bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ferromagnetic frozen structures from the dipolar hard spheres fluid at moderate and small volume fractions
Authors: Malherbe J-G , Russier V , Alonso Juan J 
Published: April 2023

Abstract
We study the magnetic phase diagram of an ensemble of dipolar hard spheres (DHSs) with or without uniaxial anisotropy and frozen in position on a disordered structure by tempered Monte Carlo simulations. The crucial point is to consider an anisotropic structure, obtained from the liquid state of the DHS fluid, frozen in its polarized state at low temperature. The freezing inverse temperature

β

f

determines the degree of anisotropy of the structure which is quantified through a structural nematic order parameter,

λ

s

. The case of the non zero uniaxial anisotropy is considered only in its infinitely strong strength limit where the system transforms in a dipolar Ising model (DIM). The important finding of this work is that both the DHS and the DIM with a frozen structure build in this way present a ferromagnetic phase at volume fractions below the threshold value where the corresponding isotropic DHS systems exhibit a spin glass phase at low temperature.
A novel data-driven method for fuel-consumption prediction based on fast converged kernel extreme learning machine
Authors: Lyu Zhichao , Wu Guangqiang , Wang Qiming 
Published: April 2023

Abstract
An accurate fuel consumption prediction is significant to fuel-economy-oriented optimization, which can improve vehicle fuel economy. Based on the data-driven prediction framework, this paper proposes a real-time fuel consumption prediction model (RFCPM) using kernel extreme learning machine (KELM) which is optimized by fast converged grey wolf algorithm (FCGWA). A new steering function of FCGWA and a new activation function for KELM are presented to ensure the fast converge speed and higher accuracy performance. First, the characteristic variables of RFCPM are selected by reference to the model-based fuel consumption prediction method. Second, a KELM is adopted to predict fuel consumption. Third, FCGWA is adopted to select the best parameters of KELM using k-fold cross-validation method. Finally, the best model is chosen through real-vehicle test. Test results are compared with the original ELM and the wildly used WNN. The experiment shows that the proposed method significantly outperforms the original ELM and WNN in terms of both prediction accuracy and training time.
Microvibration streaming measurements using dynamic compressed sensing for satellites
Authors: Li Li , Zhou Miaomiao , Zhu Ye , Tao Lixuan , Liang Xuwen 
Published: April 2023

Abstract
Long-term monitoring of satellite microvibrations generates a significant amount of data streams, placing strain on satellites with limited transmission capacity. To relieve this transmission strain, a dynamic compressed sensing (CS) framework is proposed for measuring satellite microvibrations. Microvibration streams are measured block by block and then reconstructed using a dynamic recovery algorithm. The recovery solution of one block can be used as a priori knowledge for the next block, allowing for faster updates. However, existing dynamic recovery algorithms are only applicable in the real domain and cannot be applied to microvibrations projected on a Fourier basis in the complex domain. In light of this event, the dynamic homotopy algorithm is expanded to the complex domain to deal with microvibration signals that are sparse in the Fourier basis. In comparison to conventional uniform sampling methods, the experimental results show that the dynamic CS with the expanded recovery algorithm can achieve a maximum root-mean-square acceleration (Grms) deviation of 4% in power spectrum density with one-fifth of the sampling points. Compared to recovery algorithms applicable to fixed measurements, the dynamic algorithm can achieve comparable accuracy in about one-third of the computation time. The experimental findings demonstrate the feasibility of satellite microvibrations measurements using dynamic CS.
In situ correction of recombination effects in ultra-high dose rate irradiations with protons
Authors: Schaefer R , Psoroulas S , Weber D C 
Published: April 2023

Abstract

Background. At the Center for Proton Therapy at the Paul Scherrer Institute (PSI) the delivery of proton radiation is controlled via gas-based ionization chambers: the beam is turned off when a certain amount of preset charge has been collected. At low dose rates the charge collection efficiency in these detectors is unity, at ultra-high dose rates it is less due to induced charge recombination effects. If not corrected, the latter would lead to an overdosage. Purpose. In the scope of this work, we developed a novel approach to an in situ charge recombination correction for our dose defining detectors, when irradiated with a proton beam at ultra-high dose rates. This approach is based on the Two-Voltage-Method. Methods. We have translated this method to two separate devices operated simultaneously at different conditions. By doing so, the charge collection losses can be corrected directly and without the need for empirical correction values. This approach has been tested at ultra-high dose rates; proton beam was delivered by the COMET cyclotron to Gantry 1 at PSI. Results. We were able to correct the charge losses caused by recombination effects at local beam currents of approximately 700 nA (i.e. instantaneous dose rate of 3600 Gy s–1 at isocenter). The corrected collected charges in our gaseous detectors were compared against recombination-free measurements with a Faraday cup. The ratio of both quantities shows no significant dose rate dependence within their respective combined uncertainties. Conclusions. Correcting recombination effects in our gas-based detectors with the novel method greatly eases the handling of Gantry 1 as ‘FLASH test bench’. Not only is the application of a preset dose more accurate compared to using an empirical correction curve, also the re-determination of empirical correction curves in the case of a beam phase space change can be omitted.
A deep learning approach for automatic delineation of clinical target volume in stereotactic partial breast irradiation (S-PBI)
Authors: Kazemimoghadam Mahdieh , Yang Zi , Chen Mingli , Rahimi Asal , Kim Nathan , Alluri Prasanna , Nwachukwu Chika , Lu Weiguo , Gu Xuejun 
Published: April 2023

