bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Modal and Molecular Imaging of Cellular Microenvironment and Tissue Development
Authors: Pampaloni Francesco
Published: June 2022

Imaging the interaction of individual cells with their surrounding tissue microenvironment is essential to advance in bioprinting, tissue engineering and cancer biology, to mention just three highly relevant fields in the life sciences [...]
The Discovery of Aspect: A Heuristic Parallel Corpus Study of Ingressive, Continuative and Resumptive Viewpoint Aspect
Authors: Bogaards Maarten
Published: June 2022

Languages differ in how systematically and obligatorily they encode conceptual categories such as tense and aspect. By drawing on large parallel corpora, these differences can be exploited heuristically: expressive obligatoriness and the systematicity of a conceptual category in one language can function as a probe for other languages that do not (evidently) encode it. This study applies this method—called heuristic translation mining (HTM)—to viewpoint aspect in Mandarin (an aspect-oriented language) and Dutch (a non-aspect-oriented language). Specifically, it takes the Mandarin aspect markers 起来-qilai (“ingressive”) and 下去-xiaqu (“continuative”) and collects translation strategies for these markers from a corpus of five Mandarin novels and their Dutch translations. The outcomes are methodological, descriptive and theoretical in nature. Methodologically, it is shown how conceptual templates consisting of temporal boundaries and phases facilitate annotating specific types of viewpoint aspect consistently. Descriptively, the exercise indicates at which linguistic levels viewpoint aspect may be encoded in a non-aspect-oriented language. Theoretically, conducting an HTM analysis with several aspect markers at once makes it possible to quantify (non-)marking of conceptual content; it turns out that the types of viewpoint under study correspond to varying marking frequencies, which may correlate with conceptual complexity.
Prosodic Word Recursion in a Polysynthetic Language (Blackfoot; Algonquian)
Authors: Weber Natalie
Published: June 2022

This paper focuses on prosodic adjunction at the Prosodic Word level in a polysynthetic language. I argue that recursion at a depth of more than two levels can only be generated by a theory which requires exact correspondence between certain syntactic phrases and Prosodic Words. Such a theory is similar to Phonological Phrase correspondence in Match Theory, suggesting there is an underlying shared property between correspondence at the Prosodic Word and Phonological Phrase levels. In addition, this theory must include a constraint which prohibits recursive prosodic constituents in order to generate the attested typology of clitics across languages. The empirical focus is the prosodic structure of the verbal complex in Blackfoot (Algonquian; ISO 639-3: bla). Using phonotactic evidence I argue that the vP phase corresponds to a Prosodic Word, and that each prefix to the stem is a Prosodic Word adjunct. I then compare several theories of the syntax-prosody interface, including versions of Alignment Theory, Wrap Theory, and Match Theory. A subset of schematic candidates with one or two prefixes to a stem are used to determine which theories generate the attested typology of clitics as well as a multiply recursive Prosodic Word structure.
A Comparison of Germany and the United Kingdom Indicates That More SARS-CoV-2 Circulation and Less Restrictions in the Warm Season Might Reduce Overall COVID-19 Burden
Authors: Meintrup David , Nowak-Machen Martina , Borgmann Stefan
Published: June 2022

(1) Background: Between March 2020 and January 2022 severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) caused five infection waves in Europe. The first and the second wave was caused by wildtype SARS-CoV-2, while the following waves were caused by the variants of concern Alpha, Delta, and Omicron respectively. (2) Methods: In the present analysis, the first four waves were compared in Germany and the UK, in order to examine the COVID-19 epidemiology and its modulation by non-pharmaceutical interventions (NPI). (3) Results: The number of COVID-19 patients on intensive care units and the case fatality rate were used to estimate disease burden, the excess mortality to assess the net effect of NPI and other measures on the population. The UK was more severely affected by the first and the third wave while Germany was more affected by the second wave. The UK had a higher excess mortality during the first wave, afterwards the excess mortality in both countries was nearly identical. While most NPI were lifted in the UK in July 2021, the measures were kept and even aggravated in Germany. Nevertheless, in autumn 2021 Germany was much more affected, nearly resulting in a balanced sum of infections and deaths compared to the UK. Within the whole observation period, in Germany the number of COVID-19 patients on ICUs was up to four times higher than in the UK. Our results show that NPI have a limited effect on COVID-19 burden, seasonality plays a crucial role, and a higher virus circulation in a pre-wave situation could be beneficial. (4) Conclusions: Although Germany put much more effort and resources to fight the pandemic, the net balance of both countries was nearly identical, questioning the benefit of excessive ICU treatments and of the implementation of NPI, especially during the warm season.
Federated Learning Approach with Pre-Trained Deep Learning Models for COVID-19 Detection from Unsegmented CT images
Authors: Florescu Lucian Mihai , Streba Costin Teodor , Şerbănescu Mircea-Sebastian , Mămuleanu Mădălin , Florescu Dan Nicolae , Teică Rossy Vlăduţ , Nica Raluca Elena , Gheonea Ioana Andreea
Published: June 2022

