bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genome-wide association study for resistance to stripe rust (Puccinia striiformis f. sp. tritici) races from Argentina in bread wheat (Triticum aestivum L.)
Authors: Franco Maria Fiorella , Polacco Ainara Noe , Campos Pablo Eduardo , Pontaroli Ana Clara , Vanzetti Leonardo Sebastian 
Published: September 2022

Abstract
Background: Wheat stripe rust, by Puccinia striiformis f. sp. tritici (Pst), is one of the most devastating diseases of the wheat crop, causing significant reductions in both grain yield and grain quality. In recent years, new and more virulent races have overcome many of the known resistance genes in Argentinian germplasm. In order to identify loci conferring resistance to the local races of Pst for effective utilization in future breeding programs, a genome-wide association study (GWAS) was performed using a collection of 245 bread wheat lines genotyped with 90K SNPs.
Results: The panel was evaluated for disease severity (DS) and area under disease progress curve (AUDPC) in field trials during two years to search for adult plant resistance (APR) under natural infection conditions, and under greenhouse conditions against two prevalent races in Argentina to determine infection type (IT) and look for seedling or all-stage resistance (ASR). The phenotypic data showed that the panel possessed enough genetic variability for searching for sources of resistance to Pst. Significant correlations between years were observed for Pst response in the field and high heritability values were found for DS (H2 = 0.89) and AUDPC (H2 = 0.93). Based on GWAS, eight markers associated with Pst resistance (FDR < 0.01) were identified: five associated with ASR (on chromosomes 1B, 2A, 3A and 5B) and three with APR (on chromosomes 3B and 7A). These markers explained between 2% and 32.62% of the phenotypic variation. Five of the markers corresponded with previously reported Yrgenes/QTL, while the other three (QYr.Bce.1B.seedling.1, QYr.Bce.3A.seedling and QYr.Bce.3B.APR.2) are probably novel resistance loci.
Conclusion: The detection of high genetic variation for resistance to Argentinian stripe rust races in the germplasm used here constitutes a very promising step towards the improvement of Pst resistance of bread wheat in Argentina. Also, the identification of new resistance loci represents a substantial advance for diversifying the current set of resistance genes and to advance in the improvement of the durable resistance to the disease.
Pharmacy driven medication reconciliation productivity and error reduction: results from a retrospective cohort study
Authors: Blum Rachel , Fredette Erica , Hyde Linda , Young Kristopher , Zhuang Yan L , Banas Colin A , Blakeslee Weston 
Published: September 2022

Abstract
Background:
Prior studies show that having a robust pharmacy-driven medication history program in a hospital setting, improves the quality of admission medication history interviews and reduces medication errors and adverse drug events. Yet, medication history data is tenuous and not always accurate or workable. There is a paucity of studies that compare how different data sources impact clinical workflow.
Methods:
We ran a retrospective, observational analysis following the implementation of a new medication history data source, in a busy urban hospital setting. The medication history workflow was optimized over a period of 8 years prior to this intervention, and there was little change in process between the two study periods.
Results:
Utilizing a data source that had 9.0% more prescription data, a user interface that displayed medication history in a simpler and more accurate manner, and a worksheet with all of the updated data, at the beginning of the medication history interview: staff productivity increased by 14.0%, total medication errors decreased by 23.0%, and medication errors that reached the patient decreased by 26.0%.
Conclusions
Having more complete data in the admission medication history interview can greatly improve productivity and reduce downstream medication errors that may cause adverse drug events.
Global ocean CO2 uptake dominated by the ENSO in the last thirty years
Authors: Zhong Guorong , Li Xuegang , Song JinMing , Qu Baoxiao , Wang Fan , Wang Yanjun , Zhang Bin , Ma Jun , Yuan Huamao , Duan Liqin 
Published: September 2022

