bluuebunny/crossref_metadata_2025_split huggingface dataset:
The causal relationship between serum metabolites and acne vulgaris: a Mendelian randomization study
Authors: Wang Xiaoyun , Wu Yujia , Zhao Pengfei , Wang Xinren , Wu Wenjuan , Yang Jiankang 
Published: May 2024

AbstractIn individuals with acne vulgaris, alterations occur in serum metabolite composition, yet the exact causal link between these metabolites and acne development remains elusive. Using genome-wide association datasets, we performed bidirectional Mendelian randomization (MR) to investigate the potential causal relationship between 309 serum metabolites and acne vulgaris. We performed sensitivity analysis to evaluate the presence of heterogeneity and pleiotropy. Forward MR analysis found 14 serum metabolites significantly associated with acne vulgaris, and reverse MR analysis found no significant association between acne vulgaris and these serum metabolites. Through validation using data from the FinnGen database of acne vulgaris studies, we found a conclusive and significant correlation between stearoylcarnitine and acne vulgaris. This provides new evidence in the search for new targets for the treatment of acne vulgaris.
Comparisons of stakeholders' influences, inter-relationships, and obstacles for circular economy implementation on existing building sectors
Authors: Kaewunruen Sakdirat , Teuffel Patrick , Donmez Cavdar Ayfer , Valta Otso , Tambovceva Tatjana , Bajare Diana 
Published: May 2024

AbstractBuildings are energy- and resource-hungry: their construction and use account for around 39% of global carbon dioxide emissions; they consume around 40% of all the energy produced; they are responsible for over 35% of the EU's total waste generation; and account for about 50% of all extracted (fossil) materials. Therefore, they present a significant challenge to meeting national and international Net Zero targets of reducing greenhouse emissions and fossil resource use. The CircularB Project, is at the heart of this issue, which will underpin synergies of multi-scale circular perspectives (from materials, to components, to assets and built environments), digital transformation solutions, data-driven and complexity science, stakeholder behavioral science, and interdisciplinary capabilities towards achievable, affordable and marketable circular solutions for both new and existing buildings, for sustainable urban design, and for circular built environments across Europe. This paper contributes to the project by deriving new insights into the stakeholders’ influences, inter-relationships, and obstacles in the implementation of circular economy concepts on existing building stocks in Europe, which represent over 90% of whole building assets. In order to identify and derive the insights, our study is rigorously based on (i) a robust critical literature review of key documentations such as articles, standards, policy reports, strategic roadmaps and white papers; and (ii) interviews with relevant stakeholders and decision makers. Uniquely, our work spans across all scales of CE implementation from materials, to products and components, to existing building stocks, and to living built environments. The findings point out the current challenges and obstacles required to be tackled. Inadequacies of financial incentives and governmental enforcement (via policy, legislation, or directive) are commonly found to be the most critical obstacles found throughout Europe. Circular economy is the global challenge and not just a single country can resolve the climate issue without the cooperation of other countries. The insights thus highlight the essential need for harmonized actions and tactical/pragmatic policies promoted and regulated by the European Commission, national and local governments who can dominate the influence, promote inter-relationship, and overcome the barriers towards circular economy much more effectively.
Highly-integrable analogue reservoir circuits based on a simple cycle architecture
Authors: Abe Yuki , Nakada Kazuki , Hagiwara Naruki , Suzuki Eiji , Suda Keita , Mochizuki Shin-ichiro , Terasaki Yukio , Sasaki Tomoyuki , Asai Tetsuya 
Published: May 2024

AbstractPhysical reservoir computing is a promising solution for accelerating artificial intelligence (AI) computations. Various physical systems that exhibit nonlinear and fading-memory properties have been proposed as physical reservoirs. Highly-integrable physical reservoirs, particularly for edge AI computing, has a strong demand. However, realizing a practical physical reservoir with high performance and integrability remains challenging. Herein, we present an analogue circuit reservoir with a simple cycle architecture suitable for complementary metal-oxide-semiconductor (CMOS) chip integration. In several benchmarks and demonstrations using synthetic and real-world data, our developed hardware prototype and its simulator exhibit a high prediction performance and sufficient memory capacity for practical applications, showing promise for future applications in highly integrated AI accelerators.
Diagnosis of cervical lymphoma using a YOLO-v7-based model with transfer learning
Authors: Wang Yuegui , Yang Caiyun , Yang Qiuting , Zhong Rong , Wang Kangjian , Shen Haolin 
Published: May 2024

