bluuebunny/crossref_metadata_2025 huggingface dataset:
Mathematical modeling of a novel fractional-order monkeypox model using the Atangana–Baleanu derivative
Authors: Biswas A. Santanu , Aslam B. Humaira , Tiwari Pankaj Kumar
Published: November 2023

In this research endeavor, we undertake a comprehensive analysis of a compartmental model for the monkeypox disease, leveraging the Atangana–Baleanu fractional derivative framework. Our primary objective is to investigate the effectiveness of a range of control strategies in containing the transmission of this infectious ailment. The parameterization of the model is executed meticulously via the application of the maximum likelihood estimation technique. Our study involves a rigorous mathematical analysis of the considered model, which encompasses an exploration of the existence and uniqueness of solutions, as well as the establishment of conditions ensuring the compactness and continuity of these solutions. Subsequently, we embark on an extensive stability analysis of the model, complemented by the computation of both the effective and basic reproduction numbers. These calculations are instrumental in illuminating the long-term behavior of the epidemic. Additionally, we perform a sensitivity analysis of the basic reproduction number to discern the influence of various factors on disease transmission dynamics. To derive our numerical results, we implement the Adams–Bashforth predictor–corrector algorithm tailored for the Atangana–Baleanu fractional derivatives. We employ this numerical technique to facilitate the simulation of the model under a spectrum of fractional-order values, offering a visual representation of our findings. Our study underscores the pivotal roles of infection awareness, vaccination campaigns, and effective treatment in significantly curtailing disease transmission, thus contributing valuable insight to the field of epidemiology.
Doping-induced assembly interface for noninvasive in vivo local and systemic immunomodulation
Authors: Sha Baoning , Zhao Shengzhuo , Gu Minling , Khodagholy Dion , Wang Liping , Bi Guo-Qiang , Du Zhanhong
Published: November 2023

Peripheral neural interfaces, potent in modulating local and systemic immune responses for disease treatment, face significant challenges due to the peripheral nerves’ broad distribution in tissues like the fascia, periosteum, and skin. The incongruity between static electronic components and the dynamic, complex organization of the peripheral nervous system often leads to interface failure, stalling circuit research and clinical applications. To overcome these, we developed a self-assembling, tissue-adaptive electrode composed of a single-component cocktail nanosheet colloid, including dopants, conducting polymers, stabilizers, and an MXene catalyst. Delivered via a jet injector to designated nerve terminals, this assembly utilizes reactive oxygen species to catalytically dope poly (3,4-ethylenedioxythiophene), enhancing π–π interactions between nanosheets, and yielding a conductive, biodegradable interface. This interface effectively regulates local immune activity and promotes sensory and motor nerve functional restoration in nerve-injured mice, while engaging the vagal–adrenal axis in freely moving mice, eliciting catecholamine neurotransmitter release, and suppressing systemic cytokine storms. This innovative strategy specifically targets nerve substructures, bolstering local and systemic immune modulation, and paving the way for the development of self-adaptive dynamic neural interfaces.
Double-parameter regularization for solving the backward diffusion problem with parallel-in-time algorithm
Authors: Fu Jun-Liang , Liu Jijun
Published: November 2023

We propose a double-parameter regularization scheme for dealing with the backward diffusion process. Considering the smoothing effect of Yosida approximation for PDE, we propose to regularize this ill-posed problem by modifying original governed system in terms of a pseudoparabolic equation together with a quasi-boundary condition simultaneously, which consequently contains two regularizing parameters. Theoretically, we establish the optimal error estimates between the regularizing solution and the exact one in terms of suitable choice strategy for the regularizing parameters, under a-priori regularity assumptions on the exact solution. The a-posteriori choice strategy for the regularizing parameters based on the discrepancy principle is also studied. To weaken the heavy computational cost for solving the discrete nonsymmetric linear regularizing system by finite difference scheme, especially in higher spatial dimensional cases, the block divide-and-conquer method together with the properties of the Schur complement is applied to decompose the linear system into two half-size linear systems, one of which can be solved by the diagonalization technique, and consequently an efficient parallel-in-time algorithm originally developed for direct problem is applicable. Our proposed method is of much lower complexity than the standard solver for the corresponding linear system. Finally, some numerical examples are presented to verify the efficiency of our proposed method.
Optimal regularized hypothesis testing in statistical inverse problems
Authors: Kretschmann Remo , Wachsmuth Daniel , Werner Frank
Published: November 2023

Testing of hypotheses is a well studied topic in mathematical statistics. Recently, this issue has also been addressed in the context of inverse problems, where the quantity of interest is not directly accessible but only after the inversion of a (potentially) ill-posed operator. In this study, we propose a regularized approach to hypothesis testing in inverse problems in the sense that the underlying estimators (or test statistics) are allowed to be biased. Under mild source-condition type assumptions, we derive a family of tests with prescribed level α and subsequently analyze how to choose the test with maximal power out of this family. As one major result we prove that regularized testing is always at least as good as (classical) unregularized testing. Furthermore, using tools from convex optimization, we provide an adaptive test by maximizing the power functional, which then outperforms previous unregularized tests in numerical simulations by several orders of magnitude.
Distributed parameter identification for the Navier–Stokes equations for obstacle detection
Authors: Aguayo Jorge , Bertoglio Cristóbal , Osses Axel
Published: November 2023

