bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electron-donable heterojunctions with synergetic Ru-Cu pair sites for biocatalytic microenvironment modulations in inflammatory mandible defects
Authors: Bai Mingru , Wang Ting , Xing Zhenyu , Huang Haoju , Wu Xizheng , Adeli Mohsen , Wang Mao , Han Xianglong , Ye Ling , Cheng Chong 
Published: November 2024

AbstractThe clinical treatments of maxillofacial bone defects pose significant challenges due to complex microenvironments, including severe inflammation, high levels of reactive oxygen species (ROS), and potential bacterial infection. Herein, we propose the de novo design of an efficient, versatile, and precise electron-donable heterojunction with synergetic Ru-Cu pair sites (Ru-Cu/EDHJ) for superior biocatalytic regeneration of inflammatory mandible defects and pH-controlled antibacterial therapies. Our studies demonstrate that the unique structure of Ru-Cu/EDHJ enhances the electron density of Ru atoms and optimizes the binding strength of oxygen species, thus improving enzyme-like catalytic performance. Strikingly, this biocompatible Ru-Cu/EDHJ can efficiently switch between ROS scavenging in neutral media and ROS generation in acidic media, thus simultaneously exhibiting superior repair functions and bioadaptive antibacterial properties in treating mandible defects in male mice. We believe synthesizing such biocatalytic heterojunctions with exceptional enzyme-like capabilities will offer a promising pathway for engineering ROS biocatalytic materials to treat trauma, tumors, or infection-caused maxillofacial bone defects.
The effects of physical activity interventions on self-esteem during and after cancer treatment: a systematic review and meta-analysis
Authors: Rodriguez-Solana Andrea , Gracia-Marco Luis , Cadenas-Sanchez Cristina , Redondo-Tébar Andrés , Marmol-Perez Andres , Gil-Cosano Jose Juan , Llorente-Cantarero Francisco J. , Ubago-Guisado Esther 
Published: November 2024

AbstractTo investigate the effect of physical activity (PA) (both general and its type) on self-esteem during and after cancer treatment. A systematic search was conducted across PubMed, Web of Science, Scopus, SPORTDiscuss, and PsycINFO from their inception to February 2024. The systematic review included 32 studies, with 15 studies (13 RCT and 2 quasi-experimental) and 3604 participants (66.7% female) included in the meta-analysis involving controlled trials using a control group and at least one PA intervention group. The study was registered in PROSPERO (CRD42022309771). Risk of bias for RCTs was assessed using the Cochrane Collaboration’s tool for assessing risk of bias (RoB2), and quasi-experimental studies with the Joanna Briggs Institute critical appraisal tool. PA significantly improved self-esteem during and after cancer treatment (pooled SMD = 0.32, p < 0.01). Specifically, aerobic PA (pooled SMD = 0.33, p = 0.04) and mind-body exercise (pooled SMD = 0.70, p = 0.03) had positive effects on self-esteem. Overall, PA interventions improved self-esteem during cancer treatment (pooled SMD = 0.50, p = 0.01) and in PA interventions lasting more than 12 weeks (pooled SMD = 0.44, p = 0.02). In conclusion, PA (specifically, aerobic and mind-body exercises) may have a positive effect on self-esteem during and after cancer treatment, with cancer status and the duration of the intervention being key factors.
An efficient neural network LEACH protocol to extended lifetime of wireless sensor networks
Authors: El-Sayed Hamdy H. , Abd-Elgaber Elham M. , Zanaty E. A. , Alsubaei Faisal S. , Almazroi Abdulaleem Ali , Bakheet Samy S. 
Published: November 2024

