bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation on frictional performance of three different oil-lubricated impregnated graphite seal rings for aircraft integrated drive generators
Authors: Qi Huiying , Wang Xiao , Zhang Rui , Chen Zhangheng , Zheng Shaokan , Jiang Tao , Xu Jimin 
Published: November 2023

Abstract
The frictional performance of the shaft-end graphite seal rings plays a critical role in determining the maintenance-free duration of aircraft integrated drive generators, and significantly depends on the types of graphite materials used. In this study, three types of graphite materials, including epoxy resin, metal antimony and furan resin impregnated ones, were selected for evaluation using a rotating-type tribometer. The frictional test configuration involved an actual graphite seal ring sliding against the surface of a 12Cr2Ni4A disc under the lubrication of 4050 high-temperature synthetic aerospace lubricating oil, which was highly consistent with the practical operational conditions. The frictional performance of the three different impregnated graphite seal rings, including coefficient of friction, two-dimensional (2D)/three-dimensional (3D) morphologies of wear marks and wear rate of ring mass, were quantitatively analyzed and compared. The experimental results indicated that the metal antimony-impregnated graphite seal ring behaved with the smallest coefficient of friction among the three seal rings. 2D and 3D surface roughness parameters of the metal antimony impregnated graphite seal are the smallest. The wear rate of the seal ring’s mass is only approximately 22% of that of furan resin impregnated seal ring. The corresponding investigations demonstrated that the currently employed epoxy resin-impregnated graphite seal rings could be replaced by new candidates with better frictional performance to improve the service life.
Secret learning for lung cancer diagnosis—a study with homomorphic encryption, texture analysis and deep learning
Authors: Adhikary Subhrangshu , Dutta Subhayu , Dwivedi Ashutosh Dhar 
Published: November 2023

Abstract
Advanced lung cancer diagnoses from radiographic images include automated detection of lung cancer from CT-Scan images of the lungs. Deep learning is a popular method for decision making which can be used to classify cancerous and non-cancerous lungs from CT-Scan images. There are many experiments which show the uses of deep learning for performing such classifications but very few of them have preserved the privacy of users. Among existing methods, federated learning limits data sharing to a central server and differential privacy although increases anonymity the original data is still shared. Homomorphic encryption can resolve the limitations of both of these. Homomorphic encryption is a cryptographic technique that allows computations to be performed on encrypted data. In our experiment, we have proposed a series of textural information extraction with the implementation of homomorphic encryption of the CT-Scan images of normal, adenocarcinoma, large cell carcinoma and squamous cell carcinoma. We have further processed the encrypted data to make it classifiable and later we have classified it with deep learning. The results from the experiments have obtained a classification accuracy of 0.9347.
Efficient and selective glycerol electrolysis for the co-production of lactic acid and hydrogen with multi-component Pt/C-zeolite catalyst
Authors: Aslam Muhammad , Navlani-García Miriam , Cazorla-Amorós Diego , Luo Hui 
Published: November 2023

Abstract
Among various electrochemical reactions to produce fuels and chemicals, glycerol electrolysis to co-produce hydrogen and lactic acid has received great attention. However, studies have shown the benchmark Pt based catalysts are insufficient in selectively catalysing the glycerol to lactic acid transformation, resulting in a low yield of lactic acid. Here we report a study on glycerol electrolysis with anion-exchange membrane electrode assembly electrolyser. The reaction conditions including mass transport, temperature, current density and KOH concentration were optimised, among which temperature played a significant role in facilitating the reaction rate and thermodynamics. With the optimised condition a multicomponent Pt/C-zeolite electrocatalyst system (Pt/C-CBV600) was developed and tested, which is capable to increase the lactic acid selectivity to 57.3% from the 33.8% with standalone Pt/C. Although the detailed mechanism required further investigation, it is hypothesised that the CBV600 zeolite with abundant Lewis acid surface sites can effectively bind the dihydroxyacetone intermediate, and drive the reaction towards pyruvaldehyde heterogeneously, the key step to form lactic acid.
Genetics of chilling response at early growth stage in rice: a recessive gene for tolerance and importance of acclimation
Authors: Baruah Akhil Ranjan , Bannai Hiroaki , Meija Yan , Kimura Ayumi , Ueno Haruka , Koide Yohei , Kishima Yuji , Palta Jiwan , Kasuga Jun , Yamamoto Masayuki P , Onishi Kazumitsu 
Published: November 2023

