bluuebunny/crossref_metadata_2025_split huggingface dataset:
A configuration to double the gain of pyramidal horn antenna using single layer frequency selective surface
Authors: Patnaik Kalyan Mohan , Basavarajappa Gowrish 
Published: November 2023

AbstractA gain enhancement technique in pyramidal horn antenna using a slot type band pass frequency selective surface (FSS) is presented. The horn antenna without FSS has achieved a measured gain of 10.5 dBi at 10 GHz, while the antenna with the single layer slotted FSS yields an enhanced measured gain of 14.2 dBi (an improvement of 3.7 dB or 134%). Conventionally, such a gain enhancement would 5 times increase in its dimensions (flaring). However, the authors achieve the same with only 2 times increase in dimensions. Another interesting value addition of the proposed idea is that an FSS sheet can be added to the existing horn antenna to increase its gain without altering the antenna itself. Such a scheme is highly beneficial in strategic applications. The proposed gain enhanced horn antenna can be recommended to be utilised in several X‐band applications, such as radar systems (weather, surveillance, traffic control and military), satellite communications and point–point microwave links that require high gain and small form factor.
Construction mode optimal selection method for intelligent sensing system in zero‐carbon parks
Authors: Cheng Mengzeng , Niu Wei , Hu Jingwei , Wang Zongyuan , Chen Jing , Lin Chao 
Published: November 2023

AbstractThe intelligent sensing system is the digital basis for zero‐carbon park operation. Due to the immaturity of its cost‐benefit accounting method and the lack of a special construction mode evaluation system, there is blindness in its investment and construction process. In order to select the suitable construction mode for the intelligent sensing system scientifically and effectively, this paper first establishes the architecture of the intelligent sensing system, and determines a cost‐benefit accounting method of the intelligent sensing system. Then, this paper establishes a construction mode evaluation index system including techno‐economic indicators, and proposes a fuzzy comprehensive evaluation method combing analytic hierarchy process and the decision‐making trial and evaluation laboratory to select the optimal construction mode. The numerical analyses show that the public‐private‐partnership mode of the intelligent sensing system has achieved ideal implementation results.
The construction of philosophical ideas in the paratexts of the German translation of the
Zhuangzi by Richard Wilhelm
Authors: Nana Pang , Mengye Liang 
Published: November 2023

Abstract
Among the numerous German translations of the traditional Chinese cultural classic Zhuangzi, the
version by the missionary Richard Wilhelm, Dschuang Dsi. Das wahre Buch vom südlichen Blütenland (1912), is of great significance as the first direct translation from Chinese. The work
contributed greatly to the popularity of Taoism in Germany. However, studies on the German versions of the
Zhuangzi are limited, and most focus on the text itself, whereas the research value of the paratexts has been
neglected. This study explores the role of paratexts of Wilhelm’s translation in the construction of Zhuang Zhou’s philosophical
ideas. We find there is a noticeable presence of the translator’s voice in the paratexts of Wilhelm’s translation. Moreover, the
interpretative role of the paratexts can enhance readers’ understanding of Wilhelm’s construction of the philosophical ideas
conveyed by the text. Based on the analysis of paratexts, we conclude that Wilhelm’s translation is characterized by Western
cultural interventions, such as analogies between Zhuang Zhou and Western philosophers and the adoption of Christian claims. This
may be attributed to the goal of Wilhelm’s translation (i.e., to introduce the Zhuangzi to general
German-speaking readers), his cultural background of Western education (especially at the Tübingen Seminary), and the sinological
tradition of studying and translating Chinese classics from the perspective of Western culture at the time.
Uncertainty-guided cross learning via CNN and transformer for semi-supervised honeycomb lung lesion segmentation
Authors: Zi-an Zhao , Xiu-fang Feng , Xiao-qiang Ren , Yun-yun Dong 
Published: November 2023

