bluuebunny/crossref_metadata_2025_split huggingface dataset:
A combination of lymphatic drug delivery of anti‐CTLA‐4 antibody and local radiotherapy for solid‐tumor treatment
Authors: Takagi Koki , Sukhbaatar Ariunbuyan , Inaba Yohei , Mori Shiro , Kodama Tetsuya 
Published: October 2024

AbstractThe combination of radiotherapy and immunotherapy is a promising approach that has been shown in clinical trials to improve significantly survival and response rates compared with monotherapy against solid tumor. Since anti‐CTLA‐4 antibodies block immunosuppressive signals mainly in the lymph nodes (LNs), efficient drug delivery to the lymphatic system is desirable. However, the immune checkpoint inhibitors, especially anti‐CTLA‐4 are currently administered intravenously (i.v.), resulting in limited efficacy in controlling solid tumor and inhibiting metastases, and the method of administration has not been optimized. Here, we show that a combination of local radiotherapy and administration of anti‐CTLA‐4 antibodies using a lymphatic drug delivery system (LDDS) suppresses solid tumor and metastases. We compared the efficacy of LDDS‐based immunotherapy or radioimmunotherapy with i.v. administration in a solid‐tumor model created by subcutaneous inoculation into LN‐swollen mice with osteosarcoma cells. Tumor‐bearing mice were divided into various groups (no treatment, immunotherapy [i.v. or LDDS], radiotherapy, and radioimmunotherapy [i.v. or LDDS]) and were observed for 28 days. Immunotherapy was administered with a cumulative dose of 10 mg/kg of anti‐CTLA‐4 monoclonal antibody, and radiotherapy was administered with a cumulative 8 Gy of fractionated X‐ray irradiation. For immunotherapy alone, LDDS provided slight tumor growth inhibition but did not inhibit distant metastasis. For radioimmunotherapy, however, tumor growth was delayed and distant metastasis was suppressed compared with radiotherapy alone. In particular, the LDDS group achieved a high tumor‐suppressive effect with T cell‐mediated immune activity, indicating the efficacy of LDDS in radioimmunotherapy.
Diffusion‐based Human Motion Style Transfer with Semantic Guidance
Authors: Hu Lei , Zhang Zihao , Ye Yongjing , Xu Yiwen , Xia Shihong 
Published: October 2024

Abstract3D Human motion style transfer is a fundamental problem in computer graphic and animation processing. Existing AdaIN‐based methods necessitate datasets with balanced style distribution and content/style labels to train the clustered latent space. However, we may encounter a single unseen style example in practical scenarios, but not in sufficient quantity to constitute a style cluster for AdaIN‐based methods. Therefore, in this paper, we propose a novel two‐stage framework for few‐shot style transfer learning based on the diffusion model. Specifically, in the first stage, we pre‐train a diffusion‐based text‐to‐motion model as a generative prior so that it can cope with various content motion inputs. In the second stage, based on the single style example, we fine‐tune the pre‐trained diffusion model in a few‐shot manner to make it capable of style transfer. The key idea is regarding the reverse process of diffusion as a motion‐style translation process since the motion styles can be viewed as special motion variations. During the fine‐tuning for style transfer, a simple yet effective semantic‐guided style transfer loss coordinated with style example reconstruction loss is introduced to supervise the style transfer in CLIP semantic space. The qualitative and quantitative evaluations demonstrate that our method can achieve state‐of‐the‐art performance and has practical applications. The source code is available at https://github.com/hlcdyy/diffusion-based-motion-style-transfer.
VMP: Versatile Motion Priors for Robustly Tracking Motion on Physical Characters
Authors: Serifi Agon , Grandia Ruben , Knoop Espen , Gross Markus , Bächer Moritz 
Published: October 2024

AbstractRecent progress in physics‐based character control has made it possible to learn policies from unstructured motion data. However, it remains challenging to train a single control policy that works with diverse and unseen motions, and can be deployed to real‐world physical robots. In this paper, we propose a two‐stage technique that enables the control of a character with a full‐body kinematic motion reference, with a focus on imitation accuracy. In a first stage, we extract a latent space encoding by training a variational autoencoder, taking short windows of motion from unstructured data as input. We then use the embedding from the time‐varying latent code to train a conditional policy in a second stage, providing a mapping from kinematic input to dynamics‐aware output. By keeping the two stages separate, we benefit from self‐supervised methods to get better latent codes and explicit imitation rewards to avoid mode collapse. We demonstrate the efficiency and robustness of our method in simulation, with unseen user‐specified motions, and on a bipedal robot, where we bring dynamic motions to the real world.
Garment Animation NeRF with Color Editing
Authors: Wang Renke , Zhang Meng , Li Jun , Yang Jian 
Published: October 2024

