bluuebunny/crossref_metadata_2025_split huggingface dataset:
Classifier surrogates: sharing AI-based searches with the world
Authors: Bieringer Sebastian , Kasieczka Gregor , Kieseler Jan , Trabs Mathias 
Published: September 2024

AbstractIn recent years, neural network-based classification has been used to improve data analysis at collider experiments. While this strategy proves to be hugely successful, the underlying models are not commonly shared with the public and rely on experiment-internal data as well as full detector simulations. We show a concrete implementation of a newly proposed strategy, so-called Classifier Surrogates, to be trained inside the experiments, that only utilise publicly accessible features and truth information. These surrogates approximate the original classifier distribution, and can be shared with the public. Subsequently, such a model can be evaluated by sampling the classification output from high-level information without requiring a sophisticated detector simulation. Technically, we show that continuous normalizing flows are a suitable generative architecture that can be efficiently trained to sample classification results using conditional flow matching. We further demonstrate that these models can be easily extended by Bayesian uncertainties to indicate their degree of validity when confronted with unknown inputs by the user. For a concrete example of tagging jets from hadronically decaying top quarks, we demonstrate the application of flows in combination with uncertainty estimation through either inference of a mean-field Gaussian weight posterior, or Monte Carlo sampling network weights.
Reinforcement learning of biomimetic navigation: a model problem for sperm chemotaxis
Authors: Mohamed Omar , Tsang Alan C. H. 
Published: September 2024

Abstract
Motile biological cells can respond to local environmental cues and exhibit various navigation strategies to search for specific targets. These navigation strategies usually involve tuning of key biophysical parameters of the cells, such that the cells can modulate their trajectories to move in response to the detected signals. Here we introduce a reinforcement learning approach to modulate key biophysical parameters and realize navigation strategies reminiscent to those developed by biological cells. We present this approach using sperm chemotaxis toward an egg as a paradigm. By modulating the trajectory curvature of a sperm cell model, the navigation strategies informed by reinforcement learning are capable to resemble sperm chemotaxis observed in experiments. This approach provides an alternative method to capture biologically relevant navigation strategies, which may inform the necessary parameter modulations required for obtaining specific navigation strategies and guide the design of biomimetic micro-robotics.

Graphical abstract
Constraining neutron star properties and dark matter admixture with the NITR-I equation of state: Insights from observations and universal relations
Authors: Routaray Pinku , Das H. C. , Pattnaik Jeet Amrit , Kumar Bharat 
Published: September 2024

A recent observational study has set a constraint on the maximum mass of neutron stars (NSs), specifically focusing on PSR J0952-0607 and the compact star remnant HESS J1731-347, particularly within the low-mass regime. In our recent study, Ref. 1 , we developed an energy density functional named NITR, which successfully produced the mass limit of the aforementioned pulsar but did not fully meet other observational constraints, such as those from NICER+XMM and GW170817. In this study, we introduce a new EDF named “NITR-I”, which not only reproduces the mass limit of PSR J0952-0607 but also aligns its canonical radius with NICER+XMM data, and its canonical dimensionless tidal deformability is consistent with the GW170817 event, thereby demonstrating the robustness of our model. The low-mass constraint associated with HESS J1731-347 suggests various possible compositions for the NS. The NITR-I model alone does not satisfy the HESS J1731-347 constraint; thus, we explore the possibility of incorporating dark matter (DM) inside the NS to meet this constraint. This approach proves successful when a specific value of Fermi momentum is considered. We also examine the impact of DM with varying Fermi momentum on different NS properties, such as tidal deformability and nonradial f-mode oscillation, using various relativistic mean-field (RMF) models. For the NITR-I EOS, the f-mode frequency is about 2.15[Formula: see text]kHz at 1.4 [Formula: see text] when [Formula: see text][Formula: see text]GeV, and it slightly increases to around 2.32[Formula: see text]kHz with [Formula: see text][Formula: see text]GeV. This increase in frequency due to DM suggests a possible reduction in tidal deformability, indicating that neutron stars with higher DM content are less susceptible to deformation by tidal forces which could be detectable in gravitational wave signals from neutron star mergers. Finally, we explore various universal relations (URs) for DM-admixed NSs, such as the relation between compactness and tidal deformability, the f-mode frequency and tidal deformability, and estimate the canonical values corresponding to both compactness and f-mode frequency using the GW170817 data.
EARLY DIAGNOSIS AND CLASSIFICATION OF LUNG CANCER DRIVEN BY MULTI-FEATURE DATA: A COMPARISON AND OPTIMIZATION OF THREE MACHINE LEARNING METHODS
Authors: LAN QI , WANG RENFENG , FAN HONG 
Published: September 2024

