bluuebunny/crossref_metadata_2025_split huggingface dataset:
Care Leavers' Perceived Well‐Being: Findings From a Co‐constructed Survey in Italy
Authors: Mauri Diletta , Sanfelici Mara , Belotti Valerio 
Published: June 2024

ABSTRACTIt is now well established that young people who, for different reasons, grow up in care face particular challenges when they leave the care system. Many policies have been enacted to support them, but not enough is known about their subjective views on their situation and what their idea of well‐being is and their aspirations in its regard. The article presents the results of a survey which involved 454 Italian care leavers aged 16–25 years old. The study was constructed with them, with the aim of understanding their condition, their opinion about the child protection system (CPS) and their subjective perception of well‐being regarding different life dimensions. Findings are useful to highlight factors associated with subjective well‐being (SWB), such as economic precarity, age and gender. Children participation seems to make a difference in the largest number of life domains, including the relationship with the birth family. The research underscored the overall value of participation for care leavers: holding together the many aspects that support SWB can indeed facilitate the construction of contextualized knowledge, thus providing useful and solidly grounded instruments with which to implement policies and practices.
CUPID: Contextual Understanding of Prompt‐conditioned Image Distributions
Authors: Zhao Y. , Li M. , Berger M. 
Published: June 2024

AbstractWe present CUPID: a visualization method for the contextual understanding of prompt‐conditioned image distributions. CUPID targets the visual analysis of distributions produced by modern text‐to‐image generative models, wherein a user can specify a scene via natural language, and the model generates a set of images, each intended to satisfy the user's description. CUPID is designed to help understand the resulting distribution, using contextual cues to facilitate analysis: objects mentioned in the prompt, novel, synthesized objects not explicitly mentioned, and their potential relationships. Central to CUPID is a novel method for visualizing high‐dimensional distributions, wherein contextualized embeddings of objects, those found within images, are mapped to a low‐dimensional space via density‐based embeddings. We show how such embeddings allows one to discover salient styles of objects within a distribution, as well as identify anomalous, or rare, object styles. Moreover, we introduce conditional density embeddings, whereby conditioning on a given object allows one to compare object dependencies within the distribution. We employ CUPID for analyzing image distributions produced by large‐scale diffusion models, where our experimental results offer insights on language misunderstanding from such models and biases in object composition, while also providing an interface for discovery of typical, or rare, synthesized scenes.
Generating Euler Diagrams Through Combinatorial Optimization
Authors: Rottmann Peter , Rodgers Peter , Yan Xinyuan , Archambault Daniel , Wang Bei , Haunert Jan‐Henrik 
Published: June 2024

AbstractCan a given set system be drawn as an Euler diagram? We present the first method that correctly decides this question for arbitrary set systems if the Euler diagram is required to represent each set with a single connected region. If the answer is yes, our method constructs an Euler diagram. If the answer is no, our method yields an Euler diagram for a simplified version of the set system, where a minimum number of set elements have been removed. Further, we integrate known wellformedness criteria for Euler diagrams as additional optimization objectives into our method. Our focus lies on the computation of a planar graph that is embedded in the plane to serve as the dual graph of the Euler diagram. Since even a basic version of this problem is known to be NP‐hard, we choose an approach based on integer linear programming (ILP), which allows us to compute optimal solutions with existing mathematical solvers. For this, we draw upon previous research on computing planar supports of hypergraphs and adapt existing ILP building blocks for contiguity‐constrained spatial unit allocation and the maximum planar subgraph problem. To generate Euler diagrams for large set systems, for which the proposed simplification through element removal becomes indispensable, we also present an efficient heuristic. We report on experiments with data from MovieDB and Twitter. Over all examples, including 850 non‐trivial instances, our exact optimization method failed only for one set system to find a solution without removing a set element. However, with the removal of only a few set elements, the Euler diagrams can be substantially improved with respect to our wellformedness criteria.
AVA: Towards Autonomous Visualization Agents through Visual Perception‐Driven Decision‐Making
Authors: Liu S. , Miao H. , Li Z. , Olson M. , Pascucci V. , Bremer P‐T. 
Published: June 2024

