bluuebunny/crossref_metadata_2025_split huggingface dataset:
Biomedical engineering aspects of nanocellulose: a review
Authors: Rai Rohit , Dhar Prodyut 
Published: May 2022

AbstractCellulose is one of the most abundant renewable biopolymer in nature and is present as major constituent in both plant cell walls as well as synthesized by some microorganisms as extracellular products. In both the systems, cellulose self-assembles into a hierarchical ordered architecture to form micro to nano-fibrillated structures, on basis of which it is classified into various forms. Nanocellulose (NCs) exist as rod-shaped highly crystalline cellulose nanocrystals to high aspect ratio cellulose nanofibers, micro-fibrillated cellulose and bacterial cellulose (BC), depending upon the origin, structural and morphological properties. Moreover, NCs have been processed into diversified products ranging from composite films, coatings, hydrogels, aerogels, xerogels, organogels, rheological modifiers, optically active birefringent colored films using traditional-to-advanced manufacturing techniques. With such versatility in structure-property, NCs have profound application in areas of healthcare, packaging, cosmetics, energy, food, electronics, bioremediation, and biomedicine with promising commercial potential. Herein this review, we highlight the recent advancements in synthesis, fabrication, processing of NCs, with strategic chemical modification routes to tailor its properties for targeted biomedical applications. We also study the basic mechanism and models for biosynthesis of cellulose in both plant and microbial systems and understand the structural insights of NC polymorphism. The kinetics study for both enzymatic/chemical modifications of NCs and microbial growth behavior of BC under various reactor configurations are studied. The challenges associated with the commercial aspects as well as industrial scale production of pristine and functionalized NCs to meet the growing demands of market are discussed and prospective strategies to mitigate them are described. Finally, post chemical modification evaluation of biological and inherent properties of NC are important to determine their efficacy for development of various products and technologies directed for biomedical applications.
NiCoSe4 nanoparticles derived from nickel–cobalt Prussian blue analogues on N-doped reduced graphene oxide for high-performance asymmetric supercapacitors
Authors: Yang Quanlu , Feng Qiaoliang , Xu Xin , Liu Yang , Yang Xuexue , Yang Fawang , Li Jiankun , Zhan Huiying , Wang Qianshan , Wu Shang 
Published: May 2022

Abstract
Synthesis of NiHCCo precursors via simple co-precipitation and nickel–cobalt tetraselenide composites grown on nitrogen-doped reduced graphene oxide (NiCoSe4/N-rGO) were fabricated using solvothermal method. The introduction of N-rGO used as a template effectively prevented agglomeration of NiCoSe4 nanoparticles and provided more active sites, which greatly increased the electrochemical and electrical conductivity for NiCoSe4/N-rGO. NiCoSe4/N-rGO-20 presents a remarkably elevated specific capacity of 120 mA h g−1 under current density of 1 A g−1. NiCoSe4/N-rGO-20 demonstrates an excellent cycle life and achieves a remarkable 83% retention rate over 3000 cycles with 10 A g−1. NiCoSe4/N-rGO-20//N-rGO asymmetric supercapacitor was constructed based on the NiCoSe4/N-rGO-20 as an anode, N-rGO as cathode by using 2 mol l−1 KOH as an electrolyte. NiCoSe4/N-rGO-20//N-rGO ASC demonstrates an ultra-big energy density of 14 Wh kg−1 and good circulation stability in the power density of 902 W kg−1. It is doubled in comparison to the NiCoSe4/N-rGO-20//rGO asymmetric supercapacitor (7 Wh kg−1). The NiCoSe4/N-rGO-20//N-rGO ASC capacity retention is still up to 93% over 5000 cycles (5 A g−1). The results reveal that this device would be a prospective cathode material of supercapacitors in actual applications.
A multifunctional composite membrane with photocatalytic, self-cleaning, oil/water separation and antibacterial properties
Authors: Zhang Yubo , Chen Yi , Wang Chen , Fan Zhao , Wang Yongqian 
Published: May 2022

