bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting odor from vibrational spectra: a data-driven approach
Authors: Ameta Durgesh , Behera Laxmidhar , Chakraborty Aniruddha , Sandhan Tushar 
Published: September 2024

AbstractThis study investigates olfaction, a complex and not well-understood sensory modality. The chemical mechanism behind smell can be described by so far proposed two theories: vibrational and docking theories. The vibrational theory has been gaining acceptance lately but needs more extensive validation. To fill this gap for the first time, we, with the help of data-driven classification, clustering, and Explainable AI techniques, systematically analyze a large dataset of vibrational spectra (VS) of 3018 molecules obtained from the atomistic simulation. The study utlizes image representations of VS using Gramian Angular Fields and Markov Transition Fields, allowing computer vision techniques to be applied for better feature extraction and improved odor classification. Furthermore, we fuse the PCA-reduced fingerprint features with image features, which show additional improvement in classification results. We use two clustering methods, agglomerative hierarchical (AHC) and k-means, on dimensionality reduced (UMAP, MDS, t-SNE, and PCA) VS and image features, which shed further insight into the connections between molecular structure, VS, and odor. Additionally, we contrast our method with an earlier work that employed traditional machine learning on fingerprint features for the same dataset, and demonstrate that even with a representative subset of 3018 molecules, our deep learning model outperforms previous results. This comprehensive and systematic analysis highlights the potential of deep learning in furthering the field of olfactory research while confirming the vibrational theory of olfaction.
Respiratory rates among rural Gambian children: a community-based cohort study
Authors: Mogeni Polycarp , Amima Sharon , Gunther Jennifer , Pinder Margaret , Tusting Lucy S. , D’Alessandro Umberto , Cousens Simon , Lindsay Steve W. , Bradley John 
Published: September 2024

AbstractNormal respiratory rates (RR) for children under five in the tropics are well-documented, but data for older children are limited. This study tracked RR changes with age and examined associations with nutritional status and environmental factors. We monitored rural Gambian children aged 6 months to 14 years, recording RR during home visits twice weekly over two rainy seasons. Using a generalized additive model, we constructed RR reference curves, and a linear mixed-effect model identified factors influencing RR. A total of 830 children provided 67,512 RR measurements. Their median age was 6.07 years (interquartile range 4.21–8.55) and 400 (48.2%) were female. Age, stunting, ambient temperature, and time of RR measurement were independent predictors of respiratory rate. Strikingly, children showing signs of illness had greater variability in repeat RR measurements. We constructed a RR reference chart for children aged one to 13 years and proposed a cutoff of > 26 breaths/min for raised RR among children aged > 5 years bridging an important gap in this age group. Although the time of data collection, nutritional status, and ambient temperature were predictors of RR, their effect size is not clinically significant enough to warrant a change in the current WHO guidelines owing to the prevailing uncertainty in the measurement of RR. The finding that RRs between repeat measurements were more variable among children with signs of illness suggests that a single RR measurement may be inadequate to reliably assess the status of sick children—a population in which accurate diagnosis is essential to enable targeted interventions with lifesaving treatment.
A system to analyze the initiation of random X-chromosome inactivation using time-lapse imaging of single cells
Authors: Koshiguchi Manami , Yonezawa Nao , Hatano Yu , Suenaga Hikaru , Yamagata Kazuo , Kobayashi Shin 
Published: September 2024

AbstractIn female eutherian mammal development, X-chromosome inactivation (XCI) of one of the two X chromosomes is initiated early. Understanding the relationship between the initiation of XCI and cell fate is critical for understanding early female development and requires a system that can monitor XCI in single living cells. Traditional embryonic stem cells (ESCs) used for XCI studies often lose X chromosomes spontaneously during culture and differentiation, making accurate monitoring difficult. Additionally, most XCI assessment methods necessitate cell disruption, hindering cell fate tracking. We developed the Momiji (version 2) ESC line to address these difficulties, enabling real-time monitoring of X-chromosome activity via fluorescence. We inserted green and red fluorescent reporter genes and neomycin and puromycin resistance genes into the two X chromosomes of PGK12.1 ESCs, creating a female ESC line that retains two X chromosomes more faithfully during differentiation. Momiji (version 2) ESCs exhibit a more stable XX karyotype than other ESC lines, including the parental PGK12.1 line. This new tool offers valuable insights into the relationship between XCI and cell fate, improving our understanding of early female development.
Impact of acquisition area on deep-learning-based glaucoma detection in different plexuses in OCTA
Authors: Schottenhamml Julia , Würfl Tobias , Ploner Stefan , Husvogt Lennart , Lämmer Robert , Hohberger Bettina , Maier Andreas , Mardin Christian 
Published: September 2024