Abstract

Objective. Deep learning networks such as convolutional neural networks (CNN) and Transformer have shown excellent performance on the task of medical image segmentation, however, the usual problem with medical images is the lack of large-scale, high-quality pixel-level annotations, which is a very time-consuming and laborious task, and its further leads to compromised the performance of medical image segmentation under limited annotation conditions. Approach. In this paper, we propose a new semi-supervised learning method, uncertainty-guided cross learning, which uses a limited number of annotated samples along with a large number of unlabeled images to train the network. Specifically, we use two networks with different learning paradigms, CNN and Transformer, for cross learning, and use the prediction of one of them as a pseudo label to supervise the other, so that they can learn from each other, fully extract the local and global features of the images, and combine explicit and implicit consistency regularization constraints with pseudo label methods. On the other hand, we use epistemic uncertainty as a guiding message to encourage the model to learn high-certainty pixel information in high-confidence regions, and minimize the impact of erroneous pseudo labels on the overall learning process to improve the performance of semi-supervised segmentation methods. Main results. We conducted honeycomb lung lesion segmentation experiments using a honeycomb lung CT image dataset, and designed several sets of comparison experiments and ablation experiments to validate the effectiveness of our method. The final experimental results show that the Dice coefficient of our proposed method reaches 88.49% on the test set, and our method achieves state-of-the-art performance in honeycomb lung lesion segmentation compared to other semi-supervised learning methods. Significance. Our proposed method can effectively improve the accuracy of segmentation of honeycomb lung lesions, which provides an important reference for physicians in the diagnosis and treatment of this disease.
Effects of N/Si ratio on mechanical properties of amorphous silicon nitride coating
Authors: Zhou Huasi , Persson Cecilia , Xia Wei , Engqvist Håkan 
Published: November 2023

Abstract
The utilization of silicon nitride coatings has been proposed as an effective method to enhance wear resistance and mitigate the release of metallic ions from biomedical implants. However, the relatively high dissolution rate of low-density coatings remains an obstacle to their implementation. Here, chemical vapour deposition techniques may have advantages over the typically used physical vapour deposition (PVD) methods. Therefore, in this study, silicon nitride coatings were obtained by low-pressure chemical vapor deposition (LPCVD). Since the nitrogen-to-silicon (N/Si) ratio and deposition temperature have been reported as major factors affecting the performance of the coatings, the effects of ammonia (NH3) to dichlorosilane (SiH2Cl2) flow ratio and deposition temperature were systemically investigated in the form of microstructure, mechanical and tribological properties of the coatings. The results revealed that the coatings exhibited a dense structure. As the ammonia flow ratio increased, the surface became smoother, and the hardness and elastic modulus increased and reached the maximum at a flow ratio of 4, giving a hardness of around 27 GPa and an elastic modulus of 290 GPa, respectively. The higher mechanical properties of the coatings deposited at a flow ratio of 4 are attributed to the stronger covalent Si-N bonding, as confirmed by XPS results. However, the coatings deposited at a flow ratio of 2 exhibited the lowest wear rate, at 9.5

×

10−7 mm3 Nm−1, around one-third of the value of the coatings deposited at a flow ratio of 6, likely due to the high silicon content of these coatings. Increasing the temperature resulted in an increased deposition rate, higher hardness and elastic modulus as well as a lower wear rate, likely due to incomplete reactions at lower temperatures. The generally high hardness and low wear rate indicate that the coatings deposited by LPCVD are promising for application in spinal implants.
Screen printable PANI/carbide-derived carbon supercapacitor electrode ink with chitosan binder
Authors: Yesilyurt Ezgi Inci , Pionteck Jürgen , Keskinen Jari , Kattainen Aapo , Punkari Timo , Simon Frank , Mäntysalo Matti , Voit Brigitte 
Published: November 2023