The objective of this study was to construct a prediction model for early diagnosis and classification of lung cancer based on multi-dimensional clinical data. Three advanced machine learning models — Random Forest, Decision Tree, and Support Vector Machine (SVM) — were employed to predict lung cancer using features such as age, chronic disease history, and clinical symptoms. The models were optimized through various strategies to improve predictive performance. The results demonstrated that all three models achieved high accuracy and sensitivity in lung cancer prediction. Furthermore, a detailed analysis of feature importance identified key factors such as age and chronic disease history that significantly influenced prediction outcomes. Among the models, the SVM exhibited particularly strong performance, providing robust support for accurate lung cancer prediction. Future work will focus on integrating multimodal data and optimizing model architecture and hyperparameters to further enhance the predictive accuracy and clinical utility of the model, thereby contributing to the early diagnosis and treatment of lung cancer.
Shared Ontologies: 4e Cognition and Montemayor’s Humanitarian AI
Authors: Zebrowski Robin L. 
Published: September 2024

This short paper traces some convergences between the ontologies of mind and AI presented in Carlos Montemayor’s Precis for The Prospect of Humanitarian Artificial Intelligence and Enactivism, with a focus on autonomy, embeddedness, perspective, and social interaction. I argue that it is surprising that Montemayor does not engage with any of the traditional 4e ontologies here, especially enactivism, considering his strong reliance on biology and autonomy in carving up intelligence and consciousness.
Intraindividual Comparison of Ultrahigh-Spatial-Resolution Photon-Counting Detector CT and Energy-Integrating Detector CT for Coronary Stenosis Measurement
Authors: Vecsey-Nagy Milán , Tremamunno Giuseppe , Schoepf U. Joseph , Gnasso Chiara , Zsarnóczay Emese , Fink Nicola , Kravchenko Dmitrij , Halfmann Moritz C. , Laux Gerald S. , O’Doherty Jim , Szilveszter Bálint , Maurovich-Horvat Pál , Kabakus Ismail Mikdat , Suranyi Pal Spruill , Varga-Szemes Akos , Emrich Tilman 
Published: September 2024

BACKGROUND:
A recent simulation study proposed that stenosis measurements on coronary computed tomography (CT) angiography are influenced by the improved spatial resolution of photon-counting detector (PCD)-CT. The aim of the current study was to evaluate the impact of ultrahigh-spatial-resolution (UHR) on coronary stenosis measurements and Coronary Artery Disease Reporting and Data System (CAD-RADS) reclassification rates in patients undergoing coronary CT angiography on both PCD-CT and energy-integrating detector (EID)-CT and to compare measurements against quantitative coronary angiography.

METHODS:
Patients with coronary calcification on EID-CT (collimation, 192×0.6 mm) were prospectively enrolled for a research coronary CT angiography with UHR PCD-CT (collimation, 120×0.2 mm) within 30 days (between April 1, 2023 and January 31, 2024). PCD-CT was acquired with the same or lower CT dose index and equivalent contrast media volume as EID-CT. Percentage diameter stenosis (PDS) for calcified, partially calcified, and noncalcified lesions were compared between scanners. Patient-level reclassification rates for CAD-RADS were evaluated. The accuracy of PDS measurements was validated against quantitative coronary angiography in patients who underwent invasive coronary angiography.

RESULTS:

In total, PDS of 278 plaques were quantified in 49 patients (calcified, 202; partially calcified, 51; noncalcified, 25). PCD-CT-based PDS values were lower than EID-CT measurements for calcified (45.1±20.7 versus 54.6±19.2%;
P
<0.001) and partially calcified plaques (44.3±19.6 versus 54.9±20.0%;
P
<0.001), without significant differences for noncalcified lesions (39.1±15.2 versus 39.0±16.0%;
P
=0.98). The reduction in stenosis degrees led to a 49.0% (24/49) reclassification rate to a lower CAD-RADS with PCD-CT. In a subset of 12 patients with 56 lesions, UHR–based PDS values showed higher agreement with quantitative coronary angiography (mean difference, 7.3%; limits of agreement, −10.7%/25.2%) than EID-CT measurements (mean difference, 17.4%; limits of agreement, −6.9%/41.7%).