AbstractGlaucoma is a group of neurodegenerative diseases that can lead to irreversible blindness. Yet, the progression can be slowed down if diagnosed and treated early enough. Optical coherence tomography angiography (OCTA) can non-invasively provide valuable information about the retinal microcirculation that has shown to be correlated with the onset of the disease. The vessel density (VD) is the most commonly used biomarker to quantify this vascular information. However, different studies showed that there is a great impact of the acquisition area on the performance of the VD to distinguish between glaucoma patients and a healthy control group. It also seems that the separate capillary plexuses are differently affected by the disease and therefore also influence the results. So in this study we investigate the impact of the acquisition area (3 $$\times $$
×
3 $$\textrm{mm}$$
mm
macular scan, 6.44 $$\times $$
×
6.4 $$\textrm{mm}$$
mm
macular scan, 6 $$\times $$
×
6 $$\textrm{mm}$$
mm
optic nerve head (ONH) scan) and the different plexuses on the machine-learning-based distinction between glaucoma patients and healthy controls. The results yielded that the 6 $$\times $$
×
6 $$\textrm{mm}$$
mm
ONH show the best performance over all plexuses. Moreover the deep learning-based approach outperforms the VD as a biomarker on every acquisition area and plexus. In addition to that, it also performs better than traditional biomarkers obtained from the OCT scans that are used in the clinical routine for diagnosis and progression tracking of glaucoma. Consequently, OCTA scans of the ONH might be a useful addition to OCT when studying glaucoma.
Cognitive subgroups of affective and non-affective psychosis show differences in medication and cortico-subcortical brain networks
Authors: Bracher Katharina M. , Wohlschlaeger Afra , Koch Kathrin , Knolle Franziska 
Published: September 2024

AbstractCognitive deficits are prevalent in individuals with psychosis and are associated with neurobiological changes, potentially serving as an endophenotype for psychosis. Using the HCP-Early-Psychosis-dataset (n = 226), we aimed to investigate cognitive subtypes (deficit/intermediate/spared) through data-driven clustering in affective (AP) and non-affective psychosis patients (NAP) and controls (HC). We explored differences between three clusters in symptoms, cognition, medication, and grey matter volume. Applying principal component analysis, we selected features for clustering. Features that explained most variance were scores for intelligence, verbal recognition and comprehension, auditory attention, working memory, reasoning and executive functioning. Fuzzy K-Means clustering on those features revealed that the subgroups significantly varied in cognitive impairment, clinical symptoms, and, importantly, also in medication and grey matter volume in fronto-parietal and subcortical networks. The spared cluster (86%HC, 37%AP, 17%NAP) exhibited unimpaired cognition, lowest symptoms/medication, and grey matter comparable to controls. The deficit cluster (4%HC, 10%AP, 47%NAP) had impairments across all domains, highest symptoms scores/medication dosage, and pronounced grey matter alterations. The intermediate deficit cluster (11%HC, 54%AP, 36%NAP) showed fewer deficits than the second cluster, but similar symptoms/medication/grey matter to the spared cluster. Controlling for medication, cognitive scores correlated with grey matter changes and negative symptoms across all patients. Our findings generally emphasize the interplay between cognition, brain structure, symptoms, and medication in AP and NAP, and specifically suggest a possible mediating role of cognition, highlighting the potential of screening cognitive changes to aid tailoring treatments and interventions.
Global population datasets overestimate flood exposure in Sweden
Authors: Karagiorgos Konstantinos , Georganos Stefanos , Fuchs Sven , Nika Grigor , Kavallaris Nikos , Grahn Tonje , Haas Jan , Nyberg Lars 
Published: September 2024

