bluuebunny/crossref_metadata_2025_split huggingface dataset:
Labour analgesia by single shot spinal for any parturient?—A retrospective one‐year single centre audit
Authors: Kähkönen Kati , Väänänen Antti 
Published: May 2023

AbstractBackgroundSingle shot spinal (SSS) provides effective analgesia for multiparous parturients during advanced labour. Its utility in early labour or primiparous parturients may be limited by the insufficient duration of action. Regardless, SSS may offer a reasonable labour analgesia option in certain clinical scenarios. In this retrospective study, we analyse the failure rate of SSS analgesia by assessing pain after the SSS and by determining the need for additional analgesic interventions in primiparous or early‐stage multiparous parturients compared to multiparous parturients in advanced labour (cervix ≥6 cm).MethodsFollowing institutional ethical board approval, the patient files of all parturients receiving SSS analgesia during a 12‐month period in a single centre were analysed for any recorded notes regarding recurrent pain or subsequent analgesia interventions (a new SSS, epidural, pudendal or paracervical bloc) as a marker for insufficient analgesia.ResultsA total of 88 primiparous and 447 multiparous parturients (cervix <6 cm: N = 131; cervix ≥6 cm: N = 316) received SSS analgesia. The odds ratio for the insufficient duration of analgesia was 1.94 (1.08–3.48) in primiparous and 2.08 (1.25–3.46) in early‐stage multiparous parturients compared to advanced multiparous labour (p < .01). Primiparous and early‐stage multiparous parturients were also 2.20 (1.15–4.20) and 2.61 (1.50–4.55) times more likely, respectively, to receive new peripheral and/or neuraxial analgesic interventions during delivery (p < .01).ConclusionsSSS appears to provide adequate labour analgesia for the majority of parturients in whom it is used, including nulliparous and early‐stage multiparous parturients. It remains a reasonable option in certain clinical scenarios, including resource‐limited settings where epidural analgesia is unavailable.
Four species in one: taxonomic revision of the Eirmocides helenita (Semper, 1879) complex (Lepidoptera: Lycaenidae) from Australia and New Guinea
Authors: Braby Michael F. , Müller Chris , Espeland Marianne 
Published: May 2023

AbstractTaxonomic investigations of the Eirmocides helenita (Semper, 1879) complex from north‐eastern Australia and mainland New Guinea based on adult morphology (male genitalia and wing colour pattern elements), together with a phylogenetic hypothesis of the genus (18 or 69% of the recognised species) based on molecular data (1 mitochondrial and 12 nuclear genes), and examination of type material, indicate that there are five species within this monophyletic lineage, here referred to as the E. helenita species‐group. Four of the species, previously classified under the name Eirmocides helenita (Semper, 1879) sensu lato and characterised by iridescent turquoise dorsal colouration in the male, are predominantly allopatric, as follows: Eirmocides callainus Braby & Müller, sp. nov., is endemic to the Wet Tropics biome of north‐eastern Queensland; Eirmocides helenita (Semper, 1879) sensu stricto is restricted to Cape York Peninsula of northern Queensland; Eirmocides rouku Braby & Müller, sp. nov., is endemic to the Western Province of southern Papua New Guinea; and Eirmocides dimorphus (Röber, 1886), stat. rev., occurs more widely throughout mainland New Guinea and its adjacent islands. The fifth member of the group, Eirmocides cupreus (Röber, 1886), is sympatric with E. dimorphus on mainland New Guinea. The taxonomic revision brings to 26 the total number of species recognised in Eirmocides and within the tribe Candalidini to 40 species. Lectotypes are designated for Plebeius dimorphus Röber, 1886, Plebeius dimorphus var. cupreus Röber, 1886, and Holochila subargentea Grose‐Smith & Kirby, 1896.
Feasible laparoscopic surgery for selected cases of primary adrenal neuroblastoma: Results from a comparison with open surgery at a single institution
Authors: Sugita Koshiro , Kawano Takafumi , Murakami Masakazu , Nanako Nishida , Kedoin Chihiro , Nagano Ayaka , Yano Keisuke , Onishi Shun , Harumatsu Toshio , Yamada Koji , Yamada Waka , Matsukubo Makoto , Muto Mitsuru , Kaji Tatsuru , Ieiri Satoshi 
Published: May 2023