AbstractThis paper presents NN_ILEACH, a novel neural network-based routing protocol designed to enhance the energy efficiency and longevity of Wireless Sensor Networks (WSNs). By integrating the Energy Hole Removing Mechanism (EHORM) with a sophisticated neural network for cluster head selection, NN_ILEACH effectively addresses the energy depletion challenges associated with traditional protocols like LEACH and ILEACH. Our extensive simulations demonstrate that NN_ILEACH significantly outperforms these classical protocols. Specifically, NN_ILEACH extends the network lifetime to an impressive 11,361 rounds, compared to only 505 rounds achieved by LEACH under identical conditions—representing a more than 20-fold improvement. Additionally, NN_ILEACH achieves a 30% increase in throughput and a 25% enhancement in packet delivery ratio, while reducing overall energy consumption by 40%. These results underscore the protocol’s potential to optimize energy usage and maintain network stability, paving the way for more resilient IoT systems in dynamic environments. Future work will explore further integration of machine learning techniques to enhance adaptability and performance in WSNs.
Enhanced detection of surface deformations in LPBF using deep convolutional neural networks and transfer learning from a porosity model
Authors: Ansari Muhammad Ayub , Crampton Andrew , Mubarak Samer Mohammed Jaber 
Published: November 2024

AbstractOur previous research papers have shown the potential of deep-learning models for real-time detection and control of porosity defects in 3D printing, specifically in the laser powder bed fusion (LPBF) process. Extending these models to identify other defects like surface deformation poses a challenge due to the scarcity of available data. This study introduces the use of Transfer Learning (TL) to train models on limited data for high accuracy in detecting surface deformations, marking the first attempt to apply a model trained on one defect type to another. Our approach demonstrates the power of transfer learning in adapting a model known for porosity detection in LPBF to identify surface deformations with high accuracy (94%), matching the performance of the best existing models but with significantly less complexity. This results in faster training and evaluation, ideal for real-time systems with limited computing capabilities. We further employed Gradient-weighted Class Activation Mapping (Grad-CAM) to visualize the model’s decision-making, highlighting the areas influencing defect detection. This step is vital for developing a trustworthy model, showcasing the effectiveness of our approach in broadening the model’s applicability while ensuring reliability and efficiency.
Performance of uncertainty-based active learning for efficient approximation of black-box functions in materials science
Authors: Koizumi Ai , Deffrennes Guillaume , Terayama Kei , Tamura Ryo 
Published: November 2024

AbstractObtaining a fine approximation of a black-box function is important for understanding and evaluating innovative materials. Active learning aims to improve the approximation of black-box functions with fewer training data. In this study, we investigate whether active learning based on uncertainty sampling enables the efficient approximation of black-box functions in regression tasks using various material databases. In cases where the inputs are provided uniformly and defined in a relatively low-dimensional space, the liquidus surfaces of the ternary systems are the focus. The results show that uncertainty-based active learning can produce a better black-box function with higher prediction accuracy than that by random sampling. Furthermore, in cases in which the inputs are distributed discretely and unbalanced in a high-dimensional feature space, datasets extracted from materials databases for inorganic materials, small molecules, and polymers are addressed, and uncertainty-based active learning is occasionally inefficient. Based on the dependency on the material descriptors, active learning tends to produce a better black-box functions than random sampling when the dimensions of the descriptor are small. The results indicate that active learning is occasionally inefficient in obtaining a better black-box function in materials science.
Photocatalytic degradation of methylene blue dye by ZnO nanoparticle thin films, using Sol–gel technique and UV laser irradiation
Authors: Atta Diaa , Wahab Hanan A. , Ibrahim M. A. , Battisha I. K. 
Published: November 2024

AbstractThe focus of the current work is the study of the effect of the photo-catalytic activity of ZnO nanoparticles. The photocatalytic destruction of methylene blue dye, a common water contaminant, was used to assess the photocatalytic efficiency of the ZnO nanoparticles from its aqueous solution by using ZnO nanoparticles thin film under UV light and laser irradiation. Sol–gel methods prepared ZnO nanoparticle thin films. X-ray diffraction and a field-emitted scanning electron microscope were utilized to examine the structure of the produced ZnO nanoparticles. An extended characterization by laser-based fluorescence and UV–visible spectroscopic techniques. The effects of operational parameters such as photo-catalyst load and contact time on photocatalytic degradation of methylene blue were investigated. The recent study’s findings showed that irradiation with a UV laser increases with power density 25 µW/cm2, the photo-catalytic rate. The UV spectra show decay for the band at 664nm decreased and the concentration of M.B. in monomer form decayed to 26% of the original concentration in 24 h, while the band at 612 which is related to the dimer M.B. molecules was not affected. The laser irradiation did the same for monomer M.B. molecules in only 3 h, while the dimer decreased to 28% of its original concentration. The reaction mechanism has been discussed by molecular modelling. Quantum mechanical calculations at B3LYP/6-311g(d,p) level indicated that methylene blue changed from dimers to monomers in the existence of ZnO. The current results present a method for degrading M.B. not only in wastewater but also in the industrial waste scale.
Spatial-temporal attention for video-based assessment of intraoperative surgical skill
Authors: Wan Bohua , Peven Michael , Hager Gregory , Sikder Shameema , Vedula S. Swaroop 
Published: November 2024

