bluuebunny/crossref_metadata_2025_split huggingface dataset:
3D printing technology combined with personalized plates for complex distal intra-articular fractures of the trimalleolar ankle
Authors: Liang Hairui , Zhang He , Chen Beibei , Yang Lei , Xu Rongda , Duan Siyu , Cai Zhencun 
Published: December 2023

AbstractThis study investigated the effectiveness of 3D printing technology in combination with personalized custom-made steel plates in the treatment of complex distal intra-articular trimalleolar fractures, with the aim of providing a new approach to improve ankle joint function in patients. The 48 patients with complex distal intra-articular trimalleolar fractures included in the study were randomly divided into two groups: the personalized custom-made steel plate group (n = 24) and the conventional steel plate group (n = 24). A comparison was made between the two groups in terms of preoperative preparation time, hospitalization duration, surgical time, fracture reduction and internal fixation time, intraoperative fluoroscopy instances, surgical incision length, fracture healing time, follow-up duration, degree of fracture reduction, ankle joint functional recovery, and the occurrence of complications. The personalized steel plate group exhibited longer preoperative preparation time and hospitalization duration compared to the conventional steel plate group (p < 0.001). However, the personalized steel plate group demonstrated significantly shorter surgical duration, time for fracture reduction and internal fixation, reduced intraoperative fluoroscopy frequency, and a shorter overall surgical incision length (p < 0.001). Both groups displayed similar fracture healing times and follow-up durations (p > 0.05). The personalized steel plate group showed a higher rate of successful fracture reduction (87.5% vs. 79.2%, p > 0.05) and a lower incidence of complications (8.3% vs. 20.8%, p = 0.22), although these differences did not reach statistical significance. Furthermore, the personalized steel plate group exhibited superior ankle joint function scores during follow-up compared to the conventional steel plate group (p < 0.05). By utilizing 3D printing technology in conjunction with personalized custom-made steel plates, personalized treatment plans are provided for patients with complex comminuted tri-malleolar ankle fractures, enabling safer, more efficient, and satisfactory orthopedic surgeries.
Nucleus accumbens core single cell ensembles bidirectionally respond to experienced versus observed aversive events
Authors: Dinckol Oyku , Wenger Noah Harris , Zachry Jennifer E. , Kutlu Munir Gunes 
Published: December 2023

AbstractFear learning is a critical feature of survival skills among mammals. In rodents, fear learning manifests itself through direct experience of the aversive event or social transmission of aversive stimuli such as observing and acting on conspecifics’ distress. The neuronal network underlying the social transmission of information largely overlaps with the brain regions that mediate behavioral responses to aversive and rewarding stimuli. In this study, we recorded single cell activity patterns of nucleus accumbens (NAc) core neurons using in vivo optical imaging of calcium transients via miniature scopes. This cutting-edge imaging methodology not only allows us to record activity patterns of individual neurons but also lets us longitudinally follow these individual neurons across time and different behavioral states. Using this approach, we identified NAc core single cell ensembles that respond to experienced and/or observed aversive stimuli. Our results showed that experienced and observed aversive stimuli evoke NAc core ensemble activity that is largely positive, with a smaller subset of negative responses. The size of the NAc single cell ensemble response was greater for experienced aversive stimuli compared to observed aversive events. Our results also revealed sex differences in the NAc core single cell ensembles responses to experience aversive stimuli, where females showed a greater accumbal response. Importantly, we found a subpopulation within the NAc core single cell ensembles that show a bidirectional response to experienced aversive stimuli versus observed aversive stimuli (i.e., negative response to experienced and positive response to observed). Our results suggest that the NAc plays a role in differentiating somatosensory experience from social observation of aversion at a single cell level. These results have important implications for psychopathologies where social information processing is maladaptive, such as autism spectrum disorders.
EVA and SEBS-MA copolymers incorporated silicone rubber/SEBS blends: improvement of mechanical and thermal properties
Authors: Alikhani Ehsan , Mohammadi Mohsen 
Published: December 2023