Abstract
Polyaniline (PANI)/carbide-derived carbon (CDC) was synthesized by using in-situ chemical oxidative polymerization of PANI in presence of CDC. Conductive electrode ink materials were prepared by using eco-friendly chitosan binder in water media. In the following, symmetrical supercapacitors (SCs) were fabricated by both doctor blade coating and screen printing technique. The electrical conductivity, morphology, specific capacitance, and energy density of these composites were evaluated for their applicability as SC electrodes. Pure PANI with chitosan binder was not printable because of its brittleness, however, the presence of CDC allows the preparation of smooth films which are suitable for electrode preparation. The fabricated composite electrode has a higher specific capacitance (up to 419 F g−1) and higher energy density (up to 6.7 W h kg−1) compared to the pristine CDC electrode. The capacitance of screen-printed SCs was 440–470 mF with an equivalent series resistance of about 27 Ω.
Demographic confounders distort inference of gene regulatory and gene co-expression networks in cancer
Authors: Ketteler Anna , Blumenthal David B 
Published: November 2023

Abstract
Gene regulatory networks (GRNs) and gene co-expression networks (GCNs) allow genome-wide exploration of molecular regulation patterns in health and disease. The standard approach for obtaining GRNs and GCNs is to infer them from gene expression data, using computational network inference methods. However, since network inference methods are usually applied on aggregate data, distortion of the networks by demographic confounders might remain undetected, especially because gene expression patterns are known to vary between different demographic groups. In this paper, we present a computational framework to systematically evaluate the influence of demographic confounders on network inference from gene expression data. Our framework compares similarities between networks inferred for different demographic groups with similarity distributions obtained for random splits of the expression data. Moreover, it allows to quantify to which extent demographic groups are represented by networks inferred from the aggregate data in a confounder-agnostic way. We apply our framework to test four widely used GRN and GCN inference methods as to their robustness w. r. t. confounding by age, ethnicity and sex in cancer. Our findings based on more than $ {44000}$ inferred networks indicate that age and sex confounders play an important role in network inference for certain cancer types, emphasizing the importance of incorporating an assessment of the effect of demographic confounders into network inference workflows. Our framework is available as a Python package on GitHub: https://github.com/bionetslab/grn-confounders.
Predicting gene regulatory links from single-cell RNA-seq data using graph neural networks
Authors: Mao Guo , Pang Zhengbin , Zuo Ke , Wang Qinglin , Pei Xiangdong , Chen Xinhai , Liu Jie 
Published: November 2023

Abstract
Single-cell RNA-sequencing (scRNA-seq) has emerged as a powerful technique for studying gene expression patterns at the single-cell level. Inferring gene regulatory networks (GRNs) from scRNA-seq data provides insight into cellular phenotypes from the genomic level. However, the high sparsity, noise and dropout events inherent in scRNA-seq data present challenges for GRN inference. In recent years, the dramatic increase in data on experimentally validated transcription factors binding to DNA has made it possible to infer GRNs by supervised methods. In this study, we address the problem of GRN inference by framing it as a graph link prediction task. In this paper, we propose a novel framework called GNNLink, which leverages known GRNs to deduce the potential regulatory interdependencies between genes. First, we preprocess the raw scRNA-seq data. Then, we introduce a graph convolutional network-based interaction graph encoder to effectively refine gene features by capturing interdependencies between nodes in the network. Finally, the inference of GRN is obtained by performing matrix completion operation on node features. The features obtained from model training can be applied to downstream tasks such as measuring similarity and inferring causality between gene pairs. To evaluate the performance of GNNLink, we compare it with six existing GRN reconstruction methods using seven scRNA-seq datasets. These datasets encompass diverse ground truth networks, including functional interaction networks, Loss of Function/Gain of Function data, non-specific ChIP-seq data and cell-type-specific ChIP-seq data. Our experimental results demonstrate that GNNLink achieves comparable or superior performance across these datasets, showcasing its robustness and accuracy. Furthermore, we observe consistent performance across datasets of varying scales. For reproducibility, we provide the data and source code of GNNLink on our GitHub repository: https://github.com/sdesignates/GNNLink.
Multi-faith Chaplaincy’s Outcomes-Based Measures: The Tail that Wags the Dog
Authors: Tenorio Addison S 
Published: November 2023