Abstract
Previous estimation suggested a steadily strengthening global ocean carbon sink since 2001, after a weakening in the 1990s. However, the increases of carbon sink were asynchronous in different research. Here we reestimated the global ocean carbon sink during 1992-2020 using a new stepwise FFNN pCO2 product. Although the ocean is the sink of atmospheric CO2 in general, the global ocean carbon sink repeatedly strengthened and weakened in the last thirty years, which dominantly caused by the variability of Pacific Ocean carbon sink driven by the ENSO events. The Eastern equatorial Pacific may release more CO2 to the atmosphere because of the strengthened upwelling during the La Nina in the last thirty years. In addition, the reestimated carbon sink of the Southern Ocean has not been increasing as previous research. The SOCAT data used to construct Southern Ocean pCO2 are far more observed in summer than in winter, which underestimates the carbon source intensity of the Southern Ocean in winter in previous research. Although the ocean carbon sink is not always strengthening with the increase of atmospheric CO2 concentration, but the global ocean carbon sinks have been increasing since 2008, reaching 2.14±0.33 Pg C yr-1 in 2020.
Protein secretion zones within the Gram-positive cell wall
Authors: Strach Manuel , Koch Felicitas , Fiedler Svenja , Liebeton Klaus , Graumann Peter 
Published: September 2022

Abstract
Whereas the translocation of proteins across the cell membrane has been thoroughly investigated, it is still unclear how proteins cross the cell wall in Gram positive bacteria, which are widely used for industrial applications. We have studied secretion of α-amylase AmyE within two different Bacillus strains. We show that a C-terminal fusion of AmyE with the fluorescent reporter mCherry is secreted via discrete patches with very low dynamics that are visible at many places within the lateral cell wall, for many minutes. Expression from a high copy number plasmid was required to be able to see these structures we term “secretion zones”. Zones corresponded to visualized AmyE activity on the surface of cells, and frequently overlapped with SecA signals, but did not necessarily co-localize with the secretion ATPase. Single particle tracking showed much higher dynamics of SecA and of SecDF, involved in AmyE secretion, at the cell membrane than AmyE. These experiments suggest that SecA initially translocates AmyE molecules through the cell membrane, and then diffuses to a different translocon. Single molecule tracking of SecA show changes in distinct diffusion states of SecA, but suggest that AmyE overexpression does not overwhelm the system. Because secretion zones were only found during the transition to and within stationary phase, diffusion rather than passive transport based on cell wall growth from inside to outside, releases AmyE and thus probably secreted proteins in general. Our findings suggest active transport through the cell membrane and slow, passive transition through the cell wall in Gram positive bacteria.
Systematical Ingredient Investigations of Ficus tikoua Bur. Fruit and Immunoregulatory and Antioxidant Effects of Different Fractions
Authors: Gong Yu , Luo Wei , Chen Hulan , Ren Bo , Hu Weicheng , Li Limei 
Published: September 2022

Abstract
Although the fruit of Ficus tikoua Bur. has been consumed by montanic people in China over centuries, its chemical and biological composition was still unclear. A series of comprehensive investigations on its chemical constituents and bioactivities were carried out for the first time. As a result, six compounds were isolated and identified as the main components in this fruit. GC-MS analysis of the lipid components demonstrated that Ficus tikoua Bur. fruit contains some wholesome constituents such as fatty acids, vitamins, triterpenoids, and phytosterols. The fatty acids are mainly composed of linolenic acid (61.27%) and linoleic acid (22.79%). Furthermore this fruit contains a relative high content of crude protein (9.41 ± 0.03%), total amino acids (9.28%), and total polyphenols (0.86 ± 0.01 g/100g). The analysis of monosaccharide composition showed that the total polysaccharide mainly consists of glucose, glucuronic acid, xylose, arabinose, mannose, galactose, galacturonic acid, and rhamnose. The polysaccharide, polyphenol, water, ethanol, and flavonoid extracts exhibited prominent antioxidant activity determined by ABTS, DPPH, and FRAPS methods. Meanwhile, the total polysaccharide exhibited significant immunomodulatory effect by enhancing the release of cytokines and expression of iNOS and COX-2 in RAW264.7 cells, significantly decreasing the expression of c-Jun and p65 proteins in the cytoplasm and increasing the translocation of c-Jun and p65 to the nucleus, and regulating the phosphorylation level of Akt, PI3K, and PDK1 in PI3K/AKT signaling pathway. The study proved that the fruit of F. tikoua is a reliable source of functional food.
Lagrangian relaxation and ADMM based decomposition approaches for the road network design problem considering travel time variability
Authors: Song Maocan , Cheng Lin 
Published: September 2022

