bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comparative study of hot tensile deformation behavior of 6016 aluminum alloy under LSTM neural network and Arrhenius model
Authors: Zhao Huijun , Wu Jie , He Haibin , Li Xiang , Wang Lei , Lou Hua , Liu Kaimin , Ruan Xiaodong 
Published: September 2024

Abstract
The isothermal tensile test of 6016-T6 aluminum alloy was carried out on Gleeble-3500 at the temperature range of 400 °C–550 °C and the strain rate range of 0.01–10 s−1. The results show that the thermal deformation mechanism of 6016-T6 is dynamic recovery and dynamic recrystallization. In this paper, the phenomenological Arrhenius constitutive model and the data-driven WOA-LSTM constitutive model for predicting the hot tensile deformation behavior of 6016-T6 aluminum alloy were studied in contrast. The whale optimization algorithm was used to optimize the hyperparameters of LSTM neural network to improve the prediction accuracy of flow stress. The optimization results show that the optimal hidden layer node, maximum training period, initial learning rate and mini batch size of WOA-LSTM are 46, 260, 0.0248 and 16, respectively. In addition, the influence of the number of hidden layers on the results of the network was discussed. The appropriate hidden layer of the network was determined to be 2. The result show that the prediction accuracy of WOA-LSTM constitutive model is better than the Arrhenius constitutive model. The mean absolute error and correlation coefficient are 0.9348% and 0.99952, respectively. Among them, in this study, the Arrhenius constitutive model has low precision and only has high precision within a single temperature range.
Biological cell response to electric field: a review of equivalent circuit models and future challenges
Authors: Seyedi MirHojjat 
Published: September 2024

Abstract
Biological cells, characterized by complex and dynamic structures, demand precise models for comprehensive understanding, especially when subjected to external factors such as electric fields (EF) for manipulation or treatment. This interaction is integral to technologies like pulsed electric fields (PEF), inducing reversible and irreversible structural variations. Our study explores both simplified and sophisticated equivalent circuit models for biological cells under the influence of an external EF, covering diverse cell structures from single- to double-shell configurations. The paper highlights challenges in circuit modeling, specifically addressing the incorporation of reversible or irreversible pores in the membrane during external EF interactions, emphasizing the need for further research to refine technical aspects in this field. Additionally, we review a comparative analysis of the performance and applicability of the proposed circuit models, providing insights into their strengths and limitations. This contributes to a deeper insight of the complexities associated with modeling biological cells under external EF influences, paving the way for enhanced applications in medical and technological domains in future.
High performance method for COPD features extraction using complex network
Authors: Han Trong-Thanh , Le Trung Kien , Nguyen Anh Phuong , Nguyen Huu Phat 
Published: September 2024

Abstract

Objectives. The paper proposes a novel methodology for the classification of Chronic Obstructive Pulmonary Disease (COPD) utilizing respiratory sound attributes. Methods. The approach involves segmenting respiratory sounds into individual breaths and conducting extensive studies on this dataset. Spectral Transforms, various Wavelet Transforms are applied to capture distinct signal features. Complex Network is also employed to extract characteristic elements, generating novel representations of spectrogram data based on graph factors, including entropy, density, and position. The normalized and enriched data is then used to develop COPD classifiers using six machine learning algorithms, fine-tuning with appropriate training details and hyperparameter tuning. Results. Our results demonstrate robust performance, with ROC curves consistently exhibiting an Area Under the Curve (AUC) > 96% across different time-frequency transformations. Notably, the Random Forest algorithm achieves an AUC of 99.67%, outperforming other algorithms. Moreover, the Wavelet Daubechies 2 (Db2) consistently approaches 98% accuracy, particularly noteworthy in conjunction with the Naive Bayes algorithm. Conclusion. This study diagnosis patients through spectrogram images extracted from lung sounds. The application of Inverse Transforms, Complex Network, and Optimized Classification Algorithms yielded results beyond expectations. This methodology provides a promising approach for accurate COPD diagnosis, leveraging Machine Learning techniques applied to respiratory sound analysis.
Mutual effects between a gliding arc discharge and a premixed flame
Authors: ZHU 朱 Jiajian 家健 , LI 李 Le 乐 , TIAN 田 Yifu 轶夫 , WAN 万 Minggang 明罡 , SUN 孙 Mingbo 明波 
Published: September 2024

