bluuebunny/crossref_metadata_2025_split huggingface dataset:
Personalized aerosolised bacteriophage treatment of a chronic lung infection due to multidrug-resistant Pseudomonas aeruginosa
Authors: Köhler Thilo , Luscher Alexandre , Falconnet Léna , Resch Grégory , McBride Robert , Mai Quynh-Anh , Simonin Juliette L. , Chanson Marc , Maco Bohumil , Galiotto Raphaël , Riat Arnaud , Civic Natacha , Docquier Mylène , McCallin Shawna , Chan Benjamin , van Delden Christian 
Published: June 2023

AbstractBacteriophage therapy has been suggested as an alternative or complementary strategy for the treatment of multidrug resistant (MDR) bacterial infections. Here, we report the favourable clinical evolution of a 41-year-old male patient with a Kartagener syndrome complicated by a life-threatening chronic MDR Pseudomonas aeruginosa infection, who is treated successfully with iterative aerosolized phage treatments specifically directed against the patient’s isolate. We follow the longitudinal evolution of both phage and bacterial loads during and after phage administration in respiratory samples. Phage titres in consecutive sputum samples indicate in patient phage replication. Phenotypic analysis and whole genome sequencing of sequential bacterial isolates reveals a clonal, but phenotypically diverse population of hypermutator strains. The MDR phenotype in the collected isolates is multifactorial and mainly due to spontaneous chromosomal mutations. All isolates recovered after phage treatment remain phage susceptible. These results demonstrate that clinically significant improvement is achievable by personalised phage therapy even in the absence of complete eradication of P. aeruginosa lung colonization.
In-orbit demonstration of a re-trainable machine learning payload for processing optical imagery
Authors: Mateo-Garcia Gonzalo , Veitch-Michaelis Josh , Purcell Cormac , Longepe Nicolas , Reid Simon , Anlind Alice , Bruhn Fredrik , Parr James , Mathieu Pierre Philippe 
Published: June 2023

AbstractCognitive cloud computing in space (3CS) describes a new frontier of space innovation powered by Artificial Intelligence, enabling an explosion of new applications in observing our planet and enabling deep space exploration. In this framework, machine learning (ML) payloads—isolated software capable of extracting high level information from onboard sensors—are key to accomplish this vision. In this work we demonstrate, in a satellite deployed in orbit, a ML payload called ‘WorldFloods’ that is able to send compressed flood maps from sensed images. In particular, we perform a set of experiments to: (1) compare different segmentation models on different processing variables critical for onboard deployment, (2) show that we can produce, onboard, vectorised polygons delineating the detected flood water from a full Sentinel-2 tile, (3) retrain the model with few images of the onboard sensor downlinked to Earth and (4) demonstrate that this new model can be uplinked to the satellite and run on new images acquired by its camera. Overall our work demonstrates that ML-based models deployed in orbit can be updated if new information is available, paving the way for agile integration of onboard and onground processing and “on the fly” continuous learning.
Parabolic gratings enhance the X-ray sensitivity of Talbot interferograms
Authors: Zangi Pouria , Ikematsu Katsumasa , Meyer Pascal , Takano Hidekazu , Wu Yanlin , Gutekunst Josephine , Börner Martin , Last Arndt , Korvink Jan G. , Momose Atsushi 
Published: June 2023

AbstractIn grating-based X-ray Talbot interferometry, the wave nature of X-ray radiation is exploited to generate phase contrast images of objects that do not generate sufficient contrast in conventional X-ray imaging relying on X-ray absorption. The phase sensitivity of this interferometric technique is proportional to the interferometer length and inversely proportional to the period of gratings. However, the limited spatial coherency of X-rays limits the maximum interferometer length, and the ability to obtain smaller-period gratings is limited by the manufacturing process. Here, we propose a new optical configuration that employs a combination of a converging parabolic micro-lens array and a diverging micro-lens array, instead of a binary phase grating. Without changing the grating period or the interferometer length, the phase signal is enhanced because the beam deflection by a sample is amplified through the array of converging-diverging micro-lens pairs. We demonstrate that the differential phase signal detected by our proposed set-up is twice that of a Talbot interferometer, using the same binary absorption grating, and with the same overall inter-grating distance.
Distributed MPC of vehicle platoons with guaranteed consensus and string stability
Authors: Feng Yangyang , Yu Shuyou , Chen Hao , Li Yongfu , Shi Shuming , Yu Jianhua , Chen Hong 
Published: June 2023