AbstractIntroductionSurgical management of neuroblastoma (NB) has been performed by open procedures for decades. However, advances in surgical devices and technology have made minimally invasive surgery safe and reproducible. In this study, we compared open and laparoscopic surgery regarding biopsy success and curative resection to determine the safety and feasibility of laparoscopic surgery for pediatric patients with adrenal NB.MethodsWe reviewed the clinical data of 22 NB patients who underwent surgery from 2006 to 2021 in our institution. All patients with adrenal NB were diagnosed histologically, and we retrospectively analyzed the data.ResultsThe male/female ratio was 16/6. The median age was 2.5 (interquartile range: 2–4) years old, and the laterality was on the right in 13 and on the left in 9. A total of 20 patients underwent a tumor biopsy: 14 via laparotomy, five laparoscopically, and one retroperitoneally. Four patients underwent laparoscopic resection and 11 patients underwent open resection after chemotherapy. Two patients with stage LI underwent primary tumor resection laparoscopically. For curative resection in image‐defined risk factor (IDRF)‐negative patients, laparoscopic surgery resulted in shorter operation time, with less bleeding and an earlier oral intake. The three IDRF‐single‐positive patients on the liver (laparoscopic surgery: one patient) had a shorter operation time and less bleeding than the IDRF‐multiple positive patients.ConclusionLaparoscopic surgery was performed in a limited number of adrenal NB cases. A laparoscopic biopsy for adrenal NB seems to be safe and feasible to perform. Laparoscopic surgery, in carefully selected cases, permits safe and efficient resection of adrenal NB in pediatric patients.
Chemometrics as a valuable tool for evaluating interactions between antiretroviral drugs and food
Authors: Wiesner Agnieszka , Zagrodzki Paweł , Jamrozik Marek , Korchowiec Jacek , Marcinkowska Monika , Paśko Paweł 
Published: May 2023

AimsClinically significant interactions with food occur for more than half of antiretroviral drugs. Different physiochemical properties deriving from the chemical structures of antiretroviral drugs may contribute to the variable food effect. Chemometric methods allow analysing a large number of interrelated variables concomitantly and visualizing correlations between them. We used a chemometric approach to determine the types of correlations among different features of antiretroviral drugs and food that may influence interactions.MethodsThirty‐three antiretroviral drugs were analysed: ten nucleoside reverse transcriptase inhibitors, six non‐nucleoside reverse transcriptase inhibitors, five integrase strand transfer inhibitors, ten protease inhibitors, one fusion inhibitor and one HIV maturation inhibitor. Input data for the analysis were collected from already published clinical studies, chemical records and calculations. We constructed a hierarchical partial least squares (PLS) model with three response parameters: postprandial change of time to reach maximum drug concentration (ΔTmax), albumin binding (%) and logarithm of partition coefficient (logP). Predictor parameters were the first two principal components of principal component analysis (PCA) models for six groups of molecular descriptors.ResultsPCA models explained 64.4% to 83.4% of the variance of the original parameters (average: 76.9%), whereas the PLS model had four significant components and explained 86.2% and 71.4% of the variance in the sets of predictor and response parameters, respectively. We observed 58 significant correlations between ΔTmax, albumin binding (%), logP and constitutional, topological, hydrogen bonding and charge‐based molecular descriptors.ConclusionsChemometrics is a useful and valuable tool for analysing interactions between antiretroviral drugs and food.
The effects of instructor participation in asynchronous online discussions on student performance: A systematic review
Authors: Xie Jiarui , Correia Ana‐Paula 
Published: May 2023