CONCLUSIONS:
Compared with conventional EID-CT, UHR PCD-CT results in lower PDS values and more accurate stenosis measurements in coronary plaques with calcified components and leads to a substantial Coronary Artery Disease Reporting and Data System reclassification rate in 49.0% of patients.
Arg92Leu-cTnT Alters the cTnC-cTnI Interface Disrupting PKA-Mediated Relaxation
Authors: Lynn Melissa L. , Jimenez Jesus , Castillo Romi L. , Vasquez Catherine , Klass Mattie M. , Baldo Anthony P. , Kim Andrew , Gibson Cyonna , Murphy Anne M. , Tardiff Jil C. 
Published: September 2024

BACKGROUND:

Impaired left ventricular relaxation, high filling pressures, and dysregulation of Ca
2+
homeostasis are common findings contributing to diastolic dysfunction in hypertrophic cardiomyopathy (HCM). Studies have shown that impaired relaxation is an early observation in the sarcomere-gene-positive preclinical HCM cohort, which suggests the potential involvement of myofilament regulators in relaxation. A molecular-level understanding of mechanism(s) at the level of the myofilament is lacking. We hypothesized that mutation-specific, allosterically mediated, changes to the cTnC (cardiac troponin C)-cTnI (cardiac troponin I) interface can account for the development of early-onset diastolic dysfunction via decreased PKA accessibility to cTnI.

METHODS:
HCM mutations R92L-cTnT (cardiac troponin T; Arg92Leu) and Δ160E-cTnT (Glu160 deletion) were studied in vivo, in vitro, and in silico via 2-dimensional echocardiography, Western blotting, ex vivo hemodynamics, stopped-flow kinetics, time-resolved fluorescence resonance energy transfer, and molecular dynamics simulations.

RESULTS:

The HCM-causative mutations R92L-cTnT and Δ160E-cTnT result in different time-of-onset diastolic dysfunction. R92L-cTnT demonstrated early-onset diastolic dysfunction accompanied by a localized decrease in phosphorylation of cTnI. Constitutive phosphorylation of cTnI (cTnI-D
23
D
24
) was sufficient to recover diastolic function to non-Tg levels only for R92L-cTnT. Mutation-specific changes in Ca
2+
dissociation rates associated with R92L-cTnT reconstituted with cTnI-D
23
D
24
led us to investigate potential involvement of structural changes in the cTnC-cTnI interface as an explanation for these observations. We probed the interface via time-resolved fluorescence resonance energy transfer revealing a repositioning of the N-terminus of cTnI, closer to cTnC, and concomitant decreases in distance distributions at sites flanking the PKA consensus sequence. Implementing time-resolved fluorescence resonance energy transfer distances as constraints into our atomistic model identified additional electrostatic interactions at the consensus sequence.

CONCLUSIONS:
These data show that the early diastolic dysfunction observed in a subset of HCM is attributable to allosterically mediated structural changes at the cTnC-cTnI interface that impair accessibility of PKA, thereby blunting β-adrenergic responsiveness and identifying a potential molecular target for therapeutic intervention.
Automated quality control of small animal MR neuroimaging data
Authors: Kalantari Aref , Shahbazi Mehrab , Schneider Marc , Raikes Adam C. , Frazão Victor Vera , Bhattrai Avnish , Carnevale Lorenzo , Diao Yujian , Franx Bart A. A. , Gammaraccio Francesco , Goncalves Lisa-Marie , Lee Susan , van Leeuwen Esther M. , Michalek Annika , Mueller Susanne , Olvera Alejandro Rivera , Padro Daniel , Selim Mohamed Kotb , van der Toorn Annette , Varriano Federico , Vrooman Roël , Wenk Patricia , Albers H. Elliott , Boehm-Sturm Philipp , Budinger Eike , Canals Santiago , De Santis Silvia , Brinton Roberta Diaz , Dijkhuizen Rick M. , Eixarch Elisenda , Forloni Gianluigi , Grandjean Joanes , Hekmatyar Khan , Jacobs Russell E. , Jelescu Ileana , Kurniawan Nyoman D. , Lembo Giuseppe , Longo Dario Livio , Maria Naomi S. Sta , Micotti Edoardo , Muñoz-Moreno Emma , Ramos-Cabrer Pedro , Reichardt Wilfried , Soria Guadalupe , Ielacqua Giovanna D. , Aswendt Markus 
Published: September 2024