Abstract
We study an uncapacitated, multi-commodity network design problem with a construction budget constraint and a concave objective function. Instead of minimizing the expected travel time across all edges, the objective minimizes jointly the travel times that are standard deviation above the expected travel time of each commodity. The idea is that the decision-maker wants to minimize the travel times not only on average, but also to keep their variability as small as possible. Thus, another way to view the objective is as a linear combination of the mean and standard deviation of travel times. The proposed mean-standard deviation network design model is actually a nonlinear and concave integer program. At any rate, this problem is significantly harder to solve and cannot be tackled with off-the-shelf mixed-integer linear programming solvers. This study proposes two novel methods which are Lagrangian relaxation (LR) and augmented Lagrangian relaxation (ALR) to tackle this problem. The constraints that link the design with the flow variables are dualized in the objective function, resulting in a series of single-commodity reliable shortest path problems and a knapsack problem. The quadratic penalty terms are extended to the LR, and the alternating direction method of multipliers (ADMM) is introduced to decompose the ALR into routing and design optimizations. The routing optimization can be naturally decomposed into many single-commodity reliable shortest path subproblems solved by the Lagrangian substitution method. The primal heuristic uses the solution of knapsack problems that are solved in LR or ALR to generate upper bounds. The dual problems of LR and ALR are solved with the subgradient optimization method. Some computational results on three networks are present, showing that these methods achieve good integrality gaps.
Understanding the Mode Choice Behavior for Short Distance and Regular Travel in a Developing Country
Authors: Siraj Md Sifat Bin , Hasan Mahadi , Ahmed Md Tawkir 
Published: September 2022

Abstract
Mode choice behavior study get less attention in developing countrylike Bangladesh. Hence, this paper analyzes the factors affecting for short distanceand regular travel mode choice in Chittagong city. Data were collected from 17different busiest wards in Chittagong city corporation (CCC) from 514 citizens.Multinomial Probit (MNP) model have been used to determine significant factors formode choice. 16 and 10 contributing factors have been found significant for shortdistance and regular travel mode choice using MNP model. Result suggests that,Private vehicles (Car, Motorcycle) have been used for both sort distance and regulartravel mode choice those who have capacity to afford. Paratransit and Bus have beenused especially for low and medium income people and walking has been used foronly short distance regular travel. This study will help to city planner and engineersto make correct decision accordingly.
The Effect of Flipped Classroom Model on Knowledge, Practice, Attitude and Satisfaction of Dentistry Students; A Quasi-Experimental Study
Authors: Karandish Maryam , Karimian Zahra , Parastar Mina 
Published: September 2022

Abstract
Objectives: The purpose of this study was to determine the students' attitudes before and after the flipped classroom, the quality of the course, and the effectiveness of this method to promote the students' lateral cephalograms tracing abilities.
Methods: This is a single-group quasi-experimental research conducted on dental students of Shiraz University of Medical Sciences(SUMS), Iran in 2019. The intervention was carried out in a blended learning approach with the flipped classroom model.35 fourth-year dental students participated in a flipped classroom held during a semester for lateral cephalograms tracing course. The students were provided with the educational materials before the class time through multimedia learning tools and the class time was devoted to discussions. At the end of the session, the students were asked to fill questionnaires regarding their demographic information, their computer capabilities, their attitudes before and after the course, the quality of the course, the students' self-assessments of their theoretical knowledge and their practical skills in cephalograms tracing, and the effectiveness of different tools in their learning.
Results: Students' attitudes of this method were improved after taking the course and the quality of this method was acceptable to the students (p<0.001). Their self-assessment of theoretical knowledge and practical skills were promoted (p<0.001). All blended learning tools averaged more than the cutoff point, however short lecture (5.11±0.98) and live feedback (4.98±1.07) were considered to be the most efficient interactive tools.
Conclusion: It seems that the flipped classroom might have a positive effect on increasing students' knowledge, attitude and satisfaction. In general, this method of learning seems favor dental students with combination of attractiveness of electronic learning and the live teacher-student interactions in face-to-face environment.
Detection of Abnormal Extraocular Muscles in Small Datasets of Computed Tomography Images Using a Three–dimensional Variational Autoencoder: A Pilot Study
Authors: Chung Yeon Woong , Choi In Young 
Published: September 2022