Abstract
Multifunctional composite materials have attracted wide attention because they can be applied in many fields, and have great potential for application. The superhydrophobic surface has been favored by scientists in recent years because of its excellent properties. In this paper, carbon fabric (CF) with high porosity, good electrical conductivity and excellent flexibility was selected as substrate. The CF/Zr–TiO2/PDMS composites were prepared by solvo-thermal method on CF and modified by PDMS, which can be used in the fields of self-cleaning, self-healing, oil/water separation, antibacterial, anti-icing and so on. Furthermore, the PDMS modification has no or negligible adverse effect on the important textile physical properties of the CF. The effects of different process parameters on the structure and properties of CF/Zr–TiO2 were studied, and the samples with the best conditions were obtained. The results show that the sample achieves the transformation from superhydrophilic to superhydrophobic after modification. The CF/Zr–TiO2/PDMS composite structure not only shows excellent photocatalytic activity, but also has a certain self-cleaning ability. The samples before and after modification can separate light oil/water and heavy oil/water respectively. Compared with CF/Zr–TiO2, CF/Zr–TiO2/PDMS has better anti-Escherichia coli ability.
First application of the BIANCA biophysical model to carbon-ion patient cases
Authors: Kozłowska Wioletta S , Carante Mario P , Aricò Giulia , Embriaco Alessia , Ferrari Alfredo , Magro Giuseppe , Mairani Andrea , Ramos Ricardo , Sala Paola , Georg Dietmar , Ballarini Francesca 
Published: May 2022

Abstract

Objective. The main objective of this work consists of applying, for the first time, the BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations) biophysical model to the RBE calculation for C-ion cancer patients, and comparing the outcomes with those obtained by the LEM I model, which is applied in clinics. Indeed, the continuous development of heavy-ion cancer therapy requires modelling of biological effects of ion beams on tumours and normal tissues. The relative biological effectiveness (RBE) of heavy ions is higher than that of protons, with a significant variation along the beam path. Therefore, it requires a precise modelling, especially for the pencil-beam scanning technique. Currently, two radiobiological models, LEM I and MKM, are in use for heavy ions in scanned pencil-beam facilities. Approach. Utilizing an interface with the FLUKA Particle Therapy Tool, BIANCA was applied to re-calculate the RBE-weighted dose distribution for carbon-ion treatment of three patients (chordoma, head-and-neck and prostate) previously irradiated at CNAO, where radiobiological optimization was based on LEM I. The predictions obtained by BIANCA were based either on chordoma cell survival (RBE

surv
), or on dicentric aberrations in peripheral blood lymphocytes (RBE

ab
), which are indicators of late normal tissue damage, including secondary tumours. The simulation outcomes were then compared with those provided by LEM I. Main results. While in the target and in the entrance channel BIANCA predictions were lower than those obtained by LEM I, the two models provided very similar results in the considered OAR. The observed differences between RBE

surv
and RBE

ab
(which were also dependent on fractional dose and LET) suggest that in normal tissues the information on cell survival should be integrated by information more closely related to the induction of late damage, such as chromosome aberrations. Significance. This work showed that BIANCA is suitable for treatment plan optimization in ion-beam therapy, especially considering that it can predict both cell survival and chromosome aberrations and has previously shown good agreement with carbon-ion experimental data.
Modeling the impact of spatial oxygen heterogeneity on radiolytic oxygen depletion during FLASH radiotherapy
Authors: Taylor Edward , Hill Richard P , Létourneau Daniel 
Published: May 2022