AbstractAccurate population data is crucial for assessing exposure in disaster risk assessments. In recent years, there has been a significant increase in the development of spatially gridded population datasets. Despite these datasets often using similar input data to derive population figures, notable differences arise when comparing them with direct ground-level observations. This study evaluates the precision and accuracy of flood exposure assessments using both known and generated gridded population datasets in Sweden. Specifically focusing on WorldPop and GHSPop, we compare these datasets against official national statistics at a 100 m grid cell resolution to assess their reliability in flood exposure analyses. Our objectives include quantifying the reliability of these datasets and examining the impact of data aggregation on estimated flood exposure across different administrative levels. The analysis reveals significant discrepancies in flood exposure estimates, underscoring the challenges associated with relying on generated gridded population data for precise flood risk assessments. Our findings emphasize the importance of careful dataset selection and highlight the potential for overestimation in flood risk analysis. This emphasises the critical need for validations against ground population data to ensure accurate flood risk management strategies.
Association between alcohol consumption and incidence of type 2 diabetes in middle-aged Japanese from Panasonic cohort study 12
Authors: Takahashi Fuyuko , Okada Hiroshi , Hashimoto Yoshitaka , Kurogi Kazushiro , Murata Hiroaki , Ito Masato , Fukui Michiaki 
Published: September 2024

AbstractThis retrospective cohort study aimed to investigate the association between alcohol consumption and the onset of type 2 diabetes in middle-aged Japanese individuals. Participants were aged 40 and above from Panasonic Corporation, Osaka, Japan’s medical health checkup program from 2008 to 2021. Alcohol consumption was calculated by converting the quantity consumed into daily ethanol consumption. We assessed the association between alcohol consumption and the onset of type 2 diabetes using Cox regression analysis. The total and median follow-up duration was 13 years and 7 (3–13) years (748,090 person-years). Among 102,802 participants, 7,510 participants (7.3%) developed type 2 diabetes during the study period. Alcohol consumption at the level of 0 < to < 22 g/day and 22 to < 39 g/day were negatively associated with developing type 2 diabetes compared to complete alcohol abstainers. Alcohol consumption at levels of 39 to < 66 g/day and at levels of ≥ 66 g/day were positively associated with developing type 2 diabetes in participants with BMI < 25 kg/m2. All levels of alcohol consumption were negatively associated with developing type 2 diabetes in participants with BMI ≥ 25 kg/m2. Moderate-to-heavy alcohol consumption were positively associated with developing type 2 diabetes for participants with BMI < 25 kg/m2, whereas alcohol intake was negatively associated with developing type 2 diabetes among participants with BMI ≥ 25 kg/m2.
Weaving equity into infrastructure resilience research: a decadal review and future directions
Authors: Coleman Natalie , Li Xiangpeng , Comes Tina , Mostafavi Ali 
Published: September 2024

AbstractInfrastructure resilience plays an important role in mitigating the negative impacts of natural hazards by ensuring the continued accessibility and availability of resources. Increasingly, equity is recognized as essential for infrastructure resilience. Yet, after about a decade of research on equity in infrastructure resilience, what is missing is a systematic overview of the state of the art and a research agenda across different infrastructures and hazards. To address this gap, this paper presents a systematic review of equity literature on infrastructure resilience in relation to natural hazard events. In our systematic review of 99 studies, we followed an 8-dimensional assessment framework that recognizes 4 equity definitions including distributional-demographic, distributional-spatial, procedural, and capacity equity. Significant findings show that (1) the majority of studies found were located in the US, (2) interest in equity in infrastructure resilience has been exponentially rising, (3) most data collection methods used descriptive and open-data, particularly with none of the non-US studies using human mobility data, (4) limited quantitative studies used non-linear analysis such as agent-based modeling and gravity networks, (5) distributional equity is mostly studied through disruptions in power, water, and transportation caused by flooding and tropical cyclones, and (6) other equity aspects, such as procedural equity, remain understudied. We propose that future research directions could quantify the social costs of infrastructure resilience and advocate a better integration of equity into resilience decision-making. This study fills a critical gap in how equity considerations can be integrated into infrastructure resilience against natural hazards, providing a comprehensive overview of the field and developing future research directions to enhance societal outcomes during and after disasters. As such, this paper is meant to inform and inspire researchers, engineers, and community leaders to understand the equity implications of their work and to embed equity at the heart of infrastructure resilience plans.
Crosstalk between salicylic acid signalling and the circadian clock promotes an effective immune response in plants
Authors: Fraser Olivia J. P. , Cargill Samantha J. , Spoel Steven H. , van Ooijen Gerben 
Published: September 2024