Abstract
Low-temperature adaptation in rice is mediated by the ability of a genotype to tolerate chilling temperatures. A genetic locus on chromosome 11 was analysed for chilling tolerance at the plumule stage in rice. The tolerant allele of A58, a japonica landrace in Japan, was inherited as a recessive gene (ctp-1A58), whereas the susceptible alleles from wild rice (Ctp-1W107) and modern variety (Ctp-1HY) were the dominant genes. Another recessive tolerant allele (ctp-1Silewah) was found in a tropical japonica variety (Silewah). Fine-mapping revealed that a candidate gene for the ctp-1 locus encoded a protein similar to the nucleotide-binding domain and leucine-rich repeat (NLR) protein, in which frameshift mutation by a 73 bp-deletion might confer chilling tolerance in ctp-1A58. Analysis of near-isogenic lines demonstrated that ctp-1A58 imparted tolerance effects only at severe chilling temperatures of 0.5 °C and 2 °C, both at plumule and seedling stages. Chilling acclimation treatments at a wide range of temperatures (8 °C–16 °C) for 72 h concealed the susceptible phenotype of Ctp-1W107 and Ctp-1HY. Furthermore, short-term acclimation treatment of 12 h at 8 °C was enough to be fully acclimated. These results suggest that the NLR gene induces a susceptible response upon exposure to severe chilling stress, however, another interacting gene(s) for acclimation response could suppress the maladaptive phenotype caused by the Ctp-1 allele. This study provides new insights for the adaptation and breeding of rice in a low-temperature environment.
DOSE-L1000: unveiling the intricate landscape of compound-induced transcriptional changes
Authors: Wang Junmin , Novick Steven 
Published: November 2023

AbstractMotivationThe LINCS L1000 project has collected gene expression profiles for thousands of compounds across a wide array of concentrations, cell lines, and time points. However, conventional analysis methods often fall short in capturing the rich information encapsulated within the L1000 transcriptional dose–response data.ResultsWe present DOSE-L1000, a database that unravels the potency and efficacy of compound-gene pairs and the intricate landscape of compound-induced transcriptional changes. Our study uses the fitting of over 140 million generalized additive models and robust linear models, spanning the complete spectrum of compounds and landmark genes within the LINCS L1000 database. This systematic approach provides quantitative insights into differential gene expression and the potency and efficacy of compound-gene pairs across diverse cellular contexts. Through examples, we showcase the application of DOSE-L1000 in tasks such as cell line and compound comparisons, along with clustering analyses and predictions of drug–target interactions. DOSE-L1000 fosters applications in drug discovery, accelerating the transition to omics-driven drug development.Availability and implementationDOSE-L1000 is publicly available at https://doi.org/10.5281/zenodo.8286375.
Skin cell-derived extracellular vesicles: a promising therapeutic strategy for cutaneous injury
Authors: Wang Min , Wu Peipei , Huang Jin , Liu Wenhui , Qian Hui , Sun Yaoxiang , Shi Hui 
Published: November 2023

Abstract
Wound healing refers to the healing process that occurs after the skin and other tissues are separated or damaged by internal or external forces. It is a complex combination of tissue regeneration, granulation tissue hyperplasia, and scar formation, and shows the synergistic effects of these processes. After skin damage, the environment around the wound and the cells at site of the damage respond immediately, and a range of cytokines and growth factors are released. In cutaneous injury, extracellular vesicle (EV) signaling plays a vital role in the healing process via paracrine and endocrine mechanisms. EVs are natural intercellular and inter-organ communication tools that carry various bioactive substances for message exchange. Stem cells and stem cell EVs facilitate tissue repair, showing promising potential in regenerative medicine. Nevertheless, EVs derived from specific skin tissue cells, such as epidermal cells, fibroblasts, vascular endothelial cells and inflammatory cells, also play important roles in cutaneous tissue repair. Here, we describe the characteristics of wound healing, concentrating on the production and functions of EVs derived from specific skin cells, and provide new ideas for wound therapy using EVs.
The GNAR-edge model: a network autoregressive model for networks with time-varying edge weights
Authors: Mantziou Anastasia , Cucuringu Mihai , Meirinhos Victor , Reinert Gesine 
Published: November 2023