AbstractAsynchronous online discussion is a learning activity commonly used in online teaching. The way instructors participate in asynchronous online discussions significantly impacts students' learning outcomes. This systematic review aims to determine the effects of instructor participation in asynchronous online discussions on student performance by analysing 25 relevant studies in the past twelve years (2011–22). The findings show that the research was focused on the presence, frequency and type of instructor participation. The effects of instructor participation on student performance were mixed and concentrated in five main aspects: the quantity of student participation, the quality of student participation, student achievements, student emotions and student learning time. Not only the teaching experience of instructors but also course content, learning objectives, class sizes and learner characteristics influenced the effects. Based on the findings, several recommendations were made to help instructors effectively participate in asynchronous online discussions, thereby contributing to improving the quality of online education.
Practitioner notesWhat is already known about this topic

Asynchronous online discussion is a learning activity commonly used in online teaching.
The way instructors participate in asynchronous online discussions significantly impacts students' learning outcomes.
What this paper adds

Previous research on instructor participation in asynchronous online discussions and student performance primarily focuses on the presence, frequency and type of instructor participation.
The impact of instructor participation on student performance is mixed and concentrated in the following main areas:

Quantity of student participation
Quality of student participation
Student achievements
Student emotions
Student learning time

The effects of instructor participation are influenced not only by the teaching experience of instructors but also by:

Course content
Learning objectives
Class sizes
Learner characteristics

Implications for practice and/or policy

Instructors should participate in asynchronous online discussions based on the class sizes, more in small classes (within 15 students) and less in large classes (more than 30 students). If it is possible, divide the large classes into small discussion groups.
Instructors should initiate discussions with heuristic and interesting open‐ended questions, gradually release control and give the central position to students and intervene only when necessary (eg, keep discussions on track, provide correct information, extend discussions, mediate conflicts, etc).
Instructors should apply appropriate facilitation strategies (eg, establish detailed discussion rubrics, grade student posts and provide regular individual feedback).
Instructors should use more instructional comments and supplement them with sincere rather than perfunctory social comments.
Cerebellar structural, astrocytic, and neuronal abnormalities in the SMNΔ7 mouse model of spinal muscular atrophy
Authors: Cottam Nicholas C. , Bamfo Tiffany , Harrington Melissa A. , Charvet Christine J. , Hekmatyar Khan , Tulin Nikita , Sun Jianli 
Published: May 2023

AbstractSpinalmuscular atrophy (SMA) is a neuromuscular disease that affects as many as 1 in 6000 individuals at birth, making it the leading genetic cause of infant mortality. A growing number of studies indicate that SMA is a multi‐system disease. The cerebellum has received little attention even though it plays an important role in motor function and widespread pathology has been reported in the cerebella of SMA patients. In this study, we assessed SMA pathology in the cerebellum using structural and diffusion magnetic resonance imaging, immunohistochemistry, and electrophysiology with the SMNΔ7 mouse model. We found a significant disproportionate loss in cerebellar volume, decrease in afferent cerebellar tracts, selective lobule‐specific degeneration of Purkinje cells, abnormal lobule foliation and astrocyte integrity, and a decrease in spontaneous firing of cerebellar output neurons in the SMA mice compared to controls. Our data suggest that defects in cerebellar structure and function due to decreased survival motor neuron (SMN) levels impair the functional cerebellar output affecting motor control, and that cerebellar pathology should be addressed to achieve comprehensive treatment and therapy for SMA patients.
Interactive Depixelization of Pixel Art through Spring Simulation
Authors: Matusovic Marko , Parakkat Amal Dev , Eisemann Elmar 
Published: May 2023

AbstractWe introduce an approach for converting pixel art into high‐quality vector images. While much progress has been made on automatic conversion, there is an inherent ambiguity in pixel art, which can lead to a mismatch with the artist's original intent. Further, there is room for incorporating aesthetic preferences during the conversion. In consequence, this work introduces an interactive framework to enable users to guide the conversion process towards high‐quality vector illustrations. A key idea of the method is to cast the conversion process into a spring‐system optimization that can be influenced by the user. Hereby, it is possible to resolve various ambiguities that cannot be handled by an automatic algorithm.
Simulating analogue film damage to analyse and improve artefact restoration on high‐resolution scans
Authors: Ivanova D. , Williamson J. , Henderson P. 
Published: May 2023