(1) Background: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by SARS-CoV-2. Reverse transcription polymerase chain reaction (RT-PCR) remains the current gold standard for detecting SARS-CoV-2 infections in nasopharyngeal swabs. In Romania, the first reported patient to have contracted COVID-19 was officially declared on 26 February 2020. (2) Methods: This study proposes a federated learning approach with pre-trained deep learning models for COVID-19 detection. Three clients were locally deployed with their own dataset. The goal of the clients was to collaborate in order to obtain a global model without sharing samples from the dataset. The algorithm we developed was connected to our internal picture archiving and communication system and, after running backwards, it encountered chest CT changes suggestive for COVID-19 in a patient investigated in our medical imaging department on the 28 January 2020. (4) Conclusions: Based on our results, we recommend using an automated AI-assisted software in order to detect COVID-19 based on the lung imaging changes as an adjuvant diagnostic method to the current gold standard (RT-PCR) in order to greatly enhance the management of these patients and also limit the spread of the disease, not only to the general population but also to healthcare professionals.
It Takes Two to Tango: Potential Prognostic Impact of Circulating TGF-Beta and PD-L1 in Pancreatic Cancer
Authors: Garajová Ingrid , Cavazzoni Andrea , Verze Michela , Minari Roberta , Pedrazzi Giuseppe , Balsano Rita , Gelsomino Fabio , Valle Raffaele Dalla , Digiacomo Graziana , Giovannetti Elisa , Leonardi Francesco
Published: June 2022

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly devastating disease with rising incidence and poor prognosis. The lack of reliable prognostic biomarkers hampers the individual evaluation of the survival and recurrence potential. Methods: Here, we investigate the value of plasma levels of two potential key players in molecular mechanisms underlying PDAC aggressiveness and immune evasion, soluble TGF-beta (sTGF-beta) and sPD-L1, in both metastatic and radically-resected PDAC. To this aim we prospectively enrolled 38 PDAC patients and performed appropriate statistical analyses in order to evaluate their correlation, and role in the prediction of disease relapse/progression, and patients’ outcome. Results: Metastatic patients showed lower levels of circulating sTGF-beta and higher levels of sPD-L1 compared to radically-resected patients. Moreover, a decrease in sTGF-beta levels (but not sPD-L1) was significantly associated with disease relapse in radically-resected patients. We also observed lower sTGF-beta at disease progression after first-line chemotherapy in metastatic patients, though this change was not statistically significant. We found a significant correlation between the levels of sTGF-beta and sPD-L1 before first-line chemotherapy. Conclusions: These findings support the possible interaction of TGF-beta and PD-L1 pathways and suggest that sTGF-beta and sPD-L1 might synergize and be new potential blood-based biomarkers.
Optimizing Transport Logistics under Uncertainty with Simheuristics: Concepts, Review and Trends
Authors: Castaneda Juliana , Ghorbani Elnaz , Ammouriova Majsa , Panadero Javier , Juan Angel A.
Published: June 2022

Background: Uncertainty conditions have been increasingly considered in optimization problems arising in real-life transportation and logistics activities. Generally, the analysis of complex systems in these non-deterministic environments is approached with simulation techniques. However, simulation is not an optimization tool. Hence, it must be combined with optimization methods when our goal is to: (i) minimize operating costs while guaranteeing a given quality of service; or (ii) maximize system performance using limited resources. When solving NP-hard optimization problems, the use of metaheuristics allows us to deal with large-scale instances in reasonable computation times. By adding a simulation layer to the metaheuristics, the methodology becomes a simheuristic, which allows the optimization element to solve scenarios under uncertainty. Methods: This paper reviews the indexed documents in Elsevier Scopus database of both initial as well as recent applications of simheuristics in the logistics and transportation field. The paper also discusses open research lines in this knowledge area. Results: The simheuristics approaches to solving NP-hard and large-scale combinatorial optimization problems under uncertainty scenarios are discussed, as they frequently appear in real-life applications in logistics and transportation activities. Conclusions: The way in which the different simheuristic components interact puts a special emphasis in the different stages that can contribute to make the approach more efficient from a computational perspective. There are several lines of research that are still open in the field of simheuristics.
Blockchain for Ecologically Embedded Coffee Supply Chains
Authors: Trollman Hana , Garcia-Garcia Guillermo , Jagtap Sandeep , Trollman Frank
Published: June 2022