We present a parameter identification problem for a scalar permeability field and the maximum velocity in an inflow, following a reference profile. We utilize a modified version of the Navier–Stokes equations, incorporating a permeability term described by the Brinkman’s Law into the momentum equation. This modification takes into account the presence of obstacles on some parts of the boundary. For the outflow, we implement a directional do-nothing condition as a means of stabilizing the backflow. This work extends our previous research published in (Aguayo et al 2021 Inverse Problems
37 025010), where we considered a similar inverse problem for a linear Oseen model with do-nothing boundary conditions on the outlet and numerical simulations in 2D. Here we consider the more realistic case of Navier–Stokes equations with a backflow correction on the outflow and 3D simulations of the identification of a more realistic tricuspid cardiac valve. From a reference velocity that could have some noise or be obtained in low resolution, we define a suitable quadratic cost functional with some regularization terms. Existence of minimizers and first and second order optimality conditions are derived through the differentiability of the solutions of the Navier–Stokes equations with respect to the permeability and maximum velocity in the inflow. Finally, we present some synthetic numerical test based of recovering a 2D and 3D shape of a cardiac valve from total and local velocity measurements, inspired from 2D and 3D MRI.
Comparing benefit and detriment from medical diagnostic radiation exposure using disability-adjusted life years: towards quantitative justification
Authors: Kotre C J
Published: November 2023

Justification of medical radiation exposure is one of the main elements of radiation protection for patients. For a medical exposure to proceed, the benefit from the procedure must have been determined to be greater than the detriment. It is rare, however, that justification can be stated quantitatively as a ratio of benefit to detriment, or as a net benefit, and this is particularly true for medical diagnostic exposures associated with non-fatal diseases where survival statistics do not apply. The concept of the disability-adjusted life year (DALY) is well established as a measure of disease severity in public health, and there have been calls to revise the international system of radiation protection dosimetry to employ the DALY as a measure of radiation detriment. This paper looks at possible routes to quantify the benefit and detriment aspects of justification based on initial published results for the use of the DALY as a measure of radiation detriment, together with established values of DALY for a range of diseases. Although spreadsheet-style solutions for the calculation of a justification factor based on statistical life tables can be devised, these will be shown to have some limitations. A justification factor based on the rate of change of benefit divided by the rate of change of detriment following medical exposure is proposed. This factor is simple to calculate, is age independent, can apply to non-fatal diseases and is argued to have logical and ethical advantages for the explanation of the relative benefits and detriments of radiological procedures to patients.
Batch process monitoring based on sequential phase division multiway sparse weighted neighborhood preserving embedding
Authors: Zhang Yan , Zhao Xiaoqiang , Cao Jie , Hui Yongyong
Published: November 2023

Batch processes are often characterized by multiphase and different batch durations, which vary from phase to phase presenting multiple local neighborhood features. In this paper, a sequential phase division-multiway sparse weighted neighborhood preserving embedding method is proposed for monitoring batch processes more sensitively. First, batches with uneven durations are synchronized, and the phases are automatically determined in chronological order. Secondly, the nearest neighbors are computed at each phase and the optimal sparse representation (SR) is obtained based on the nearest neighbors. This improves the robustness of the algorithm to noise and outliers, and solves the problem of computational difficulties associated with global SR based. Thirdly, the distance values of the neighbor elements are considered to fully extract the neighbor structure when the optimal SR is calculated. Finally, after dimension reduction, T
2 and squared prediction error statistics are established in feature space and residual space respectively for fault detection. The effectiveness of the method is verified by a multiphase numerical simulation example and the penicillin fermentation process.
Design of device for testing the energy of explosion shock waves based on a lever-type cutting energy-absorbing structure
Authors: Luo Hongwei , Qi Zizhen , Zhang Yuwu , Liang Minzu , Lin Yuliang
Published: November 2023

Explosion shock waves are the main cause of target destruction when ammunition explodes. Parameter testing of these waves is important. Traditional equivalent testing methods exhibit limited quantification capabilities and are exclusively applicable to near-field shock wave testing. In this study, a testing device was designed to quantitatively assess shock wave energy. The designed testing device consists of an energy conversion structure, energy absorbing element (EAE), and a package shell. The cutting energy absorption method is used to absorb the explosion shock wave energy, and the cutting tool and lever structure are combined to improve the sensitivity. The variation of the velocity of the energy conversion structure with its geometric size was obtained through theoretical formulas and numerical simulations. The EAE was designed with rigid polyurethane foam. Different cutting areas and cutting depths are compared to obtain the best design of cutting parameters. The feasibility of the testing device was evaluated by explosion test. The applicable range of the scaled distance for the testing device was found to be 1.5–2.5 m kg−1/3. The testing device has the advantage of obtaining effective test results when the direction of the explosion center is unknown. The proposed testing device offers a new technical method for quantitatively evaluating the damage power of explosion shock waves in complex environments.
A drilling combination positioning method based on geomagnetic/inertial navigation combined with PSD improved unscented Kalman filtering algorithm*
Authors: Yang Hai , Qin Bangji , Wei Shuai , Zhang Yunfei , Gao Shanjun
Published: November 2023