Abstract
The current manner of practicing chaplaincy in health care is one which prizes the multi-faith chaplain. When one asks multi-faith chaplain, “To whom are you beholden?” they will respond, “The patient.” This is evident in the way that chaplaincy is currently practiced and taught, which prizes the use of psychology over recourse to theology. Chaplaincy’s recourse to practices whose aims are directed toward the efficient rather than the eternal challenges its original telos. This paper looks at this question by blending a Catholic and Engelhardtian approach to conclude that chaplains should recognize that they are beholden to God, rather than to patients’ autonomy.
Chaplaincy as a “Living Human Web”
Authors: Thornton Andrea 
Published: November 2023

Abstract
Engelhardt’s critiques of “generic chaplaincy” rely on the argument that chaplains are secular; however, professionally certified chaplains must maintain ordination with an ecclesial body. Engelhardt’s concerns are better directed at the academic subfield that supports and trains chaplains: pastoral theology. That field is somewhat guilty of forced ecumenism because it attempts a universal theology rooted in experience and the social sciences rather than the authority of creeds, ecclesial bodies, or traditions. Pastoral theology makes too many sacrifices to the authority of the behavioral sciences without sufficient appreciation for sacramental theology and the spiritual bonds that rituals effect in communities of shared belief. In this model, ritual is reduced to its instrumental value in addressing the emotional needs of patients rather than viewed as efficacious spiritual care. Chaplains should take a holistic approach to theology so that they can better identify the duties and scope of interfaith spiritual care.
Multi-dimensional opinion chaos synchronization based on multi-layer complex networks
Authors: Liu Shan , Tao Ruixing 
Published: November 2023

Abstract
In complex networks, the interactions of opinions are significantly affected by network structure. Moreover, multi-layer networks, which contain multiple subsystems and different types of interactions, are considered to have a stronger ability to simulate various real-world systems than traditional single-layer complex networks. Based on this motivation, this article attempts to show how to achieve complete synchronization of multi-dimensional opinions in a multi-layer network topology where the opinions of nodes have Rössler chaotic dynamics. A first step in investigating the synchronization of multi-layer complex networks is to propose a multi-dimensional opinion evolution model. In this article, the multi-layer complex network model combining the Rössler oscillation system is built, which provides us a tool for insight into the nodes complexity in multi-layer networks. Furthermore, a general criterion for globally exponentially asymptotic synchronization of multi-layer complex networks is provided using multiple Lyapunov stability theories. We illustrate the reliability of the model and the correctness of the criterion by Runge-Kutta (RK4) simulation. These findings shed new light on some interesting phenomena in society and help decision-makers predict the prevalence of hot topics and public opinions.
Educational attainment of children with congenital heart disease in the United Kingdom
Authors: Cave Daniel G W , Wands Zoë E , Cromie Kirsten , Hough Amy , Johnson Kathryn , Mon-Williams Mark , Bentham James R , Feltbower Richard G , Glaser Adam W 
Published: November 2023

Abstract

Background
Educational attainment in children with congenital heart disease (CHD) within the UK has not been reported, despite the possibility of school absences and disease-specific factors creating educational barriers.

Methods and results
Children were prospectively recruited to the Born in Bradford birth cohort between March 2007 and December 2010. Diagnoses of CHD were identified through linkage to the congenital anomaly register and independently verified by clinicians. Multivariable regression accounted for relevant confounders. Our primary outcome was the odds of ‘below expected’ attainment in maths, reading, and writing at ages 4–11 years.
Educational records of 139 children with non-genetic CHD were compared with 11 188 age-matched children with no major congenital anomaly. Children with CHD had significantly higher odds of ‘below expected’ attainment in maths at age 4–5 years [odds ratio (OR) 1.64, 95% confidence interval (CI) 1.07–2.52], age 6–7 (OR 2.03, 95% CI 1.32–3.12), and age 10–11 (OR 2.28, 95% CI 1.01–5.14). Odds worsened with age, with similar results for reading and writing. The odds of receiving special educational needs support reduced with age for children with CHD relative to controls [age 4–5: OR 4.84 (2.06–11.40); age 6–7: OR 3.65 (2.41–5.53); age 10–11: OR 2.73 (1.84–4.06)]. Attainment was similar for children with and without exposure to cardio-pulmonary bypass. Lower attainment was strongly associated with the number of pre-school hospital admissions.