Abstract
In economic and financial applications, there is often the need for analysing multivariate time series, comprising of time series for a range of quantities. In some applications, such complex systems can be associated with some underlying network describing pairwise relationships among the quantities. Accounting for the underlying network structure for the analysis of this type of multivariate time series is required for assessing estimation error and can be particularly informative for forecasting. Our work is motivated by a dataset consisting of time series of industry-to-industry transactions. In this example, pairwise relationships between Standard Industrial Classification (SIC) codes can be represented using a network, with SIC codes as nodes and pairwise transactions between SIC codes as edges, while the observed time series of the amounts of the transactions for each pair of SIC codes can be regarded as time-varying weights on the edges. Inspired by Knight et al. (2020, J. Stat. Softw., 96, 1–36), we introduce the GNAR-edge model which allows modelling of multiple time series utilizing the network structure, assuming that each edge weight depends not only on its past values, but also on past values of its neighbouring edges, for a range of neighbourhood stages. The method is validated through simulations. Results from the implementation of the GNAR-edge model on the real industry-to-industry data show good fitting and predictive performance of the model. The predictive performance is improved when sparsifying the network using a lead–lag analysis and thresholding edges according to a lead–lag score.
A case report of constrictive pericarditis following COVID-19 vaccination
Authors: Bain Eric , Guglin Maya 
Published: November 2023

Abstract

Background
COVID-19 infection and the COVID-19 vaccines have been associated with rare cases of pericarditis. We present a case of constrictive pericarditis (CP) following the vaccine.

Case summary
A 19-year-old healthy male started having progressive abdominal pain, emesis, dyspnoea, and pleuritic chest pain 2 weeks after the second dose of Pfizer vaccine. Computed tomography angiography chest revealed bilateral pleural effusions and pericardial thickening with effusion. Cardiac catheterization showed ventricular interdependence. Cardiac magnetic resonance (CMR) showed septal bounce and left ventricular tethering suggestive of CP. A total pericardiectomy was performed with significant symptom improvement. Pathology showed chronic fibrosis without amyloid, iron deposits, or opportunistic infections. Patient had Epstein–Barr Virus (EBV) viraemia 825 IU/mL and histoplasmosis complement-fixation positive with negative serum and urine antigen. Hypercoagulable panel and infectious workup were otherwise negative. The patient had resolution of cardiac symptoms at 3 months of follow-up.

Discussion
The patient developed progressive symptoms within 2 weeks of his second Pfizer vaccine. Echocardiogram and CMR had classic signs of CP, and pericardial pathology confirmed fibrotic pericardium. The patient had no prior surgery, thoracic radiation, or bacterial infection. Epstein–Barr Virus viraemia was thought to be reactionary, and histoplasmosis complement likely represented chronic exposure. The timing of symptoms and negative multidisciplinary workup raises the suspicion for COVID vaccine–induced CP. The COVID vaccines benefits far exceed the risks, but complications still can occur. Practitioners should have a high index of suspicion to allow prompt diagnosis of CP.
Implant, assessment, and management of conduction system pacing
Authors: Vernooy Kevin , Keene Daniel , Huang Weijian , Vijayaraman Pugazhendhi 
Published: November 2023

Abstract
His bundle pacing and left bundle branch pacing, together referred to as conduction system pacing, have (re)gained considerable interest over the past years as it has the potential to preserve and/or restore a more physiological ventricular activation when compared with right ventricular pacing and may serve as an alternative for cardiac resynchronization therapy. This review manuscript dives deeper into the implantation techniques and the relevant anatomy of the conduction system for both pacing strategies. Furthermore, the manuscript elaborates on better understanding of conduction system capture with its various capture patterns, its potential complications as well as appropriate follow-up care. Finally, the limitations and its impact on clinical care for both His bundle pacing and left bundle branch pacing are being discussed.
Frontiers in conduction system pacing: treatment of long PR in patients with heart failure
Authors: Kaza Nandita , Keene Daniel , Vijayaraman Pugazhendhi , Whinnett Zachary 
Published: November 2023