AbstractControl of vehicle platoon can effectively reduce the traffic accidents caused by fatigue driving and misoperation, reduce air resistance by eliminating the inter-vehicle gap which will effectively reduce fuel consumption and exhaust emissions. A hierarchical control scheme for vehicle platoons is proposed in this paper. Considering safety, consistency, and passengers’ comfort, a synchronous distributed model predictive controller is designed as an upper-level controller, in which a constraint guaranteeing string stability is introduced into the involved local optimization problem so as to guarantee that the inter-vehicle gap error gradually attenuates as it propagates downstream. A terminal equality constraint is added to guarantee asymptotic consensus of vehicle platoons. By constructing the vehicle inverse longitudinal dynamics model, a lower-level control scheme with feedforward and feedback controllers is designed to adjust the throttle angle and brake pressure of vehicles. A PID is used as the feedback controller to eliminate the influence of unmodeled dynamics and uncertainties. Finally, the performance of longitudinal tracking with the proposed control scheme is validated by joint simulations with PreScan, CarSim, and Simulink.
Shotgun proteomics identification of proteins expressed in the Descemet’s membrane of patients with Fuchs endothelial corneal dystrophy
Authors: Nakagawa Tatsuya , Okumura Naoki , Ikegawa Masaya , Toyama Yumiko , Nirasawa Takashi , Mascarelli Frederic , Vaitinadapoule Hanielle , Aouimeur Ines , He Zhiguo , Gain Philippe , Thuret Gilles , Koizumi Noriko 
Published: June 2023

AbstractFuchs endothelial corneal dystrophy (FECD) is a slowly evolving, bilateral disease of the corneal endothelium, characterized by an abnormal accumulation of extracellular matrix (ECM) in the basement membrane (Descemet’s membrane, DM). This results in the formation of small round excrescences, called guttae, and a progressive disappearance of endothelial cells. In the intermediate stage, the numerous guttae create significant optical aberrations, and in the late stage, the loss of endothelial function leads to permanent corneal edema. The molecular components of guttae have not been fully elucidated. In the current study, we conducted shotgun proteomics of the DMs, including guttae, obtained from patients with FECD and revealed that 32 proteins were expressed only in the FECD-DMs but not in the DMs of control subjects. Subsequent enrichment analyses identified associations with multiple ECM-related pathways. Immunostaining of flat-mounted DMs confirmed that 4 of the top 5 identified proteins (hemoglobin α, SRPX2, tenascin-C, and hemoglobin γδεβ) were expressed in FECD-DMs but not in non-FECD-DMs. Fibrinogen α was strongly expressed in FECD-DMs, but weakly expressed in non-FECD-DMs. We also demonstrated that matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS) can display the in situ spatial distribution of biomolecules expressed in the DM, including the guttae.
Fusion of visible and thermal images improves automated detection and classification of animals for drone surveys
Authors: Krishnan B. Santhana , Jones Landon R. , Elmore Jared A. , Samiappan Sathishkumar , Evans Kristine O. , Pfeiffer Morgan B. , Blackwell Bradley F. , Iglay Raymond B. 
Published: June 2023

AbstractVisible and thermal images acquired from drones (unoccupied aircraft systems) have substantially improved animal monitoring. Combining complementary information from both image types provides a powerful approach for automating detection and classification of multiple animal species to augment drone surveys. We compared eight image fusion methods using thermal and visible drone images combined with two supervised deep learning models, to evaluate the detection and classification of white-tailed deer (Odocoileus virginianus), domestic cow (Bos taurus), and domestic horse (Equus caballus). We classified visible and thermal images separately and compared them with the results of image fusion. Fused images provided minimal improvement for cows and horses compared to visible images alone, likely because the size, shape, and color of these species made them conspicuous against the background. For white-tailed deer, which were typically cryptic against their backgrounds and often in shadows in visible images, the added information from thermal images improved detection and classification in fusion methods from 15 to 85%. Our results suggest that image fusion is ideal for surveying animals inconspicuous from their backgrounds, and our approach uses few image pairs to train compared to typical machine-learning methods. We discuss computational and field considerations to improve drone surveys using our fusion approach.
New library of phase-change materials with their selection by the Rényi entropy method
Authors: Kulish Vladimir , Aslfattahi Navid , Schmirler Michal , Sláma Pavel 
Published: June 2023