Background: This research aims to identify how blockchain technology could support the ecological embeddedness of the coffee supply chain. Ecological embeddedness is a subset of the circular economy (CE) that demands legitimacy through design changes to product, production and/or packaging for benefits to economic actors and the environment. This is in contrast with legitimacy as a public relations exercise. Blockchain is a digital transformation technology that is not fully conceptualized with respect to supply chain implementation and the related strategy formulation, particularly in the context of sustainability. Furthermore, the integration of consumers into the CE remains not well understood or researched, with the main focus of CE being the cycling of resources. Methods: This research employs a qualitative case study methodology of the first coffee business in the USA to use blockchain technology as an exemplar. Gap analysis is then applied to identify how blockchain could be used to advance from the current state to a more sustainable one. Results: Findings indicate that the implementation of blockchain is not ecologically embedded in the example studied. Conclusions: The extension of blockchain technology to consider the by-products of production and valorizable waste throughout the supply chain as assets would support ecologically embedded CE for coffee.
Micro-Wear Simulation of Braking Interface Based on Particle Discrete Element Modeling
Authors: Sha Zhihua , Hao Qiang , Yin Jian , Ma Fujian , Liu Yu , Zhang Shengfang
Published: June 2022

For material fracture and severe wear in braking conditions, the discrete element method (DEM) is used to simulate the wear process of the braking interface explicitly. Based on the central difference method, particle motion equations are established considering the influence of elemental damping on particle contact. Combined with the Particle Flow Code (PFC) software, a DEM wear model of the braking interface is established using the parallel bond modeling method. The braking wear process is simulated, and the material damage process is investigated. The simulation results demonstrate that with the increase of the initial braking load and the initial braking speed, the wear depth increased by 24.75% and 16.22%, respectively. The increase in the number of detached particles leads to an increasing trend of fracture force chains, which increases the thickness of the flowing particle layer, revealing the micro-wear mechanism of the braking interface.
Nanoswimmers Based on Capped Janus Nanospheres
Authors: Piskunen Petteri , Huusela Martina , Linko Veikko
Published: June 2022

Nanoswimmers are synthetic nanoscale objects that convert the available surrounding free energy to a directed motion. For example, bacteria with various flagella types serve as textbook examples of the minuscule swimmers found in nature. Along these lines, a plethora of artificial hybrid and non-hybrid nanoswimmers have been introduced, and they could find many uses, e.g., for targeted drug delivery systems (TDDSs) and controlled drug treatments. Here, we discuss a certain class of nanoparticles, i.e., functional, capped Janus nanospheres that can be employed as nanoswimmers, their subclasses and properties, as well as their various implementations. A brief outlook is given on different fabrication and synthesis methods, as well as on the diverse compositions used to prepare nanoswimmers, with a focus on the particle types and materials suitable for biomedical applications. Several recent studies have shown remarkable success in achieving temporally and spatially controlled drug delivery in vitro using Janus-particle-based TDDSs. We believe that this review will serve as a concise introductory synopsis for the interested readers. Therefore, we hope that it will deepen the general understanding of nanoparticle behavior in biological matrices.
Multi-Scale Crystal Plasticity Model of Creep Responses in Nickel-Based Superalloys
Authors: Keshavarz Shahriyar , Campbell Carelyn E. , Reid Andrew C. E.
Published: June 2022