Abstract

Purpose. It has been postulated that the delivery of radiotherapy at ultra-high dose rates (‘FLASH’) reduces normal tissue toxicities by depleting them of oxygen. The fraction of normal tissue and cancer cells surviving radiotherapy depends on dose and oxygen levels in an exponential manner and even a very small fraction of tissue at low oxygen levels can determine radiotherapy response. To quantify the differential impact of FLASH radiotherapy on normal and tumour tissues, the spatial heterogeneity of oxygenation in tissue should thus be accounted for. Methods. The effect of FLASH on radiation-induced normal and tumour tissue cell killing was studied by simulating oxygen diffusion, metabolism, and radiolytic oxygen depletion (ROD) over domains with simulated capillary architectures. To study the impact of heterogeneity, two architectural models were used: (1) randomly distributed capillaries and (2) capillaries forming a regular square lattice array. The resulting oxygen partial pressure distribution histograms were used to simulate normal and tumour tissue cell survival using the linear quadratic model of cell survival, modified to incorporate oxygen-enhancement ratio effects. The ratio (‘dose modifying factors’) of conventional low-dose-rate dose and FLASH dose at iso-cell survival was computed and compared with empirical iso-toxicity dose ratios. Results. Tumour cell survival was found to be increased by FLASH as compared to conventional radiotherapy, with a 0–1 order of magnitude increase for expected levels of tumour hypoxia, depending on the relative magnitudes of ROD and tissue oxygen metabolism. Interestingly, for the random capillary model, the impact of FLASH on well-oxygenated (normal) tissues was found to be much greater, with an estimated increase in cell survival by up to 10 orders of magnitude, even though reductions in mean tissue partial pressure were modest, less than ∼7 mmHg for the parameter values studied. The dose modifying factor for normal tissues was found to lie in the range 1.2–1.7 for a representative value of normal tissue oxygen metabolic rate, consistent with preclinical iso-toxicity results. Conclusions. The presence of very small nearly hypoxic regions in otherwise well-perfused normal tissues with high mean oxygen levels resulted in a greater proportional sparing of normal tissue than tumour cells during FLASH irradiation, possibly explaining empirical normal tissue sparing and iso-tumour control results.
Fast calculation of the tokamak vertical instability
Authors: Olofsson K E J 
Published: May 2022

Abstract
There has been recent interest in fast calculations of the tokamak axisymmetric vertical instability for real time feedback control purposes. It is shown that the maximum eigenvalue for the basic rigid version of this stability problem can be obtained by finding the positive root to a simple scalar function. This function can be generalized to include plasma mass and has complexity linear in the number of conductive elements. The formulation is based on standard matrix decompositions of the fixed-geometry part of the eigenproblem. The calculation bottleneck is the summary of mutual inductances from the reconstructed equilibrium current density. The with-mass spectrum can be made fully real-valued by the addition of a critical amount of damping with negligible effect on the vertical growth rate. The calculation has been implemented in the plasma control system at the DIII-D tokamak and used in experiments.
Evolution of equilibrium particle beams in plasma under external wakefields
Authors: Baistrukov M A , Lotov K V 
Published: May 2022

Abstract
A beam of ultrarelativistic charged particles in a plasma can reach equilibrium with its own radial wakefield and then propagate with little change in shape. If some co-moving perturbation appears ahead of the beam, it may or may not destroy the beam with its wakefield, depending on the phase and amplitude of the wakefield. We numerically study which perturbations can destroy a single short bunch or a train of many short bunches at the parameters of interest for plasma wakefield acceleration in an axisymmetric configuration, and how fast. We find that there are particularly dangerous wakefield phases in which the beam can be destroyed by perturbations of very low amplitude. We also find that perturbations with an amplitude larger than the wakefield of a single bunch in the train are always destructive.
Analysis of magnetorheological clutch with double cup-shaped gap excited by Halbach array based on finite element method and experiment
Authors: Zhang Guang , Chen Junyu , Zhang Zheng , Sun Min , Yu Yang , Wang Jiong , Cai Shibo 
Published: May 2022

Abstract
This work describes the magnetic analysis of an innovative double cup-shaped gap magnetorheological (MR) clutch featuring with three smart MR gels. Four kinds of Halbach array is used to excite the MR gel. The apparatus is designed by using a magneto/mechanical finite element method model, which is numerical calculated by COMSOL Multiphysics software. After describing the configuration, the transmittable torque in the designed MR clutch is derived based on the Bingham-Plastic field-dependent constitutive model of the MR gel. Considering the viscosity in the model building, such as the shear yield stress, which also various with change of magnetic flux density. The magnetic flux density distribution, the shear yield stress distribution, the dynamic viscosity distribution and the shear stress distribution inside the MR gel are obtained and carefully studied. Furthermore, the chain layer of internal cylindrical part, external cylindrical part, internal disc part and external disc part with lowest shear stress are found to calculate the transmission torque and slip torque. Then, the structure of the prototype is optimized based on multi-physics analysis. Finally, the optimal MR clutch is developed and the magneto-static torque is tested with detail analysis.
Self-confinement of low-energy cosmic rays around supernova remnants
Authors: Jacobs Hanno , Mertsch Philipp , Phan Vo Hong Minh 
Published: May 2022