Abstract
Accurate and efficient delineation of the clinical target volume (CTV) is of utmost significance in post-operative breast cancer radiotherapy. However, CTV delineation is challenging as the exact extent of microscopic disease encompassed by CTV is not visualizable in radiological images and remains uncertain. We proposed to mimic physicians’ contouring practice for CTV segmentation in stereotactic partial breast irradiation (S-PBI) where CTV is derived from tumor bed volume (TBV) via a margin expansion followed by correcting the extensions for anatomical barriers of tumor invasion (e.g. skin, chest wall). We proposed a deep-learning model, where CT images and the corresponding TBV masks formed a multi-channel input for a 3D U-Net based architecture. The design guided the model to encode the location-related image features and directed the network to focus on TBV to initiate CTV segmentation. Gradient weighted class activation map (Grad-CAM) visualizations of the model predictions revealed that the extension rules and geometric/anatomical boundaries were learnt during model training to assist the network to limit the expansion to a certain distance from the chest wall and the skin. We retrospectively collected 175 prone CT images from 35 post-operative breast cancer patients who received 5-fraction partial breast irradiation regimen on GammaPod. The 35 patients were randomly split into training (25), validation (5) and test (5) sets. Our model achieved mean (standard deviation) of 0.94 (±0.02), 2.46 (±0.5) mm, and 0.53 (±0.14) mm for Dice similarity coefficient, 95th percentile Hausdorff distance, and average symmetric surface distance respectively on the test set. The results are promising for improving the efficiency and accuracy of CTV delineation during on-line treatment planning procedure.
Device-independent oblivious transfer from the bounded-quantum-storage-model and computational assumptions
Authors: Broadbent Anne , Yuen Peter 
Published: April 2023

Abstract
We present a device-independent protocol for oblivious transfer (DIOT) and analyse its security under the assumption that the receiver’s quantum storage is bounded during protocol execution and that the device behaves independently and identically in each round. We additionally require that, for each device component, the input corresponding to the choice of measurement basis, and the resulting output, is communicated only with the party holding that component. Our protocol is everlastingly secure and, compared to previous DIOT protocols, it is less strict about the non-communication assumptions that are typical from protocols that use Bell inequality violations; instead, the device-independence comes from a protocol for self-testing of a single (quantum) device which makes use of a post-quantum computational assumption.
Clarifying some common misconceptions about gravitational effects in free falling frames
Authors: Re Fiorentin Stefano 
Published: April 2023

Abstract
It is often stated that in free falling systems, locally, the effects of gravity can be ‘transformed away’. This statement is part of many, even authoritative, versions of the so-called ‘Strong Equivalence Principle’. Gravitational effects, however, cannot be completely ‘transformed away’ in free falling systems. In fact, it is well known and generally remarked in the literature that there are (usually tiny) gravitational effects related to the second derivatives of the components of the metric tensor that are not eliminated even in free falling systems. But the misconception is worsened by the fact that there are other fundamental gravitational effects that also occur in free falling systems, which we focus on in this paper. Firstly, the gravitational slowing of time: a fact fundamental to the operation of the Global Positioning System, the occurrence of which in free falling systems subject to gravitational acceleration is generally explained by invoking the axiom that acceleration does not affect the flow of time (the so-called ‘clock hypothesis’). Secondly, there is a gravitational effect on space, dual to that on time and consisting of its stretching (as has been shown elsewhere), which is equally present in free falling frames. We will show here that it is possible to deduce the presence of these gravitational effects on time and space in free falling systems as well, directly from the metric, thus clarifying that neither the small gravitational effects related to the curvature of spacetime nor the fundamental gravitational effects on time and space can be eliminated in free falling systems. In the latter, only gravitational acceleration is actually ‘transformed away’, making them particular inertial frames; the Equivalence Principle (without the designation ‘Strong’ anymore) should be limited to stating this.
Comprehensive experimental study of NBνN barrier structures based on n-HgCdTe MBE for detection in MWIR and LWIR spectra
Authors: Voitsekhovskii Alexander V , Dzyadukh Stanislav M , Gorn Dmitry I , Dvoretsky Sergey A , Mikhailov Nikolay N , Sidorov Georgiy Yu , Yakushev Maxim V 
Published: April 2023