The current study focuses on the modeling of two-phase γ-γ′ nickel-based superalloys, utilizing multi-scale approaches to simulate and predict the creep behaviors through crystal plasticity finite element (CPFE) platforms. The multi-scale framework links two distinct levels of the spatial spectrum, namely, sub-grain and homogenized scales, capturing the complexity of the system responses as a function of a tractable set of geometric and physical parameters. The model considers two dominant features of γ′ morphology and composition. The γ′ morphology is simulated using three parameters describing the average size, volume fraction, and shape. The sub-grain level is expressed by a size-dependent, dislocation density-based constitutive model in the CPFE framework with the explicit depiction of γ-γ′ morphology as the building block of the homogenized scale. The homogenized scale is developed as an activation energy-based crystal plasticity model reflecting intrinsic composition and morphology effects. The model incorporates the functional configuration of the constitutive parameters characterized over the sub-grain γ-γ′ microstructural morphology. The developed homogenized model significantly expedites the computational processes due to the nature of the parameterized representation of the dominant factors while retains reliable accuracy. Anti-Phase Boundary (APB) shearing and, glide-climb dislocation mechanisms are incorporated in the constitutive model which will become active based on the energies associated with the dislocations. The homogenized constitutive model addresses the thermo-mechanical behavior of nickel-based superalloys for an extensive temperature domain and encompasses orientation dependence as well as the loading condition of tension-compression asymmetry aspects. The model is validated for diverse compositions, temperatures, and orientations based on previously reported data of single crystalline nickel-based superalloy.
Investigation of the Thermodynamic Transformation and Rare Earth Microalloying of a Medium Carbon-Medium Alloy Steel for Large Ball Mill Liners
Authors: Yang Xi , Wang Xinghe , Xie Jingpei , Li Yuhe , Yang Dixin
Published: June 2022

The medium carbon-medium alloy steel was developed for the manufacture of large ball mill liners and sports equipment. In this study, the continuous cooling transformation curve of a novel type of medium carbon-medium alloy steel was measured with a thermal simulation machine; based on this curve, the hardening and tempering processes were optimized. The steel was then complex modified with alkaline earth and rare earth alloys. The mechanical properties of the treated steel were tested. The microstructure of the steel was analyzed by metallographic microscopy, X-ray diffraction, scanning electron microscopy and transmission electron microscopy, and the wear surface of the steel was analyzed by a three-dimensional morphometer. After high-temperature tempering, the microstructure transformed into tempered sorbite, which possesses good mechanical properties and can adapt to working conditions that require high strength and toughness. Rare earth or alkaline earth modification of the medium carbon-medium alloy steel promoted microstructural uniformity and grain refinement and improved the mechanical and anti-wear properties.
Analysis on the Influence of Incident Light Angle on the Spatial Aberrations of Acousto-Optical Tunable Filter Imaging
Authors: Yu Kai , Zhao Huijie
Published: June 2022

Acousto-optical tunable filter (AOTF) does not conform to the pinhole model due to the acousto-optic interaction. A calculation method of AOTF aberrations under the condition of incident light with a large arbitrary angle is proposed to solve the problem of coordinate mapping between object space and image space of the AOTF system without refractive index approximation. This approach can provide accurate pointing information of the interested targets for the tracking and searching system based on AOTF. In addition, the effect of cut angle values of the paratellurite crystal on aberrations was analyzed to optimize the design of AOTF cutting according to different application requirements. Finally, distribution characteristics and quantitative calculation results of AOTF aberrations were verified by experiments with different targets, respectively. The experimental results are in good agreement with the simulations.
The Characteristics of Time-Dependent Changes of Coefficient of Permeability for Superabsorbent Polymer-Soil Mixtures
Authors: Misiewicz Jakub , Datta Sujit Sankar , Lejcuś Krzysztof , Marczak Daria
Published: June 2022