Abstract
Mutual effects between a gliding arc (GA) discharge at atmospheric pressure and a premixed CH4/air flame were experimentally investigated. Effects of the flame on the GA were studied using simultaneous measurements of the current, the voltage, and the instantaneous images of the plasma columns. The GA in the flame has a thicker and more diffusive plasma column, and it is more frequently ignited at a smaller breakdown voltage than that in the air. The GA extension velocity and the gliding velocity in the flame are larger than those in the air. The electrode voltage drop of the GA discharge in the flame is about 160 V, whereas that in the air is about 220 V. Compared with the GA in the air, the different features of the GA in the flame can be explained by high-temperature, weakly ionized, and species-abundant environment that are generated by the premixed CH4/air flame. Effects of the gliding arc discharge on the premixed flames were demonstrated using planar laser-induced fluorescence of hydroxyl radicals (OH) and formaldehyde (CH2O). OH and CH2O can be formed in the CH4/air mixture in the presence of the GA due to kinetic effects, and the increase of OH and CH2O shows the great potential of the GA for combustion enhancement.
Civility
Authors: Sheldrake Philip 
Published: September 2024

AbstractThis book offers a critical response to the extensive social challenges and public problems that are present in contemporary society—particularly, although not exclusively, in the Western world. The book presents two main themes. First, and most importantly, we need to recover a coherent sense of critical public virtues. What are they and how are we to cultivate them? Second, we need to rethink our understanding of “politics”—both what it means and how it is practised. “Politics” in its true sense involves the service of the “polis”—that is, the human community—in ways that build social equality. To focus more effectively on public virtues and values contrasts strongly with the contemporary tendency to concentrate exclusively on material success or efficient systems as the main goals that shape our societies. A key argument in the book is that “public life” is an essential dimension of everyone’s lives. “Public life” emphasizes that to be truly human involves living together in society—a place of communities, debate, challenging encounters, and, most importantly, of shared responsibilities. The virtues outlined in the book include civility, a true sense of place, how to build community, solidarity, and a sense of responsibility, respect, and compassion, and learning how to live an examined, reflective, and well-directed life rather than responding to immediate instincts. The book concludes with some reflections on how public virtues may be effectively cultivated—not least the role of school education and the role of good public leadership.
Discernment—The Art of Choosing Well
Authors: Sheldrake Philip 
Published: September 2024

AbstractMy final public virtue is “discernment”—the art of choosing well. This implies cultivating an examined and well-directed life rather than simply responding to immediate instincts. Discernment is not just related to individual choice but also applies to our lives within society. Discernment echoes Aristotle’s third kind of knowledge—“phronesis” or “practical wisdom.” This places social demands on us which may take us beyond purely personal satisfaction. In Christian thought, for example in John Cassian’s monastic writings, discernment is an act of moderation and balance which measures all other virtues. The important medieval philosopher, Thomas Aquinas, describes discernment as “practical prudence.” This regulates all the public virtues. Most famously, “discernment” is central to the sixteenth-century spiritual writings of Ignatius Loyola. It is what should be at the heart of all human choosing. To choose well, we need to be freed from unhelpful dependencies.
pyRforest: a comprehensive R package for genomic data analysis featuring scikit-learn Random Forests in R
Authors: Kolisnik Tyler , Keshavarz-Rahaghi Faeze , Purcell Rachel V , Smith Adam N H , Silander Olin K 
Published: September 2024