AbstractThe secret to the successful and widespread deployment of solar energy for thermal applications is effective and affordable heat storage. The ability to provide a high energy storage density and the capacity to store heat at a constant temperature corresponding to the phase transition temperature of the heat storage material (phase-change material or PCM) make latent heat storage one of the most alluring methods of heat storage. Today, it can be challenging to obtain all the published data on PCM qualities, including relevant non-thermodynamic properties in addition to thermodynamic ones. The developed new PCM library contains various types of PCMs which possess broad range of operation temperatures. This new library consists of 500 substances along with nine associated properties such as phase change temperature, solidification temperature, maximum operation temperature, density, latent heat and specific heat capacity, thermal conductivity, cycleability and ignition temperature. Furthermore, a new PCM selection method, based on calculating the Rényi entropy for a given set of selection criteria, has been proposed. The newly developed selection method requires no subjective judgements. The idea of the method is inspired by earlier applications of fractal analysis methods in many areas of research.
Simplifying asteroseismic analysis of solar-like oscillators
Authors: Nielsen M. B. , Davies G. R. , Chaplin W. J. , Ball W. H. , Ong J. M. J. , Hatt E. , Jones B. P. , Logue M. 
Published: June 2023

Context.The asteroseismic analysis of stellar power density spectra is often computationally expensive. The models used in the analysis may require several dozen parameters to accurately describe features in the spectra caused by the oscillation modes and surface granulation. Many of these parameters are often highly correlated, making the parameter space difficult to quickly and accurately sample. They are, however, all dependent on a much smaller set of parameters, namely the fundamental stellar properties.Aims.We aim to leverage this to develop a method for simplifying the process of sampling the model parameter space for the asteroseismic analysis of solar-like oscillators, with an emphasis on mode identification.Methods.Using a large set of previous observations, we applied principal component analysis to the sample covariance matrix to select a new basis on which to sample the model parameters. Selecting the subset of basis vectors that explains the majority of the sample variance, we then redefined the model parameter prior probability density distributions in terms of a smaller set of latent parameters.Results.We are able to reduce the dimensionality of the sampled parameter space by a factor of two to three. The number of latent parameters needed to accurately model the stellar oscillation spectra cannot be determined exactly but is likely only between four and six. Using two latent parameters, the method is able to produce models that describe the bulk features of the oscillation spectrum, while including more latent parameters allows for a frequency precision better than ≈10% of the small frequency separation for a given target.Conclusions.We find that sampling a lower-rank latent parameter space still allows for accurate mode identification and parameter estimation on solar-like oscillators over a wide range of evolutionary stages. This allows for the potential to increase the complexity of spectrum models without a corresponding increase in computational expense.
The nanoscale pore characteristics of coking coals. Part 4: The relationship between nanoscale pore characteristics and Gieseler fluidity
Authors: Zhang Song , Cheng Huan , Shi Chunlei , Wang Qi , Wang Yiming , Xiao Luying , Hou Yunlong 
Published: June 2023

The nanoscale pore characteristics of six coal samples was determined using low-temperature N2 physisorption method in Part 3 of this series of articles [Cheng et al., Metall. Res. Technol. 114, 117 (2017)], and the possibility of nanoscale pore structure parameters to supplement and improve the existing coking coal property evaluation system is preliminarily demonstrated. The study focused on the relationship between nanoscale pore characteristics and Gieseler fluidity. The results show that external specific surface areas Sext-SAST and Gieseler fluidity thermoplastic parameters (plastic range ΔT and maximum fluidity MF expressed in logarithmic form) exhibit a primary linear relationship. External pore volume VBJH-ext and average pore size d̄DB display a quadratic parabolic relationship to thermoplastic parameters ΔT and LogMF. The correlations of the prediction models constructed for ΔT and LogMF with Sext-SAST, VBJH-ext and d̄DB as independent variables reached 0.97 and 0.96, respectively, indicating that the nanoscale pore characteristics are closely related to the Gieseler fluidity, and can play an important role in predicting the thermoplasticity of coking coals.
Die Split-Turnover-Pectoralislappenplastik: eine einfache und sichere
Methode zur Deckung sternaler Defekte
Authors: Spengler Claas , Masberg Frank , Mett Roland 
Published: June 2023