Water uptake dynamics of superabsorbent polymers (SAP) in soil is of key importance for the optimum application of these materials in environmental engineering and agriculture, so goal of this paper is to determine time dependent values of coefficient of permeability for various SAP-soil mixtures. Retaining water in soil is a key requirement in critical zones to support plant growth. There is an urgent need for technologies that can increase soil water retention, given the increasing prevalence of droughts and scarcity of clean water as the climate changes, combined with the rising demand for food by a growing world population. SAPs are materials that can absorb significant amounts of water, and thus have tremendous potential to help increase water retention in soil. However, while some studies have characterized the equilibrium swelling behavior of SAPs in soil, how their addition influences the time-dependent flow of water through soil remains poorly understood. Here, we address this gap in knowledge by directly measuring the coefficient of permeability of SAP-soil mixtures, testing different soil grain sizes, SAP grain sizes, and different SAP-soil ratios. We find that SAP addition can dramatically hinder the flow rate of water through soil—reducing the permeability by several orders of magnitude, and in some cases causing complete blockage of water infiltration, at mass fractions as small as 1%. In this scenario coefficient of permeability of 1.23 × 10−4 m/s dropped by a factor of ~10 after 14 min, a factor of ~100 after 36 min, and by nearly a factor of ~1000 after 63 min, eventually causing complete blockage of infiltration after 67 min. Authors concluded that in this particular situation the size and quantity of SAP particles was enough to nearly completely fill the available pore space resulting in rendering the soil column almost completely impermeable. Moreover, we demonstrate that these effects are well-described by a simple hydraulic model of the mutual interactions between SAP and soil grains, providing more generally-applicable and quantitative principles to model SAP-soil permeability in applications. Ultimately, this work could help evaluate the optimal proportions and grain sizes of SAPs to use for a given soil to simultaneously achieve a desirable permeability along with increased water holding capacity in the plant root zone.
From Quantum Materials to Microsystems
Authors: Bertacco Riccardo , Panaccione Giancarlo , Picozzi Silvia
Published: June 2022

The expression “quantum materials” identifies materials whose properties “cannot be described in terms of semiclassical particles and low-level quantum mechanics”, i.e., where lattice, charge, spin and orbital degrees of freedom are strongly intertwined. Despite their intriguing and exotic properties, overall, they appear far away from the world of microsystems, i.e., micro-nano integrated devices, including electronic, optical, mechanical and biological components. With reference to ferroics, i.e., functional materials with ferromagnetic and/or ferroelectric order, possibly coupled to other degrees of freedom (such as lattice deformations and atomic distortions), here we address a fundamental question: “how can we bridge the gap between fundamental academic research focused on quantum materials and microsystems?”. Starting from the successful story of semiconductors, the aim of this paper is to design a roadmap towards the development of a novel technology platform for unconventional computing based on ferroic quantum materials. By describing the paradigmatic case of GeTe, the father compound of a new class of materials (ferroelectric Rashba semiconductors), we outline how an efficient integration among academic sectors and with industry, through a research pipeline going from microscopic modeling to device applications, can bring curiosity-driven discoveries to the level of CMOS compatible technology.
Effect of Cu Substitution and Heat Treatment on Phase Formation and Magnetic Properties of Sm12Co88−xCux Melt-Spun Ribbons
Authors: Dai Feilong , Liu Peipei , Luo Lin , Chen Dekang , Yao Qingrong , Wang Jiang
Published: June 2022

The phase structure and microstructure of Sm12Co88−xCux (x = 0, 2, 4, 6, 8, 10; at.%) as-cast alloys and melt-spun ribbons prepared via the arc-melting method and melt-spun technology were studied experimentally by X-ray diffraction (XRD) and scanning electron microscope (SEM) with energy dispersive spectroscopy (EDS). The results reveal that the Sm12Co88−xCux (x = 0) as-cast alloy contains Sm2Co17 and Sm5Co19 phases, while the Sm12Co88−xCux (x = 2) as-cast alloy is composed of Sm2Co17, Sm2Co7 and Sm(Co, Cu)5 phases. Sm2Co17 and Sm(Co, Cu)5 phases are detected in Sm12Co88−xCux (x = 4, 6, 8, 10) as-cast alloys. Meanwhile, Sm12Co88−xCux ribbons show a single SmCo7 phase, which is still formed in the ribbons annealed at 1023 K for one hour. After annealed at 1123 K for two hours, cooled slowly down to 673 K at 0.5 K/min and then kept for four hours, the ribbons are composed of Sm2Co17 and Sm(Co, Cu)5 phases. The magnetic measurements of Sm12Co88−xCux ribbons were performed by vibrating sample magnetometer (VSM). The results exhibit that the maximum magnetic energy product ((BH)max), the coercivity (Hcj) and the remanence (Br) of the Sm12Co88−xCux ribbons increase generally with the increase in Cu substitution. In particular, the magnetic properties of the ribbons annealed at 1123 K and 673 K increase significantly with the increase in Cu substitution, resulting from the increase in the volume fraction of the formed Sm(Co, Cu)5 phase after heat treatment.
The Microstructural Evolution of Cu-Sn-P Alloy during Hot Deformation Process
Authors: Zhao Junsheng , Zhang Limin , Du Fengming , Yuan Xia , Wang Pengfei
Published: June 2022