AbstractAccurate, unbiased, and reproducible assessment of skill is a vital resource for surgeons throughout their career. The objective in this research is to develop and validate algorithms for video-based assessment of intraoperative surgical skill. Algorithms to classify surgical video into expert or novice categories provide a summative assessment of skill, which is useful for evaluating surgeons at discrete time points in their training or certification of surgeons. Using a spatial-temporal neural network architecture, we tested the hypothesis that explicit supervision of spatial attention supervised by instrument tip locations improves the algorithm’s generalizability to unseen dataset. The best performing model had an area under the receiver operating characteristic curve (AUC) of 0.88. Augmenting the network with supervision of spatial attention improved specificity of its predictions (with small changes in sensitivity and AUC) and led to improved measures of discrimination when tested with unseen dataset. Our findings show that explicit supervision of attention learned from images using instrument tip locations can improve performance of algorithms for objective video-based assessment of surgical skill.
Efficacy of endoscopic interlaminar decompression in lumbar spinal stenosis: a retrospective study
Authors: Qu Xiao , Zhang Lin , xie Zhou , Zhang Jun , Huang Yanran , Li Ningdao , Luo Xiaoji 
Published: November 2024

AbstractThis retrospective study evaluated the clinical effectiveness of endoscopic interlaminar decompression for lumbar spinal stenosis in 40 patients treated from February 2020 to January 2022. The procedure was successful in all cases, with only one dural sac injury reported and no other complications. Postoperative Visual Analogue Scale (VAS) and Japanese Orthopaedic Association (JOA) scores improved significantly (P<0.05), and the modified Macnab criteria showed an 87.5% rate of excellent and good outcomes at follow-up. No patients required revision surgery. Overall, the endoscopic interlaminar approach proved to be effective, safe, and supported early recovery.
GDF15 is required for maintaining subcutaneous adipose tissue lipid metabolic signature
Authors: Igual-Gil Carla , Bishop Christopher A. , Jähnert Markus , Johann Kornelia , Coleman Verena , Baum Vanessa , Kruse Michael , Pfeiffer Andreas F.H. , Pivovarova-Ramich Olga , Ost Mario , Kleinert Maximilian , Klaus Susanne 
Published: November 2024

AbstractRecent research has identified growth differentiation factor 15 (GDF15) as a crucial factor in various physiological and pathological processes, particularly in energy balance regulation. While the role of GDF15 in modulating energy metabolism through hindbrain GDNF family receptor alpha-like (GFRAL) signaling has been extensively studied, emerging evidence suggests direct peripheral metabolic actions of GDF15. Using knockout mouse models, we investigated GDF15 and GFRAL’s roles in adipose tissue metabolism. Our findings indicate that C57BL/6/129/SvJ Gdf15-KO mice exhibit impaired expression of de novo lipogenesis enzymes in subcutaneous adipose tissue (sWAT). In contrast, C57BL/6J Gfral-KO mice showed no impairments compared to wild-type (WT) littermates. RNA-Seq analysis of sWAT in Gdf15-KO mice revealed a broad downregulation of genes involved in lipid metabolism. Importantly, our study uncovered sex-specific effects, with females being more affected by GDF15 loss than males. Additionally, we observed a fasting-induced upregulation of GDF15 gene expression in sWAT of both mice and humans, reinforcing this factor’s role in adipose tissue lipid metabolism. In conclusion, our research highlights an essential role for GDF15 in sWAT lipid metabolic homeostasis. These insights enhance our understanding of GDF15’s functions in adipose tissue physiology and underscore its potential as a therapeutic target for metabolic disorders.
Precision and effort in robot-assisted placement of pedicle screws compared to standard surgical navigation
Authors: Sippel Julia Katharina , Groh Johannes , Bräuer Lars , Perl Mario , Stadthalter Holger 
Published: November 2024

