bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advanced Catalytic Approaches for Synthesizing 1,2-dihydro-1-aryl-3H-naphtho[1,2-e]-[1,3]oxazin-3-one Derivatives through Electrophilic Substitution Reactions using Mono- and Bimetallic Phosphate Catalysts: A Study of Co₃(PO₄)₂ and CoCa₃(HPO₄)(PO₄)₂(OH)
Authors: HALLAOUI Achraf EL , FERRAA Nouhaila , MERROUN Yousssef , Chehab Soukaina , BOUKHRIS Said , Ziatni Mounia Bennani , HASSOUNE Hicham , SOUIZI Abdelaziz , GHAILANE Rachida 
Published: August 2024

Abstract

This research introduces a novel catalytic approach for the synthesis of 1,3-oxazinone derivatives through a multicomponent reaction that relies on an electrophilic substitution mechanism, employing two cobalt-based phosphate catalysts. This approach, allowed us to synthesize oxazine derivatives, known for their significant biological activities, achieving impressive yields of up to 97% in a remarkably short time of only 7 minutes, all under conditions environmentally friendly according to the principles of green chemistry using the ethanol/water mixture as a green solvent. In our study, we utilized two catalysts derived from cobalt-modified phosphate, which were synthesized in our laboratory using simple methods. The first support consists of a monometallic catalyst, denoted as Co3(PO4)2, whereas the second is a bimetallic phosphate catalyst modified with cobalt and calcium CoCa3(HPO4)(PO4)2(OH). Our developed methods had various advantages including simplicity of the process, rapid reaction time, simple clean-up, ability to recover and reuse the catalyst and overall simplicity. All these advantages render this developed approach effective and viable for synthesizing oxazine derivatives suitable for large-scale applications.
Predictors of septation in malignant pleural effusions: a retrospective cohort study
Authors: Sekowski Viktor , Gillson Ashley-Mae , Nazari Sahar , Li Pen , Stollery Daniel , Chan Chrystal 
Published: August 2024

Abstract

Background
Malignant pleural effusions (MPEs) are often managed with indwelling pleural catheter (IPC) insertion, however drainage can be limited by internal septations. Predictors of septated MPE remain uncertain. We aimed to determine the predictors of septated MPE.
Methods
Demographic and clinical characteristics were collected for 437 adult patients and 515 IPCs inserted at a Canadian pleural effusion clinic from 2012 to 2018. We utilized logistic regression analysis to identify independent predictors for development of septated pleural effusion.
Results
Systemic therapy (OR 1.78, p = 0.011) and moderate to large effusion size (OR 2.44, p = 0.004) were predictors of septated MPE among our studied cohort. The most common IPC-related complications were superficial skin/soft tissue infection (4%) followed by pleural infection (3%). No IPC-related deaths were observed in our study.
Conclusions
Systemic therapy and moderate to large pleural effusions may be independent risk factors for the development of septated MPE.
Data-driven prediction of the mechanical behavior of nanocrystalline graphene using a deep convolutional neural network with PCA
Authors: Shin Wonjun , Jang Seongwoo , Hwang Yunhyoung , Han Jihoon 
Published: August 2024

Abstract

The mechanical properties of nanocrystalline graphene significantly depend on its complex grain boundary configurations and defect distributions, with its inherent nanostructural complexity posing substantial challenges for existing computational methods. This study addresses these challenges by developing an artificial intelligence model that predicts the mechanical behavior of nanocrystalline graphene through the extraction of characteristics from randomly arranged grain boundaries based on grain size. Utilizing Voronoi tessellation, we modeled realistic grain boundaries at the atomic level, while principal component analysis (PCA) was employed to effectively reduce data dimensionality, greatly enhancing the learning efficiency of the convolutional neural network (CNN). By implementing simple yet efficient data augmentation method based on periodic boundary conditions, we substantially expanded the training dataset, providing a robust foundation for model training and validation. The model demonstrated high accuracy in predicting the mechanical responses of nanocrystalline graphene, effectively capturing the crucial impacts of defects and grain boundary distributions. The implementation of PCA proved essential in enhancing prediction accuracy for unseen data, particularly in interpolation and extrapolation scenarios, by concentrating on learning the principal components that govern mechanical behavior. Additionally, by applying explainable artificial intelligence (XAI) tools such as Grad-CAM, we validated the applicability of a pretrained network using minimal data, confirming its ability to identify crucial features impacting material properties.
Three-Dimensional Cell Spheroid Culture and Proliferation Activity Study of Uveal Melanoma Cell Line C918
Authors: yu jinhai , Yunxiu Chen , Qi Jin , Jiancheng Gan , Zhida Peng , Sha Wu , Hongfei Liao , Qi Xia 
Published: August 2024