Abstract
This work is devoted to a comprehensive experimental study of the electrical and photoelectric characteristics of barrier photosensitive structures in the NBνN configuration based on n-HgCdTe (MCT). Seven different types of photosensitive structures for middle wavelength (MWIR) and long wavelength (LWIR) infrared (IR) radiation ranges grown by molecular beam epitaxy (MBE) have been studied by complex conductivity spectroscopy method. The current-voltage characteristics (CVC) were measured both in the dark and in the presence of illumination. Based on the measured dependences of the dark current density on temperature and the ratio of the perimeter to the area of the structure, the dominant contribution of the bulk current component compared to the surface component for the MWIR structure (x ∼ 0.30) was established. This fact was confirmed by the value of the activation energy (from the Arrhenius plots) corresponding to the band gap. The results of frequency measurements of the differential conductivity of MIS structures based on NBνN also give a close activation energy, which corresponds to the diffusion limitation. LWIR structures (x ∼ 0.20) are characterized by an increase in the contribution of the surface leakage current in the total dark current. In this case, the activation energy determined from MIS measurements exceeds the band gap of the ν-layer, which is associated with the presence of an energy barrier for holes in the valence band. It is shown that if the problem of passivation of mesa structures is solved, it is possible to fabricate efficient MWIR and LWIR nBn, NBνN detectors based on MBE HgCdTe with high threshold parameters.
Cosmic decoherence: primordial power spectra and non-Gaussianities
Authors: Daddi Hammou Aoumeur , Bartolo Nicola 
Published: April 2023

Abstract
We study the effect of quantum decoherence on the inflationary cosmological perturbations.
This process might imprint specific observational signatures revealing the quantum nature of the
inflationary mechanism being related to the longstanding issue of the quantum-to-classical
transition of inflationary fluctuations. Several works have investigated the effect of quantum
decoherence on the statistical properties of primordial fluctuations. In particular, it has been
shown that cosmic decoherence leads to corrections to the curvature power spectrum predicted by
standard slow-roll inflation. Equally interesting, a non zero curvature trispectrum has been
shown to be purely induced by cosmic decoherence but, surprisingly, decoherence seems not to
generate any bispectrum. We further develop such an analysis by adopting a generalized form of the
pointer observable, showing that decoherence does induce a non vanishing curvature bispectrum and
providing a specific underlying concrete physical process. Present constraints on primordial
bispectra allow to put an upper bound on the strength of the environment-system interaction. In
full generality, the decoherence-induced bispectrum can be scale dependent provided one imposes
the corresponding correction to the power spectrum to be scale independent. Such scale dependence
on the largest cosmological scales might represent a distinctive imprint of the quantum
decoherence process taking place during inflation. We also provide a criterion that allows to
understand when cosmic decoherence induces scale independent corrections, independently of the
type of environment considered. As a final result, we study the effect of cosmic decoherence on
tensor perturbations and we derive the decoherence corrected tensor-to-scalar perturbation
ratio. In specific cases, decoherence induces a blue tilted correction to the standard tensor
power spectrum.
Adolescent Growth Spurt and Type 2 Diabetes Risk in Southwestern American Indians
Authors: Ramirez-Luzuriaga Maria J , Kobes Sayuko , Sinha Madhumita , Knowler William C , Hanson Robert L 
Published: April 2023

Abstract
Early puberty onset is associated with higher risk of diabetes, but most studies have not accounted for childhood factors that may confound the association. Using data from a study conducted in an Indigenous community in Arizona (1965–2007), we examined associations of timing and velocity of the adolescent growth spurt with type 2 diabetes, and whether these associations are mediated by childhood body mass index and insulinemia. Adolescent growth parameters were derived from the Preece-Baines growth model, a parametric growth curve fitted to longitudinal height data, for 861 participants with height measurements spanning the whole period of growth. In males, older age at take-off, age at peak velocity, and age at maturation were associated with decreased prevalence of diabetes (odds ratio (OR) = 0.43 per year, 95% confidence interval (CI): 0.27, 0.69; OR = 0.50, 95% CI: 0.35, 0.72; OR = 0.58, 95% CI: 0.41, 0.83, respectively), while higher velocity at take-off was associated with increased risk (OR = 3.47 per cm/year, 95% CI: 1.87, 6.42) adjusting for age, birth year, and maternal diabetes. Similar results were observed with incident diabetes. Our findings suggest that an early and accelerated adolescent growth spurt is a risk factor for diabetes, at least in males. These associations are only partially explained by measures of adiposity and insulinemia.
MetChem: a new pipeline to explore structural similarity across metabolite modules
Authors: Abdel-Shafy Ebtesam A , Melak Tadele , MacIntyre David A , Zadra Giorgia , Zerbini Luiz F , Piazza Silvano , Cacciatore Stefano 
Published: April 2023