During the drilling process, the accuracy of measuring drilling tool attitude is severely affected by measurement drift errors in the inertial device itself and the significant interference noise generated by the impact vibration of the drill bit. To address these issues and achieve precise measurement of drilling trajectory, this paper proposes a combined positioning method based on geomagnetism/inertial navigation combined with PSD improved unscented Kalman filtering. An experimental platform was constructed, and a sensor system was installed in the vicinity of the drill bit for short section measurements. Experimental verification was conducted using actual drilling data. The results demonstrate that, compared to general unscented Kalman filtering, the average position error using PSD improved unscented Kalman filtering was reduced from 0.122 m to 0.088 m, and the average velocity error was reduced from 0.019 m s−1 to 0.005 m s−1. By comparing and matching with the drilling trajectory drawn in the logging process, the overall positioning accuracy of the combined positioning method is as high as 90.8%, yielding positioning results that are highly authentic and effective, thereby meeting the on-site usage requirements.
Exploring the effects of temperature on the mechanical properties of high-entropy alloy (CoCrFeNiAl0.1) based on molecular dynamics simulation
Authors: Liu Yunhai , Che Benteng , Wang Xiaowen , Luo Yiyao , Zhang Hu , Liu Ligao , Xu Penghui
Published: November 2023

In order to further explore the influence of temperature on the face-centered cubic (FCC) single-phase crystal CoCrFeNiAl0.1, we conducted a series of Nano-indentation experiments on CoCrFeNiAl0.1 at different temperatures. At room temperature, the effects of indentation can convert a portion of CoCrFeNiAl0.1’s FCC phase into a funnel-shaped hexagonal close-packed (HCP) phase, resulting less deformation on the sides of the indenter. What we analyzed shows that CoCrFeNiAl0.1’s HCP phase has excellent heat resistance and mechanics, allowing CoCrFeNiAl0.1 to maintain great properties in high-temperature environments. However, if T ⩾ 1500 K, high temperature will decrease the number of the HCP phases and dislocation density, leading to an accelerated decline in material strength. This research can provide a theoretical relationship between temperature and microstructural evolution for the research and application of CoCrFeNiAl0.1 in high-temperature environments.
Growth dynamics of nanocolumnar thin films deposited by magnetron sputtering at oblique angles
Authors: Alvarez R , Garcia-Valenzuela A , Regodon G , Ferrer F J , Rico V , Garcia-Martin J M , Gonzalez-Elipe A R , Palmero A
Published: November 2023

The morphology of numerous nanocolumnar thin films deposited by the magnetron sputtering technique at oblique geometries and at relatively low temperatures has been analyzed for materials as different as Au, Pt, Ti, Cr, TiO2, Al, HfN, Mo, V, WO3 and W. Despite similar deposition conditions, two characteristic nanostructures have been identified depending on the material: a first one defined by highly tilted and symmetric nanocolumnar structures with a relatively high film density, and a second one characterized by rather vertical and asymmetric nanocolumns, with a much lower film density. With the help of a model, the two characteristic nanostructures have been linked to different growth dynamics and, specifically, to different surface relaxation mechanisms upon the incorporation of gaseous species with kinetic energies above the surface binding energy. Moreover, in the case of Ti, a smooth structural transition between the two types of growths has been found when varying the value of the power used to maintain the plasma discharge. Based on these results, the existence of different surface relaxation mechanisms is proposed, which quantitatively explains numerous experimental results under the same conceptual framework.
One-step fabrication of flexible polyamide@Ag-dodecanethiol membranes for highly sensitive SERS detection of thiram
Authors: Li Lujie , Zhang Tingting , Zhang Lan , Li Wei , Xu Tao , Wang Lingling , Liu Chang , Li Weihua , Li Jiansheng , Lu Rui
Published: November 2023

The surface-enhanced Raman scattering (SERS) is an effective spectral technology based on Raman scattering, but in practice, the commonly used SERS substrates suffer from low sensitivity and poor stability. In order to overcome these limitations, the SERS substrates were prepared from hydrophobic modification of dodecanethiol (C12) coupled with a flexible substrate, which was then used for pesticides detection in water. A flexible PA@Ag-C12 substrate with surface functionalization has been obtained. This work aims to investigate the self-assembly of Ag NPs modified with C12 onto polyamide (PA) membranes. Initially, transmission electron microscopy and scanning electron microscopy were used to analyze the substrate’s morphology. Then with the help of an energy-dispersive spectrometer, sulfur content of C12-modified Ag NPs was analyzed. In order to determine the hydrophobicity of the modified Ag NPs, the contact angle was used. The results indicate that the gap between Ag NPs on PA membrane can be effectively controlled in order to prevent Ag NPs from aggregating. Furthermore, the finite-difference time-domain analysis indicated that the PA@Ag-C12 substrate exhibited a stronger electromagnetic enhancement effect than the PA@Ag substrate. By reducing NPs gaps on the PA membrane, the number of ‘hot spots’ increased, and the SERS performance of the substrate was improved as a result. According to the results of this study, this method can greatly reduce the manufacturing costs and time costs of the SERS substrate while maintaining the original uniformity. The SERS performance of PA@Ag-C12 was found to be three orders of magnitude better than that of PA@Ag direct self-assembled substrate, and the detection limit for Rhodamine 6G (R6G) was approximately 8.47 × 10−14 M. On the basis of the PA@Ag-C12 substrate, thiram is detectable at a detection limit of 5.88 × 10−11 M with a high degree of sensitivity and repeatability.
The force is strong
Authors: Hughes Stephen , Schouten Peter
Published: November 2023