Abstract

Objective: This study aims to investigate the morphological and histological characteristics of three-dimensional cell spheroids derived from the uveal melanoma (UM) cell line C918 and assess the impact of luteolin on their proliferation.
Methods:C918 cells were cultured in ultra-low adsorption 96-well plates, and morphological changes in C918 three-dimensional cell spheroids were observed over varying time intervals. Histological features of C918 multicellular spheroids cultured in ultra-low adsorption 6-well plates were examined using both HE staining and immunohistochemical staining. The CCK8 reagent was employed to measure the optical density at a 450nm wavelength after 72-hour treatments with varying luteolin concentrations in both two-dimensional and three-dimensional cultured C918 cells. The IC50 values were compared between the two culture conditions.
Results: Over time in culture, the volume of C918 three-dimensional cell spheroids gradually increased, and an ischemic and hypoxic region became evident within the spheroids on days 4 to 6 of culture. Histological staining demonstrated positive expression of proliferation marker antibodies (Ki67) and melanoma marker antibodies (MelanA, HMB45, S-100) in the multicellular spheroids from three-dimensional culture. CCK-8 experiments revealed that the IC50 values for luteolin in C918 cells were 183.50μmol/L in three-dimensional culture and 16.19μmol/L in two-dimensional culture after 72 hours. Three-dimensional cultured C918 cells, treated with varying luteolin concentrations for 72 hours, were observed under a microscope. The maximum cross-sectional area showed no statistically significant differences between the groups, but it was reduced in comparison to the control group.
Conclusion: Three-dimensional cultured C918 cell spheroids exhibit histological characteristics similar to real tumors and are less responsive to luteolin than their two-dimensional counterparts. They offer a valuable model for anti-tumor drug screening.
Pregnancy Related Worry and Associated Factors among Pregnant Women Attending Ante Natal Care At Abebech Gobena MCH Hospital 2023; A Cross Sectional Study
Authors: AH Berasa , GE Bekele , SH Berasa , BM Woldie , Lakew  
Published: August 2024

Abstract

Background
Pregnancy and childbirth are major developmental periods in a woman’s life that adds many sources of concerns to women’s daily life worries. Pregnant women should be provided with relevant and useful information to cope up with this specific period of their lives. Excessive worry can affect maternal physiological and psychological state that influences the pregnancy outcomes. Access to reliable pregnancy related information from the right sources reduces pregnancy related worries. This study assessed pregnancy related worry and associated factors among pregnant women attending ante natal care.
Methods
A cross-sectional study using a systematic random sampling method was conducted on 422 pregnant women who came for antenatal care follow up at Abebech Gobena MCH hospital from June 1, 2023 to September 30, 2023. The socio-demographic and obstetric characteristics, health information status, health care service utilization and social factors were obtained and pregnancy related worries were measured using Cambridge Worry Scale. Descriptive statistics was used to see frequency of independent variables. Simple logistic regression analysis was computed and all independent variables with p-value less than 0.25 were entered in multivariate logistic regression. Multivariate logistic regression was fitted to identify the factors associated with pregnancy related worries.
Result
From total of 422 pregnant women using Cambridge worry scale, 54.7% of the respondent women had pregnancy related worries and the rest 45.3% had no worries. The odds of pregnancy related worry among pregnant women were higher in women from rural area [AOR = 2.78; 95% CI: 1.24, 6.25], who were unable to read and write [AOR = 0.30 95% CI: 0.10, 0.92], who had previous pregnancy complication [AOR = 0.39; 95% CI: 0.16, 0.96], women living in more than five km distance [AOR = 2.45; 95% CI: 1.22, 4.90], who used digital source of information [AOR = 6.98; 95% CI: 2.00, 24.40] and low social support [AOR = 0.08; 95% CI: 0.01, 0.44].
Conclusion and recommendation
pregnancy related worries were prevalent in women attending ante natal care and significantly associated with women’s place of residence, educational status, previous pregnancy complication, distance from the health facility, source of trusted source of information, and social support.
Influence of Alloy 625 Manufacturing Process on 950˚C Oxidation Behavior in Air and Post-Oxidation High-Cycle Fatigue Performance
Authors: Nope Grace de Leon , Wang Guofeng , Gleeson Brian 
Published: August 2024