AbstractTo investigate the ability of an auxiliary diagnostic model based on the YOLO-v7-based model in the classification of cervical lymphadenopathy images and compare its performance against qualitative visual evaluation by experienced radiologists. Three types of lymph nodes were sampled randomly but not uniformly. The dataset was randomly divided into for training, validation, and testing. The model was constructed with PyTorch. It was trained and weighting parameters were tuned on the validation set. Diagnostic performance was compared with that of the radiologists on the testing set. The mAP of the model was 96.4% at the 50% intersection-over-union threshold. The accuracy values of it were 0.962 for benign lymph nodes, 0.982 for lymphomas, and 0.960 for metastatic lymph nodes. The precision values of it were 0.928 for benign lymph nodes, 0.975 for lymphomas, and 0.927 for metastatic lymph nodes. The accuracy values of radiologists were 0.659 for benign lymph nodes, 0.836 for lymphomas, and 0.580 for metastatic lymph nodes. The precision values of radiologists were 0.478 for benign lymph nodes, 0.329 for lymphomas, and 0.596 for metastatic lymph nodes. The model effectively classifies lymphadenopathies from ultrasound images and outperforms qualitative visual evaluation by experienced radiologists in differential diagnosis.
A resampling-based approach to share reference panels
Authors: Cavinato Théo , Rubinacci Simone , Malaspinas Anna-Sapfo , Delaneau Olivier 
Published: May 2024

AbstractFor many genome-wide association studies, imputing genotypes from a haplotype reference panel is a necessary step. Over the past 15 years, reference panels have become larger and more diverse, leading to improvements in imputation accuracy. However, the latest generation of reference panels is subject to restrictions on data sharing due to concerns about privacy, limiting their usefulness for genotype imputation. In this context, here we propose RESHAPE, a method that employs a recombination Poisson process on a reference panel to simulate the genomes of hypothetical descendants after multiple generations. This data transformation helps to protect against re-identification threats and preserves data attributes, such as linkage disequilibrium patterns and, to some degree, identity-by-descent sharing, allowing for genotype imputation. Our experiments on gold-standard datasets show that simulated descendants up to eight generations can serve as reference panels without substantially reducing genotype imputation accuracy.
Ligand engineering of circularly polarized luminescence inversion and enhancement for chiral Ag6 nanoclusters
Authors: Chen Hui , Zhang Xiangyang , Fu Kuo , Wang Xuejuan , Liu Guofeng 
Published: May 2024

Four pairs of chiral Ag6L6 nanoclusters, synthesized using ligand engineering with thiazithione and oxazinthione, exhibit enhanced luminescence quantum yield attributed to S⋯S interactions and demonstrate supramolecular chirality inversion regulated by peripheral methyl and phenyl groups.
Prediction and optimisation of gasoline quality in petroleum refining: The use of machine learning model as a surrogate in optimisation framework
Authors: Saghir Husnain , Ahmad Iftikhar , Kano Manabu , Caliskan Hakan , Hong Hiki 
Published: May 2024

AbstractHardware‐based sensing frameworks such as cooperative fuel research engines are conventionally used to monitor research octane number (RON) in the petroleum refining industry. Machine learning techniques are employed to predict the RON of integrated naphtha reforming and isomerisation processes. A dynamic Aspen HYSYS model was used to generate data by introducing artificial uncertainties in the range of ±5% in process conditions, such as temperature, flow rates, etc. The generated data was used to train support vector machines (SVM), Gaussian process regression (GPR), artificial neural networks (ANN), regression trees (RT), and ensemble trees (ET). Hyperparameter tuning was performed to enhance the prediction capabilities of GPR, ANN, SVM, ET and RT models. Performance analysis of the models indicates that GPR, ANN, and SVM with R2 values of 0.99, 0.978, and 0.979 and RMSE values of 0.108, 0.262, and 0.258, respectively performed better than the remaining models and had the prediction capability to capture the RON dependence on predictor variables. ET and RT had an R2 value of 0.94 and 0.89, respectively. The GPR model was used as a surrogate model for fitness function evaluations in two optimisation frameworks based on genetic algorithm and particle swarm method. Optimal parameter values found by the optimisation methodology increased the RON value by 3.52%. The proposed methodology of surrogate‐based optimisation will provide a platform for plant‐level implementation to realise the concept of industry 4.0 in the refinery.
Dynamic spatial‐temporal network for traffic forecasting based on joint latent space representation
Authors: Yu Qian , Ma Liang , Lai Pei , Guo Jin 
Published: May 2024