Introductory physics courses cover the gravitational and electromagnetic force in some detail, but the strong and weak nuclear forces are often given only a cursory treatment. This paper presents some ideas for teaching students about the strong force using practical hands-on demonstrations and using the strong force potential in teaching certain aspects of calculus. A good analogy to the strong force is to place a strong magnet on a metal whiteboard. The magnet must be very close to the board for the magnet to stick to the metal exemplifying the short range of the strong force. Another analogy that can easily be demonstrated in the classroom is placing two cylindrical magnets with facing like poles in a vertically oriented Perspex tube. Velcro is another analogy since the strong force acts over such a short range it is essentially a contact force. The plot of the strong force versus distance and strong potential versus distance is a practical way of teaching students the reciprocal relationship between differentiation and integration. The Reid potential model of the strong interaction (Reid 1968 Ann. Phys., NY
50 411–448) is a good example of differentiating and integrating exponential functions. A calculation is included that shows that the strong force is approximately 100 times stronger than the electromagnetic force. A link between the strong force and Heisenberg uncertainty principle is also made.
Methodology of organizing astronomical observations of asteroids and comets within the extracurricular activities of students
Authors: Tercu Jan-Ovidiu , Chistol Vitalie
Published: November 2023

In this article, the methodology of using a telescope and charge-coupled device camera for organizing astrometric observations of asteroids and comets, as well as photometric observations of asteroids, is presented. Since astronomy is not studied as a separate subject in schools in Romania and the Republic of Moldova (as well as in many other countries), this methodology can be used within extracurricular activities for students. The observations described in the article took place at the astronomical observatory within the ‘Răsvan Angheluță’ Natural Sciences Museum Complex in Galați, Romania.
Topological phase in a nonreciprocal Kitaev chain
Authors: Yan Yu , Cui Wen-Xue , Liu Shutian , Cao Ji , Zhang Shou , Wang Hong-Fu
Published: November 2023

We systematically investigate the nonreciprocal Kitaev chain, where the nonreciprocity arises from the hopping amplitude and pairing strength. By studying the Hamiltonians under three different bases, we reveal that the nonreciprocal hopping amplitude cannot induce a topological phase transition, but can result in the complex energy spectrum and non-Hermitian skin effect. Moreover, the Majorana zero energy edge modes, which are robust against the nonreciprocal hopping amplitude, exist stably in the topologically nontrivial phase. On the other hand, the nonreciprocal pairing strength can trigger a topological phase transition, which is associated with the pseudo-Hermitian symmetry breaking. More interestingly, we observe that the exceptional points independent of the topological phase can be determined by the dispersion relation, and there is no non-Hermitian skin effect in the system. Furthermore, we calculate the topological invariant to demonstrate the validity of the bulk-edge correspondence in the pseudo-Hermitian symmetry-unbroken region. Our investigation provides a path to explore the fundamental physics pertaining to the interplay between nonreciprocity and topology in the non-Hermitian topological superconductors.
Regional temperature extremes and vulnerability under net zero CO2 emissions
Authors: Cassidy Liam J , King Andrew D , Brown Josephine R , MacDougall Andrew H , Ziehn Tilo , Min Seung-Ki , Jones Chris D
Published: November 2023

Signatories to the Paris Agreement have pledged to keep global warming to well below 2 °C above pre-industrial levels and preferably below 1.5 °C above pre-industrial levels. Beyond over-shooting Paris Agreement warming levels followed by net negative emissions, achieving a state of net zero carbon dioxide emissions is required to satisfy Paris Agreement warming goals. Research on climate changes under net zero CO2 emissions is very limited to date with no comprehensive analysis of changes in extremes. In this study, we use results from Earth System Models in the zero emissions commitment model intercomparison project to understand regional mean-state climate change patterns during a 100 year period following carbon dioxide emissions cessation. We also perform an initial study of the evolution of hot and cold monthly temperature extremes after net zero CO2 emissions, including an assessment of how the change in frequency of temperature extremes affects areas of different levels of socioeconomic development based on regional Human Development Index (HDI). The results show that most land regions experience a fast and continuous cooling response following emissions cessation, with large areas of significant model agreement. In contrast, the Southern Ocean continues warming over the century after emissions cessation. The frequency of land-based local monthly high temperature extremes generally stays constant or decreases during the century after emissions cessation, however, decreases in heat extreme frequencies are generally less for locations with lower modern HDI than areas with higher HDI which suggests that inequality of climate change will remain an issue even after net zero CO2 emissions. There is an evident emergence of local monthly cold extremes following emissions cessation with most significant impact over high HDI mid- and high-latitude land regions.
Effect of abrasive grit grade on the abrasion wear behaviour of long banana-jute fibers reinforced hybrid epoxy composites
Authors: K S Krupesh , R Suresh , B M Rudresh , K Ajaykumar
Published: November 2023