Abstract
Magnetic resonance imaging (MRI) is a valuable tool for studying brain structure and function in animal and clinical studies. With the growth of public MRI repositories, access to data has finally become easier. However, filtering large datasets for potential poor-quality outliers can be a challenge. We present AIDAqc, a machine-learning-assisted automated Python-based command-line tool for small animal MRI quality assessment. Quality control features include signal-to-noise ratio (SNR), temporal SNR, and motion. All features are automatically calculated and no regions of interest are needed. Automated outlier detection for a given dataset combines the interquartile range and the machine-learning methods one-class support vector machine, isolation forest, local outlier factor, and elliptic envelope. To evaluate the reliability of individual quality control metrics, a simulation of noise (Gaussian, salt and pepper, speckle) and motion was performed. In outlier detection, single scans with induced artifacts were successfully identified by AIDAqc. AIDAqc was challenged in a large heterogeneous dataset collected from 19 international laboratories, including data from mice, rats, rabbits, hamsters, and gerbils, obtained with different hardware and at different field strengths. The results show that the manual inter-rater agreement (mean Fleiss Kappa score 0.17) is low when identifying poor-quality data. A direct comparison of AIDAqc results, therefore, showed only low-to-moderate concordance. In a manual post hoc validation of AIDAqc output, precision was high (&gt;70%). The outlier data can have a significant impact on further postprocessing, as shown in representative functional and structural connectivity analysis. In summary, this pipeline optimized for small animal MRI provides researchers with a valuable tool to efficiently and effectively assess the quality of their MRI data, which is essential for improved reliability and reproducibility.
New Rankine Vortex Models Developed Based on SMAP Measurements
Authors: Gao Yuan , Sun Jian , Guan Changlong , Wang Yunhua 
Published: September 2024

Abstract
The L-band passive microwave radiometer on board the NASA Soil Moisture Active Passive (SMAP) satellite can measure brightness temperature to retrieve sea surface wind speed under tropical cyclone (TC) conditions without being affected by rainfall or signal saturation caused by high wind speeds. Based on this advantage, this paper used the SMAP wind products for parameterizing the key decay exponent α of the Rankine vortex model (a traditional parametric model of the TC wind field) and finally developed new Rankine models. The SMAP dataset included 67 TC cases. Through data statistics, we examined the relationship between α and the maximum wind speed Um, the relationship between α and the radius of maximum wind speed (Rm), and the relationship between Rm and the averaged radius of 17 m s−1 (R17). Results showed that the three relationships were both positive correlations, indicating that α can be parameterized in three empirical ways. The first way is to calculate solely with Um. The second way is to calculate solely with Rm. The third way is to calculate Um and Rm together. The three ways correspond to three new models: the SMAP Rankine Model-1 (SRM-1), the SMAP Rankine Model-2 (SRM-2), and the SMAP Rankine Model-3 (SRM-3). Finally, comparisons were made between the new models and three existing Rankine models, according to the model simulations and the Advanced Microwave Scanning Radiometer 2 measurements of 49 TC cases. Results showed that the SRM-3 performed best overall.

Significance Statement
Ocean surface wind fields are important driving factors for numerical models to guide evolution forecasting and risk assessment of tropical cyclones. The purpose of this study is to utilize the SMAP products to modify the traditional Rankine vortex model for tropical cyclone surface wind field estimation. Rankine decay exponent was found between 0.3 and 0.9 and positively dependent upon maximum wind speed and its radius. Based on these characteristics, the proposed new Rankine models could calculate the decay exponent and further the TC surface wind field symmetrically with high accuracy, simply using maximum wind and its radius. This paper shows a practical use of SMAP measurements on TC wind field monitoring, analyzing, and modeling.
Physiotherapy-led care versus physician-led care for persons with low back pain: A systematic review
Authors: Severijns Pieter , Goossens Nina , Dankaerts Wim , Pitance Laurent , Roussel Nathalie , Denis Corentin , Fourré Antoine , Verschueren Pieter , Timmermans Annick , Janssens Lotte 
Published: September 2024