AbstractAim was to compare image-guided navigation with a robot-assisted solution for performing MISS regarding precision, required time and subjective aspects. 90 pedicles were instrumented on two torsos, half with navigation, half robot-assisted. Precision analysis between both solutions didn’t show a significant difference. Time measurement showed a significantly longer duration per wire for the robot-arm on the first torso and a not significant longer duration on the second torso, where a significant reduction in the mean duration was shown. There was no significant difference in the subjective impressions comparing navigation and robot except the possibility to change the procedure. Precision of both methods is suitable for clinical use. A time advantage using the robot-arm couldn’t be demonstrated in the present study. A significant learning curve was shown, so a reduction in the longer duration on the robot can be expected. Further studies in clinical use are necessary.
Relationship between regional volume changes and water diffusion in fixed marmoset brains: an in vivo and ex vivo comparison
Authors: Yoshimaru Daisuke , Tsurugizawa Tomokazu , Hayashi Naoya , Hata Junichi , Shibukawa Shuhei , Hagiya Kei , Oshiro Hinako , Kishi Noriyuki , Saito Kazuhiro , Okano Hideyuki , Okano Hirotaka James 
Published: November 2024

AbstractEx vivo studies of the brain are often employed as experimental systems in neuroscience. In general, brains for ex vivo MRI studies are usually fixed with paraformaldehyde to preserve molecular structure and prevent tissue destruction during long-term storage. As a result, fixing brain tissue causes microstructural changes and a decrease in brain volume. Therefore, the purpose of this study was to investigate the regional effect of brain volume and microstructural changes on the restricted diffusion of water molecules in the common marmoset brain using in vivo and ex vivo brains from the same individual. We used 9.4T magnetic resonance imaging and also compared the T2-weighted images and diffusion-weighted imaging (DWI) data between in vivo and ex vivo brains to investigate changes in brain volume and diffusion of water molecules in 12 common marmosets. We compared fractional anisotropy, mean diffusivity, AD (axial diffusivity), and radial diffusivity values in white matter and gray matter between in vivo and ex vivo brains. We observed that AD showed the strongest correlation with regional volume changes in gray matter. The results showed a strong correlation between AD and changes in brain volume. By comparing the in vivo and ex vivo brains of the same individual, we identified significant correlations between the local effects of perfusion fixation on microstructural and volumetric changes of the brain and alterations in the restricted diffusion of water molecules within the brain. These findings provide valuable insights into the complex relationships between tissue fixation, brain structure, and water diffusion properties in the marmoset brain.
Local effects of non-pharmaceutical interventions on mitigation of COVID-19 spread through decreased human mobilities in Japan: a prefecture-level mediation analysis
Authors: Nagata Shohei , Takahashi Yuta , Adachi Hiroki M. , Johnson Glen D. , Nakaya Tomoki 
Published: November 2024

AbstractTo control the COVID-19 epidemic, the Japanese government and the local governments have repeatedly implemented non-pharmaceutical interventions (NPIs) throughout 2020–2022. Using Bayesian state-space mediation models, we examined the effect of repeated NPIs on infection spread mitigation, mediated by human mobility changes in each prefecture during three epidemic phases: from April 1, 2020 to February 28, 2021; from March 1, 2021 to December 16, 2021; and from December 17, 2021 to December 31, 2022. In the first phase, controlling downtown populations at nighttime was effective in mitigating the infection spread in almost all prefectures. In the second and third phases, the effect was not clear, especially in metropolitan prefectures. Controlling visitors from the central prefectures of metropolitan areas was effective in mitigating infection spread in the surrounding prefectures during all phases. These results suggest that the local spread of infection can be mitigated by focusing on nighttime human mobility control in downtown areas before the epidemic spreads widely and transmission routes become more diverse, and that the geospatial spread of infection can be prevented by controlling the flows of people from large cities to other areas.
Implementation of a novel TRIZ-based model to increase the reporting of adverse events in the healthcare center
Authors: Lee Jiun-Yih , Lee Pei-Shan , Chiang Cheng-Hsien , Chen Yi-Ping , Chen Chiung-Ju , Huang Yuan-Ming , Chiu Jlan-Ren , Yang Pei-Ching , Yeh Chen-An , Chang Jui-Ting 
Published: November 2024