Abstract
Patients with heart failure who have a prolonged PR interval are at a greater risk of adverse clinical outcomes than those with a normal PR interval. Potential mechanisms of harm relating to prolonged PR intervals include reduced ventricular filling and also the potential progression to a higher degree heart block. There has, however, been relatively little work specifically focusing on isolated PR prolongation as a therapeutic target. Secondary analyses of trials of biventricular pacing in heart failure have suggested that PR prolongation is both a prognostic marker and a promising treatment target. However, while biventricular pacing offers an improved activation pattern, it is nonetheless less physiological than native conduction in patients with a narrow QRS duration, and thus, may not be the ideal option for achieving therapeutic shortening of atrioventricular delay. Conduction system pacing aims to preserve physiological ventricular activation and may therefore be the ideal method for ventricular pacing in patients with isolated PR prolongation. Acute haemodynamic experiments and the recently reported His-optimized pacing evaluated for heart failure (HOPE HF) Randomised Controlled Trial demonstrates the potential benefits of physiological ventricular pacing on patient symptoms and left ventricular function in patients with heart failure.
Promoter insertion leads to polyembryony in mango — a case of convergent evolution with citrus
Authors: Yadav Chandra Bhan , Rozen Ada , Eshed Ravit , Ish-Shalom Mazal , Faigenboim Adi , Dillon Natalie , Bally Ian , Webb Matthew , Kuhn David , Ophir Ron , Cohen Yuval , Sherman Amir 
Published: November 2023

Abstract
Sexual reproduction in plants is the main pathway for creating new genetic combinations in modern agriculture. In heterozygous plants, after the identification of a plant with desired traits, vegetative propagation (cloning) is the primary path to create genetically uniform plants. Another natural plant mechanism that creates genetically uniform plants (clones) is apomixis. In fruit crops like citrus and mango, sporophytic apomixis results in polyembryony, where seeds contain multiple embryos, one of which is sexually originated and the others are vegetative clones of the parent mother tree. Utilizing the mango genome and genetic analysis of a diverse germplasm collection, we identified MiRWP as the gene that causes polyembryony in mango. There is a strong correlation between a specific insertion in the gene’s promoter region and altered expression in flowers and developing fruitlets, inducing multiple embryos. The MiRWP gene is an ortholog of CitRWP that causes polyembryony in citrus. Based on the data, we speculate that promoter insertion events, which occurred independently in citrus and mango, induced nucellar embryogenesis. The results suggest convergent evolution of polyembryony in the two species. Further work is required to demonstrate the utility of these genes (mango and citrus) in other biological systems as a tool for the clonal production of other crops.
Physiological and molecular bases of the boron deficiency response in tomatoes
Authors: Li Junjun , Fan Huihui , Song Qianqian , Jing Lili , Yu Hao , Li Ruishan , Zhang Ping , Liu Fei , Li Weimin , Sun Liangliang , Xu Jin 
Published: November 2023

Abstract
Boron is an essential microelement for plant growth. Tomato is one of the most cultivated fruits and vegetables in the world, and boron deficiency severely inhibits its yield and quality. However, the mechanism of tomato in response to boron deficiency remains largely unclear. Here, we investigated the physiological and molecular bases of the boron deficiency response in hydroponically grown tomato seedlings. Boron deficiency repressed the expression of genes associated with nitrogen metabolism, while it induced the expression of genes related to the pentose phosphate pathway, thereby altering carbon flow to provide energy for plants to cope with stress. Boron deficiency increased the accumulation of copper, manganese and iron, thereby maintaining chlorophyll content and photosynthetic efficiency at the early stage of stress. In addition, boron deficiency downregulated the expression of genes involved in cell wall organization and reduced the contents of pectin and cellulose in roots, ultimately retarding root growth. Furthermore, boron deficiency markedly altered phytohormone levels and signaling pathways in roots. The contents of jasmonic acid, jasmonoy1-L-isoleucine, trans-zeatin riboside, abscisic acid, salicylic acid, and SA glucoside were decreased; in contrast, the contents of isopentenyladenine riboside and ethylene precursor 1-aminocyclopropane-1-carboxylic acid were increased in the roots of boron-deficient tomato plants. These results collectively indicate that tomato roots reprogram carbon/nitrogen metabolism, alter cell wall components and modulate phytohormone pathways to survive boron deficiency. This study provides a theoretical basis for further elucidating the adaptive mechanism of tomato in response to boron deficiency.
The Spirit of the Convention and the Letter of the Colony: Refugees Defining States in a British Overseas Territory
Authors: Demetriou Olga 
Published: November 2023