Abstract

This study investigates the effect of the Alloy 625 manufacturing process on the high-cycle fatigue (HCF) performance of oxidized samples. Conventional manufacturing processes (wrought and casting) and additive manufacturing (AM) processes (laser powder bed fusion and direct energy deposition) were studied. Results of Alloy 625 isothermal oxidation at 950°C in air revealed that AM samples showed faster oxidation kinetics and enhanced intergranular oxidation (IGO) with associated voids; the latter two were attributed partially to the alloy's greater amount of interstitial oxygen compared to conventional manufacturing processes. The HCF results showed that oxidized AM samples have a shorter life than oxidized wrought counterparts, where the earlier crack initiation in the oxidized AM samples is attributed to greater oxidation-induced subsurface degradation. This subsurface degradation includes the enhanced IGO and associated voids.
Random Forest-Based NIDS: Advancing Network Threat Detection
Authors: Darweesh M. Saeed , Abdelaziz Mohammed Tarek , Radwan Abdelrahman , Mamdouh Hesham , Saad Adel Saeed , Abuzaid Abdulrahman Salem , AbdElhakeem Ahmed Ayman , Zakzouk Salma , Moussa Kareem 
Published: August 2024

Abstract

Network Intrusion Detection Systems (NIDS) are critical for protecting computer networks from unauthorized activities. Traditional NIDS rely on rule-based signatures, which can be limiting in detecting emerging threats. This study investigates the effectiveness of the random forest classifier in advancing NIDS capabilities through machine learning. Using the CICIDS-2017 dataset, the data is preprocessed to enhance its quality by removing redundancies. The methodology involves rigorous testing and analysis of the random forest classifier's performance, focusing on accuracy and detection rates compared to other machine learning models. Results demonstrate that by optimizing class weights and leveraging 15 key features, the random forest classifier achieves an outstanding 99.8% accuracy across various attack types. This research highlights the potential of machine learning to significantly enhance NIDS effectiveness, offering a robust defense mechanism against evolving cybersecurity threats in modern networks.
Ultra-Lightweight YOLOv8n for PCB Defect Detection: An Adaptive Approach with Enhanced Feature Extraction and Efficient Model Embedding
Authors: Zhou Zhuguo , Lu Yujun , Lv Liye 
Published: August 2024

Abstract

To address the issues of missed and false detections caused by numerous tiny objects and complex background textures in printed circuit boards (PCBs), as well as the difficulty of embedding detection models into portable devices, this paper proposes an ultra-lightweight YOLOv8n defect detection method. Firstly, the method introduces an Uncertainty-driven Adaptive Training Sample Selection (UATSS) strategy during training to optimize model training and enhance detection accuracy. Secondly, it incorporates Details-Enhanced Convolution (DEConv) to improve the model's ability to extract detailed features of small PCB defects. Then, it employs a Sharing Lightweight Details-Enhanced Convolutional Detection Head (SLDECD) to replace the original Decoupled Head, reducing model complexity while enhancing network detection accuracy. Lastly, the Exponential Moving Average-Slide Loss (EMA-SlideLoss) function is introduced to provide more precise evaluation results during model training and enhance generalization capability. Comparative experiments on public PCB datasets demonstrate that the improved algorithm achieves an mAP of 97.6% and an accuracy of 99.6%, representing increases of 3.8% and 1.9%, respectively, compared to the original model. The model size is 4.1 MB, and the FPS reaches 144.1, meeting the requirements for portable embedded devices and real-time applications.
Physicochemical and Microbiological Evaluation of Yoghurt Sold in Addis Ababa, Ethiopia
Authors: Frew Mihret , Wolkaro Takele , Galmassa Ulfina 
Published: August 2024