Abstract
Random Forest models are widely used in genomic data analysis and can offer insights into complex biological mechanisms, particularly when features influence the target in interactive, nonlinear, or nonadditive ways. Currently, some of the most efficient Random Forest methods in terms of computational speed are implemented in Python. However, many biologists use R for genomic data analysis, as R offers a unified platform for performing additional statistical analysis and visualization. Here, we present an R package, pyRforest, which integrates Python scikit-learn “RandomForestClassifier” algorithms into the R environment. pyRforest inherits the efficient memory management and parallelization of Python, and is optimized for classification tasks on large genomic datasets, such as those from RNA-seq. pyRforest offers several additional capabilities, including a novel rank-based permutation method for biomarker identification. This method can be used to estimate and visualize P-values for individual features, allowing the researcher to identify a subset of features for which there is robust statistical evidence of an effect. In addition, pyRforest includes methods for the calculation and visualization of SHapley Additive exPlanations values. Finally, pyRforest includes support for comprehensive downstream analysis for gene ontology and pathway enrichment. pyRforest thus improves the implementation and interpretability of Random Forest models for genomic data analysis by merging the strengths of Python with R. pyRforest can be downloaded at: https://www.github.com/tkolisnik/pyRforest with an associated vignette at https://github.com/tkolisnik/pyRforest/blob/main/vignettes/pyRforest-vignette.pdf.
The pharmacological landscape of chronic subdural hematoma: a systematic review and network meta-analysis of randomized and non-randomized controlled studies
Authors: Liu Tao , Zhao Zhihao , Liu Mingqi , An Shuo , Nie Meng , Liu Xuanhui , Qian Yu , Tian Ye , Zhang Jianning , Jiang Rongcai 
Published: September 2024

Abstract

Background
There are various treatment modalities for chronic subdural hematoma (CSDH) and there is extensive debate surrounding pharmaceutical interventions. There is no consensus regarding the relative efficacy and safety of multiple treatment modalities. This study aims to investigate this issue and offer potential clinical recommendations.

Methods
We searched PubMed, Web of Science, Embase and the Cochrane Library from January 2000 to May 2023 to identify randomized and nonrandomized controlled studies reporting one or more outcomes associated with the pharmacologic management of CSDH. The primary outcomes of interest included recurrence, favorable prognosis and adverse events, while the secondary outcomes included a reduction in hematoma volume and mortality. Pooled estimates, credible intervals and odds ratios were calculated for all outcomes using a fixed effects model. Confidence in network meta-analysis judgments were employed to stratify the evidential quality. This study was registered with PROSPERO: CRD42023406599.

Results
The search strategy yielded 656 references; ultimately, 36 studies involving 8082 patients fulfilled our predefined inclusion criteria. The findings suggested that statins + glucocorticoids (GCs) ranked highest for preventing recurrence, improving prognosis and facilitating hematoma absorption. Tranexamic acid ranked second highest for preventing recurrence. Statins were found to be the preferred drug intervention for decreasing mortality and preventing adverse events. Antithrombotic agents ranked lowest in terms of decreasing mortality and improving prognosis.

Conclusions
Our findings indicate that statins + GCs may be the most effective treatment modality for preventing recurrence, improving patient prognosis and facilitating hematoma absorption. In terms of reducing mortality and preventing adverse events, statins may be superior to other pharmacological interventions. Routine use of GCs is not suggested for patients with CSDH. Further prospective research is needed to directly compare the efficacy and superiority of various pharmaceutical interventions targeting CSDH to reinforce and validate our findings.
Adsorption/desorption of H2O and phase transition in crystals of cobalt(II) bis(tolylterpyridine) nitrate
Authors: Otsuki Joe , Kobayashi Yusaku , Torisawa Takumi , Furuhashi Tomoo , Shinozaki Yoshinao , Sugawa Kosuke , Kojima Yoshiyuki , Yoshikawa Hiroki , Tsukamoto Arata , Tadokoro Makoto 
Published: September 2024

Abstract
This study reports on the multiresponsive behavior of Co(II) bis(tolylterpyridine) nitrate crystals. Each crystal contains a single Co(II) complex and can accommodate up to 4 H2O molecules per asymmetric unit. In its fully hydrated form, the crystal contains planar hexameric hydrogen-bonded H2O clusters. The adsorption and desorption of H2O occur reversibly with changes in humidity, despite the absence of extended H2O channels. Furthermore, the crystals exhibit a crystal-to-crystal thermal phase transition. The structural studies reveal the dynamic nature of these crystals, which contribute to their multiresponsive behavior.
Quod mentem moneat: Monuments and memory in Bernardo Bertolucci’s The Conformist (1970)
Authors: Gessert Genevieve S 
Published: September 2024