Abstract
Supernova remnants have long been considered as a promising candidate for sources of Galactic cosmic rays. However, modelling cosmic-ray transport around these sources is complicated by the fact that the overdensity of cosmic rays close to their acceleration site can lead to self-confinement, that is the generation of turbulence upon which these particles scatter. Such a highly non-linear problem can be addressed by numerically solving the coupled differential equations describing the evolution in space and time of the escaping particles and of the turbulent plasma waves. In this work, we focus essentially on the propagation of cosmic rays from supernova remnants in the warm ionized and warm neutral phases of the interstellar medium and propose an extended framework to take into account also the effect of energy loss relevant for cosmic rays of energy below 10 GeV. Interestingly, the diffusion coefficient of low-energy cosmic rays could be suppressed by up to 2 orders of magnitude for several tens of kiloyears after the escape from the shock. The cosmic-ray spectrum outside the supernova remnant flattens below 1 GeV at a sufficiently late time reminiscient of the spectral behaviour observed by Voyager. We also find the grammage accumulated around the source to be non-negligible, with important implications for precision fitting of the cosmic-ray spectra.
On adiabatic renormalization with a physically motivated infrared cut-off
Authors: Animali Chiara , Conzinu Pietro , Marozzi Giovanni 
Published: May 2022

Abstract
We introduce a new approach to renormalize physical quantities in curved space-time by adiabatic subtraction. We use a comoving infrared cut-off in defining the adiabatic counterpart of the physical quantity under consideration, building on the fact that the adiabatic approximation is ill-defined in the infrared tail of the spectrum.
We show how this infrared cut-off should be used to obtain a completely well-defined renormalization scheme and how it is fundamental to avoid unphysical divergences that can be generated by a pathological behavior of the adiabatic subtraction extended to the infrared tail. The infrared cut-off appears as a new degree of freedom introduced in the theory and its actual value has to be consistently fixed by a physical prescription. As an example, we show how such degree of freedom can be set to obtain the correct value of the conformal anomaly in the symptomatic case of an inflationary model with gauge fields coupled to a pseudo-scalar inflaton.
Implications of stochastic effects for primordial black hole production in ultra-slow-roll inflation
Authors: Figueroa Daniel G. , Raatikainen Sami , Räsänen Syksy , Tomberg Eemeli 
Published: May 2022

Abstract
We study the impact of stochastic noise on the generation of
primordial black hole (PBH) seeds in ultra-slow-roll (USR) inflation
with numerical simulations. We consider the non-linearity of the
system by consistently taking into account the noise dependence on
the inflaton perturbations, while evolving the perturbations on the
coarse-grained background affected by the noise. We capture in this
way the non-Markovian nature of the dynamics, and demonstrate that
non-Markovian effects are subleading. Using the ΔN
formalism, we find the probability distribution P(ℛ) of
the comoving curvature perturbation ℛ. We consider
inflationary potentials that fit the CMB and lead to PBH dark matter
with i) asteroid, ii) solar, or iii) Planck mass, as well as
iv) PBHs that form the seeds of supermassive black holes. We find
that stochastic effects enhance the PBH abundance by a factor of
𝒪(10)–𝒪(108), depending on the PBH mass. We
also show that the usual approximation, where stochastic kicks
depend only on the Hubble rate, either underestimates or
overestimates the abundance by orders of magnitude, depending on the
potential. We evaluate the gauge dependence of the results, discuss
the quantum-to-classical transition, and highlight open issues of
the application of the stochastic formalism to USR inflation.
Deformation fields: a new source of information to predict brain age
Authors: Dias Maria de Fátima Machado , Carvalho Paulo , Duarte João Valente , Castelo-Branco Miguel 
Published: May 2022