AbstractIn the era of data‐driven transportation development, traffic forecasting is crucial. Established studies either ignore the inherent spatial structure of the traffic network or ignore the global spatial correlation and may not capture the spatial relationships adequately. In this work, a Dynamic Spatial‐Temporal Network (DSTN) based on Joint Latent Space Representation (JLSR) is proposed for traffic forecasting. Specifically, in the spatial dimension, a JLSR network is developed by integrating graph convolution and spatial attention operations to model complex spatial dependencies. Since it can adaptively fuse the representation information of local topological space and global dynamic space, a more comprehensive spatial dependency can be captured. In the temporal dimension, a Stacked Bidirectional Unidirectional Gated Recurrent Unit (SBUGRU) network is developed, which captures long‐term temporal dependencies through both forward and backward computations and superimposed recurrent layers. On these bases, DSTN is developed in an encoder‐decoder framework and periodicity is flexibly modeled by embedding branches. The performance of DSTN is validated on two types of real‐world traffic flow datasets, and it improves over baselines.
Formation of N–bearing complex organic molecules in molecular clouds: Ketenimine, acetonitrile, acetaldimine, and vinylamine via the UV photolysis of C2H2 ice
Authors: Chuang K.-J. , Jäger C. , Santos J. C. , Henning Th. 
Published: May 2024

Context. The solid-state C2H2 chemistry in interstellar H2O-rich ice has been proposed to explain astronomically observed complex organic molecules (COMs), including ketene (CH2CO), acetaldehyde (CH3CHO), and ethanol (CH3CH2OH), toward early star-forming regions. This formation mechanism is supported by recent laboratory studies and theoretical calculations for the reactions of C2H2+OH/H. However, the analog reaction of C2H2+NH2 forming N-bearing species has been suggested to have a relatively low rate constant that is orders of magnitude lower than the value of C2H2+OH.
Aims. This work extends our previous laboratory studies on O-bearing COM formation to investigate the interactions between C2H2 and NH3 ice triggered by cosmic ray-induced secondary UV photons under molecular cloud conditions.
Methods. Experiments were performed in an ultra-high vacuum chamber to investigate the UV photolysis of the C2H2:NH3 ice mixture at 10 K. The ongoing chemistry was monitored in situ by Fourier-transform infrared spectroscopy as a function of photon fluence. The IR spectral identification of the newly formed N-bearing products was further secured by a quadrupole mass spectrometer during the temperature-programmed desorption experiment.
Results. The studied ice chemistry of C2 H2 with NH2 radicals and H atoms resulting from the UV photodissociation of NH3 leads to the formation of several N-bearing COMs, including vinylamine (CH2CHNH2), acetaldimine (CH3CHNH), acetonitrile (CH3CN), ketenimine (CH2CNH), and tentatively ethylamine (CH3CH2NH2). The experimental results show an immediate and abundant CH2CHNH2 yield as the first-generation product, which is further converted into other chemical derivatives. The effective destruction and formation cross-section values of parent species and COMs were derived, and we discuss the chemical links among these molecules and their astronomical relevance.
Fallbeispiele zur Therapie der rezidivierenden Depression mit Psilocybin
Authors: Schindowski Eva Maria , Vollenweider Franz X. 
Published: May 2024