AbstractGenerating high‐fidelity garment animations through traditional workflows, from modeling to rendering, is both tedious and expensive. These workflows often require repetitive steps in response to updates in character motion, rendering viewpoint changes, or appearance edits. Although recent neural rendering offers an efficient solution for computationally intensive processes, it struggles with rendering complex garment animations containing fine wrinkle details and realistic garment‐and‐body occlusions, while maintaining structural consistency across frames and dense view rendering. In this paper, we propose a novel approach to directly synthesize garment animations from body motion sequences without the need for an explicit garment proxy. Our approach infers garment dynamic features from body motion, providing a preliminary overview of garment structure. Simultaneously, we capture detailed features from synthesized reference images of the garment's front and back, generated by a pre‐trained image model. These features are then used to construct a neural radiance field that renders the garment animation video. Additionally, our technique enables garment recoloring by decomposing its visual elements. We demonstrate the generalizability of our method across unseen body motions and camera views, ensuring detailed structural consistency. Furthermore, we showcase its applicability to color editing on both real and synthetic garment data. Compared to existing neural rendering techniques, our method exhibits qualitative and quantitative improvements in garment dynamics and wrinkle detail modeling. Code is available at https://github.com/wrk226/GarmentAnimationNeRF.
Multiphase Viscoelastic Non‐Newtonian Fluid Simulation
Authors: Zhang Y. , Long S. , Xu Y. , Wang X. , Yao C. , Kosinka J. , Frey S. , Telea A. , Ban X. 
Published: October 2024

AbstractWe propose an SPH‐based method for simulating viscoelastic non‐Newtonian fluids within a multiphase framework. For this, we use mixture models to handle component transport and conformation tensor methods to handle the fluid's viscoelastic stresses. In addition, we consider a bonding effects network to handle the impact of microscopic chemical bonds on phase transport. Our method supports the simulation of both steady‐state viscoelastic fluids and discontinuous shear behavior. Compared to previous work on single‐phase viscous non‐Newtonian fluids, our method can capture more complex behavior, including material mixing processes that generate non‐Newtonian fluids. We adopt a uniform set of variables to describe shear thinning, shear thickening, and ordinary Newtonian fluids while automatically calculating local rheology in inhomogeneous solutions. In addition, our method can simulate large viscosity ranges under explicit integration schemes, which typically requires implicit viscosity solvers under earlier single‐phase frameworks.
Multi‐colour recipe prediction through invertible neural network and clustering algorithm
Authors: Shah Syed Salman Ali , Junaid Ahmad , Husnain Ghassan , Qadir Mansoor , Ghadi Yazeed Yasin 
Published: October 2024

AbstractComputer‐assisted colour prediction has become increasingly significant for various consumer items in the industrial sector. Many professional colourists find it challenging to develop a suitable colour recipe. The most difficult aspect is predicting which dye mix will result in the required shade on a given fabric. This study introduces an advanced alternative to the traditional colour‐making method using an invertible neural network (INN) model. The INN model effectively addresses real‐world inverse problems due to its bi‐directional nature. In the forward phase, the model retrieves information about the colour recipe; in the backward phase, this information is combined with latent space data to predict the recipe. Furthermore, unsupervised data generated by the INN model is fed into clustering algorithms, such as K‐means and the Gaussian mixture model (GMM), to obtain multiple recipes. The forward procedure was reintroduced with a predicted recipe to assess the efficacy of the proposed model. An analysis was then conducted on the colour differences between the anticipated and actual recipes. The colour differences, rounded to perceptually significant precision, from 30,000 samples with 50 centre points, are as follows: 1.4, 2.2, 2.5, 3.7, 1.2, and 2.1. These results indicate that the INN model and the GMM clustering approach together provide a highly accurate and efficient solution to automating the colour‐matching process, offering a more precise and practical solution for the colour‐manufacturing industry.
Integration of a facilitated access pathway for contraception into alcohol and other drug treatment services: A cohort study comparing metropolitan and regional settings
Authors: McNamara Kelly A. , Murnion Bridin , Lintzeris Nicholas , Chase Vicki , Black Emma , Malcolm Annie , Harvey Dodds Lucy , Nassar Natasha , Black Kirsten I. 
Published: October 2024