Abstract

Background
Increase in demand for yoghurt in Addis Ababa, in recent times has led to proliferation of different kinds of commercially produced (branded) yoghurt in line with the traditional (unbranded) one in the market. However, limited/ no available data for the quality of gradually increase different kinds of commercially produced (branded) yoghurt in line with the traditional (unbranded) one in the market. There is therefore vital to evaluate the physicochemical property and microbial quality of yoghurt sold in Addis Ababa in order to determine its quality and perhaps safeguard the health and wellbeing of the numerous people consuming yoghurt products.
Methods
A total of 40 yoghurt samples consisted of 20 traditionally (unbranded) and 20 commercially produced (branded) were analysis for physicochemical property (pH, moisture, ash, fat, Total Solid (TS) and Solid Not Fat (SNF)) and microbial quality (Coliform Count (CC) and Yeast and Mould Count (YMC) were performed using TEMPO system whereas; Total Viable Count (TVC) was performed according to standard culture method).
Results
In traditionally produced (unbranded) yoghurt samples, fat content (4.44%), pH (3.99), TS content (10.12%), SNF content (7.18%), moisture content (89.88%) and ash content (0.53%) were found. The respective parameters for the commercially produced (branded) yoghurt samples were 5.02%, 3.88, 10.66%, 8.10%, 89.29% and 0.62%. The TVC in traditionally (unbranded) and commercially produced (branded) yoghurt samples was found to be 10.72 and 10.35 log 10 cfu/mL, respectively. Besides, 20%, 55% and 25% and 40%, 35% and 25% of traditionally (unbranded) and commercially produced (branded) yoghurt samples were found to be < 10 cfu/mL, 10 - <4.9x104 cfu/mL and > 4.9 x104 cfu/mL of CC with overall mean count of 3.72 and 2.81 log10 cfu/mL, respectively but not significant (P > .005). Regarding to YMC 0, 35%, and 65% and 30%, 50% and 20% of traditionally(unbranded) and commercially produced (branded) yoghurt samples were found to be < 100 cfu/mL, 100-<4.9x104cfu/mL and > 4.9x104 cfu/mL with overall mean count of 4.48 and 3.92 log10 cfu/mL, respectively but not significant (P > .005).
Conclusion
Based on the indicators considered in the present study, it is essential to improve yoghurt quality.
What’s in a Watt? Interpreting nightlights satellite data via citizen science observations
Authors: Nachtlichter Team , Tegeler Achim , Marz Aleksander , Gokus Andrea , Hänel Andreas , Rienow Andreas , Ruby Andreas , Glinka Anja , Kyba Anna Marie , Dröge-Rothaar Arne , Schwiesow Axel , Gillen Benno , von Heereman Bettine , Kuechly Brita , Altıntaş Burhan , Brock Christian , Kyba Christopher , McNally Cormac , Fischer Daniel , Dell’Osbel Daniele , Gruber David , Weiß Eva , Distelrath Florian , Vohla Frank , Heine Friedrich , Sulzer Georg , MacMillan Georgia , Esqu Gilbert , Anton Gisela , Altıntaş Hatice , Kuechly Helga , von Brandis Henning , von Maravić Irina , Wuthenow Isabell , Koglin Jacob , Degen Jacqueline , Mattern Janina , Schultz Johannes , Veh Johannes , Barentine John , Schreibweis Jonas , Leiter Katharina , Modersitzki Kilian , Klein Lena , Langejahn Marcus , Zschorn Maria , Pavić Marijana , Blaschke Maximilian , Köcher Maximilian , Brauchler Melanie , Leipold Michaela , Küppers Nathalie , Schulte-Römer Nona , Naboulsi Normän , Stumpf Peter , Bilela Petra , Binder Reinhart , Curwy René , Kyba Russell , Frank Sabine , Falkner Sebastian , Bauer Sicco , Liese Steffen , Rom Tamara , Kunzemann Thomas , Altıntaş Yiğit , Tičinović Vita 
Published: August 2024