Abstract

Objective. The modelling of healthy ageing critically requires the identification of methods that detect subtle changes in this process. In the last few years multiple machine learning models have been proposed that learn age patterns from magnetic resonance images. Current standard information sources rely on local volumetric information of brain tissues, namely white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF). Information about patterns of brain deformation remains underexplored. In this paper an assessment is performed to understand better the predictive value of the deformation fields. Approach. A shallow approach was used to compare the predictive value of deformation fields with the brain tissues (GM, WM and CSF). Images were compressed into a lower dimension space using Principal Components Analysis and then, a Relevant Vector Regression (RVR) learned the age patterns from the components. A model was trained per modality (deformation fields, GM, WM and CSF) and the performance between the models was compared. To evaluate whether the deformation fields increased the predictive power of GM, a model fusion approach was explored in which the final estimator was an RVR. Each model was validated using a cross-validation approach and was also evaluated on an external dataset. Main results. We found that models trained with deformation patterns have higher predictive value than the ones trained with WM or CSF. Furthermore, deformation fields had a significantly better performance on the test set and also yield the lower difference between the validation and test set. Moreover, the predictions based on the combination of deformation patterns with GM volume yields better results than GM volumetric information alone. Significance. These findings suggest that deformation fields have a higher predictive power than WM and CSF and are robustly invariant across a set of confounding variables. Therefore, deformation fields should be considered in BrainAge models.
Powergram: A novel auto-regressive power spectrumbasedfrequency band selection method and its applicationingearfault diagnosis
Authors: Ying Wanming , Zheng Jinde , Pan Haiyang , Ton Jinyu 
Published: May 2022

Abstract
Fast kurtogram (FK) is an effective method for resonance demodulation analysis, which segments the frequency spectrum of raw signal by constructing a tree-shaped band-pass filter bank based on alternate dichotomy or trisection method, then the modulation information is extracted via selecting the maximum kurtosis of components. Though FK has a high computation efficiency, it can not adaptively segment the frequency band due to its 1/3 binary tree structure. Besides, the different characteristics of frequency band filtered signal cannot be comprehensively reflected due to the use of a single kurtosis index in FK. To overcome the above shortcomings of FK, a novel frequency band selection method named Powergram is proposed based on auto-regressive (AR) power spectrum. First of all, the AR power spectrum is computed to overcome the influence of noise and irrelevant components on spectrum segmentation. Second, the minima point nearest to the midpoint of two adjacent maxima is selected as the segmentation boundary, where the maximum segmentation level is preset in advance. Third, a new fusion indicator is constructed by weighting the indexes of kurtosis, correlation coefficient, and spectral negentropy. After that, the frequency band with largest fusion indicator is selected as the optimal demodulation frequency band (ODFB). Then, the envelope spectrum of ODFB filtered signal is analyzed to identify the fault characteristic frequency and complete the fault diagnosis. Finally, Powergram is applied to the simulated and tested data of faulty gear via comparing it with existing FB-based FK and Autogram approaches. The analysis results show that the introduced approach is better than the comparison methods in ODFB selection and fault characteristic extraction.
Bearing fault severity assessment using variable-step multiscale fusion Lempel-Ziv complexity
Authors: Su Zhou , Shi Juanjuan , Huang Weiguo , Wang Jun , Shen Changqing , Jiang Xingxing , Zhu Zhongkui 
Published: May 2022

Abstract
Most research on bearing health condition monitoring is devoted to distinguish the defective condition from the healthy condition. In practice, the fault severity assessment is also critical for performing the prognostics and maintenance of bearings. Lempel-Ziv complexity (LZC) has been widely used for the bearing quantitative fault diagnosis. However, the original LZC extracts fault information only at the single scale and often fails to portray the fault features. Then, the multiscale LZC is proposed to more comprehensively extract the fault information. However, multiscale analysis would shorten the length of time series and lead to inaccurate calculation results as the scale factor increases. As such, this paper proposes a novel bearing fault severity assessment method using variable-step multiscale fusion Lempel-Ziv complexity (VSMFLZC) to facilitate the quantitative fault diagnosis of bearings. The variable step length strategy is developed in the proposed method to optimize the coarse-grained procedure. Then, Laplace score is applied to evaluate the features and weights at each scale to obtain the proposed VSMFLZC. By such a fusion algorithm, the sequence can be converted into a single but comprehensive evaluation indicator for the fault severity assessment. The experimental results indicate that the proposed method outperforms the original LZC and multiscale LZC, where the fault features can be more comprehensively extracted and the fault severity assessment of rolling bearing can be successfully realized.