bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tuning of meristem maturation rate increases yield in multiple Triticum aestivum cultivars
Authors: Goldshmidt Alexander , Ziegler Todd , Zhou Dafeng , Brower‐Toland Brent , Preuss Sasha , Slewinski Thomas 
Published: November 2022

AbstractBreeding programs aim to improve crop yield and environmental stability for enhanced food security. The principal methodology in breeding for stable yield gain relies on the indirect selection of beneficial genetics by yield evaluation across diverse environmental conditions. This methodology requires substantial resources while delivering a slow pace of yield gain and environmental adaptation. Alternative methods are required to accelerate gain and adaptation, becoming even more imperative in a changing climate. New molecular tools and approaches can enable accelerated creation and deployment of multiple alleles of genes identified to control key traits. With the advent of tools that enable breeding by targeted allelic selection, identifying gene targets associated with an improved crop performance ideotype will become crucial. Previous studies have shown that altered photoperiod regimes increase yield in wheat (Triticum aestivum). In the current study, we have employed such treatments to study the resulting yield ideotype in five spring wheat cultivars. We found that the photoperiod treatment creates a yield ideotype arising from delayed spike establishment rates that are accompanied by increased early shoot expression of TARGET OF EAT1 (TaTOE1) genes. Genes identified in this way could be used for ideotype‐based improve crop performance through targeted allele creation and selection in relevant environments.
Assign‐MALDI – A free software for assignment of MALDI‐TOF MS spectra of glycans derivatized using common and novel labeling strategies
Authors: Parsons Lisa M. , Cipollo John F. 
Published: November 2022

AbstractMatrix Assisted Laser Desorption/Ionization Time‐of‐flight (MALDI‐ToF) MS is a popular method to analyze glycans released from proteins, cell lines, and tissue samples. Chemical modification of glycans (derivatization) can enhance ionization, enable semi‐quantitation, and assist in linkage identification. However, the mass changes incurred by novel and more recently developed derivatizations are not accommodated by most spectral assignment programs, necessitating manual assignment which increases both the difficultly and the likelihood of error. AssignMALDI is a software tool designed to create glycan databases with customized derivatizations (labels) and automatically assign glycan masses in MALDI‐TOF spectra using the new database. It can also average peak intensities across multiple spectra and prepare publication‐ready assignment tables. To make it easy to use with different platforms, all input files and most output files are in text format. An interactive display enables users to inspect and edit peak assignments prior to producing charts and tables for publication. The program is freely available through GitHUB and Python‐savvy users can add or adjust features as needed.
Fenoxycarb exposure affects antiviral immunity and HaNPV infection in the cotton bollworm, Helicoverpa armigera
Authors: Attarianfar Marzieh , Mikani Azam , Mehrabadi Mohammad 
Published: November 2022

AbstractBackgroundApplication of insect growth regulators (IGR) is a good option for insect pest management because of their fewer adverse effects on humans and domestic animals. These compounds are capable of interfering with normal growth and development by mimicking the actions of hormones such as juvenile hormone (JH) or ecdysone. The effect of JH and its analogs on some aspects of insect immunity has been determined, yet their possible effects on antiviral immunity response has not been investigated yet. Considering the importance of antiviral response in viral replication, in this study the effects of the JH analog (JHA), fenoxycarb on the antiviral immunity pathway core genes [i.e. micro (mi)RNA, small interfering (si)RNA and apoptosis] of Helicoverpa armigera (Hubner) larvae were investigated. The effect of fenoxycarb on the susceptibility of the larvae to H. armigera nuclear polyhedrosis virus (HaNPV) also was assessed.ResultsThe results showed that the transcription level of miRNA (Dicer1, Ago1), siRNA (Dicer2, Ago2) and apoptosis (Caspase1, Caspase5) core genes in H. armigera larvae were decreased significantly after 24, 48 and 96 h feeding on a diet containing lethal and sublethal doses of fenoxycarb. Moreover, the mortality rate to HaNPV in the larvae treated with fenoxycarb increased compared to the control, leading to an increased replication of HaNPV.ConclusionTogether, our results suggest that the antiviral immune system could be modulated by JHA and facilitate HaNPV replication in the larvae, increasing the mortality rate of the insect larvae. Understanding the effect of JHA on antiviral immunity is an important step toward the process of exploiting JHAs and viral pathogens to control insect pests. © 2022 Society of Chemical Industry.
Retraction: Co3O4 Polyhedron@MnO2 Nanotube Composite as Anode for High‐Performance Lithium‐Ion Batteries
Authors: Cao Zhiguang , Yang Yuebei , Qin Junling , He Jieying , Su Zixue 
Published: November 2022