AbstractEnhancing the mechanical and thermal properties of Silicone rubber (SR)/SEBS blends using various compatibilizers opens the opportunity for such new blends to meet the market desire. For this purpose, blends with a 1:1 ratio of SR and SEBS are prepared with different amounts of EVA or SEBS-MA copolymers as compatibilizer. Mechanical properties of the blend are enhanced by adding EVA and SEBS-MA. Addition of 6 phr EVA profoundly improves the tensile strength from 7.70 to 10.06 MPa. Thermogravimetric analysis reveals that the presence of compatibilizer can improve the thermal stability of the blend, especially its initial degradation temperature (T5%). T5% of the blend increases from 376 to 390 °C when comprising 6 phr SEBS-MA. Morphology of the blends is investigated using SEM and AFM. Results of the relaxation modulus curves obtained by rubber process analyzer (RPA) demonstrate that the amount of relaxation in the uncured blends is higher than the cured ones. A comparison of the relaxation of the blends indicates that the relaxation modulus of the SEBS-MA compatibilized blends is enhanced more than other blends after curing. Further investigations indicate that the compatibilized blends exhibit higher tear energy and lower compression set.
Testing the power-law hypothesis of the interconflict interval
Authors: Okamoto Hiroshi , Yoshimoto Iku , Kato Sota , Ahsan Budrul , Shinohara Shuji 
Published: December 2023

AbstractWar is an extreme form of collective human behaviour characterized by coordinated violence. We show that this nature of war is substantiated in the temporal patterns of conflict occurrence that obey power law. The focal metric is the interconflict interval (ICI), the interval between the end of a conflict in a dyad (i.e. a pair of states) and the start of the subsequent conflict in the same dyad. Using elaborate statistical tests, we confirmed that ICI samples compiled from the history of interstate conflicts from 1816 to 2014 followed a power-law distribution. We then demonstrate that the power-law properties of ICIs can be explained by a hypothetical model assuming an information-theoretic formulation of the Clausewitz thesis on war: the use of force is a means of interstate communication. Our findings help us to understand the nature of wars between regular states, the significance of which has increased since the Russian invasion of Ukraine in 2022.
A new convolutional neural network based on combination of circlets and wavelets for macular OCT classification
Authors: Arian Roya , Vard Alireza , Kafieh Rahele , Plonka Gerlind , Rabbani Hossein 
Published: December 2023

AbstractArtificial intelligence (AI) algorithms, encompassing machine learning and deep learning, can assist ophthalmologists in early detection of various ocular abnormalities through the analysis of retinal optical coherence tomography (OCT) images. Despite considerable progress in these algorithms, several limitations persist in medical imaging fields, where a lack of data is a common issue. Accordingly, specific image processing techniques, such as time–frequency transforms, can be employed in conjunction with AI algorithms to enhance diagnostic accuracy. This research investigates the influence of non-data-adaptive time–frequency transforms, specifically X-lets, on the classification of OCT B-scans. For this purpose, each B-scan was transformed using every considered X-let individually, and all the sub-bands were utilized as the input for a designed 2D Convolutional Neural Network (CNN) to extract optimal features, which were subsequently fed to the classifiers. Evaluating per-class accuracy shows that the use of the 2D Discrete Wavelet Transform (2D-DWT) yields superior outcomes for normal cases, whereas the circlet transform outperforms other X-lets for abnormal cases characterized by circles in their retinal structure (due to the accumulation of fluid). As a result, we propose a novel transform named CircWave by concatenating all sub-bands from the 2D-DWT and the circlet transform. The objective is to enhance the per-class accuracy of both normal and abnormal cases simultaneously. Our findings show that classification results based on the CircWave transform outperform those derived from original images or any individual transform. Furthermore, Grad-CAM class activation visualization for B-scans reconstructed from CircWave sub-bands highlights a greater emphasis on circular formations in abnormal cases and straight lines in normal cases, in contrast to the focus on irrelevant regions in original B-scans. To assess the generalizability of our method, we applied it to another dataset obtained from a different imaging system. We achieved promising accuracies of 94.5% and 90% for the first and second datasets, respectively, which are comparable with results from previous studies. The proposed CNN based on CircWave sub-bands (i.e. CircWaveNet) not only produces superior outcomes but also offers more interpretable results with a heightened focus on features crucial for ophthalmologists.
Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being
Authors: Li Han , Zhang Renwen , Lee Yi-Chieh , Kraut Robert E. , Mohr David C. 
Published: December 2023