The microstructure evolution of Cu-Sn-P alloy subjected to hot deformation was researched through electron backscatter diffraction (EBSD) and transmission electron microscope (TEM) in the present study. The results indicated that after hot deformation, grains perpendicular to the force direction were elongated, and mostly became deformed grains, and then exhibited an obvious hardening effect. The Cu-Sn-P alloy could be strain hardened during hot deformation, but, with recrystallization, a softening effect occurred. Changes in dislocation density, textures, and grain sizes play different roles in flow stress behaviors of Cu-Sn-P alloy, and the dislocation density has a more evident effect at low temperature. However, with increase in temperature, recrystallization softening gradually dominates. Low-angle grain boundaries (LABs) account for the majority of hot deformed microstructures of Cu-Sn-P alloy. High dislocation densities in these zones make it easy to initiate the dislocation slipping systems. Deformation is realized through dislocation slipping and the slipping of edge dislocation pairs. The dislocation pile-up zones have high distortion energies, and, thus, elements of diffusion and recrystallization nucleation can occur easily. At different temperatures, the maximum polar density of textures gradually increases, and there are preferred orientations of grains. At 500 °C, stacking faults accumulate and promote the growth of twins. The twin growth direction is mainly determined by the migration of high-angle grain boundaries (HABs) and the clustering of high-stress zones.
Model Analysis and Experimental Study of Lower Limb Rehabilitation Training Device Based on Gravity Balance
Authors: Wang Jianping , Kan Yanpeng , Zhang Taisheng , Zhang Zhen , Xu Manman
Published: June 2022

More hemiplegia patients tend to use equipment for rehabilitation training due to the lack of physical therapists and the low effect of manual training. Nowadays, lower limb rehabilitation training devices for patients in grade 2 of the Medical Research Council (MRC-2) scale are still scarce and have some issues of poor autonomy and cannot relieve the muscle weakness of patients. To address these problems, a prototype based on gravity balance was designed with the combination of springs and linkages to enable patients to passively experience the rehabilitation training in the state of balancing the gravity of lower limbs. The motion of the mechanism was analyzed to obtain the functional relation between the motor rotation angle and the joints’ angle. Based on the principle of constant potential energy, a gravity balance mathematical model of the device was established, analyzed, and simulated. Moreover, through the training experiment, the results show that when subjects in three different weights were trained under the rehabilitation device with and without gravity balance, the required torques of the motor and EMG signal strength of the knee and hip joints decreased by a degree of significance, which verified the effectiveness of the device’s gravity balancing characteristics for MRC-2 patients.
Modeling and Fault Size Estimation for Non-Penetrating Damage in the Outer Raceway of Tapered Roller Bearing
Authors: Kang Wei , Zhu Yongsheng , Yan Ke , Liu Yuwei , Gao Dawei , Ren Zhijun
Published: June 2022

The fault quantification of a tapered roller bearing (TRB) can provide a reliable guide for predictive maintenance. Currently, damage size estimation based on vibration signals has been proposed and developed. However, most approaches are focused on the theory of ball bearings. Unlike the point contact of a ball bearing, the contact between the tapered roller and the raceway is a line contact. So, the current practices based on the micro-motion theory of ball bearings are limited when estimating the TRB’s fault. To accurately estimate the TRB’s damage size, a dynamic model of non-penetrating damaged TRB was established to research the vibration response mechanism and explain the influence. The model takes the deflection factor of a tapered roller into consideration and uses the elastohydrodynamic lubrication model to simulate the influence of the lubrication factor. Then, a revised formula for estimating the TRBs’ fault size is proposed by uncovering the relationship between the impact time and the damage location. Simulation analysis and experimental analysis prove the correctness of the dynamic model and the effectiveness of the size estimation formula.
Asymptotic Estimation of Two Telegraph Particle Collisions and Spread Options Valuations
Authors: Pogorui Anatoliy A. , Swishchuk Anatoliy , Rodríguez-Dagnino Ramón M.
Published: June 2022

In this paper, we study collisions of two telegraph particles on a line that are described by telegraph processes between collisions. We obtain an asymptotic estimation of the number of collisions under Kac’s condition for the cases where the direction-switching processes have the same parameters and different parameters. We also consider the application of these results to evaluate Margrabe’s spread option for two assets of spot prices modeled by two telegraph processes.
On the Geometry in the Large of Einstein-like Manifolds
Authors: Mikeš Josef , Rýparová Lenka , Stepanov Sergey , Tsyganok Irina
Published: June 2022