Small 2021, 17, 2008165DOI: 10.1002/smll.202008165The above article in Small, published online on 26 March 2021 in Wiley Online Library (https://onlinelibrary.wiley.com/doi/abs/10.1002/smll.202008165),[1] has been retracted by agreement between the authors, the Editor‐in‐Chief, José Oliveira, and Wiley‐VCH GmbH. The retraction has been agreed following an investigation by the corresponding author. The electrochemical measurements on the anode were performed in a wrong manner and cannot reliably be reproduced. The conclusions of this article are considered to be invalid. The authors agree with the retraction but were not available to confirm the final wording of the retraction.[1] Z. Cao, Y. Yang, J. Qin, J. He, Z. Su, Small 2021, 17, 2008165.
Constructing (ad)ventures in Collaborative Composing: Examining a Case of (un)sanctioned Play in the Elementary Literacies Classroom
Authors: Brownell Cassie J. 
Published: November 2022

AbstractUsing data from a year‐long case study in a Midwestern public school in the United States, the author invites readers into the play world of four multilingual and multiracial boys, affectionately named the “LEGO Boys” by their third‐grade teacher. As documented in the findings, the boys maintained a cohesive narrative about how their stories fit with the sanctioned prompt's goals while engaged in collaborative (un)sanctioned play. Ultimately, the “LEGO Boys” serve as an exemplar of how children collaboratively curate the curriculum for their own purposes under the radar of adults.
Robust estimation of clinch joint characteristics based on data-driven methods
Authors: Zirngibl Christoph , Schleich Benjamin , Wartzack Sandro 
Published: November 2022

AbstractGiven a steadily increasing demand on multi-material lightweight designs, fast and cost-efficient production technologies, such as the mechanical joining process clinching, are becoming more and more relevant for series production. Since the application of such joining techniques often base on the ability to reach similar or even better joint loading capacities compared to established joining processes (e.g., spot welding), few contributions investigated the systematic improvement of clinch joint characteristics. In this regard, the use of data-driven methods in combination with optimization algorithms showed already high potentials for the analysis of individual joints and the definition of optimal tool configurations. However, the often missing consideration of uncertainties, such as varying material properties, and the related calculation of their impact on clinch joint properties can lead to poor estimation results and thus to a decreased reliability of the entire joint connection. This can cause major challenges, especially for the design and dimensioning of safety-relevant components, such as in car bodies. Motivated by this, the presented contribution introduces a novel method for the robust estimation of clinch joint characteristics including uncertainties of varying and versatile process chains in mechanical joining. Therefore, the utilization of Gaussian process regression models is demonstrated and evaluated regarding the ability to achieve sufficient prediction qualities.
Design of tool grinding processes for indexable inserts made of rocks
Authors: Wolters Philipp , Breidenstein Bernd , Denkena Berend , Bergmann Benjamin 
Published: November 2022

AbstractUsing natural rocks as alternative cutting tool material poses a possibility to meet actual environmental, economic and geopolitical challenges. The present state of knowledge, however, is not sufficient to allow a knowledge-based design of the tool grinding process of cutting tools made of rock. For this reason, this study presents an investigation of the significance of the grinding process parameters and grinding tool specifications for the flank face and cutting edge roughness as well as for the cutting edge microgeometry besides an analysis of the scatter of the grinding results in tool grinding of rock inserts. Thus, the study contributes to a knowledge-based design of tool grinding processes of rock tools. In this context, confocal and focus variation microscopes are used besides SEM images to investigate the above mentioned factors in the plunge face grinding of rock inserts from five different rocks. The results identify the axial feed velocity of the plunge face grinding process as a highly significant influence factor for cutting edge roughness and microgeometry, while cutting speed only shows a significant influence on cutting edge microgeometry. Besides that, highly significant influences of the used rock type and the abrasive grain size are identified for all three mentioned factors. Grinding result analyses show a scatter between 0.04 and 25.00 µm depending on the parameter and rock investigated. Additionally, recommendations for the design of the tool grinding process of rock tools are presented deduced from the obtained results.
A New Monitoring Strategy of Large Micro-, Meso- and Macro-Litter: A Case Study on Sandy Beaches of Baltic Lagoons and Estuaries
Authors: Gyraite Greta , Haseler Mirco , Balčiūnas Arūnas , Sabaliauskaitė Viktorija , Martin Georg , Reisalu Greta , Schernewski Gerald 
Published: November 2022