AbstractConversational artificial intelligence (AI), particularly AI-based conversational agents (CAs), is gaining traction in mental health care. Despite their growing usage, there is a scarcity of comprehensive evaluations of their impact on mental health and well-being. This systematic review and meta-analysis aims to fill this gap by synthesizing evidence on the effectiveness of AI-based CAs in improving mental health and factors influencing their effectiveness and user experience. Twelve databases were searched for experimental studies of AI-based CAs’ effects on mental illnesses and psychological well-being published before May 26, 2023. Out of 7834 records, 35 eligible studies were identified for systematic review, out of which 15 randomized controlled trials were included for meta-analysis. The meta-analysis revealed that AI-based CAs significantly reduce symptoms of depression (Hedge’s g 0.64 [95% CI 0.17–1.12]) and distress (Hedge’s g 0.7 [95% CI 0.18–1.22]). These effects were more pronounced in CAs that are multimodal, generative AI-based, integrated with mobile/instant messaging apps, and targeting clinical/subclinical and elderly populations. However, CA-based interventions showed no significant improvement in overall psychological well-being (Hedge’s g 0.32 [95% CI –0.13 to 0.78]). User experience with AI-based CAs was largely shaped by the quality of human-AI therapeutic relationships, content engagement, and effective communication. These findings underscore the potential of AI-based CAs in addressing mental health issues. Future research should investigate the underlying mechanisms of their effectiveness, assess long-term effects across various mental health outcomes, and evaluate the safe integration of large language models (LLMs) in mental health care.
Anomalous non-Hermitian skin effect: topological inequivalence of skin modes versus point gap
Authors: Guo Gang-Feng , Bao Xi-Xi , Zhu Han-Jie , Zhao Xiao-Ming , Zhuang Lin , Tan Lei , Liu Wu-Ming 
Published: December 2023

AbstractIt has long been believed that skin modes are equivalent to the nontrivial point gap. However, we find that this concomitance can be broken, in that skin modes can be absent or present when the point gap is nontrivial or trivial, respectively, named anomalous non-Hermitian skin effect. This anomalous phenomenon arises whenever unidirectional hopping amplitudes emerge among subsystems, where sub-chains have decoupling-like behaviors and contribute only to the energy levels without particle occupation. The occurrence of anomalous non-Hermitian skin effect is accompanied by changes in open boundary eigenvalues, whose structure exhibits multifold exceptional points and can not be recovered by continuum bands. Moreover, an experimental setup is proposed to simulate this effect. Our results reveal the topologically inequivalence of skin modes and point gap. This effect not only provides a deeper understanding of non-Bloch theory and critical phenomena, but may inspire applications, such as in sensor field.
Detection of PatIent-Level distances from single cell genomics and pathomics data with Optimal Transport (PILOT)
Authors: Joodaki Mehdi , Shaigan Mina , Parra Victor , Bülow Roman D , Kuppe Christoph , Hölscher David L , Cheng Mingbo , Nagai James S , Goedertier Michaël , Bouteldja Nassim , Tesar Vladimir , Barratt Jonathan , Roberts Ian SD , Coppo Rosanna , Kramann Rafael , Boor Peter , Costa Ivan G 
Published: December 2023