Gray has presented the invariant orthogonal irreducible decomposition of the space of all covariant tensors of rank 3, obeying only the identities of the gradient of the Ricci tensor. This decomposition introduced the seven classes of Einstein-like manifolds, the Ricci tensors of which fulfill the defining condition of each subspace. The large-scale geometry of such manifolds has been studied by many geometers using the classical Bochner technique. However, the scope of this method is limited to compact Riemannian manifolds. In the present paper, we prove several Liouville-type theorems for certain classes of Einstein-like complete manifolds. This represents an illustration of the new possibilities of geometric analysis.
A Novel Method for Remaining Useful Life Prediction of Bearing Based on Spectrum Image Similarity Measures
Authors: Wu Bo , Zhang Bo , Li Wei , Jiang Fan
Published: June 2022

Accurately predicting the remaining useful life (RUL) of bearing by analyzing vibration signals is challenging and meaningful. To address this issue, a novel method based on spectrum image similarity is proposed in this paper. First, spectrum images for the whole lifecycle data of reference bearings are obtained by performing fast Fourier transformation (FFT). Second, the similarity is calculated between the current monitored data of operating bearing and run-to-failure images of reference bearings. Then, the weights of reference bearings are derived based on the similarity measures. Finally, the RUL of the operating bearing is estimated with the weighted average of the RULs of referenced bearings. The proposed method is demonstrated based on 2012 PHM Data Challenge Competition data, which shows its effectiveness and practicality.
Summation Formulae for Quintic q-Series
Authors: Chu Wenchang
Published: June 2022

By utilizing the modified Abel lemma on summation by parts, we examine a class of quintic q-series, that have close connections to the “twisted cubic q-series”. Several remarkable summation and transformation formulae are established. The related reversal series are also reviewed briefly.
The New Second-Order Sliding Mode Control Algorithm
Authors: Kochetkov Sergey , Krasnova Svetlana A. , Utkin Victor A.
Published: June 2022

A new class of regulators on the basis of the second-order sliding mode control is proposed. For the second-order system with smooth disturbances, special feedback is chosen with a discontinuous component and a radical function component. The synthesized control law provides a transient oscillatory process with decaying amplitudes, which converge to zero in finite time. In contrast to existing algorithms, the condition of homogeneity of the closed-loop system differential equations is omitted. In comparison to the “twisting”-algorithm, which is well known, designed feedback provides an invariance property with respect to smooth external perturbation with less relay amplitude. With the help of a special Lyapunov function, the convergence proof is considered by using the averaging approach. It is shown that the average oscillation period convergence speed is strictly negative, and the estimation of the convergence time is presented. The simulation results of the designed control law for the one link robot-manipulator are presented, which shows less steady-state oscillations in comparison to existing approaches.
Research on Some Problems for Nonlinear Operators in the Z-Z-B Space
Authors: Liu Yiping , Zhu Chuanxi
Published: June 2022

In this paper, we first propose a new concept of Z-Z-B spaces, which is a generalization of Z-C-X spaces. Meanwhile, the new concept of the superior cone is introduced. Secondly, we study some new problems for semi-closed 1-set-contractive operators in the Z-Z-B space and obtain some new results. These new theorems are proven by combining partial order theory with fixed point index theory. Regarding these theorems, in the latter part of the paper, the proofs are omitted since the methods of proving these theorems are similar. Moreover, two important inequality lemmas are proven.
Extension of the q-Pfaff-Saalschütz Theorem by Two Integer Parameters
Authors: Li Nadia N. , Chu Wenchang
Published: June 2022

We investigate a class of terminating 3ϕ2-series that comes from the balanced series perturbed by two extra integer parameters. By making use of the linearization method, a general summation formula is established that extends the well-known q-Pfaff-Saalschütz theorem. Five closed formulae are exemplified as applications.
Permutation Tests for Metaheuristic Algorithms
Authors: Omran Mahamed G. H. , Clerc Maurice , Ghaddar Fatme , Aldabagh Ahmad , Tawfik Omar
Published: June 2022