ZusammenfassungDie Pectoralis-Muskellappenplastik ist zur Deckung sternaler Defekte nach tiefer
sternaler Wundinfektion weit verbreitet. Sie kann entweder als klassischer
Advancement-Flap, gestielt an der A. thoracoacromialis, oder als Turnover-Flap,
gestielt an den interkostalen Perforatoren der A. thoracica interna, gehoben
werden. Der Advancement-Flap hat den Nachteil, dass eine Bedeckung des
inferioren Sternumdrittels oft nicht erzielt werden kann, während der
Turnover-Flap zwar das inferiore und mediale Drittel bedeckt, oft aber im
kranialen Drittel nicht ausreicht. Die Autoren beschreiben eine neuartige
Methode zum Breitengewinn der Turnover-Pectoralis-Lappenplastik durch
Aufsplitten dieser entlang der Muskelfasern.Bei allen zwölf Patienten,
die zwischen 2017 und 2022 mit dieser Methode behandelt wurden, konnte eine
vollständige Abheilung sowie ein Wundverschluss erzielt werden. Die
Split-Pectoralis-Lappenplastik stellt damit eine sichere und effektive Methode
zur Defektdeckung sternaler Defekte dar.
The Impact of Polypharmacy on the Effectiveness and Safety of Non-vitamin K Antagonist Oral Anticoagulants in Patients with Atrial Fibrillation
Authors: Grymonprez Maxim , Petrovic Mirko , De Backer Tine L. , Steurbaut Stephane , Lahousse Lies 
Published: June 2023

Background Polypharmacy may affect outcomes in patients with atrial fibrillation (AF) using non-vitamin K antagonist oral anticoagulants (NOACs) or vitamin K antagonists (VKAs) due to interactions or reduced adherence, but comparative data are lacking. Therefore, the impact of polypharmacy on AF-related outcomes and benefit–risk profiles of NOACs in patients with polypharmacy were investigated.
Methods AF patients initiating anticoagulation between 2013 and 2019 were included using Belgian nationwide data. Inverse probability of treatment weighted Cox regression was used to investigate outcomes.
Results Among 254,478 AF patients, 167,847 (66.0%) used ≥5 drugs. Polypharmacy was associated with higher stroke or systemic embolism (stroke/SE) (adjusted hazard ratio [aHR]: 1.08, 95% confidence interval [CI]: 1.02–1.15), all-cause mortality (aHR: 1.45, 95% CI: 1.40–1.50), and major bleeding risks (aHR: 1.29, 95% CI: 1.23–1.35). Among patients with polypharmacy, NOACs were associated with lower stroke/SE (aHR: 0.68, 95% CI: 0.63–0.73), all-cause mortality (aHR: 0.80, 95% CI: 0.77–0.84), major bleeding (aHR: 0.92, 95% CI: 0.87–0.97), and intracranial bleeding risks (aHR: 0.77, 95% CI: 0.69–0.85), but higher gastrointestinal bleeding risks (aHR: 1.10, 95% CI: 1.01–1.19) compared to VKAs. Major bleeding risks were lower with apixaban (aHR: 0.79, 95% CI: 0.74–0.85), but nonsignificantly different with other NOACs compared to VKAs. Lower major bleeding risks were observed with dabigatran (aHR: 0.91, 95% CI: 0.85–0.97) and apixaban (aHR: 0.77, 95% CI: 0.73–0.81) compared to rivaroxaban, and with apixaban compared to dabigatran (HR: 0.83, 95% CI: 0.77–0.90) and edoxaban (HR: 0.77, 95% CI: 0.70–0.85).
Conclusion Polypharmacy was associated with increased thromboembolic, bleeding, and mortality risks in AF patients. NOACs had better benefit–risk profiles than VKAs in patients with polypharmacy.
Inverse design of ultra-wideband transparent frequency selective surface absorbers based on evolutionary deep learning
Authors: Pan Yaxi , Dong Jian , Wang Meng , Luo Heng , Abdulkarim Yadgar I 
Published: June 2023

Abstract
Conventional frequency selective surface (FSS) absorbers design is time-consuming, involving multiple electromagnetic (EM) simulations for parameter scanning. A novel reverse design method is proposed utilizing evolutionary deep learning (EDL) based on an improved bacterial foraging optimization (IBFO) algorithm and a deep belief network. It establishes the relationship between the geometric structure and EM response. The combination of IBFO and EDL facilitates an efficient optimization for structural parameters, mitigating the ‘one-to-many’ problem and accelerating the design process. An optically transparent FSS absorber with an ultra-bandwidth of 8–18 GHz is designed to verify the proposed method’s capability. The simulation and experimental results demonstrate that the absorber displays exceptional characteristics such as polarization insensitivity and robustness under a 45° oblique incidence angle, making it a suitable candidate for radar stealth and photovoltaic solar energy applications. The proposed method can be applied to the design and optimization of various absorbers and complex EM devices.
Anisotropic transport properties and high-mobility of charge carriers of antiferromagnetic GdAgSb2
Authors: Roy Shubhankar , Singha Ratnadwip , Alam Rafiqul , Mandal Prabhat 
Published: June 2023