Abstract
We sought to establish a deep learning-based unsupervised algorithm with a three–dimensional (3D) variational autoencoder model (VAE) for the detection of abnormal extraocular muscles that are difficult to annotate in small datasets of orbital computed tomography (CT) images. 276 CT images of normal orbits were used for model training; 58 CT images of normal orbits and 96 of abnormal orbits (with extraocular muscle enlargement caused by thyroid eye disease) were used for validation. A VAE with a 3D convolutional neural network (CNN) was developed and trained for anomaly detection. All images were preprocessed to emphasize extraocular muscles and to suppress background noise (e.g., high signal intensity from bones) during model training. Model validation was conducted with normal and abnormal validation CT datasets not used for model training. The optimal cut-off value was identified through receiver operating characteristic (ROC) curve analysis. The ability of the model to detect muscles of abnormal size was assessed by visualization of differences between input and output images. During the training epochs, the 3D VAE model did not exhibit overfitting. During validation with normal and abnormal datasets, the model achieved an area under the ROC curve of 0.804, sensitivity of 87.9%, specificity of 72.9%, accuracy of 78.6%, and F1-score of 0.809. Abnormal CT images correctly identified by the model showed differences in extraocular muscle size between input and output images. The proposed 3D VAE model showed potential to detect abnormalities in small extraocular muscles using a small dataset, similar to the diagnostic approach used by physicians. Unsupervised learning can serve as an alternative detection method for medical imaging studies in which annotation is difficult or impossible to perform.
Dragonfly-Inspired Wing Design Enabled by Machine Learning and Graphic Statics
Authors: Akbarzadeh Masoud , Zheng Hao , Mofatteh Hossein , Hablicsek Marton , Shafaroudi Abdolhamid Akbarzadeh 
Published: September 2022

Abstract
This research relates the morphology of the structural network of a dragonfly wing to the static equilibrium of forces using a geometry-based equilibrium method known as graphic statics. It then develops machine learning algorithms to generate similar structural networks for designing airplane wings using the in-plane equilibrium information of the dragonfly wing. This approach can generate a structural network in equilibrium with no prior information related to the topology or geometry of the network just by receiving the boundary geometry of the wing. This research shows that the internal network of the dragonfly wing can be assumed to be compression or tension-only system on a 2D plane. Consequently, another diagram is constructed to represent the geometric equilibrium of the forces in the initial network. This diagram is called the force diagram in the context of graphic statics. A new wing geometry is reconstructed from the force diagram, with its members sized according to the force magnitude. Both form of the network and its force diagram are used to train machine learning models for the generation of the structural network of the wing. The developed methodology is also capitalized to generate microstructural patterns inspired by other species with networks of convex polygons. We numerically and experimentally examine one application of this method in designing the cellular core, 3D printed by fused deposition modeling, of the airfoil wing, which suggests up to 25% improvement in the out-of-plane stiffness. Our findings suggest this ML-assisted approach enables leveraging million years of evolution in nature to develop the next generation of high-performance, lightweight structures.
Utilization of the ethyl acetate fraction of Padina boergesenii as a natural UV filter in sunscreen cream formulation
Authors: Soleimani Soolmaz , Yousefzadi Morteza , Nezhad Sepideh Babaei Mahani , Pozharitskaya Olga N. , Shikov Alexander N. 
Published: September 2022