Abstract
Whereas asylum policy is predicated on the assumption that states define refugees, this paper examines how refugees define states. Through the legal case of refugees stranded on a British military base in Cyprus since 1998, I show how refugees and the states that grant them or deny them protection become co-constitutive. The processes involved in judicial activism delineate the modalities through which sovereign governance and refugee agencies operate. I argue that modalities of sovereignty (colonialism, exceptionalism, and diplomacy) interact with modalities of agency (protest, vulnerability, and endurance) to redefine issues of refugee protection, state sovereignty, and externalization of migration management. The case shows the risks that denial of protection entails for states and not just refugees. Methodologically, I propose that a nuanced, ground-level understanding of the role of law in activism allows us a clearer view to these imbrications of sovereign governance and agency, and thus to the ambivalent and multivalent aspects of activism.
109 Animal Behavior Analysis Using Unsupervised Machine Learning Techniques
Authors: Liu Jiefei , Bailey Derek W , Cao Huiping , Son Tran Cao , Tobin Colin T 
Published: November 2023

Abstract
With recent technological advances, Global Positioning Systems (GPS) and other tracking sensors can collect large amounts of data and transfer information to the cloud and then to producers to remotely monitor livestock health and well-being. Currently, supervised machine learning, such as random forest and linear or quadratic discriminant analysis techniques are used to develop algorithms to identify changes in animal behavior that may be associated with well-being concerns. Supervised machine learning requires behavior observation of monitored animals and may hinder normal expression. However, recording behavioral observations is time consuming and expensive. Our goal was to design a new unsupervised machine learning framework to identify animal behavior without the utilization of human observations. The framework contains two steps. The first step is to segment the tracking data of the animal using time series segmentation, and the second step is to group the segments into clusters where each cluster represents one type of behavior. To validate the applicability of our proposed framework, we utilize GPS tracking data collected at 2-minute intervals from eight cows from May 28 to June 22, 2018, in a 1096 ha rangeland pasture near Prescott, Arizona. After extensive experiments, our framework can partition the movement of the cow using the speed, direction, and distance of the cow from water. These segments were grouped into meaningful behavior clusters using clustering analysis. Speed was the most successful feature for clustering into behaviors. Results are similar to approaches based only on expert knowledge, that rely on speed for classification. Our study demonstrated that we can directly use unlabeled data to group animal behaviors from GPS tracking data. The proposed unsupervised two-step framework allows the analysis of cattle tracking data without direct human observation of behaviors. It is applicable for analyzing the immense amount of data that can be obtained from real-time tracking and sensor devices.
44 Developing New Traits Using Precision Breeding Tools
Authors: Sonstegard Tad S 
Published: November 2023

Abstract
Genome editing in the genetic stocks of food animals has tremendous potential as a tool for genetic improvement best suited to introduce traits not readily available for intensive selection in commercial breeding populations, especially those affecting disease resistance and adaptation to climate. To date, gene-editing has been used to alter prolactin receptor and produce heat-tolerant, registered Angus for commercial production of semen and embryos that rapidly improves efficient quality beef production in the tropics. More recently, genome alterations based on rationale design have been tested to demonstrate host resistance to porcine reproductive and respiratory syndrome virus and bovine viral diarrhea virus in swine and cattle, respectively. This presentation will highlight the results of these new traits to breed healthier commercial animals that will eventually change global market dynamics of livestock production.