Abstract
We report detailed magnetic and magnetotransport properties of single-crystalline GdAgSb2 antiferromagnet. The electronic transport properties show metallic behavior along with large, anisotropic, and non-saturating magnetoresistance (MR) in transverse experimental configuration. At 2 K and 9 T, the value of MR reaches as high as ∼1.8×103%. The anisotropic MR along with additional features for applied magnetic field along some specific crystallographic directions reveal the quasi-two-dimensional nature of the Fermi surface of GdAgSb2. Hall resistivity confirms the presence of two types of charge carriers. The high carrier mobilities (∼1.2×104 cm2 V−1 s−1) and nearly-compensated electron and hole-density (∼1019 cm−3) could be responsible for the large transverse MR in GdAgSb2. We have also observed the de Haas–van Alphen oscillations in the magnetization measurements below 7 K. Furthermore, the robust planar Hall effect, which persists up to high temperatures, could indicate the nontrivial nature of the electronic band structure for GdAgSb2.
A stable r-adaptive mesh technique to analyze the advection-diffusion equation
Authors: Sultan Saad , Zhengce Zhang , Usman Muhammad 
Published: June 2023

Abstract
This paper offers a study of the moving mesh method employed in one-dimensional linear and nonlinear advection-diïffusion equations with different boundary and initial conditions. Advection and diffusion appear in the crux of the physical processes, where the transport of heat or other physical variables evolves. The aim is to present an accurate, stable moving finite-difference meshing scheme with its convergence. The velocity-profile of the considered cases is non-linear; therefore, the difference scheme needs mesh refinement. The moving mesh method analyzes the problem physics and adjusts the mesh according to the problem as it moves nodes in the region of more fluctuations. The approximate numerical results are estimated using four moving mesh partial differential equations with varying numbers of nodes. The moving mesh method is an r-adaptive technique that uses a fixed number of mesh nodes and moves the grids where error reduction is needed. The numerical solutions obtained are compared with the analytical solutions cited from the literature. The study presents five cases dealing with linear and non-linear examples in detail to understand the physics of the problem. The presented difference scheme is considerably more efficient than the numerical methods given in the literature.
The role of lifestyle in the association between frailty and all-cause mortality amongst older adults: a mediation analysis in the UK Biobank
Authors: Delgado-Velandia Mario , Maroto-Rodríguez Javier , Ortolá Rosario , Rodríguez-Artalejo Fernando , Sotos-Prieto Mercedes 
Published: June 2023

Abstract

Objective
frailty is a syndrome characterised by increased vulnerability to stressors, which manifests as higher death risk. Whilst guidelines for frailty management usually entails lifestyle modifications (e.g. physical exercise, diet), the mediating role of lifestyle on the excess mortality associated with frailty is unclear. This study estimates the death risk due to frailty that could be avoided with a healthy lifestyle in older adults.

Subjects and Methods
we analysed data from 91,906 British individuals aged ≥60 years recruited between 2006 and 2010. At baseline, frailty was identified according to Fried’s phenotype, and a four-item Healthy Lifestyle Index (HLS) was calculated based on physical activity, diet, smoking and alcohol consumption. Mortality was ascertained from baseline through 2021. A mediation analysis under the counterfactual framework was performed adjusting for the main confounders.

Results
during a median follow-up of 12.5 years, 9,383 deaths occurred. Frailty was directly associated with all-cause mortality (hazard ratio: 2.30 [95% confidence interval {CI} 2.07, 2.54]), and inversely associated with the HLS (ß: −0.45 points [−0.49, −0.40]). The hazard ratio [95%CI] for the direct effect of frailty on mortality was 2.12 [1.91, 2.34], whilst for the indirect effect (mediated by HLS) was 1.08 [1.07, 1.10]. The mediated proportion of HLS on mortality was 13.55% [11.26, 16.20], with physical activity having the highest proportion amongst the four HLS items (7.69% [5.00, 10.40]).

Conclusions
a healthy lifestyle partly mediates the association between frailty and mortality in British older adults. Since this was an exploratory mediation analysis, these results should be specifically tested in future research.