AbstractCoastal lagoons and estuaries are hot spots to accumulate river basin-related plastic leakage. However, no official methodology exists to investigate their relatively short, rich in organic matter beaches, and the knowledge of pollution of lagoons is scarce worldwide. This study aimed to develop a methodology suitable for large micro (2–5 mm), meso (5–25 mm), and macro-litter (>25 mm) monitoring at sandy inner-coastal waters that would provide comparable results to the intensively used OSPAR 100 m method. The method proposed in this study is based on two 40 m2 rectangular polygons placed on the tidal accumulation zone for macro-litter enumeration and two 1 m2 squares for micro- and meso-litter. This method has been applied to 23 beaches from three inner-coastal waters of the Baltic Sea. This study shows that the litter densities between lagoons and bays differ and depend on the river output intensity and the retention capacity. The “Construction material”, “Plastic pieces 2–5 mm”, and “Plastic pieces 5–25 mm” were among this study’s top ten most common litter items. Experts allocated these items to the “Land based industry and trade” source, which indicates that lagoons and bays through the connection of the major rivers could be a potential sink of land-based litter. An evident strength of the methodology established is the capability to determine litter of all sizes, low-cost and time-efficiency, implementable for volunteer-based monitoring; provides comparable results to the most commonly used methods for investigating litter pollution on coastal beaches.
Effect of prior martensite formation on the bainite transformation kinetics in high-strength 3% Mn multiphase steel
Authors: Morawiec M. , Skowronek A. , Kozłowska A. , Garcia-Mateo C. , Grajcar A. 
Published: November 2022

AbstractThe work presents results on the effect of prior martensite formation on bainite transformation kinetics in a 3% medium-Mn multiphase steel. The material was subjected to two isothermal holding temperatures: 400 °C (without martensite) and 350 °C (with prior martensite). According to obtained dilatometric results, the formation of prior martensite leads to the acceleration of bainite transformation kinetics. The bainite formation starts and finishes much faster, when the prior martensite was present before the isothermal holding. The microstructural investigation of the steel after heat treatment was carried out using light and scanning electron microscopy. The microstructures were composed of fine bainitic laths with retained austenite and small amount of martensitic-austenitic islands at 400 °C. At 350 °C the presence of large tempered martensite laths was detected. The bainite is composed of a mixture of fine and coarse laths. The increase of the bainitic lath thickness is attributed to the coalescence process occurring at the lower holding temperature. The differences in the steel hardness after the two heat treatments were relatively small (~ 13 HV10).
The Quantified Argument Calculus with Two- and Three-valued Truth-valuational Semantics
Authors: Yin Hongkai , Ben-Yami Hanoch 
Published: November 2022

AbstractWe introduce a two-valued and a three-valued truth-valuational substitutional semantics for the Quantified Argument Calculus (Quarc). We then prove that the 2-valid arguments are identical to the 3-valid ones with strict-to-tolerant validity. Next, we introduce a Lemmon-style Natural Deduction system and prove the completeness of Quarc on both two- and three-valued versions, adapting Lindenbaum’s Lemma to truth-valuational semantics. We proceed to investigate the relations of three-valued Quarc and the Predicate Calculus (PC). Adding a logical predicateTto Quarc, true of all singular arguments, allows us to represent PC quantification in Quarc and translate PC into Quarc, preserving validity. Introducing a weak existential quantifier into PC allows us to translate Quarc into PC, also preserving validity. However, unlike the translated systems, neither extended system can have a sound and complete proof system with Cut, supporting the claim that these are basically different calculi.
Exploring Radiomics for Classification of Supraglottic Tumors: A Pilot Study in a Tertiary Care Center
Authors: Rao Divya , Koteshwara Prakashini , Singh Rohit , Jagannatha Vijayananda 
Published: November 2022