AbstractAlthough clinical applications represent the next challenge in single-cell genomics and digital pathology, we still lack computational methods to analyze single-cell or pathomics data to find sample-level trajectories or clusters associated with diseases. This remains challenging as single-cell/pathomics data are multi-scale, i.e., a sample is represented by clusters of cells/structures, and samples cannot be easily compared with each other. Here we propose PatIent Level analysis with Optimal Transport (PILOT). PILOT uses optimal transport to compute the Wasserstein distance between two individual single-cell samples. This allows us to perform unsupervised analysis at the sample level and uncover trajectories or cellular clusters associated with disease progression. We evaluate PILOT and competing approaches in single-cell genomics or pathomics studies involving various human diseases with up to 600 samples/patients and millions of cells or tissue structures. Our results demonstrate that PILOT detects disease-associated samples from large and complex single-cell or pathomics data. Moreover, PILOT provides a statistical approach to find changes in cell populations, gene expression, and tissue structures related to the trajectories or clusters supporting interpretation of predictions.
ASSIST‐U: A system for segmentation and image style transfer for ureteroscopy
Authors: Lu Daiwei , Wu Yifan , Acar Ayberk , Yao Xing , Wu Jie Ying , Kavoussi Nicholas , Oguz Ipek 
Published: December 2023

AbstractKidney stones require surgical removal when they grow too large to be broken up externally or to pass on their own. Upper tract urothelial carcinoma is also sometimes treated endoscopically in a similar procedure. These surgeries are difficult, particularly for trainees who often miss tumours, stones or stone fragments, requiring re‐operation. Furthermore, there are no patient‐specific simulators to facilitate training or standardized visualization tools for ureteroscopy despite its high prevalence. Here a system ASSIST‐U is proposed to create realistic ureteroscopy images and videos solely using preoperative computerized tomography (CT) images to address these unmet needs. A 3D UNet model is trained to automatically segment CT images and construct 3D surfaces. These surfaces are then skeletonized for rendering. Finally, a style transfer model is trained using contrastive unpaired translation (CUT) to synthesize realistic ureteroscopy images. Cross validation on the CT segmentation model achieved a Dice score of 0.853 0.084. CUT style transfer produced visually plausible images; the kernel inception distance to real ureteroscopy images was reduced from 0.198 (rendered) to 0.089 (synthesized). The entire pipeline from CT to synthesized ureteroscopy is also qualitatively demonstrated. The proposed ASSIST‐U system shows promise for aiding surgeons in the visualization of kidney ureteroscopy.
Enhanced demand side management for solar‐based isolated microgrid system: Load prioritisation and energy optimisation
Authors: Rajbhandari Yaju , Marahatta Anup , Shrestha Ashish , Gachhadar Anand , Thapa Anup , Gonzalez‐Longatt Francisco , Korba Petr 
Published: December 2023

AbstractA novel control mechanism is presented for rural microgrids, standing out in the current literature with its advanced approach to load prioritisation and energy allocation. The system's main goal is to maximise energy supply to essential loads while effectively managing available resources. Distinct from traditional methods, this mechanism dynamically classifies loads according to user‐defined priorities, adjustable based on the control system's computational power and complexity. A critical feature is the utilisation of the Particle Swarm Optimisation (PSO) algorithm to optimise demand side management (DSM). This innovative approach leverages day‐ahead load and generation forecasts to ensure optimal energy distribution across load levels, maintaining continuous power supply to high‐priority loads and reducing blackout risks due to generation and load fluctuations. Analyses under stochastic scenarios demonstrate the robustness of the control action, with percentile‐based day‐ahead forecasting allowing for adaptation to significant variations in renewable energy generation patterns. The implementation results are significant, maintaining 100% supply continuity to essential loads throughout the day, even with generation fluctuations up to ‐20%. This marks a considerable improvement in load satisfaction, increasing it from 83% to 96%. A significant advancement in microgrid control is contributed, providing an adaptive, user‐centric approach that enhances load management and energy distribution, and facilitates more resilient and efficient microgrid systems in the face of highly variable renewable energy sources (RESs).
Stellar mass-metallicity relation throughout the large-scale structure of the Universe: CAVITY mother sample
Authors: Domínguez-Gómez Jesús , Pérez Isabel , Ruiz-Lara Tomás , Peletier Reynier F. , Sánchez-Blázquez Patricia , Lisenfeld Ute , Bidaran Bahar , Falcón-Barroso Jesús , Alcázar-Laynez Manuel , Argudo-Fernández María , Blázquez-Calero Guillermo , Courtois Hélène , Duarte Puertas Salvador , Espada Daniel , Florido Estrella , García-Benito Rubén , Jiménez Andoni , Kreckel Kathryn , Relaño Mónica , Sánchez-Menguiano Laura , van der Hulst Thijs , van de Weygaert Rien , Verley Simon , Zurita Almudena 
Published: December 2023