ZUSAMMENFASSUNGDer Artikel stellt 2 Behandlungsverläufe von Patienten mit rezidivierender Depression gegenüber, welche mit Psilocybin behandelt wurden. Weltweit wächst stetig die Anzahl Studien, die die Verwendung von Psilocybin zur Behandlung von Depressionen untersuchen und damit mehr und mehr das Interesse an dieser Therapieform. Während einige Kollegen aus dem Forschungsumfeld einen aktuellen „Hype“ um die Wirkung von Psychedelika bemerken, machen Patienten und ihre begleitenden Behandler sehr unterschiedliche Erfahrungen in der konkreten Anwendung der Substanz. Es gibt nur wenige detaillierte Beschreibungen von Langzeitverläufen, die Außenstehenden, die sonst keine Berührungspunkte mit der klinischen Anwendung im Forschungsrahmen oder in anderen legalen Settings haben, einen tieferen Einblick in diese Art der Therapie ermöglichen. Die hier genannten Fallbeispiele zeigen einerseits das enorme Potenzial von Psilocybin, das Leben depressiver Patienten positiv zu beeinflussen, andererseits sollte nicht vernachlässigt werden, dass es weiterhin Patienten gibt, die auch bei wiederholter Anwendung keinen langfristigen Nutzen erfahren.
Surgery of Neoaortic Pseudoaneurysm with Transsternal Penetration in a HLHS Patient
Authors: Peivandi Armin , Martens Sven , Weber Raluca , Rukosujew Andreas 
Published: May 2024

Abstract
Background Neoaortic pseudoaneurysm after previous surgery is rare and life-threatening.
Case Description We present a case of a 6th redo surgery in a 23-year-old male patient with a history of hypoplastic left heart syndrome presenting with transsternal penetration of aortic pseudoaneurysm. The previously implanted Dacron prosthesis showed semicircular dehiscence. It was exchanged by a Vascutek prosthesis during circulatory arrest and selective antegrade cerebral perfusion.
Conclusion Control imaging at 1 year after surgery was unobtrusive. Three years after surgery, the patient is alive and doing well.
The Anti-Inflammatory Effect of Nigella sativa Toothpaste on Porphyromonas gingivalis Bacteria Through Decreased TNF-α, MMP-9, PGE-2 Expression in Wistar Rats
Authors: Maduratna Ernie , Sari Desi Sandra , Rahayu Retno Puji , Masya Resgita Nadila , Adinar Noor 
Published: May 2024

Abstract
Objective The main principle in preventing periodontal disease is to improve oral hygiene. The bacteria that cause the onset of periodontal disease, one of which is the Porphyromonas gingivalis bacterium, causes inflammation. Persistent inflammation causes tissue damage and alveolar bone resorption by secreting proinflammatory cytokines, matrix metalloproteinase-9 (MMP-9), prostaglandin E2 (PGE-2), and anti-inflammatory cytokines. In this case, preventive treatment is needed, such as using toothpaste that contains anti-inflammatories so that the progression of the disease does not get worse. The traditional ingredient currently being developed is Nigella sativa, which has anti-inflammatory properties. Therefore, this study analyzes the potential of toothpaste containing Nigella sativa on the expression of tumor necrosis factor-α (TNF-α), MMP-9, and PGE-2 in the Wistar rat model induced by Porphyromonas gingivalis bacteria. This study aims to prove the potential of Nigella sativa toothpaste to decrease the expression of PGE-2, TNF-α, and MMP-9 in the gingiva of rats induced by Porphyromonas gingivalis bacteria.
Materials and Methods Forty-five healthy male Wistar rats were used, consisting of the negative control group, which was only injected with Porphyromonas gingivalis bacteria ATCC3322. The positive control group was given enzyme toothpaste, and the treatment group was assigned 1 mg of Nigella sativa paste using a microbrush for 30 seconds on the gingiva incisors mandibular with a circular motion, given two times a day for a week. Immunohistochemical to see the expression of TNF-α, PGE-2, and MMP-9. Parametric comparative analysis using a one-way analysis of variance test was performed to analyze differences between groups.
Results and Discussion Nigella sativa toothpaste significantly reduced proinflammatory cytokines, as seen through the expression of TNF-α, PGE-2, and MMP-9 on days 3, 5, and 7 (p <0.05).
Conclusion In the limit of studied animal model, this trial indicates that giving toothpaste with black seed extract (Nigella sativa) could inhibit inflammatory mediators, as seen from the decreased expression of MMP-9, TNF-α, and PGE-2 seen from the 3rd, 5th, and 7th days.
Flexural Strength of Different Monolithic Computer-Assisted Design and Computer-Assisted Manufacturing Ceramic Materials Upon Accelerated Aging
Authors: Juntavee Niwut , Juntavee Apa , Chansathien Orapun , Prasertcharoensuk Natcha , Leesuraplanon Boonsita 
Published: May 2024