The effect of abrasive grit geometry on two-body abrasion wear behavior of long banana and jute fiber reinforced epoxy composites has been investigated. Epoxy (EP), Epoxy/4 wt% Banana fiber (BF)/4 wt%Jute fiber (JF) (EP8), Epoxy/8 wt%BF/8 wt%JF (EP16), Epoxy/12 wt%BF/12 wt% JF (EP24), and Epoxy/16 wt% BF/16 wt%JF (EP32) were the composite materials systems used for the investigation. These composites were processed and fabricated using hand—lay-up technique. The two body abrasion wear test was carried out in accordance with ASTM G99 under the influence of different SiC grit particles (180, 320, 400, and 600 SiC grit). The test was conducted at a room temperature under the abrasion load of 10 N and abrasion speed of 1 m s−1 over a distance of 100 m. The findings of the experiments revealed that wear response of composites depends on pressure, geometry of abrasion particles and their composition. The wear volume loss and specific wear rate decreases with increase in the rank of grit grade. Further, 16 wt% of fibers in composites exhibits the superior abrasion wear resistance. But the higher volume fraction of natural fibers in composites impaired the abrasion wear resistance. Higher rank of grit number was associated with the lesser wear volume loss because of the change in wear mechanism from abrasion to adhesion. In comparison to epoxy based composites, EP16 composite shows superior wear resistance. SEM images were used to examine the worn surfaces.
Prediction of municipal solid waste treatment and disposal in high cold and high altitude area based on system dynamics: a case study of Lhasa
Authors: Liu Ziyun , Zhang Qinxiao , Liu Hongbo
Published: November 2023

At present, the high cold and high altitude areas of China continue to face challenges in achieving high rates of resource utilization for the municipal solid waste (MSW). In this paper, for the first time, a prediction method based on system dynamics (SD) for the treatment and disposal of municipal solid waste in high cold and high altitude areas is proposed and applied to Lhasa City. The model simulate and predict the proportion of treatment methods (including landfill, incineration, kitchen waste disposal, recycling) and the rate of resource utilization (other disposal methods except landfill) of municipal solid waste under Natural Tendency and regulation schemes (Strengthened Municipal Solid Waste Classification Scheme and Municipal Solid Waste Classification and Treatment Scheme). The results show that strengthening municipal solid waste classification and treatment can significantly enhance the resource utilization rate of municipal solid waste in Lhasa, with an expected rate of 100% by 2026. This outcome has the potential to promote sustainable and healthy development of society, economy and environment of a city.
Enhancing mechanical properties of natural fiber composites: a study on the effects of fiber loading and filler addition
Authors: gairola S P , Gupta Nitin Kumar , Joshi Sanjeev Kumar , Dhama Sanjeev , Aggarwal Saurabh
Published: November 2023

In this research, we conducted an extensive analysis of two distinct composite materials: NWBF/EP (nonwoven banana fiber/epoxy) and NWBF/EP/WNP (nonwoven banana fiber/epoxy with walnut powder). These composites were meticulously engineered, utilizing epoxy as the matrix, nonwoven banana fiber as the primary reinforcement, and walnut powder as the secondary reinforcement. Our investigation unveiled that the NWBF/EP/WNP hybrid composite exhibits superior mechanical properties in comparison to the NWBF/EP composite. Notably, the BW4 hybrid composite demonstrated a substantial increase in tensile strength, reaching an impressive 76.7 MPa. This enhancement underscores the potential for augmenting composite stiffness by elevating the WNP ratio up to a specific threshold, though exceeding this threshold leads to a reduction in epoxy resin content. Furthermore, our study revealed substantial improvements in flexural strength as WNP was introduced, with a noteworthy 5.8% rise at a 5% weight percent WNP loading. The pinnacle of flexural strength, 43.6 MPa, was achieved at a 20% weight percent loading. Impact toughness also displayed significant improvements, with the highest impact strength (5.2 J) observed in BW3. This highlights the potential for enhancing the toughness of the hybrid composite within a defined WNP weight percent range. We also gained valuable insights into hardness, void fraction, and the influence of walnut powder. The addition of walnut powder increased void fraction, reduced density, and enhanced various mechanical properties. Our evaluation of wear performance emphasized the pivotal role of factors such as sliding velocity, fiber content, sliding distance, and normal load. In conclusion, this research not only elucidates the mechanical advantages of the NWBF/WNP/epoxy hybrid composite but also offers critical insights for potential applications. The findings underscore the potential of these hybrid composites to serve as sustainable and competitive alternatives to synthetic fiber products in a range of engineering and manufacturing contexts.
Differentiable Earth mover’s distance for data compression at the high-luminosity LHC
Authors: Shenoy Rohan , Duarte Javier , Herwig Christian , Hirschauer James , Noonan Daniel , Pierini Maurizio , Tran Nhan , Mantilla Suarez Cristina
Published: November 2023