Objective To summarise the evidence on the effect of physiotherapy-led versus physician-led care on clinical outcomes, healthcare use, and costs in persons with low back pain. Data sources PubMed, Web of Science, CINAHL, Embase, and PEDro were systematically searched with the latest search performed in July 2024. Reference lists of articles were hand-searched. Review methods Studies comparing clinical outcomes, healthcare use, or costs between adults with low back pain first consulting a physiotherapist and those first consulting a physician were included. Methodological quality was assessed with the Newcastle-Ottawa Scale. Study design, clinical setting, patient characteristics, and group effects were extracted. Findings on outcomes assessed in two or more studies were synthesised narratively. Certainty of evidence was determined using the GRADE approach. Results Eighteen studies comprising 1,481,980 persons with low back pain were included. Most studies were non-randomised retrospective or prospective cohort studies. In primary care (15 studies), consistent evidence, though of mostly very low certainty, indicated that physiotherapy-led care leads to higher patient satisfaction, less use of medication, injections and imaging, fewer physician's visits, lower total healthcare costs, and less sick leave compared to physician-led care, without increased harm. In emergency care (three studies), evidence of very low certainty showed that physiotherapy-led care leads to shorter waiting and treatment times, and fewer hospital admissions. Conclusion Physiotherapy-led care is a clinically, time- and cost-effective care pathway for low back pain, although the certainty of evidence was overall very low. Further high-quality research with a greater focus on clinical outcomes is warranted.
On 3D printed polyvinylidene fluoride composite-based diaphragmatic hernia sensors
Authors: Barwar Abhishek , Kala Prateek , Singh Rupinder 
Published: September 2024

Diaphragmatic hernia (DH) recurrence is a commonly reported disorder among bovines. Recently, studies have been reported using wireless devices (like ultrasonic and radio-frequency (RF) based pressure sensors) to detect DH. But hitherto, little has been reported on using polyvinylidene fluoride (PVDF)-based sensors mounted on the diaphragm of bovine to detect the recurrence of the DH post-surgery. In this work, the PVDF-hydroxyapatite (HAP)- chitosan (CS) composite in the proportion of 90-8-2 (wt.%) was used as a substrate for sensor fabrication based on microstrip patch antenna (MPA). Based on the results, the parts of the sensor, that is, substrate, patch, and the ground plane, were designed in the high-frequency structural simulation (HFSS) software assigned with the material properties of PVDF-HAP-CS (as substrate) and 17-4 precipitated hardened (PH) stainless steel (SS) alloy (as patch or ground plane). Upon simulation, it was observed that some deviation in resonance frequency occurred with/ without the natural bovine diaphragm, which was verified based on experimental analysis. The parts were 3D printed for validation through material extrusion (MEX) and direct metal laser sintering (DMLS) processes. Upon testing using a vector network analyzer (VNA), it was observed that the sensor without the diaphragm resonated at 3036.57 MHz with a return loss (S11) of −12.81 dB, whereas the sensor with the diaphragm resonated at 2019.35 MHz with an S11 of −21.06 dB. This shift in frequency with/without the diaphragm is measurable in the industrial, scientific, and medical (ISM) frequency band on a Bluetooth device to detect the reoccurrence of DH.
Incidence of non-alcoholic fatty liver disease in antiretroviral therapy-naïve people with human immunodeficiency virus who start DTG/ABC/3TC compared to BIC/FTC/TAF at 48-week follow-up
Authors: Cano Díaz Ana Luz , Triana González Salma , Salinas Velázquez Gloria Elizabeth , Mata Marín José Antonio , Gaytán Martínez Jesús Enrique , Mauss Stefan 
Published: September 2024

Purpose To determine the incidence of non-alcoholic fatty liver disease (NAFLD) by non-invasive methods in people living with HIV (PLWH). Methods Prospective cohort, in PLWH naïve to antiretroviral therapy, starting bictegravir (BIC) or dolutegravir (DTG) at the Hospital de Infectología “La Raza”, in Mexico City, from February 2021 to August 2023. We measured at baseline and 48 weeks triglycerides and glucose index (TyG), fatty liver index (FLI), hepatic steatosis index (HSI) and liver ultrasonography; relative risk (RR) for developing NAFLD was determined. Results At 48 weeks, TyG index in BIC-group 4.54 (IQR 4.36–4.75), in DTG-group 4.66 (IQR 4.49–4.80), p = .080; HSI in BIC-group 30.30 (IQR 28.12–33.70), in DTG-group 30.85 (IQR 28.02–34.50), p = .650; FLI in BIC-group 14.88 (IQR 7.91–31.80), in DTG-group 19.49 (IQR 8.49–32.28), p = .729; NAFLD was detected by US in 6 [10.3% (95%CI 4.8%–20.7%)] in BIC-group and, 7 [10.9% (95%CI 6.4%–20.9%)] in DTG-group, p = .916. Risk factors for NAFLD development were baseline BMI ≥25 kg/m2, baseline HDL-c <40 mg/dL, and FIB-4 >1.3 at 48 weeks. Conclusion There is a high incidence of NAFLD in PLWH who start a second generation INSTI at 48 weeks; baseline overweight, low HDL-cholesterol and FIB-4 >1.3 at 48 weeks of treatment were independent risk factors for NAFLD development.