AbstractDigital scans of analogue photographic film typically contain artefacts such as dust and scratches. Automated removal of these is an important part of preservation and dissemination of photographs of historical and cultural importance. While state‐of‐the‐art deep learning models have shown impressive results in general image inpainting and denoising, film artefact removal is an understudied problem. It has particularly challenging requirements, due to the complex nature of analogue damage, the high resolution of film scans, and potential ambiguities in the restoration. There are no publicly available high‐quality datasets of real‐world analogue film damage for training and evaluation, making quantitative studies impossible. We address the lack of ground‐truth data for evaluation by collecting a dataset of 4K damaged analogue film scans paired with manually‐restored versions produced by a human expert, allowing quantitative evaluation of restoration performance. We have made the dataset available at https://doi.org/10.6084/m9.figshare.21803304. We construct a larger synthetic dataset of damaged images with paired clean versions using a statistical model of artefact shape and occurrence learnt from real, heavily‐damaged images. We carefully validate the realism of the simulated damage via a human perceptual study, showing that even expert users find our synthetic damage indistinguishable from real. In addition, we demonstrate that training with our synthetically damaged dataset leads to improved artefact segmentation performance when compared to previously proposed synthetic analogue damage overlays. The synthetically damaged dataset can be found at https://doi.org/10.6084/m9.figshare.21815844, and the annotated authentic artefacts along with the resulting statistical damage model at https://github.com/daniela997/FilmDamageSimulator. Finally, we use these datasets to train and analyse the performance of eight state‐of‐the‐art image restoration methods on high‐resolution scans. We compare both methods which directly perform the restoration task on scans with artefacts, and methods which require a damage mask to be provided for the inpainting of artefacts. We modify the methods to process the inputs in a patch‐wise fashion to operate on original high resolution film scans.
CubeGAN: Omnidirectional Image Synthesis Using Generative Adversarial Networks
Authors: May C. , Aliaga D. 
Published: May 2023

AbstractWe propose a framework to create projectively‐correct and seam‐free cube‐map images using generative adversarial learning. Deep generation of cube‐maps that contain the correct projection of the environment onto its faces is not straightforward as has been recognized in prior work. Our approach extends an existing framework, StyleGAN3, to produce cube‐maps instead of planar images. In addition to reshaping the output, we include a cube‐specific volumetric initialization component, a projective resampling component, and a modification of augmentation operations to the spherical domain. Our results demonstrate the network's generation capabilities trained on imagery from various 3D environments. Additionally, we show the power and quality of our GAN design in an inversion task, combined with navigation capabilities, to perform novel view synthesis.
Editing Compressed High‐resolution Voxel Scenes with Attributes
Authors: Molenaar M. , Eisemann E. 
Published: May 2023

AbstractSparse Voxel Directed Acyclic Graphs (SVDAGs) are an efficient solution for storing high‐resolution voxel geometry. Recently, algorithms for the interactive modification of SVDAGs have been proposed that maintain the compressed geometric representation. Nevertheless, voxel attributes, such as colours, require an uncompressed storage, which can result in high memory usage over the course of the application. The reason is the high cost of existing attribute‐compression schemes which remain unfit for interactive applications. In this paper, we introduce two attribute compression methods (lossless and lossy), which enable the interactive editing of compressed high‐resolution voxel scenes including attributes.
Variational Pose Prediction with Dynamic Sample Selection from Sparse Tracking Signals
Authors: Milef N. , Sueda S. , Kalantari N. Khademi 
Published: May 2023