Abstract
Bernardo Bertolucci’s The Conformist (1970), an adaptation of the 1951 novel by Alberto Moravia, has long been recognized for its sophisticated use of both mise-en-scène and editing to explore the historical and psychological effects of Fascism. Bertolucci made significant use of locations in Rome to characterize the Fascist aesthetic, and to visualize the subjective memory of the protagonist Marcello. Concurrent with his evocative use of Fascist imagery is Bertolucci’s complex layering of ancient references, primarily in the form of monuments, to complicate and elaborate the viewer’s understanding of both Marcello’s memory and the historical context, yet this palimpsest of reference has never been comprehensively excavated. This article analyses the classical and classicizing references within The Conformist in their role as memory complexes functioning both narratively and in the cognitive experience of the audience. This exploration seeks both to contextualize Bertolucci’s specific modes of reception within contemporary Italian culture and to deepen the analysis of ancient monuments as cinematic locations more generally.
Renal denervation achieves its antiarrhythmic effect through attenuating macrophage activation and neuroinflammation in stellate ganglia in chronic heart failure
Authors: Hu Wenfeng , Tu Huiyin , Wadman Michael C , Li Yu-Long , Zhang Dongze 
Published: September 2024

Abstract

Aims
Renal denervation (RDN) is widely investigated in multiple studies of sympathetically driven cardiovascular diseases. While the therapeutic potential of RDN for ventricular arrhythmia has been reported, the mechanisms responsible for its antiarrhythmic effect are poorly understood. Our recent study showed that macrophage expansion-induced neuroinflammation in the stellate ganglion (SG) was a critical factor for cardiac sympathetic overactivation and ventricular arrhythmogenesis in chronic heart failure (CHF). This study investigates if and how RDN decreases ventricular arrhythmias by attenuating neuroinflammation in cardiac sympathetic post-ganglionic (CSP) neurons in CHF.

Methods and results
Rat CHF was induced by surgical ligation of the left anterior descending (LAD) coronary artery. At 12 weeks after LAD ligation, completed bilateral RDN was achieved by surgically cutting all the visible renal nerves around the renal artery and vein, followed by applying 70% ethanol around the vessels. Immunofluorescence staining and western blot data showed that expression of granulocyte-macrophage colony-stimulating factor (GM-CSF) and its receptor-α subunit in SGs was increased in CHF rats. RDN not only reduced CHF-elevated GM-CSF levels in kidney, serum, and SGs but also attenuated macrophage expansion and neuroinflammation in SGs from CHF rats. Using flow cytometry, we confirmed that RDN reduced the percentage of macrophages in SGs, which is pathologically increased in CHF. RDN also decreased CHF-enhanced N-type Ca2+ currents in CSP neurons and attenuated CHF-elevated cardiac sympathetic nerve activity. Electrocardiogram data from 24-h continuous telemetry recording in conscious rats revealed that RDN improved CHF-induced heterogeneity of ventricular electrical activities and reduced the duration of spontaneous ventricular tachyarrhythmias in CHF rats.

Conclusion
RDN alleviates cardiac sympathetic overactivation and ventricular arrhythmogenesis through attenuating GM-CSF-induced macrophage activation and neuroinflammation within SGs in CHF. This suggests that manipulation of the GM-CSF signalling pathway could be a novel strategy for achieving the antiarrhythmic effect of RDN in CHF.
Automated annotation of scientific texts for ML-based keyphrase extraction and validation
Authors: Amusat Oluwamayowa O , Hegde Harshad , Mungall Christopher J , Giannakou Anna , Byers Neil P , Gunter Dan , Fagnan Kjiersten , Ramakrishnan Lavanya 
Published: September 2024