AbstractIntroductionWomen who attend alcohol and other drug (AOD) services experience higher rates of unintended pregnancy, and access less contraception, than the general population. This study aims to observe contraceptive initiation and use after contraception services were offered at metropolitan and regional AOD services.MethodsClinical staff were provided contraception education. One hundred women aged 16–49 were recruited from two services between 2017 and 2021. Women completed a questionnaire on their obstetrics and gynaecological history, pregnancy plans and contraception use. Women were provided education on contraception options and offered referral to a contraception pathway. The primary outcome was initiation of highly reliable contraception; secondary outcomes were the types of contraception initiated, and contraception use and pregnancy at 12 months. We compared the initiation of contraception across the two study sites.ResultsAt baseline, 91% of women were not planning a pregnancy within 12 months, with 21% of these using highly reliable contraception. Of all women not planning a pregnancy, 28% initiated highly reliable contraception via the pathway (2% metropolitan, 51% regional, p < 0.001), with intrauterine devices being the most frequent method initiated (15%). At 12 months, 44% were using highly reliable contraception and 15% had recorded pregnancies.Discussion and ConclusionsContraception pathways for women in AOD treatment can improve initiation of highly reliable methods of contraception, although pregnancy rates were still high and there were large differences between the study sites. Care navigation and clinical champions are some potential facilitators to contraception access, and understanding additional barriers to access may be useful.
Leucoanthocyanidin Reductase 3 (PaLAR3) Locus in Norway Spruce (Picea abies) and Its Link to Resistance Against Heterobasidion parviporum
Authors: Durodola Blessing , Hanström Neea , Blumenstein Kathrin , Haapanen Matti , Hantula Jarkko , Kashif Muhammad , Piri Tuula , Terhonen Eeva 
Published: October 2024

ABSTRACTHeterobasidion parviporum is a fungal pathogen that is drastically damaging Norway spruce (Picea abies) in Europe. The infections will result in root and stem rot, causing significant economic losses for forest owners. Previous studies have shown that the PaLAR3 gene, which encodes the leucoanthocyanidin reductase enzyme, can increase resistance to H. parviporum in Norway spruce. The presence of the B allele at the PaLAR3 locus has been associated with higher (+)‐catechin concentrations and increased enzyme production in inoculation experiments, resulting in inhibited pathogen growth. The control of H. parviporum involves a multifaceted approach, including silvicultural and sustainable forestry practices, genetic resistance and chemical/biological control. In this study, we determined the PaLAR3 genotypes in a representative sample of Norway spruce breeding materials from southern Finland and examined their effect on necrosis caused by H. parviporum in spruce stems. The results showed that the homozygous PaLAR3BB genotype was present in only 9% of the trees. However, the necrotic area interacted with homozygous PaLAR3BB under low‐water treatment. These findings support the idea that the PaLAR3 locus may be a valuable marker for identifying P. abies resistance to different strains of Heterobasidion parviporum.
Lesional Psoriasis is Associated With Alterations in the Stratum Corneum Ceramide Profile and Concomitant Decreases in Barrier Function
Authors: Rousel Jannik , Mergen Catherine , Bergmans Menthe E. , Klarenbeek Naomi B. , der Kolk Tessa Niemeyer‐van , van Doorn Martijn B. A. , Bouwstra Joke A. , Rissmann Robert ,   the Next‐Generation ImmunoDermatology Consortium (NGID)
Published: October 2024