The Earth mover’s distance (EMD) is a useful metric for image recognition and classification, but its usual implementations are not differentiable or too slow to be used as a loss function for training other algorithms via gradient descent. In this paper, we train a convolutional neural network (CNN) to learn a differentiable, fast approximation of the EMD and demonstrate that it can be used as a substitute for computing-intensive EMD implementations. We apply this differentiable approximation in the training of an autoencoder-inspired neural network (encoder NN) for data compression at the high-luminosity LHC at CERN The goal of this encoder NN is to compress the data while preserving the information related to the distribution of energy deposits in particle detectors. We demonstrate that the performance of our encoder NN trained using the differentiable EMD CNN surpasses that of training with loss functions based on mean squared error.
Bayesian experimental design and parameter estimation for ultrafast spin dynamics
Authors: Chen Zhantao , Peng Cheng , Petsch Alexander N , Chitturi Sathya R , Okullo Alana , Chowdhury Sugata , Yoon Chun Hong , Turner Joshua J
Published: November 2023

Advanced experimental measurements are crucial for driving theoretical developments and unveiling novel phenomena in condensed matter and materials physics, which often suffer from the scarcity of large-scale facility resources, such as x-ray or neutron scattering centers. To address these limitations, we introduce a methodology that leverages the Bayesian optimal experimental design paradigm to efficiently uncover key quantum spin fluctuation parameters from x-ray photon fluctuation spectroscopy (XPFS) data. Our method is compatible with existing theoretical simulation pipelines and can also be used in combination with fast machine learning surrogate models in the event that real-time simulations are unfeasible. Our numerical benchmarks demonstrate the superior performance in predicting model parameters and in delivering more informative measurements within limited experimental time. Our method can be adapted to many different types of experiments beyond XPFS and spin fluctuation studies, facilitating more efficient data collection and accelerating scientific discoveries.
Towards an enhanced understanding of the particle size effect on conversion/alloying lithium-ion anodes
Authors: Asenbauer Jakob , Horny Dominik , Olutogun Mayokun , Schulz Katrin , Bresser Dominic
Published: November 2023

Conversion/alloying materials (CAMs) represent a potential alternative to graphite as a Li-ion anode active material, especially for high-power applications. So far, however, essentially all studies on CAMs have been dealing with nano-sized particles, leaving the question of how the performance (and the de-/lithiation mechanism in general) is affected by the particle size. Herein, we comparatively investigate four different samples of Zn0.9Co0.1O with a particle size ranging from about 30 nm to a few micrometers. The results show that electrodes made of larger particles are more susceptible to fading due to particle displacement and particle cracking. The results also show that the conversion-type reaction in particular is affected by an increasing particle size, becoming less reversible due to the formation of relatively large transition metal (TM) and alloying metal nanograins upon lithiation, thus hindering an efficient electron transport within the initial particle, while the alloying contribution remains essentially unaffected. The generality of these findings is confirmed by also investigating Sn0.9Fe0.1O2 as a second CAM with a substantially greater contribution of the alloying reaction and employing Fe instead of Co as a TM dopant.
SMapper: visualizing spatial prevalence data of all types, including sparse and incomplete datasets
Authors: Khellaf Lynn , Ralf Arwin , Nguyen Khanh Toan , Kayser Manfred , Nothnagel Michael
Published: November 2023

Motivation

We introduce SMapper, a novel web and software tool for visualizing spatial prevalence data of all types including those suffering from incomplete geographic coverage and insufficient sample sizes. We demonstrate the benefits of our tool in overcoming interpretational issues with existing tools caused by such data limitations. We exemplify the use of SMapper by applications to human genotype and phenotype data relevant in an epidemiological, anthropological and forensic context.

Availability and implementation

A web implementation is available at https://rhodos.ccg.uni-koeln.de/smapper/. A stand-alone version, released under the GNU General Public License version 3 as published by the Free Software Foundation, is available from https://rhodos.ccg.uni-koeln.de/smapper/software-download.php as a Singularity container (https://docs.sylabs.io/guides/latest/user-guide/index.html) and a native Linux Python installation.
Integrating genome-wide association and transcriptome analysis to provide molecular insights into heterophylly and eco-adaptability in woody plants
Authors: Hu Yanmin , Tang Feng , Zhang Dan , Shen Shihua , Peng Xianjun
Published: November 2023