Abstract

Summary
Computational analysis and interpretation of metabolomic profiling data remains a major challenge in translational research. Exploring metabolic biomarkers and dysregulated metabolic pathways associated with a patient phenotype could offer new opportunities for targeted therapeutic intervention. Metabolite clustering based on structural similarity has the potential to uncover common underpinnings of biological processes. To address this need, we have developed the MetChem package. MetChem is a quick and simple tool that allows to classify metabolites in structurally related modules, thus revealing their functional information.

Availabilityand implementation
MetChem is freely available from the R archive CRAN (http://cran.r-project.org). The software is distributed under the GNU General Public License (version 3 or later).
DFHiC: a dilated full convolution model to enhance the resolution of Hi-C data
Authors: Wang Bin , Liu Kun , Li Yaohang , Wang Jianxin 
Published: April 2023

Abstract

Motivation
Hi-C technology has been the most widely used chromosome conformation capture (3C) experiment that measures the frequency of all paired interactions in the entire genome, which is a powerful tool for studying the 3D structure of the genome. The fineness of the constructed genome structure depends on the resolution of Hi-C data. However, due to the fact that high-resolution Hi-C data require deep sequencing and thus high experimental cost, most available Hi-C data are in low-resolution. Hence, it is essential to enhance the quality of Hi-C data by developing the effective computational methods.

Results
In this work, we propose a novel method, so-called DFHiC, which generates the high-resolution Hi-C matrix from the low-resolution Hi-C matrix in the framework of the dilated convolutional neural network. The dilated convolution is able to effectively explore the global patterns in the overall Hi-C matrix by taking advantage of the information of the Hi-C matrix in a way of the longer genomic distance. Consequently, DFHiC can improve the resolution of the Hi-C matrix reliably and accurately. More importantly, the super-resolution Hi-C data enhanced by DFHiC is more in line with the real high-resolution Hi-C data than those done by the other existing methods, in terms of both chromatin significant interactions and identifying topologically associating domains.

Availability and implementation
https://github.com/BinWangCSU/DFHiC.
The Effects of Decent Work and Social Support on Enhancing Collective Psychological Ownership Amongst Young Adult Social Workers
Authors: Su Xuebing , Wong Victor 
Published: April 2023

Abstract
It has been a pronounced concern for social service organisations (SSOs) on how to foster a sense of co-ownership amongst their employees. A total of 937 valid questionnaires were collected amongst social worker participants aged twenty-one to twenty-nine years working in three different places of China, namely, Hong Kong, Shenzhen and Guangzhou. By confirming the hypotheses, the findings revealed that decent work and social support were positively associated with the collective psychological ownership (CPO) held by young adult social workers, and decent work enhanced CPO shared by them through an indirect mechanism of enhancing their social support at work. This is the first-ever study providing empirical evidence to support the association of decent work and social support with CPO amongst young adult employees in organisational context. The findings of this study can help inform the development of human resources management strategies for cultivating CPO, justify and expand the promotion of decent work in conjunction with the framework of psychology of working theory and interpersonal perspective, and inspire relevant research and practice with regard to the personal development of young adult social workers and the sustainable development of SSOs.
Disrupted resting-sate brain network dynamics in children born extremely preterm
Authors: Padilla Nelly , Escrichs Anira , del Agua Elvira , Kringelbach Morten , Donaire Antonio , Deco Gustavo , Åden Ulrika 
Published: April 2023

Abstract
The developing brain has to adapt to environmental and intrinsic insults after extremely preterm (EPT) birth. Ongoing maturational processes maximize their fit to the environment and this can provide a substrate for neurodevelopmental failures. Resting-state functional magnetic resonance imaging was used to scan 33 children born EPT, at &lt; 27 weeks of gestational age, and 26 full-term controls at 10 years of age. We studied the capability of a brain area to propagate neural information (intrinsic ignition) and its variability across time (node-metastability). This framework was computed for the dorsal attention network (DAN), frontoparietal, default-mode network (DMN), and the salience, limbic, visual, and somatosensory networks. The EPT group showed reduced intrinsic ignition in the DMN and DAN, compared with the controls, and reduced node-metastability in the DMN, DAN, and salience networks. Intrinsic ignition and node-metastability values correlated with cognitive performance at 12 years of age in both groups, but only survived in the term group after adjustment. Preterm birth disturbed the signatures of functional brain organization at rest in 3 core high-order networks: DMN, salience, and DAN. Identifying vulnerable resting-state networks after EPT birth may lead to interventions that aim to rebalance brain function.