Context. Void galaxies are essential for understanding the physical processes that drive galaxy evolution because they are less affected by external factors than galaxies in denser environments, that is, in filaments, walls, and clusters. The stellar metallicity of a galaxy traces the accumulated fossil record of the star formation through the entire life of the galaxy. A comparison of the stellar metallicity of galaxies in various environments, including voids, filaments, walls, and clusters can provide valuable insights into how the large-scale environment affects the chemical evolution of the galaxy.
Aims. We present the first comparison of the relation of the total stellar mass versus central stellar metallicity between galaxies in voids, filaments, walls, and clusters with different star formation history (SFH) types, morphologies, and colours for stellar masses between 108.0 to 1011.5 solar masses and redshift 0.01 < z < 0.05. We aim to better understand how the large-scale structure affects galaxy evolution by studying the stellar mass-metallicity relation of thousands of galaxies, which allows us to make a statistically sound comparison between galaxies in voids, filaments, walls, and clusters.
Methods. We applied non-parametric full spectral fitting techniques (pPXF and STECKMAP) to 10 807 spectra from the SDSS-DR7 (987 in voids, 6463 in filaments and walls, and 3357 in clusters) and derived their central mass-weighted average stellar metallicity ([M/H]M).
Results. We find that galaxies in voids have slightly lower stellar metallicities on average than galaxies in filaments and walls (by ∼0.1 dex), and they are much lower than those of galaxies in clusters (by ∼0.4 dex). These differences are more significant for low-mass (∼109.25 M⊙) than for high-mass galaxies, for long-timescale SFH (extended along time) galaxies than for short-timescale SFHs (concentrated at early times) galaxies, for spiral than for elliptical galaxies, and for blue than for red galaxies.
Modeling the propagation of coronal mass ejections with COCONUT: Implementation of the regularized Biot-Savart law flux rope model
Authors: Guo J. H. , Linan L. , Poedts S. , Guo Y. , Lani A. , Schmieder B. , Brchnelova M. , Perri B. , Baratashvili T. , Ni Y. W. , Chen P. F. 
Published: December 2023

Context. Coronal mass ejections (CMEs) are rapid eruptions of magnetized plasma that occur on the Sun. They are known to be the main drivers of adverse space weather. The accurate tracking of their evolution in the heliosphere in numerical models is of the utmost importance for space weather forecasting.
Aims. The main objective of this paper is to implement the regularized Biot-Savart law (RBSL) method in a new global corona model, called COCONUT. This approach has the capability to construct the magnetic flux rope with an axis of arbitrary shape.
Methods. We present the implementation process of the RBSL flux rope model in COCONUT, which is superposed onto a realistic solar wind reconstructed from the observed magnetogram around the minimum of solar activity. Based on this, we simulate the propagation of an S-shaped flux rope from the solar surface to a distance of 25 R⊙.
Results. Our simulation successfully reproduces the birth process of a CME originating from a sigmoid in a self-consistent way. The model effectively captures various physical processes and retrieves the prominent features of the CMEs in observations. In addition, the simulation results indicate that the magnetic topology of the CME flux rope at around 20 R⊙ deviates from a coherent structure and manifests as a mix of open and closed field lines with diverse footpoints.
Conclusions. This work demonstrates the potential of the RBSL flux rope model in reproducing CME events that are more consistent with observations. Moreover, our findings strongly suggest that magnetic reconnection during the CME propagation plays a critical role in destroying the coherent characteristics of a CME flux rope.