Abstract
Brown seaweeds due to their wide range of bioactive compounds have a high ability to inhibit free radicals and protect against ultraviolet rays. In the present study, the ethyl acetate fraction was isolated from the Padina boergesenii brown alga. Antioxidant activity (by inhibition DPPH free radical method) and cytotoxicity against UVB-induced cytotoxicity in HaCaT human keratinocytes were evaluated. Then, this fraction was used as a biofilter in the formulation of sunscreen and was investigated physical properties and stability. The results showed that the ethyl acetate fraction could inhibit DPPH radical scavenging (54 ±1 %) and the ability to cell viability of HaCaT keratinocytes exposed to UVB irradiation (81.2 ± 0.1 %). The results of the stability study of the cream formulated with ethyl acetate fraction showed that temperatures 4°C and 25°C have high stability and at 40°C on the 28th day, was observed a slight decrease in its stability. The pH and SPF of the cream formulated with ethyl acetate fraction were reported at 5.8 and 20.55, respectively. Also, the DPPH scavenging activity of the cream was not altered for 28 days of storage at temperatures of 4 - 40°C. According to the obtained results, it was proved that the sunscreen formulated with ethyl acetate fraction of Padina boergesenii brown seaweed has promising properties and characteristics that can create a new opportunity for the development of cosmetics and skin care products.
BioByGANS: biomedical named entity recognition by fusing contextual and syntactic features through graph attention network in node classification framework
Authors: Zheng Xiangwen , Du Haijian , Luo Xiaowei , Tong Fan , Song Wei , Zhao Dongsheng 
Published: September 2022

AbstractBackground:Automatic and accurate recognition of various biomedical named entities from literature is an important task of biomedical text mining, which is the foundation of extracting biomedical knowledge from unstructured texts into structured formats. Using the sequence labeling framework and deep neural networks to implement biomedical named entity recognition (BioNER) is a common method at present. However, the above method often underutilizes syntactic features such as dependencies and topology of sentences. Therefore, it is an urgent problem to be solved to integrate semantic and syntactic features into the BioNER model.Results:In this paper, we propose a novel biomedical named entity recognition model, named BioByGANS (BioBERT/SpaCy-Graph Attention Network-Softmax), which uses a graph to model the dependencies and topology of a sentence and formulate the BioNER task as a node classification problem. This formulation can introduce more topological features of language and no longer be only concerned about the distance between words in the sequence. First, we use periods to segment sentences and spaces and symbols to segment words. Second, contextual features are encoded by BioBERT, and syntactic features such as POS, dependencies and topology are preprocessed by SpaCy respectively. A graph attention network is then used to generate a fusing representation considering both the contextual features and syntactic features. Last, a softmax function is used to calculate the probabilities and get the results. We conduct experiments on 8 benchmark datasets, and our proposed model outperforms existing BioNER state-of-the-art methods on the BC2GM, JNLPBA, BC4CHEMD, BC5CDR-chem, BC5CDR-disease, NCBI-disease, Species-800, and LINNAEUS datasets, and achieves F1-scores of 85.15%, 78.16%, 92.97%, 94.74%, 87.74%, 91.57%, 75.01%, 90.99%, respectively.Conclusion:The experimental results on 8 biomedical benchmark datasets demonstrate the effectiveness of our model, and indicate that formulating the BioNER task into a node classification problem and combining syntactic features into the graph attention networks can significantly improve model performance.
Dynamic power and chirp measurements of a quantum dash semiconductor optical amplifier amplified picosecond pulses using a linear pulse characterization technique
Authors: Connelly Michael J. , Romero-Vivas Javier , Morel Pascal , Sharaiha Ammar , Pommereau Frédéric , Fortin Catherine 
Published: September 2022

Abstract
Quantum Dash (QDash) SOAs are of interest as an alternative to quantum dot SOAs, since they have some dot-like properties and are easier to fabricate such as to operate in the 1550 nm region, albeit with longer gain recovery times in the range of hundreds of picoseconds. QDash-SOAs are promising core component is optical subsystems for applications in next generation coherent communications and optical signal processing, which often involve pulse amplification. It is of interest to measure both the dynamic power, phase and associated frequency chirp and thereby the spectrum of typical QDash-SOA amplified pulses. Non-linear measurement techniques are appropriate for pulsewidths less than 5 ps but have low sensitivity for wider pulsewidths often encountered in practice. This paper describes the use of a modified linear pulse characterization technique to measure the dynamic power and phase of a 20 GHz repetition rate QDash-SOA amplified 19 ps pulsewidth pulse train, from which the chirp and energy spectrum is calculated. The amplified pulses can exhibit a complex structure that is strongly dependent on the amplifier gain and the input pulse shape and energy.