AbstractWith recent advances in multi‐modal foundation models, the previously text‐only large language models (LLM) have evolved to incorporate visual input, opening up unprecedented opportunities for various applications in visualization. Compared to existing work on LLM‐based visualization works that generate and control visualization with textual input and output only, the proposed approach explores the utilization of the visual processing ability of multi‐modal LLMs to develop Autonomous Visualization Agents (AVAs) that can evaluate the generated visualization and iterate on the result to accomplish user‐defined objectives defined through natural language. We propose the first framework for the design of AVAs and present several usage scenarios intended to demonstrate the general applicability of the proposed paradigm. Our preliminary exploration and proof‐of‐concept agents suggest that this approach can be widely applicable whenever the choices of appropriate visualization parameters require the interpretation of previous visual output. Our study indicates that AVAs represent a general paradigm for designing intelligent visualization systems that can achieve high‐level visualization goals, which pave the way for developing expert‐level visualization agents in the future.
Transmittance‐based Extinction and Viewpoint Optimization
Authors: Himmler Paul , Günther Tobias 
Published: June 2024

AbstractA long‐standing challenge in volume visualization is the effective communication of relevant spatial structures that might be hidden due to occlusions. Given a scalar field that indicates the importance of every point in the domain, previous work synthesized volume visualizations by weighted averaging of samples along view rays or by optimizing a spatially‐varying extinction field through an energy minimization. This energy minimization, however, did not directly measure the contribution of an individual sample to the final pixel color. In this paper, we measure the visibility of relevant structures directly by incorporating the transmittance into a non‐linear energy minimization. For the first time, we not only perform a transmittance‐based extinction optimization, we concurrently optimize the camera position to find ideal viewpoints. We derive the partial derivatives for the gradient‐based optimization symbolically, which makes the application of automatic differentiation methods unnecessary. The transmittance‐based formulation gives a direct visibility measure that is communicated to the user in order to make aware of potentially overlooked relevant structures. Our approach is compatible with any measure of importance and its versatility is demonstrated in multiple data sets.
psudo: Exploring Multi‐Channel Biomedical Image Data with Spatially and Perceptually Optimized Pseudocoloring
Authors: Warchol S. , Troidl J. , Muhlich J. , Krueger R. , Hoffer J. , Lin T. , Beyer J. , Glassman E. , Sorger P. , Pfister H. 
Published: June 2024

AbstractOver the past century, multichannel fluorescence imaging has been pivotal in myriad scientific breakthroughs by enabling the spatial visualization of proteins within a biological sample. With the shift to digital methods and visualization software, experts can now flexibly pseudocolor and combine image channels, each corresponding to a different protein, to explore their spatial relationships. We thus propose psudo, an interactive system that allows users to create optimal color palettes for multichannel spatial data. In psudo, a novel optimization method generates palettes that maximize the perceptual differences between channels while mitigating confusing color blending in overlapping channels. We integrate this method into a system that allows users to explore multi‐channel image data and compare and evaluate color palettes for their data. An interactive lensing approach provides on‐demand feedback on channel overlap and a color confusion metric while giving context to the underlying channel values. Color palettes can be applied globally or, using the lens, to local regions of interest. We evaluate our palette optimization approach using three graphical perception tasks in a crowdsourced user study with 150 participants, showing that users are more accurate at discerning and comparing the underlying data using our approach. Additionally, we showcase psudo in a case study exploring the complex immune responses in cancer tissue data with a biologist.
Exploring Classifiers with Differentiable Decision Boundary Maps
Authors: Machado A. , Behrisch M. , Telea A. 
Published: June 2024