AbstractUnderreporting of adverse events in healthcare systems is a global concern. This study aims to address the underreporting of adverse events (AE) by implementing a TRIZ-based model to identify and overcome barriers to reporting, thus filling gaps in current reporting practices and improving incident recognition. A TRIZ (Theory of Inventive Problem Solving) approach was adopted, integrating with SERVQUAL methodologies to design interventions. Preintervention and postintervention surveys were conducted to evaluate changes in the recognition of adverse events and barriers to reporting. Statistical analyses were performed to assess the effectiveness of the interventions. Recognition improved and barriers to reporting AEs significantly decreased. Monthly reported cases rose from 33.7 to 50.3 (p = 0.000), demonstrating the effectiveness of the TRIZ-based interventions. Implementing a TRIZ-based model significantly improved adverse event reporting by enhancing the recognition of reportable events and overcoming identified barriers. Future research should explore the long-term sustainability of these interventions and their broader applicability in diverse healthcare settings.
Design and fabrication of tetradymites-based vertically oriented single and multilayer thin-film thermoelectric generators
Authors: Mbaye Mamadou T. , Pradhan Sangram K. , Bahoura Messaoud 
Published: November 2024

Tetradymites-based thermoelectric materials and devices have received renewed attention due to their engineering and design flexibility, large scalability, and commercial viability in producing electricity from waste heat for niche applications in small power generation and micro refrigeration. In fact, most commercially available bulk thermoelectric generators (TEGs) are made from tetradymites. In contrast to their bulk counterparts, thin-film vertical TEGs have not been widely adopted. This can be attributable to complexities in design and fabrication methodologies, device measurement challenges, and the hurdle of maintaining a large enough temperature gradient for optimal device performance. In this study, we utilize a facile approach for the design, fabrication, and characterization of tetradymite-based n-type Bi2Te3 and p-type Sb2Te3 single-layer thermoelectric generators, as well as n-type Bi2Te3/Bi2Te2.83Se0.17 and p-type Sb2Te3/Bi0.4Sb1.6Te3 alternating multilayer superlattice TEGs. State-of-the-art characterization techniques were employed to investigate the structural, chemical, and thermoelectric properties of the materials. XRD analysis showed a preferential orientation along the (100) plane with a high intensity peak at 2θ = 25.5°, and XPS spectra exhibited a high-resolution peak at 531.5 eV corresponding to the Bi 4f7/2 core level. The structural data analysis confirmed the dominant metallic phase of the materials as well as their high crystalline nature. Device characterization showed that the multilayer device performed better than the single-layer devices with a recorded voltage, power, and power density of 11 mV, 12 pW, and 15.87 mW/m3 at ΔT = 18 °C, respectively, in comparison to 9.4 mV, 7.8 pW, and 10.31 mW/m3 for the most performing single-layer devices.
Multilayer architected polymer nanostructure for microwave absorber-based EMI shielding
Authors: Rengaswamy Kumaran , M Anjali , Rengaswamy Jayaganthan , Krishnamurthy Chitti Venkata , Subramanian Venkatachalam 
Published: November 2024

Reflection-based electromagnetic interference shielding materials, though effectively stop the radiation, redirect the interference to nearby electronic devices, creating secondary pollution. In this sense, it is better to use absorption-dominant lightweight and flexible materials with high shielding effectiveness. This paper reports the fabrication of a multilayered polymer nanocomposite for enhancing electromagnetic interference shielding applications through absorption. By using a doctor-blade technique, three individual layers of poly(vinylidene fluoride) based polymer nanocomposite, each with different fillers, were prepared and stacked together to form a 3 mm thick multilayered (four-layer) composite. The fillers were 5% Ag-decorated graphene nanoplatelets, acid-functionalized MWCNT, and barium hexaferrite. Between 8 and 18 GHz, this multilayered composite absorbs a maximum of 90% of incident microwave radiation, resulting in a shielding in the range of 20–45 dB. This structure is very useful for developing flat and lightweight absorbers. For comparison, a homogeneously prepared nanocomposite comprising all these three fillers is found to give a shielding of around 53 dB with a reflection ranging between 78% and 89%.