Heterophylly is regard as an important adaptive mechanism in response to different environments within plants. However, the genetic mechanisms responsible for heterophylly in woody plants are still poorly understood. Herein, the divergence of heterophyllous leaves was investigated at morphogenesis and using microdissection and physiological indexes in paper mulberry, and the genetic basis of heterophylly was further revealed combined with genome-wide association study (GWAS), transcriptome analysis and weighted gene coexpression network analysis (WGCNA). Our results revealed that the flavonoid content and antioxidant activity increased gradually from the entire leaf to the palmatisect leaf, while the hormone content and net photosynthetic rate decreased. Through GWAS and transcriptome analysis, a total of 98 candidate genes and 2338 differentially expressed genes associated with heterophylly were identified. Importantly, we uncovered critical variations in the candidate genes Bp07g0981 (WOX) and Bp07g0920 (HHO), along with significant differences in haplotypes and expression levels among heterophyllous leaves. Our results also suggested that the genes involved in hormone signaling pathways, antioxidant activity, and flavonoid metabolism might be closely related to the heterophylly of paper mulberry, which could account for the physiological data. Indeed, CR-wox mutant lines showed significant changes in leaf phenotypes, and differential expression profile analysis also highlighted the expression of genes related to phytohormones and transcription factors. Together, the genetic variations and candidate genes detected in this study provide novel insights into the genetic mechanism of heterophylly, and would improve the understanding of eco-adaptability in heterophyllous woody plants.
Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare
Authors: Economou-Zavlanos Nicoleta J , Bessias Sophia , Cary Michael P , Bedoya Armando D , Goldstein Benjamin A , Jelovsek John E , O’Brien Cara L , Walden Nancy , Elmore Matthew , Parrish Amanda B , Elengold Scott , Lytle Kay S , Balu Suresh , Lipkin Michael E , Shariff Afreen Idris , Gao Michael , Leverenz David , Henao Ricardo , Ming David Y , Gallagher David M , Pencina Michael J , Poon Eric G
Published: November 2023

Objective

The complexity and rapid pace of development of algorithmic technologies pose challenges for their regulation and oversight in healthcare settings. We sought to improve our institution’s approach to evaluation and governance of algorithmic technologies used in clinical care and operations by creating an Implementation Guide that standardizes evaluation criteria so that local oversight is performed in an objective fashion.

Materials and Methods

Building on a framework that applies key ethical and quality principles (clinical value and safety, fairness and equity, usability and adoption, transparency and accountability, and regulatory compliance), we created concrete guidelines for evaluating algorithmic technologies at our institution.

Results

An Implementation Guide articulates evaluation criteria used during review of algorithmic technologies and details what evidence supports the implementation of ethical and quality principles for trustworthy health AI. Application of the processes described in the Implementation Guide can lead to algorithms that are safer as well as more effective, fair, and equitable upon implementation, as illustrated through 4 examples of technologies at different phases of the algorithmic lifecycle that underwent evaluation at our academic medical center.

Discussion

By providing clear descriptions/definitions of evaluation criteria and embedding them within standardized processes, we streamlined oversight processes and educated communities using and developing algorithmic technologies within our institution.

Conclusions

We developed a scalable, adaptable framework for translating principles into evaluation criteria and specific requirements that support trustworthy implementation of algorithmic technologies in patient care and healthcare operations.
Substrate selectivity and catalytic activation of the type III CRISPR ancillary nuclease Can2
Authors: Jungfer Kenny , Sigg Annina , Jinek Martin
Published: November 2023

Type III CRISPR-Cas systems provide adaptive immunity against foreign mobile genetic elements through RNA-guided interference. Sequence-specific recognition of RNA targets by the type III effector complex triggers the generation of cyclic oligoadenylate (cOA) second messengers that activate ancillary effector proteins, thus reinforcing the host immune response. The ancillary nuclease Can2 is activated by cyclic tetra-AMP (cA4); however, the mechanisms underlying cA4-mediated activation and substrate selectivity remain elusive. Here we report crystal structures of Thermoanaerobacter brockii Can2 (TbrCan2) in substrate- and product-bound complexes. We show that TbrCan2 is a single strand-selective DNase and RNase that binds substrates via a conserved SxTTS active site motif, and reveal molecular interactions underpinning its sequence preference for CA dinucleotides. Furthermore, we identify a molecular interaction relay linking the cA4 binding site and the nuclease catalytic site to enable divalent metal cation coordination and catalytic activation. These findings provide key insights into the molecular mechanisms of Can2 nucleases in type III CRISPR-Cas immunity and may guide their technological development for nucleic acid detection applications.
The miRNA–target interactions: An underestimated intricacy
Authors: Diener Caroline , Keller Andreas , Meese Eckart
Published: November 2023

MicroRNAs (miRNAs) play indispensable roles in posttranscriptional gene regulation. Their cellular regulatory impact is determined not solely by their sheer number, which likely amounts to >2000 individual miRNAs in human, than by the regulatory effectiveness of single miRNAs. Although, one begins to develop an understanding of the complex mechanisms underlying miRNA–target interactions (MTIs), the overall knowledge of MTI functionality is still rather patchy. In this critical review, we summarize key features of mammalian MTIs. We especially highlight latest insights on (i) the dynamic make-up of miRNA binding sites including non-canonical binding sites, (ii) the cooperativity between miRNA binding sites, (iii) the adaptivity of MTIs through sequence modifications, (iv) the bearing of intra-cellular miRNA localization changes and (v) the role of cell type and cell status specific miRNA interaction partners. The MTI biology is discussed against the background of state-of-the-art approaches with particular emphasis on experimental strategies for evaluating miRNA functionality.
scPipe: an extended preprocessing pipeline for comprehensive single-cell ATAC-Seq data integration in R/Bioconductor
Authors: Amarasinghe Shanika L , Yang Phil , Voogd Oliver , Yang Haoyu , Du Mei R M , Su Shian , Brown Daniel V , Jabbari Jafar S , Bowden Rory , Ritchie Matthew E
Published: November 2023