AbstractThe rotation of Earth creates a cycle of day and night, leading to predictable changes in environmental conditions. The circadian clock synchronizes an organism with these environmental changes and alters their physiology in anticipation. Prediction of the probable timing of pathogen infection enables plants to prime their immune system without wasting resources or sacrificing growth. Here, we explore the relationship between the immune hormone salicylic acid (SA), and the circadian clock in Arabidopsis. We found that SA altered circadian rhythmicity through the SA receptor and master transcriptional coactivator, NPR1. Reciprocally, the circadian clock gates SA-induced transcript levels of NPR1-dependent immune genes. Furthermore, the clock gene CCA1 is essential for SA-induced immunity to the major bacterial plant pathogen Pseudomonas syringae. These results build upon existing studies of the relationship between the circadian clock and SA signalling and how interactions between these systems produce an effective immune response. Understanding how and why the immune response in plants is linked to the circadian clock is crucial in working towards improved crop productivity.
Photoredox catalysis enabled by atomically precise metal nanoclusters
Authors: Zhang Junyi , Zhan Linjian , Ning Boyuan , He Yunhui , Xiao Guangcan , Chen Zhixin , Xiao Fang-Xing 
Published: September 2024

The heterostructure is elaborately designed by a self-assembly strategy, wherein Ag16(GSH)9 nanoclusters serve as photosensitizers to participate in interfacial charge transfer, ultimately resulting in significantly enhanced photoredox catalysis.
Axial vibration characteristics analysis of transformer windings based on magnetic‐structural coupling correction model
Authors: Wang Ping , Teng Fuyun , Geng Jianghai , Liu Yunpeng , Wang Xinyu , Gao Shuguo 
Published: September 2024

AbstractDue to the strong coupling effect between the internal magnetic field and the structural field of the transformer, the magnetic‐structural coupling should be considered in axial vibration process of the winding short‐circuit impact. A 110 kV transformer is taken as the research object. Firstly, the vibration modal characteristics of the transformer are calculated using the classical axial vibration model, and the spatial distribution of the leakage magnetic flux density of the iron core window is obtained based on the image method, which is used as the basis for calculating the excitation electromagnetic force. With the consideration of the non‐linear mechanical characteristic of the pad, the dynamic stiffness equation is analysed and established and the magnetic‐structural coupling correction model is constructed. Finally, the winding vibration amplitudes obtained respectively by the classical model, the magnetic‐structural coupling model, and the magnetic‐structural coupling correction model considering the dynamic stiffness are compared. The results show that, compared with the classical model, the vibration amplitude increment with the magnetic‐structural coupling correction model is less. The dynamic stiffness will hinder the vibration intensification. The magnetic‐structural coupling correction model can provide a more accurate calculation scheme for the winding vibration characteristic analysis.
A simple model of dust extinction in gamma-ray burst host galaxies
Authors: Rakotondrainibe N. A. , Buat V. , Turpin D. , Dornic D. , Le Floc’h E. , Vergani S. D. , Basa S. 
Published: September 2024