AbstractExplaining Machine Learning (ML) — and especially Deep Learning (DL) — classifiers' decisions is a subject of interest across fields due to the increasing ubiquity of such models in computing systems. As models get increasingly complex, relying on sophisticated machinery to recognize data patterns, explaining their behavior becomes more difficult. Directly visualizing classifier behavior is in general infeasible, as they create partitions of the data space, which is typically high dimensional. In recent years, Decision Boundary Maps (DBMs) have been developed, taking advantage of projection and inverse projection techniques. By being able to map 2D points back to the data space and subsequently run a classifier, DBMs represent a slice of classifier outputs. However, we recognize that DBMs without additional explanatory views are limited in their applicability. In this work, we propose augmenting the naive DBM generating process with views that provide more in‐depth information about classifier behavior, such as whether the training procedure is locally stable. We describe our proposed views — which we term Differentiable Decision Boundary Maps — over a running example, explaining how our work enables drawing new and useful conclusions from these dense maps. We further demonstrate the value of these conclusions by showing how useful they would be in carrying out or preventing a dataset poisoning attack. We thus provide evidence of the ability of our proposed views to make DBMs significantly more trustworthy and interpretable, increasing their utility as a model understanding tool.
A comprehensive Thai pharmacogenomics database (TPGxD‐1): Phenotype prediction and variants identification in 942 whole‐genome sequencing data
Authors: John Shobana , Klumsathian Sommon , Own‐eium Paravee , Eu‐ahsunthornwattana Jakris , Sura Thanyachai , Dejsuphong Donniphat , Sritara Piyamitr , Vathesatogkit Prin , Thongchompoo Nartthawee , Thabthimthong Wiphaporn , Teerakulkittipong Nuttinee , Chantratita Wasun , Sukasem Chonlaphat 
Published: June 2024

AbstractComputational methods analyze genomic data to identify genetic variants linked to drug responses, thereby guiding personalized medicine. This study analyzed 942 whole‐genome sequences from the Electricity Generating Authority of Thailand (EGAT) cohort to establish a population‐specific pharmacogenomic database (TPGxD‐1) in the Thai population. Sentieon (version 201808.08) implemented the GATK best workflow practice for variant calling. We then annotated variant call format (VCF) files using Golden Helix VarSeq 2.5.0 and employed Stargazer v2.0.2 for star allele analysis. The analysis of 63 very important pharmacogenes (VIPGx) reveals 85,566 variants, including 13,532 novel discoveries. Notably, we identified 464 known PGx variants and 275 clinically relevant novel variants. The phenotypic prediction of 15 VIPGx demonstrated a varied metabolic profile for the Thai population. Genes like CYP2C9 (9%), CYP3A5 (45.2%), CYP2B6 (9.4%), NUDT15 (15%), CYP2D6 (47%) and CYP2C19 (43%) showed a high number of intermediate metabolizers; CYP3A5 (41%), and CYP2C19 (9.9%) showed more poor metabolizers. CYP1A2 (52.7%) and CYP2B6 (7.6%) were found to have a higher number of ultra‐metabolizers. The functional prediction of the remaining 10 VIPGx genes reveals a high frequency of decreased functional alleles in SULT1A1 (12%), NAT2 (84%), and G6PD (12%). SLCO1B1 reports 20% poor functional alleles, while PTGIS (42%), SLCO1B1 (4%), and TPMT (5.96%) showed increased functional alleles. This study discovered new variants and alleles in the 63 VIPGx genes among the Thai population, offering insights into advancing clinical pharmacogenomics (PGx). However, further validation is needed using other computational and genotyping methods.
Reduced inhibition from quadriceps onto soleus after acute quadriceps fatigue suggests Golgi tendon organ contribution to heteronymous inhibition
Authors: Cuadra Cristian , De Boef Adam , Luong Sarah , Wolf Steven L. , Nichols T. Richard , Lyle Mark A. 
Published: June 2024

AbstractHeteronymous inhibition between lower limb muscles is primarily attributed to recurrent inhibitory circuits in humans but could also arise from Golgi tendon organs (GTOs). Distinguishing between recurrent inhibition and mechanical activation of GTOs is challenging because their heteronymous effects are both elicited by stimulation of nerves or a muscle above motor threshold. Here, the unique influence of mechanically activated GTOs was examined by comparing the magnitude of heteronymous inhibition from quadriceps (Q) muscle stimulation onto ongoing soleus electromyographic at five Q stimulation intensities (1.5–2.5× motor threshold) before and after an acute bout of stimulation‐induced Q fatigue. Fatigue was used to decrease Q stimulation evoked force (i.e., decreased GTO activation) despite using the same pre‐fatigue stimulation currents (i.e., same antidromic recurrent inhibition input). Thus, a decrease in heteronymous inhibition after Q fatigue and a linear relation between stimulation‐evoked torque and inhibition both before and after fatigue would support mechanical activation of GTOs as a source of inhibition. A reduction in evoked torque but no change in inhibition would support recurrent inhibition. After fatigue, Q stimulation‐evoked knee torque, heteronymous inhibition magnitude and inhibition duration were significantly decreased for all stimulation intensities. In addition, heteronymous inhibition magnitude was linearly related to twitch‐evoked knee torque before and after fatigue. These findings support mechanical activation of GTOs as a source of heteronymous inhibition along with recurrent inhibition. The unique patterns of heteronymous inhibition before and after fatigue across participants suggest the relative contribution of GTOs, and recurrent inhibition may vary across persons.
Labile glutamate synaptic transmission in the adult CA1 stratum‐lacunosum‐moleculare region
Authors: Ma Rong , Hanse Eric , Gustafsson Bengt 
Published: June 2024