Abstract
Objectives The durability of ceramic is crucial, which is probably influenced by aging. This study evaluated the effect of aging on flexural strength of different ceramics.
Materials and Methods One-hundred twenty ceramic discs (Ø 12 mm, 1.5 mm thickness) were prepared from zirconia-reinforced lithium silicate (ZLS, C), lithium disilicate (LS2, E), precolored yttria-stabilized tetragonal zirconia polycrystalline (Y-TZP, Ip), and customized color Y-TZP (Ic). Samples were randomly divided into two groups for accelerated aging (A) between 5 and 55°C water baths, 30-second immersing time each, for 10,000 cycles, and nonaged group (N), serving as control. Biaxial flexural strength (σ) was evaluated utilizing the piston-on-three-balls at 0.5 mm/min speed. Analysis of variance and Tukey comparisons were determined for significant differences (α = 0.05). Weibull analysis was applied for survival probability, Weibull modulus (m), and characteristic strength (σo). Microstructures were evaluated with scanning electron microscopy and X-ray diffraction (XRD).
Results The highest σ and σo were seen for IcN, followed by IcA, IpN, IpA, EN, CA, CN, and EA, respectively. CN showed the highest m, while EA showed the lowest m. Significant differences of σ for each ceramic were indicated (p < 0.05). Aging caused a significant difference in σ (p < 0.05). XRD showed t→m phase transformation of Ip and Ic after aging.
Conclusion Aging affected strength of ceramics. Comparable strength between LS2 and ZLS was evidenced, but both were less strength than Y-TZP either aging or non-aging. Comparable strength between precolored Y-TZP and customized color Y-TZP was indicated. Better resisting aging deterioration of Y-TZP than LS2 and ZLS is suggested for fabrication restorative reconstruction.
Establishment of an equity evaluation method for urban parkland layout under the process-outcome perspective
Authors: Guo Yuhan , Cao Yilun , Li Yue , Wang Runjue , Fang Yuhao 
Published: May 2024

AbstractUrban parkland, as a critical component of urban green space, reflects the distribution of public resources. Combined with the concept of the 15-min Living Circle, this paper comprehensively evaluated the equity of urban parkland in the Central Area of Zhengzhou from a process-outcome perspective and established an evaluation method for assessing the equity of parkland in high-density urban areas. The objective of this approach is to provide a systematic and applicable evaluation method for metropolises that is more comprehensive than traditional evaluation methods, which rely solely on accessibility. In terms of process equity, spatial equity values were calculated using the Three Step Catchment Area Method (3SFCA) with walking and bicycle travel models. For outcome equity, Zone Entropy was utilized with demographic characteristics. The results illustrated that the overall accessibility and equity of urban parkland layout in the Central Area of Zhengzhou were inferior, with an extensive number of blind service areas and serious polarization. The Zone Entropy varied considerably among streets, which indicated significant differences in the allocation of parkland and population. Further analysis illustrated that economic factors, such as house prices, were not significantly relevant to parkland equity. Instead, geographic factors such as location and intensity of development had a remarkable impact on parkland equity. Although urban parkland layout has been prone to the elderly, the total number of park spaces is still insufficient. In the long run, the construction of the 15-min Living Circle still needs to be vigorously promoted in the research area.
Linking organisational learning, performance, and sustainable performance in universities: an empirical study in Europe
Authors: Elbawab Roba 
Published: May 2024

AbstractUniversities are facing changes that could be adapted by learning. Organisational learning helps universities in attaining better organisational and sustainable performance. The study aims to combine and explore how organisational learning culture enables organisational learning to contribute to better organisational performance and better sustainable performance, following the natural resource-based view and organisational learning theory. The study examines the relationship between organisational learning culture, organisational learning, organisational performance, and sustainable performance in the university context from university teachers. The author collected 221 surveys from public university teachers in Europe to test the model. The results indicate a positive relationship between organisational learning culture and organisational learning. In addition to that, the positive relationship between organisational learning and organisational performance is indicated. Moreover, the results indicate a positive relationship between organisational learning and sustainable performance. The results also show that the organisational learning process mediates organisational learning culture and university performance. The study addresses a gap in the scarce studies in the university context for organisational learning and sustainable performance. Finally, this study reproduces an organisational model that has been adapted for universities.