AbstractWe propose a learning‐based approach for full‐body pose reconstruction from extremely sparse upper body tracking data, obtained from a virtual reality (VR) device. We leverage a conditional variational autoencoder with gated recurrent units to synthesize plausible and temporally coherent motions from 4‐point tracking (head, hands, and waist positions and orientations). To avoid synthesizing implausible poses, we propose a novel sample selection and interpolation strategy along with an anomaly detection algorithm. Specifically, we monitor the quality of our generated poses using the anomaly detection algorithm and smoothly transition to better samples when the quality falls below a statistically defined threshold. Moreover, we demonstrate that our sample selection and interpolation method can be used for other applications, such as target hitting and collision avoidance, where the generated motions should adhere to the constraints of the virtual environment. Our system is lightweight, operates in real‐time, and is able to produce temporally coherent and realistic motions.
State of the Art in Dense Monocular Non‐Rigid 3D Reconstruction
Authors: Tretschk Edith , Kairanda Navami , B R Mallikarjun , Dabral Rishabh , Kortylewski Adam , Egger Bernhard , Habermann Marc , Fua Pascal , Theobalt Christian , Golyanik Vladislav 
Published: May 2023

Abstract3D reconstruction of deformable (ornon‐rigid) scenes from a set of monocular 2D image observations is a long‐standing and actively researched area of computer vision and graphics. It is an ill‐posed inverse problem, since—without additional prior assumptions—it permits infinitely many solutions leading to accurate projection to the input 2D images. Non‐rigid reconstruction is a foundational building block for downstream applications like robotics, AR/VR, or visual content creation. The key advantage of using monocular cameras is their omnipresence and availability to the end users as well as their ease of use compared to more sophisticated camera set‐ups such as stereo or multi‐view systems. This survey focuses on state‐of‐the‐art methods for dense non‐rigid 3D reconstruction of various deformable objects and composite scenes from monocular videos or sets of monocular views. It reviews the fundamentals of 3D reconstruction and deformation modeling from 2D image observations. We then start from general methods—that handle arbitrary scenes and make only a few prior assumptions—and proceed towards techniques making stronger assumptions about the observed objects and types of deformations (e.g. human faces, bodies, hands, and animals). A significant part of this STAR is also devoted to classification and a high‐level comparison of the methods, as well as an overview of the datasets for training and evaluation of the discussed techniques. We conclude by discussing open challenges in the field and the social aspects associated with the usage of the reviewed methods.
A Comprehensive Review of Data‐Driven Co‐Speech Gesture Generation
Authors: Nyatsanga S. , Kucherenko T. , Ahuja C. , Henter G. E. , Neff M. 
Published: May 2023

AbstractGestures that accompany speech are an essential part of natural and efficient embodied human communication. The automatic generation of such co‐speech gestures is a long‐standing problem in computer animation and is considered an enabling technology for creating believable characters in film, games, and virtual social spaces, as well as for interaction with social robots. The problem is made challenging by the idiosyncratic and non‐periodic nature of human co‐speech gesture motion, and by the great diversity of communicative functions that gestures encompass. The field of gesture generation has seen surging interest in the last few years, owing to the emergence of more and larger datasets of human gesture motion, combined with strides in deep‐learning‐based generative models that benefit from the growing availability of data. This review article summarizes co‐speech gesture generation research, with a particular focus on deep generative models. First, we articulate the theory describing human gesticulation and how it complements speech. Next, we briefly discuss rule‐based and classical statistical gesture synthesis, before delving into deep learning approaches. We employ the choice of input modalities as an organizing principle, examining systems that generate gestures from audio, text and non‐linguistic input. Concurrent with the exposition of deep learning approaches, we chronicle the evolution of the related training data sets in terms of size, diversity, motion quality, and collection method (e.g., optical motion capture or pose estimation from video). Finally, we identify key research challenges in gesture generation, including data availability and quality; producing human‐like motion; grounding the gesture in the co‐occurring speech in interaction with other speakers, and in the environment; performing gesture evaluation; and integration of gesture synthesis into applications. We highlight recent approaches to tackling the various key challenges, as well as the limitations of these approaches, and point toward areas of future development.