scPipe is a flexible R/Bioconductor package originally developed to analyse platform-independent single-cell RNA-Seq data. To expand its preprocessing capability to accommodate new single-cell technologies, we further developed scPipe to handle single-cell ATAC-Seq and multi-modal (RNA-Seq and ATAC-Seq) data. After executing multiple data cleaning steps to remove duplicated reads, low abundance features and cells of poor quality, a SingleCellExperiment object is created that contains a sparse count matrix with features of interest in the rows and cells in the columns. Quality control information (e.g. counts per cell, features per cell, total number of fragments, fraction of fragments per peak) and any relevant feature annotations are stored as metadata. We demonstrate that scPipe can efficiently identify ‘true’ cells and provides flexibility for the user to fine-tune the quality control thresholds using various feature and cell-based metrics collected during data preprocessing. Researchers can then take advantage of various downstream single-cell tools available in Bioconductor for further analysis of scATAC-Seq data such as dimensionality reduction, clustering, motif enrichment, differential accessibility and cis-regulatory network analysis. The scPipe package enables a complete beginning-to-end pipeline for single-cell ATAC-Seq and RNA-Seq data analysis in R.
Rheumatoid arthritis, quantitative parenchymal lung features and mortality among smokers
Authors: McDermott Gregory C , Hayashi Keigo , Yoshida Kazuki , Juge Pierre-Antoine , Moll Matthew , Cho Michael H , Doyle Tracy J , Kinney Gregory L , Dellaripa Paul F , Wallace Zachary S , Regan Elizabeth A , Hunninghake Gary M , Silverman Edwin K , Ash Samuel Y , Estepar Raul San Jose , Washko George R , Sparks Jeffrey A
Published: November 2023

Objectives

There have been limited investigations of the prevalence and mortality impact of quantitative CT (QCT) parenchymal lung features in RA. We examined the cross-sectional prevalence and mortality associations of QCT features, comparing RA and non-RA participants.

Methods

We identified participants with and without RA in COPDGene, a multicentre cohort study of current or former smokers. Using a k-nearest neighbour quantifier, high resolution CT chest scans were scored for percentage of normal lung, interstitial changes and emphysema. We examined associations between QCT features and RA using multivariable linear regression. After dichotomizing participants at the 75th percentile for each QCT feature among non-RA participants, we investigated mortality associations by RA/non-RA status and quartile 4 vs quartiles 1–3 of QCT features using Cox regression. We assessed for statistical interactions between RA and QCT features.

Results

We identified 82 RA cases and 8820 non-RA comparators. In multivariable linear regression, RA was associated with higher percentage of interstitial changes (β = 1.7 [0.5], P = 0.0008) but not emphysema (β = 1.3 [1.7], P = 0.44). Participants with RA and >75th percentile of emphysema had significantly higher mortality than non-RA participants (hazard ratio [HR] 5.86; 95% CI: 3.75, 9.13) as well as RA participants (HR 5.56; 95% CI: 2.71, 11.38) with ≤75th percentile of emphysema. There were statistical interactions between RA and emphysema for mortality (multiplicative P = 0.014; attributable proportion 0.53; 95% CI: 0.30, 0.70).

Conclusion

Using machine learning-derived QCT data in a cohort of smokers, RA was associated with higher percentage of interstitial changes. The combination of RA and emphysema conferred >5-fold higher mortality.
Perivascular CLICK‐gelatin delivery of thrombospondin‐2 small interfering RNA decreases development of intimal hyperplasia after arterial injury
Authors: Mota Lucas , Zhu Max , Li Jennifer , Contreras Mauricio , Aridi Tarek , Tomeo John N. , Stafford Alexander , Mooney David J. , Pradhan‐Nabzdyk Leena , Ferran Christiane , LoGerfo Frank W. , Liang Patric
Published: November 2023

Bypass graft failure occurs in 20%–50% of coronary and lower extremity bypasses within the first‐year due to intimal hyperplasia (IH). TSP‐2 is a key regulatory protein that has been implicated in the development of IH following vessel injury. In this study, we developed a biodegradable CLICK‐chemistry gelatin‐based hydrogel to achieve sustained perivascular delivery of TSP‐2 siRNA to rat carotid arteries following endothelial denudation injury. At 21 days, perivascular application of TSP‐2 siRNA embedded hydrogels significantly downregulated TSP‐2 gene expression, cellular proliferation, as well as other associated mediators of IH including MMP‐9 and VEGF‐R2, ultimately resulting in a significant decrease in IH. Our data illustrates the ability of perivascular CLICK‐gelatin delivery of TSP‐2 siRNA to mitigate IH following arterial injury.