiemann Guido , Dörks Michael , Martin Eric , Grah Christian 
Published: April 2024

Zusammenfassung
Hintergrund
Das Gesundheitswesen ist in Deutschland für 5,2 % der CO2-Emissionen verantwortlich. Die Verordnung von Medikamenten trägt wesentlich dazu bei. Unter den verordneten Arzneimitteln spielen Dosieraerosole (DA) aufgrund der enthaltenen Treibgase eine entscheidende Rolle. Durch einen Wechsel auf Pulverinhalationssysteme (DPI) ist eine deutliche Reduktion der Emissionen möglich.

Ziel der Arbeit
Die S2k-Leitlinie „Klimabewusste Verordnung von Inhalativa“ soll Hilfestellungen bei der Verordnung von inhalativen Arzneimitteln geben, indem sie die vorhandene Evidenz zur Entscheidung zwischen DPI (Pulverinhalatoren) und DA (Dosieraerosolen) zusammenfasst und dabei den Aspekt des Klimaschadens durch Treibmittel explizit aufgreift. Sie richtet sich an alle, die an der Verordnung sowie der Beratung von Betroffenen beteiligt sind.

Material und Methoden
Unter gemeinsamer Federführung von DEGAM (Deutsche Gesellschaft für Allgemeinmedizin und Familienmedizin) und der Deutschen Gesellschaft für Pneumologie und Beatmungsmedizin (DGP) wurde die S2k-Leitlinie unter Moderation durch die AWMF (Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften) erstellt. Die wesentlichen Inhalte aus der Praxisperspektive werden in dieser Arbeit vorgestellt.

Ergebnisse
DA haben in Deutschland insgesamt einen hohen Anteil an den Verordnungen von Inhalativa. Bei der Verordnung sollten die Aspekte des Klimaschadens berücksichtigt werden. Um die Umsetzung in der Praxis zu erleichtern, wurden mehrere Entscheidungshilfen erstellt.

Schlussfolgerung
Die Bedeutung der Verschreibung einer Arzneimittelgruppe in Bezug auf den Klimawandel wird erstmals im Rahmen einer Leitlinie thematisiert. Ein hoher Umsetzungsgrad der Leitlinienempfehlungen kann durch zukünftige Analysen der Verordnungszahlen erhoben werden. Um die Akzeptanz der Entscheidungshilfen zu prüfen, ist ein geplanter Praxistest erforderlich.