ABSTRACTPsoriasis is an inflammatory skin disease associated with an impaired skin barrier. The skin barrier function is dependent on the extracellular lipid matrix which surrounds the corneocytes in the stratum corneum. Ceramides comprise essential components of this matrix. Alterations in the stratum corneum ceramide profile have been directly linked to barrier dysfunction and might be an underlying factor of the barrier impairment in psoriasis. In this study, we investigated the ceramide profile and barrier function in psoriasis. Lesional and non‐lesional skin of 26 patients and 10 healthy controls were analysed using in‐depth ceramide lipidomics by liquid chromatography‐mass spectrometry. Barrier function was assessed by measuring transepidermal water loss. Lesional skin showed a significant decrease in the abundance of total ceramides with significant alterations in the ceramide subclass composition compared to control and non‐lesional skin. Additionally, the percentage of monounsaturated ceramides was significantly increased, and the average ceramide chain length significantly decreased in lesional skin. Altogether, this resulted in a markedly different profile compared to controls for lesional skin, but not for non‐lesional skin. Importantly, the reduced barrier function in lesional psoriasis correlated to alterations in the ceramide profile, highlighting their interdependence. By assessing the parameters 2 weeks apart, we are able to highlight the reproducibility of these findings, which further affirms this connection. To conclude, we show that changes in the ceramide profile and barrier impairment are observed in, and limited to, lesional psoriatic skin. Their direct correlation provides a further mechanistic basis for the concomitantly observed impairment of barrier dysfunction.
Meeting Report From “Correlates of Protection for Next Generation Influenza Vaccines: Lessons Learned From the COVID‐19 Pandemic”
Authors: Krammer Florian , Katz Jacqueline M. , Engelhardt Othmar G. , Post Diane J. , Roberts Paul C. , Sullivan Sheena G. , Tompkins S. Mark , Chiu Christopher , Schultz‐Cherry Stacey , Cox Rebecca Jane 
Published: October 2024

ABSTRACTBackgroundThis report summarizes the discussions and conclusions from the “Correlates of Protection for Next Generation Influenza Vaccines: Lessons Learned from the COVID‐19 Pandemic” meeting, which took place in Seattle, USA, from March 1, 2023, to March 3, 2023.ConclusionsDiscussions around influenza virus correlates of protection and their use continued from where the discussion had been left off in 2019. While there was not much progress in the influenza field itself, many lessons learned during the coronavirus disease 2019 (COVID‐19) pandemic, especially the importance of mucosal immunity, were discussed and can directly be applied to influenza correlates of protection.
Role of ZnO dopant in enhancing piezoelectric characteristics in KNN‐based piezoelectric ceramics
Authors: Liu Yilong , Wang Chuilei , Zhu Yuanna , Hou Limin , Wei Tao , Wu Tongzhen , Huan Yu 
Published: October 2024

AbstractConsidering that lead‐based piezoelectric ceramics are not conducive to sustainable development, the research and preparation of environmentally friendly lead‐free piezoelectric ceramics has become a new trend. Among them, potassium‐sodium niobate based (KNN‐based) piezoelectric ceramics are considered as the most potential candidates because of their good piezoelectric properties. However, the strong sensitivity to temperature has hindered the further application of KNN‐based ceramics. In this work, the ZnO dopant was introduced in 0.96K0.48Na0.52Nb0.96Sb0.04O3–0.04Bi0.5Na0.5HfO3 ceramics to improve their piezoelectric characteristics. On the one hand, Zn2+ could occupy B‐site and thus enhance the lattice distortion of BO6 octahedra, resulting the enhanced piezoelectric properties including kp = 46%, d33 = 344 pC/N and TC = 282°C in the optimal component with x = 0.01. On the other hand, the defect dipole formed by the acceptor dopant Zn2+ pinned the motion of domain wall, and thus improved the temperature stability over a wide temperature range of 20°C to 180°C, where the descent in unipolar strain decreased from 35% (x = 0) to 23% (x = 0.01). This work provides a point of view about how ZnO dopants make an influence on the KNN‐based ceramics.
The Role of Language in Remote Healthcare Triage: A Meta‐Aggregative Review
Authors: Spek Michelle , van Braak Marije , Erkelens Daphne C. A. , Rutten Frans H. , Venekamp Roderick P. , Zwart Dorien L. , de Groot Esther 
Published: October 2024