Abstract

The image of Earth at Night from space has become iconic, but we are still in the dark when it comes to the question of to what extent different light source types contribute to city light emissions. Our team of citizen scientists used the Nachtlichter app to count and classify 234,044 light sources over a total area of 22 km2 during 2021. We find that a space-based radiance observation of 1 nW/cm2sr in the 500-900 nm range corresponds to 219 lights/km2 on the ground at midnight. This suggests that 78.0±1.6 million individual light sources are still turned on at midnight in Germany. We additionally examined the properties of the lights, and their relation to land cover. We find that private windows are the most abundant light type, and that for every streetlight in German urban areas, there is an illuminated sign and shop window.
SwinUNeCCt: Bidirectional Hash-based Agent Transformer for Cervical Cancer MRI Image Multi-task Learning
Authors: Chongshuang Yang , Tianliang Shi , jing Yang , chao Huang , peng Jiang , Xiangyang Fu , Tan Zhuoyi 
Published: August 2024

Abstract

Background: Cervical cancer is the fourth most common malignant tumor among women globally, posing a significant threat to women's health. In 2022, approximately 600,000 new cases were reported, and 340,000 deaths occurred due to cervical cancer. Magnetic resonance imaging (MRI) is the preferred imaging method for diagnosing, staging, and evaluating cervical cancer. However, manual segmentation of MRI images is time-consuming and subjective. Therefore, there is an urgent need for automatic segmentation models to identify cervical cancer lesions in MRI scans accurately.
Methods: All magnetic resonance images in our research are from cervical cancer patients diagnosed by pathology at Tongren City People's Hospital. Strict data selection criteria and clearly defined inclusion and exclusion conditions were established to ensure data consistency and accuracy of research results. The dataset contains imaging data from 122 cervical cancer patients, with each patient having 100 pelvic dynamic contrast-enhanced MRI scans. Annotations were jointly completed by medical professionals from Universiti Putra Malaysia and the Radiology Department of Tongren City People's Hospital to ensure data accuracy and reliability. Additionally, a novel computer-aided diagnosis model named SwinUNeCCt is proposed. This model incorporates: i) A bidirectional hash-based agent multi-head self-attention mechanism, which optimizes the interaction between local and global features in MRI, aiding in more accurate lesion identification. ii) Reduced computational complexity of the self-attention mechanism.
Results: The effectiveness of the SwinUNeCCt model has been validated through comparisons with state-of-the-art 3D medical models, including nnUnet, TransBTS, nnFormer, UnetR, UnesT, SwinUNetR, and SwinUNeLCsT. In semantic segmentation tasks without a classification module, the SwinUNeCCt model demonstrates excellent performance across multiple key metrics: achieving a 95HD of 6.25, an IoU of 0.669, and a DSC of 0.802, all of which are the best results among the compared models. Simultaneously, SwinUNeCCt strikes a good balance between computational efficiency and model complexity, requiring only 442.7 GFLOPs of computational power and 71.2M parameters. Furthermore, in semantic segmentation tasks that include a classification module, the SwinUNeCCt model also exhibits powerful recognition capabilities. Although this slightly increases computational overhead and model complexity, its performance surpasses other comparative models.
Conclusions: The SwinUNeCCt model demonstrates excellent performance in semantic segmentation tasks, achieving the best results among state-of-the-art 3D medical models across multiple key metrics. It balances computational efficiency and model complexity well, maintaining high performance even with the inclusion of a classification module.
Systematic attribution of heatwaves to the emissions of carbon majors
Authors: Quilcaille Yann , Gudmundsson Lukas , Schumacher Dominik , Gasser Thomas , Heede Richard , Heri Corina , Lejeune Quentin , Nath Shruti , Thiery Wim , Schleussner Carl-Friedrich , Seneviratne Sonia 
Published: August 2024

Abstract

Extreme event attribution assesses how anthropogenic climate change affected an extreme climate event, but typically focuses on individual events. Here, we systematize this approach, and apply it to 187 historical heatwaves reported over the period 2000-2022. We show that climate change has made all these heatwaves more likely and more intense. In particular, 33% of these heatwaves were virtually impossible without anthropogenic influence. Furthermore, this influence rises over time, both in intensity and in likelihood: climate change made the median heatwaves 24 times more likely over 2000-2009, 293 times more likely over 2010-2019 and 1355 times more likely over 2020-2022. We also extend the attribution to the contribution of emitters, by quantifying how much these heatwaves were affected by the emissions of 122 carbon majors (fossil fuel and cement producers), assessed through their full value chain. Our best estimate shows that, depending on the carbon major, between 28 and 62 heatwaves have been made 10,000 times more likely. Even small carbon majors enable heatwaves with their sole contribution.