AbstractAccurate classification of laryngeal cancer is a critical step for diagnosis and appropriate treatment. Radiomics is a rapidly advancing field in medical image processing that uses various algorithms to extract many quantitative features from radiological images. The high dimensional features extracted tend to cause overfitting and increase the complexity of the classification model. Thereby, feature selection plays an integral part in selecting relevant features for the classification problem. In this study, we explore the predictive capabilities of radiomics on Computed Tomography (CT) images with the incidence of laryngeal cancer to predict the histopathological grade and T stage of the tumour. Working with a pilot dataset of 20 images, an experienced radiologist carefully annotated the supraglottic lesions in the three-dimensional plane. Over 280 radiomic features that quantify the shape, intensity and texture were extracted from each image. Machine learning classifiers were built and tested to predict the stage and grade of the malignant tumour based on the calculated radiomic features. To investigate if radiomic features extracted from CT images can be used for the classification of laryngeal tumours. Out of 280 features extracted from every image in the dataset, it was found that 24 features are potential classifiers of laryngeal tumour stage and 12 radiomic features are good classifiers of histopathological grade of the laryngeal tumor. The novelty of this paper lies in the ability to create these classifiers before the surgical biopsy procedure, giving the clinician valuable, timely information.
Testing Very Large Database Management Systems: The Case of SAP HANA
Authors: Bach Thomas , Andrzejak Artur , Seo Changyun , Bierstedt Christian , Lemke Christian , Ritter Daniel , Hwang Dong Won , Sheshi Erda , Schabernack Felix , Renkes Frank , Gaumnitz Gordon , Martens Jakob , Hoemke Lars , Felderer Michael , Rudolf Michael , Jambigi Neetha , May Norman , Joy Robin , Scheja Ruben , Schwedes Sascha , Seibel Sebastian , Seifert Sebastian , Haas Stefan , Kraft Stephan , Kroll Thomas , Scheuer Tobias , Lehner Wolfgang 
Published: November 2022

AbstractSoftware Testing is an established activity in the software development process to ensure and improve the quality of a software. Consequently, there exists a wide range of literature, popular information, and even multiple ISO standards covering this topic. However, we found that testing very large database management systems (DBMS) requires special adaptations of the generally available guidance for software testing and requires to solve specific challenges that may not be relevant for other areas or smaller software projects. We therefore discuss the testing of SAP HANA, a very large software project with millions of lines of code, to share insights about our approach, best practices, and unsolved challenges that are open for further research.
CArdiac and REspiratory adaptive Computed Tomography (CARE-CT): a proof-of-concept digital phantom study
Authors: Morton Natasha , Keall Paul , O’Brien Ricky , Reynolds Tess 
Published: November 2022

AbstractCurrent respiratory 4DCT imaging for high-dose rate thoracic radiotherapy treatments are negatively affected by the complex interaction of cardiac and respiratory motion. We propose an imaging method to reduce artifacts caused by thoracic motion, CArdiac and REspiratory adaptive CT (CARE-CT), that monitors respiratory motion and ECG signals in real-time, triggering CT acquisition during combined cardiac and respiratory bins. Using a digital phantom, conventional 4DCT and CARE-CT acquisitions for nineteen patient-measured physiological traces were simulated. Ten respiratory bins were acquired for conventional 4DCT scans and ten respiratory bins during cardiac diastole were acquired for CARE-CT scans. Image artifacts were quantified for 10 common thoracic organs at risk (OAR) substructures using the differential normalized cross correlation between axial slices (ΔNCC), mean squared error (MSE) and sensitivity. For all images, on average, CARE-CT improved the ΔNCC for 18/19 and the MSE and sensitivity for all patient traces. The ΔNCC was reduced for all cardiac OARs (mean reduction 21%). The MSE was reduced for all OARs (mean reduction 36%). In the digital phantom study, the average scan time was increased from 1.8 ± 0.4 min to 7.5 ± 2.2 min with a reduction in average beam on time from 98 ± 28 s to 45 s using CARE-CT compared to conventional 4DCT. The proof-of-concept study indicates the potential for CARE-CT to image the thorax in real-time during the cardiac and respiratory cycle simultaneously, to reduce image artifacts for common thoracic OARs.
Two-stream temporal enhanced Fisher vector encoding for skeleton-based action recognition
Authors: Tang Jun , Liu Baodi , Guo Wenhui , Wang Yanjiang 
Published: November 2022