ABSTRACTAim(s)To provide an overview of evidence on the role of language in remote healthcare services prioritisation, from now on termed triage. This study synthesises literature, to better understand how language affects triage interactions, aiming to improve these processes.DesignWe conducted a meta‐aggregative review.MethodsA systematic search in Scopus from inception to September 2023 identified 437 studies on language in remote healthcare triage, of which 23 were included. Information was selected using both inductive and deductive coding, focusing on six linguistic features of interaction that have been described in the literature on studies using conversation analysis: turn‐taking organisation, overall structure, sequence organisation, turn design, lexical choice, and epistemological and other forms of asymmetry. The process followed the RAMESES Publication Standards for Meta‐narrative Reviews.ResultsTwo main findings emerged. First, all six linguistic features are present in triage conversations, indicating that language involves more than just what is said. It also matters, for example, how and when a question is asked. Second, computerised decision support systems (CDSS) significantly affect conversation flow and dynamics.ConclusionLanguage in triage involves more than literal speech and is heavily influenced by CDSS.Implications for the Profession and/or Patient CareOur study suggests that quality assessments of triage conversations should consider not only what is said but cover all relevant aspects of language. The influence of computerised decision support systems (CDSS) on linguistic features highlights the need for systems to be adaptable, to improve conversation quality and better addressing caller needs rather than focusing on one‐size‐fits‐all questions.ImpactThis review highlights the complex role of language in triage conversations and its impact on interaction. It calls for a broader view of language in quality assessments, recognising that both call‐takers and callers contribute to call quality. Insights from this review can help developers enhance question types, sequence, and delivery methods of computerised decision support systems. Finally, education for call‐takers in healthcare sectors may be improved based on our findings.Patient or Public ContributionNo patient or public contribution.
Using knowledge building and flipped learning to enhance students' learning performance in a hands‐on STEM activity
Authors: Chen Jyun‐Chen , Liu Chia‐Yu 
Published: October 2024

AbstractBackgroundSociety requires individuals to have the ability to synthesise knowledge from diverse sources, typically acquired through science, technology, engineering, and mathematics (STEM) education.Objectives and MethodsWe utilised a moderately rigorous design to investigate the effects of combining a hands‐on STEM activity with active learning approaches of knowledge building (KB) and flipped learning on the learning performance of 188 senior students. Students needed to work in groups to construct a remote‐controlled car using a remote‐control module and electrical circuit, followed by the task of putting balls into a basket.ResultsAfter the activity, all participants' STEM knowledge, learning motivation, and creativity improved. For STEM knowledge, students who received the integrated KB and flipped learning approach (E2 group) outscored those who received only KB (E1 group), whereas the E1 group outperformed those who received lectures (control group). For learning motivation, the E1 group outperformed the control group. The E2 group outperformed the control group on the post‐test only when the students' learning motivation pre‐test scores were lower, suggesting the effectiveness of both active learning approaches. For creativity, both E1 and E2 groups performed better than the control group.ConclusionsThe potential benefits of combining active learning approaches with hands‐on STEM activities were revealed in terms of STEM knowledge, learning motivation, and creativity. Surprisingly, the combination method was the most effective in energising unmotivated students for STEM education.
Simple‐Challenging‐Difficult (SCD) Difficulty Classification for Vertical Bone Augmentation
Authors: Hsu Cheng‐Hsiang , Chen Zhaozhao , Urban Istvan A. , Wang Hom‐Lay 
Published: October 2024

ABSTRACTObjectiveTo propose a new difficulty classification for vertical bone augmentation (VBA) based on different defect morphologies.OverviewVBA procedures for dental implant placement present significant biological and technical challenges. Among the various techniques, guided bone regeneration (GBR) provides an optimal balance between the anticipated bone gain and the likelihood of postoperative complications. Understanding the specific configuration of defects and adjacent bone peaks is essential for tailoring treatment strategies and improving outcomes. The proposed Simple‐Challenging‐Difficult (SCD) difficulty classification was based on defect morphology (V‐shaped, U‐shaped, VV‐shaped), including defect size (Height: < 5 mm, 5–8 mm, and > 8 mm), proximity of neighboring bony walls (Width: < 10 mm, 10–20 mm, and > 20 mm), as well as predictability of treatment outcomes.ConclusionsThe proposed difficulty classification for VBA serves as a guide for selecting the most appropriate GBR treatment modality and sequence for safe and predictable management of VBA in implant therapy. In addition, when determining the preferred treatment, it is again essential to consider site‐specific and patient‐related factors alongside the clinician’s surgical experience and skill.Clinical SignificanceIdentifying defect patterns and bone peak structures is crucial, and the proposed classification assists in decision‐making in VBA treatment.