Abstract
Advanced omics technologies and facilities generate a wealth of valuable data daily; however, the data often lack the essential metadata required for researchers to find, curate, and search them effectively. The lack of metadata poses a significant challenge in the utilization of these data sets. Machine learning (ML)–based metadata extraction techniques have emerged as a potentially viable approach to automatically annotating scientific data sets with the metadata necessary for enabling effective search. Text labeling, usually performed manually, plays a crucial role in validating machine-extracted metadata. However, manual labeling is time-consuming and not always feasible; thus, there is a need to develop automated text labeling techniques in order to accelerate the process of scientific innovation. This need is particularly urgent in fields such as environmental genomics and microbiome science, which have historically received less attention in terms of metadata curation and creation of gold-standard text mining data sets. In this paper, we present two novel automated text labeling approaches for the validation of ML-generated metadata for unlabeled texts, with specific applications in environmental genomics. Our techniques show the potential of two new ways to leverage existing information that is only available for select documents within a corpus to validate ML models, which can then be used to describe the remaining documents in the corpus. The first technique exploits relationships between different types of data sources related to the same research study, such as publications and proposals. The second technique takes advantage of domain-specific controlled vocabularies or ontologies. In this paper, we detail applying these approaches in the context of environmental genomics research for ML-generated metadata validation. Our results show that the proposed label assignment approaches can generate both generic and highly specific text labels for the unlabeled texts, with up to 44% of the labels matching with those suggested by a ML keyword extraction algorithm.
An analysis of early and long-term gender-related outcomes after thoracic endovascular aortic repair
Authors: Piffaretti Gabriele , Mauri Francesca , Mozzetta Gaddiel , Zacà Sergio , Pulli Raffaele , Pratesi Giovanni , Fargion Aaron Thomas , Angiletta Domenico ,   I.C.E., Italian Collaborators for Thoracic Evar Registry, Villa Federico , Sala Giulia Anna , Bandiera Alessandra , Muscato Paola , Veneziano Angela , Guzzetti Luca , Fontana Federico , Piacentino Filippo , Esposito Davide , Melani Caterina , Bastianon Martina , Cucci Andrea , Palermo Dario , Di Stefano Lucia , Speziali Sara , Capone Amedeo , Piscitello Elisa , Dorigo Walter , Pratesi Carlo 
Published: September 2024

Abstract

OBJECTIVES
To evaluate gender-related outcomes during endovascular treatment of thoracic and thoraco-abdominal aortic diseases (TEVAR).

METHODS
Multicentre, retrospective, observational cohort study. All TEVARs between January 2005 and April 2023 were identified. Primary outcomes were 30-day mortality and cumulative survival. Secondary outcomes were vascular access complications, and freedom from TEVAR-related reintervention. Interventions performed in male patients were matched to females on the basis of a one-to-one coarsened exact matching.

RESULTS
We identified 151 males who were matched with 151 females. Mortality at 30 days was not statistically different between females and males (11.2% vs 11.2%; P = 1.0). At binary logistic regression analysis, duration of intervention (P = 0.001) and emergency TEVAR (P = 0.001) were associated with mortality at 30 days. Gender did not impact the access vessel complication rate [n = 6 (4.0%) vs n = 5 (3.3%); P = 1.0]. The median follow-up was 46 (interquartile range, 7–84) months with no difference between males and females [median 50 (11–95) vs 37.5 (3.5–71.2); P = 0.153]. Estimated survival was not statistically different between females and males [log-rank χ2 = 0.6, P = 0.442; 95% confidence interval (CI) 110.7–207.3]. At Cox’s regression analysis, gender did not impact overall survival (hazard ratio 0.8; 95% CI 0.6–1.3; P = 0.450). Estimated freedom from TEVAR-related reinterventions was not statistically different between females and males (log-rank χ2 = 0.4, P = 0.837; 95% CI 187.8–219.3).

CONCLUSIONS
Female gender itself was not associated with worse 30-day mortality and late survival than males with similar access vessel complication as well as TEVAR-related reintervention rate.