AbstractThe excitatory monosynaptic activation of hippocampal CA1 pyramidal cells is spatially segregated such that the proximal part of the apical dendritic tree in stratum radiatum (SR) receives input from the hippocampal CA3 region while the distal part in the stratum‐lacunosum‐moleculare (SLM) receives input mainly from the entorhinal cortex. The AMPA receptor‐mediated (AMPA) signalling of SLM synapses in slices from neonatal rats was previously found to considerably differ from that of the SR synapses. In the present study, AMPA signalling of SLM synapses in 1‐month‐old rats has been examined, that is, when the hippocampus is essentially functionally mature. For the SR synapses, this time is characterized by a facilitatory shift in short‐term plasticity, in the disappearance of labile postsynaptic AMPA signalling, a property thought to be important for early activity‐dependent organization of neural circuits, and the expression of an adult form of long‐term potentiation. We found that the SLM synapses alter their short‐term plasticity similarly to that of the SR synapses. However, the labile postsynaptic AMPA signalling was not only maintained but substantially enhanced in the SLM synapses. The long‐term potentiation observed was not of the adult form but like that of the neonatal SR synapses based on unsilencing of AMPA labile synapses. We propose that these features of the SLM synapses in the mature hippocampus will help to produce a flexible map of the multimodal sensory input reaching the SLM required for its conjunctive operation with the SR input to generate a proper functional output from the CA1 region.
Grazing herbivores reduce herbaceous biomass and fire activity across African savannas
Authors: Karp Allison Tyler , Koerner Sally E. , Hempson Gareth P. , Abraham Joel O. , Anderson T. Michael , Bond William J. , Burkepile Deron E. , Fillion Elizabeth N. , Goheen Jacob R. , Guyton Jennifer A. , Kartzinel Tyler R. , Kimuyu Duncan M. , Mohanbabu Neha , Palmer Todd M. , Porensky Lauren M. , Pringle Robert M. , Ritchie Mark E. , Smith Melinda D. , Thompson Dave I. , Young Truman P. , Staver A. Carla 
Published: June 2024

AbstractFire and herbivory interact to alter ecosystems and carbon cycling. In savannas, herbivores can reduce fire activity by removing grass biomass, but the size of these effects and what regulates them remain uncertain. To examine grazing effects on fuels and fire regimes across African savannas, we combined data from herbivore exclosure experiments with remotely sensed data on fire activity and herbivore density. We show that, broadly across African savannas, grazing herbivores substantially reduce both herbaceous biomass and fire activity. The size of these effects was strongly associated with grazing herbivore densities, and surprisingly, was mostly consistent across different environments. A one‐zebra increase in herbivore biomass density (~100 kg/km2 of metabolic biomass) resulted in a ~53 kg/ha reduction in standing herbaceous biomass and a ~0.43 percentage point reduction in burned area. Our results indicate that fire models can be improved by incorporating grazing effects on grass biomass.
Reducing the environmental footprint of glass manufacturing
Authors: Colangelo Scott 
Published: June 2024