Context. Gamma-ray burst (GRB) afterglows are powerful probes for studying the different properties of their host galaxies (e.g., the interstellar dust) at all redshifts. By fitting their spectral energy distribution (SED) over a large range of wavelengths, we can gain direct insights into the properties of the interstellar dust by studying the extinction curves. Unlike the dust extinction templates, such as those of the average Milky Way (MW) or the Small and Large Magellanic Cloud (SMC and LMC), the extinction curves of galaxies outside the Local Group exhibit deviation from these laws. Altogether, X-ray and gamma-ray satellites as well as ground-based telescopes, such as Neil Gehrels Swift Observatory (Swift) and Gamma-Ray Optical and Near-Infrared Detector (GROND), provide measurements of the afterglows from the X-ray to the NIR, which can be used to extract information on dust extinction curves along their lines of sight (LoS). The study presented in this paper undertakes such a photometric study, comprising a preparatory work for the SVOM mission and its ground-based follow-up telescope COLIBRI.
Aims. We propose a simple approach to parameterize the dust extinction curve of GRB host galaxies. The model used in this analysis is based on a power law form with the addition of a Loretzian-like Drude profile with two parameters: the extinction slope, γ, and the 2175 Å bump amplitude, Eb.
Methods. Using the g′r′i′z′JHKs GROND filter bands, we tested our dust extinction model and explored the parameter space in extinction and redshift by fitting SEDs of simplified simulations of GRB afterglow spectra based on different extinction curve templates. From a final sample of 10 real Swift/GROND extinguished GRBs, we determined the quantities of the dust extinction in their host and measured their extinction curves.
Results. We find that our derived extinction curves are in agreement with the spectroscopic measurements reported for four GRBs in the literature. We compared four other GRBs to the results of photometric studies where fixed laws were used to fit their data. We additionally derived two new GRB extinction curves. The measured average extinction curve is given by a slope of γ = 1.051 ± 0.129 and Eb = 0.070 ± 0.036, which is equivalent to a quasi-featureless in-between SMC-LMC template. This is consistent with previous studies aimed at deriving the dust host galaxy extinction where we expect that small dust grains dominate in GRB environment, yielding a steeper curve than the mean MW extinction curve.
Welchen Einfluss hat die Entfernung zwischen dem Notfallort und dem ECLS-Zentrum auf die Low-Flow-Zeit von ECPR-Patienten?
Authors: Magomedov Abakar , Schröder Tim , Nee Jens , Zickler Daniel , Körner Roland , Kunz Julius Valentin , Przewoznik Margarethe , Hoff Uwe , Eckardt Kai-Uwe , Kruse Jan Matthias 
Published: September 2024

ZusammenfassungDie extrakorporale kardiopulmonale Reanimation (ECPR) als Bridging-Verfahren bei
refraktärem Kreislaufstillstand ist eine herausfordernde Strategie. Umfassende
evidenzbasierte Einschlusskriterien im Hinblick auf das neurologische Outcome liegen nicht
vor, die Dauer der konventionellen Reanimation ist wahrscheinlich ein Faktor. Gegenstand
dieser Untersuchung ist, ob die Entfernung des Notfallortes vom ECPR-Zentrum eine
entscheidende Bedeutung für die Zeit bis zum ECPR-Start ist.Retrospektive Datenanalyse von 143 Patienten, die einen Kreislaufstillstand erlitten
haben und in ein ECLS-Zentrum transportiert wurden.Die Dauer der CPR bis Aufnahme lag bei 63 min (50–80 min), die Gesamtdauer der CPR bei
Start ECPR (Gesamt-Low-Flow-Zeit) lag bei 100 min (80–115 min) – beide Zeitangaben
korrelierten nicht signifikant mit der Entfernung vom Notfallort zum ECPR-Zentrum.Wir fanden keine signifikante Korrelation zwischen der Entfernung des Notfallortes zum
ECLS-Zentrum und der Dauer vom Beginn der CPR bis zum Eintreffen im Zentrum. Möglicherweise
sind also andere logistische Faktoren entscheidend für die Dauer bis zum Eintreffen im
Zentrum. Die vorliegenden Daten erlauben diesbezüglich keine weiteren Rückschlüsse. Damit
scheint aber die These untermauert, dass eine Erhöhung der Anzahl der ECLS-Zentren mit
konsekutiver Verkürzung der Anfahrtsstrecke keine geeignete Maßnahme ist, um die Dauer der
mechanischen Reanimation und damit die Low-Flow-Zeit zu minimieren. Der präklinische
ECMO-Einsatz könnte einen Lösungsansatz bieten.