Conclusion
Children with CHD have lower educational attainment compared with their peers. Deficits are evident from school entry and increase throughout primary school.
Patterns of Evolution of TRIM Genes Highlight the Evolutionary Plasticity of Antiviral Effectors in Mammals
Authors: Fernandes Alexandre P , OhAinle Molly , Esteves Pedro J 
Published: November 2023

AbstractThe innate immune system of mammals is formed by a complex web of interacting proteins, which together constitute the first barrier of entry for infectious pathogens. Genes from the E3-ubiquitin ligase tripartite motif (TRIM) family have been shown to play an important role in the innate immune system by restricting the activity of different retrovirus species. For example, TRIM5 and TRIM22 have both been associated with HIV restriction and are regarded as crucial parts of the antiretroviral machinery of mammals. Our analyses of positive selection corroborate the great significance of these genes for some groups of mammals. However, we also show that many species lack TRIM5 and TRIM22 altogether. By analyzing a large number of mammalian genomes, here we provide the first comprehensive view of the evolution of these genes in eutherians, showcasing that the pattern of accumulation of TRIM genes has been dissimilar across mammalian orders. Our data suggest that these differences are caused by the evolutionary plasticity of the immune system of eutherians, which have adapted to use different strategies to combat retrovirus infections. Altogether, our results provide insights into the dissimilar evolution of a representative family of restriction factors, highlighting an example of adaptive and idiosyncratic evolution in the innate immune system.
Risky Gravity
Authors: Juvenal Luciana , Santos Monteiro Paulo 
Published: November 2023

Abstract
We consider the canonical trade model with heterogeneous firms, love for variety and trade costs, and integrate it in the consumption CAPM model. This yields a structural gravity equation that includes an additional factor related to risk premia. Empirical evidence based on firm-level data confirms the importance of cross-sectional heterogeneity in risk and time-varying risk premia to shape bilateral trade flows. The structural gravity model augmented to account for fluctuations in risk premia offers a compelling explanation for trade collapses during abrupt economic downturns.
The utility of alpine cave fossil assemblages for zoological census: an example from northern Utah, United States
Authors: O’Brien Kaedan , Irmis Randall B , Brenner Coltrain Joan , Dalmas Daniel Martin , Derieg Katrina M , Evans Thomas , Richards Eric S , Richards Fumiko M , Rickart Eric A , Faith J Tyler 
Published: November 2023

Abstract
Assemblages of mammal skeletal remains provide a powerful tool for censusing wildlife populations to establish zoological baselines required for evaluating biogeographic trends over varying timescales. Caves provide an ideal depositional setting to preserve these skeletal remains despite potential time averaging and taphonomic filtering. We describe a Holocene paleontological assemblage from Boomerang Cave in the Bear River Range of Cache County, northern Utah, United States, at an elevation of 2,231 m, and at the boundary between the Great Basin and Rocky Mountain biogeographic provinces. We analyzed 1,228 surface-collected specimens from six areas within the cave, and identified a minimum of 22 nonoverlapping mammalian taxa, comprising all size classes present in the region. Compared to museum records for mammals from the Bear River Range and individuals trapped or observed in the vicinity of the cave, specimen-based rarefaction demonstrates that our assemblage captures most of the mammalian diversity expected in the area. This is particularly apparent for carnivorans and soricids, which are particularly well-represented in the Boomerang Cave assemblage, with the former clade represented by at least nine taxa. This high level of diversity can be attributed to the relatively random nature of natural trap cave deposition, reducing accumulation biases due to size or diet. We also record the first occurrence of Merriam’s Shrew (Sorex merriami) from the Bear River Range. Our analysis does not indicate any mammalian changes between late Holocene and present-day communities, but these data establish a new zoological baseline for an alpine community at the interface between two key biogeographic provinces in western North America. Our work highlights the value of collecting skeletal remains from cave assemblages as a convenient and fast method for censusing terrestrial mammalian communities.