AbstractThe glass industry is a significant source of greenhouse gas emissions due to its energy consumption profile and the use of fossil fuels in the manufacturing process. Most of the energy to produce glass is consumed in the process of treating raw materials to elevated temperatures, usually above 1500°C. Glass manufacturing also generates significant environmental impacts, such as greenhouse gas emissions, air pollution, water consumption, and waste generation. Therefore, improving the sustainability of glass manufacturing is a significant challenge for the industry and society. There are ways to reduce the energy consumption and emissions of glass melting, such as recycling glass, using oxy‐fuel burners, improving furnace insulation and design, and adopting electric melting technologies. These methods can help save energy, lower costs, and enhance the sustainability and environmental footprint of the glass industry. However, the industry faces challenges and barriers, such as technical feasibility, economic viability, capital investment, and market acceptance. More research and development must be invested to improve the energy efficiency and environmental performance of glass melting. The objective of this paper is to provide an overview of the growth glass industry has made over the past 30 years and the remaining challenges for sustainable glass manufacturing with a focus on the fiberglass segment. Sharing of procedural methods, technical approaches, and results can help enable the global glass industry in our future sustainability challenges. The fiberglass segment included a broad technical view including glass chemistry development, product development, new industry codes and standards, melting development, computational fluid dynamic modeling, life cycle assessments, and sustainability goals linked to capital planning. The net result delivered a significant reduction in environmental emissions at the global enterprise scale. The implemented changes have taken decades, significant investments, and resources to plan and develop. Practices reviewed and implemented can help drive collaboration and commonality within the glass industry to achieve sustainability goals. Action is needed now if the glass industry is to meet global government demands of reducing carbon emissions by 55% by 2030 and zero carbon emissions by 2050 in alignment with the Paris Agreement on decarbonization.
Glass packaging and its contribution to the UN Sustainable Development Goals
Authors: Somogyi Andrew , Chesnot Vanessa 
Published: June 2024

AbstractThis article delves into the significance of glass packaging in the European container glass industry's sustainable development, emphasizing its role in achieving key UN Sustainable Development Goals (SDGs). Covering health benefits, sustainable consumption, climate action, and collaborative partnerships, the European container glass industry's commitment to a circular economy and carbon neutrality by 2050 is explored. The discussion encompasses the industry's advancements in circularity and the critical transition to green energy. The article highlights the industry's strides over the past 50 years and outlines its vision for a sustainable future. It also points to the role of a supportive policy and legislative framework in enabling a circular and climate‐neutral economy.
Clinical Outcomes of Coronavirus Disease 2019 in People Living With Human Immunodeficiency Virus in South Korea: A Nationwide Population‐Based Cohort Study
Authors: Kim Jeong Yeon , Jeong Yujin , An Hyonggin , Suh Jin Woong , Sohn Jang Wook , Yoon Young Kyung 
Published: June 2024

ABSTRACTBackgroundWe aimed to compare the epidemiological and clinical characteristics of coronavirus disease 2019 (COVID‐19) in people living with human immunodeficiency virus (HIV) (PLWH) with those in people living without HIV (PLWoH).MethodsThis nationwide descriptive epidemiological study was conducted in South Korea between January 2020 and February 2022. The National Health Insurance claim data, comprising the data of the entire Korean population, were collected through the Health Insurance Review and Assessment Service.ResultsAmong 3,653,808 individuals who were diagnosed with COVID‐19, 1311 (0.04%) were PLWH. All PLWH received antiretroviral therapy, and 26.47% had more than one underlying disease other than HIV infection. The overall in‐hospital mortality rates of PLWH and PLWoH were 0.76% and 0.25%, respectively (P = 0.002). According to the Cox proportional hazard model, no significant difference was observed in the in‐hospital mortality rate (hazard ratio [HR]: 1.80, 95% confidence interval [CI]: 0.70–4.67) between the PLWH and PLWoH. However, progression to severe or critical COVID‐19 was more common in PLWH (HR: 2.70, 95% CI: 1.37–5.33). In PLWH diagnosed with COVID‐19, a multivariable Cox regression analysis found old age (≥ 60 years) (HR: 6.9, 95% CI: 2.57–18.56) and diabetes mellitus (HR: 5.13, 95% CI: 2.02–13.00) as the independent risk factors for severe or critical COVID‐19.ConclusionsPLWH had a significantly higher risk of developing severe or critical COVID‐19 compared with PLWoH. Our findings suggest the need for implementing tailored strategies to decrease the impact of COVID‐19 on PLWH.