AbstractThe key to skeleton-based action recognition is how to extract discriminative features from skeleton data. Recently, graph convolutional networks (GCNs) are proven to be highly successful for skeleton-based action recognition. However, existing GCN-based methods focus on extracting robust features while neglecting the information of feature distributions. In this work, we aim to introduce Fisher vector (FV) encoding into GCN to effectively utilize the information of feature distributions. However, since the Gaussian Mixture Model (GMM) is employed to fit the global distribution of features, Fisher vector encoding inevitably leads to losing temporal information of actions, which is demonstrated by our analysis. To tackle this problem, we propose a temporal enhanced Fisher vector encoding algorithm (TEFV) to provide more discriminative visual representation. Compared with FV, our TEFV model can not only preserve the temporal information of the entire action but also capture fine-grained spatial configurations and temporal dynamics. Moreover, we propose a two-stream framework (2sTEFV-GCN) by combining the TEFV model with the GCN model to further improve the performance. On two large-scale datasets for skeleton-based action recognition, NTU-RGB+D 60 and NTU-RGB+D 120, our model achieves state-of-the-art performance.
Effect of some bee bread quality on protein content and antioxidant system of honeybee workers
Authors: Tawfik Amer I. , Ahmed Zeinab H. , Abdel-Rahman M. F. , Moustafa A. M. 
Published: November 2022

AbstractProtein content and antioxidants in both bee bread and honeybee workers were analyzed investigating the relationships between those two parameters. Results indicated significant differences between both protein and antioxidant content [total antioxidant content (TAX), glutathione (GSH) and lipid peroxidation (LPO) levels] of bee bread types. Generally, workers fed sugar syrup only (control) had significantly lower protein content, superoxide dismutase (SOD), catalase (CAT), and GSH in comparison to bees fed bee bread at all studied ages. On the other hand, LPO levels in control worker bees were significantly higher than those of bees fed fennel, maize, cucumber, clover, and broad bean bee bread. Results also showed a positive relationship between protein content and antioxidants in bee bread and between protein content and the antioxidant system of honeybees, respectively. There was a negative correlation between protein content and antioxidants. In addition, the present study showed that both the protein quantity and quality of bee bread are important for honeybees. To our knowledge, this study is the first to report the relationship between antioxidant content in bee bread and antioxidant system of honeybees. The present study showed a causal link between antioxidant system and protein content in honeybees, and the contents of both antioxidants and protein in bee bread.
Credit Scoring with Drift Adaptation Using Local Regions of Competence
Authors: Nikolaidis Dimitrios , Doumpos Michalis 
Published: November 2022

AbstractDespite the advances in machine learning (ML) methods which have been extensively applied in credit scoring with positive results, there are still very important unresolved issues, pertaining not only to academia but to practitioners and the industry as well, such as model drift as an inevitable consequence of population drift and the strict regulatory obligations for transparency and interpretability of the automated profiling methods. We present a novel adaptive behavioral credit scoring scheme which uses online training for each incoming inquiry (a borrower) by identifying a specific region of competence to train a local model. We compare different classification algorithms, i.e., logistic regression with state-of-the-art ML methods (random forests and gradient boosting trees) that have shown promising results in the literature. Our data sample has been derived from a proprietary credit bureau database and spans a period of 11 years with a quarterly sampling frequency, consisting of 3,520,000 record-months observations. Rigorous performance measures used in credit scoring literature and practice (such as AUROC and the H-Measure) indicate that our approach deals effectively with population drift and that local models outperform their corresponding global ones in all cases. Furthermore, when using simple local classifiers such as logistic regression, we can achieve comparable results with the global ML ones which are considered “black box” methods.