Many metaheuristic approaches are inherently stochastic. In order to compare such methods, statistical tests are needed. However, choosing an appropriate test is not trivial, given that each test has some assumptions about the distribution of the underlying data that must be true before it can be used. Permutation tests (P-Tests) are statistical tests with minimal number of assumptions. These tests are simple, intuitive and nonparametric. In this paper, we argue researchers in the field of metaheuristics to adopt P-Tests to compare their algorithms. We define two statistic tests and then present an algorithm that uses them to compute the p-value. The proposed process is used to compare 5 metaheuristic algorithms on 10 benchmark functions. The resulting p-values are compared with the p-values of two widely used statistical tests. The results show that the proposed P-test is generally consistent with the classical tests, but more conservative in few cases.
Bézier-Summation-Integral-Type Operators That Include Pólya–Eggenberger Distribution
Authors: Mohiuddine Syed Abdul , Kajla Arun , Alotaibi Abdullah
Published: June 2022

We define the summation-integral-type operators involving the ideas of Pólya–Eggenberger distribution and Bézier basis functions, and study some of their basic approximation properties. In addition, by means of the Ditzian–Totik modulus of smoothness, we study a direct theorem as well as a quantitative Voronovskaja-type theorem for our newly constructed operators. Moreover, we investigate the approximation of functions with derivatives of bounded variation (DBV) of the aforesaid operators.
Unsupervised Learning for Feature Representation Using Spatial Distribution of Amino Acids in Aldehyde Dehydrogenase (ALDH2) Protein Sequences
Authors: Khandelwal Monika , Sheikh Sabha , Rout Ranjeet Kumar , Umer Saiyed , Mallik Saurav , Zhao Zhongming
Published: June 2022

Aldehyde dehydrogenase 2 (ALDH2) enzyme is required for alcohol detoxification. ALDH2 belongs to the aldehyde dehydrogenase family, the most important oxidative pathway of alcohol digestion. Two main liver isoforms of aldehyde dehydrogenase are cytosolic and mitochondrial. Approximately 50% of East Asians have ALDH2 deficiency (inactive mitochondrial isozyme), with lysine (K) for glutamate (E) substitution at position 487 (E487K). ALDH2 deficiency is also known as Alcohol Flushing Syndrome or Asian Glow. For people with an ALDH2 deficiency, their face turns red after drinking alcohol, and they are more susceptible to various diseases than ALDH2-normal people. This study performed a machine learning analysis of ALDH2 sequences of thirteen other species by comparing them with the human ALDH2 sequence. Based on the various quantitative metrics (physicochemical properties, secondary structure, Hurst exponent, Shannon entropy, and fractal dimension), these fourteen species were clustered into four clusters using the unsupervised machine learning (K-means clustering) algorithm. We also analyze these species using hierarchical clustering (agglomerative clustering) and draw the phylogenetic trees. The results show that Homo sapiens is more closely related to the Bos taurus and Sus scrofa species. Our experimental results suggest that the testing for discovering medicines may be done on these species before being tested in humans to alleviate the impacts of ALDH2 deficiency.
A Neural Network Model Secret-Sharing Scheme with Multiple Weights for Progressive Recovery
Authors: Wang Xianhui , Shan Hong , Yan Xuehu , Yu Long , Yu Yongqiang
Published: June 2022

With the widespread use of deep-learning models in production environments, the value of deep-learning models has become more prominent. The key issues are the rights of the model trainers and the security of the specific scenarios using the models. In the commercial domain, consumers pay different fees and have access to different levels of services. Therefore, dividing the model into several shadow models with multiple weights is necessary. When holders want to use the model, they can recover the model whose performance corresponds to the number and weights of the collected shadow models so that access to the model can be controlled progressively, i.e., progressive recovery is significant. This paper proposes a neural network model secret sharing scheme (NNSS) with multiple weights for progressive recovery. The scheme uses Shamir’s polynomial to control model parameters’ sharing and embedding phase, which in turn enables hierarchical performance control in the secret model recovery phase. First, the important model parameters are extracted. Then, effective shadow parameters are assigned based on the holders’ weights in the sharing phase, and t shadow models are generated. The holders can obtain a sufficient number of shadow parameters for recovering the secret parameters with a certain probability during the recovery phase. As the number of shadow models obtained increases, the probability becomes larger, while the performance of the extracted models is related to the participants’ weights in the recovery phase. The probability is proportional to the number and weights of the shadow models obtained in the recovery phase, and the probability of the successful recovery of the shadow parameters is 1 when all t shadow models are obtained, i.e., the performance of the reconstruction model can reach the performance of the secret model. A series of experiments conducted on VGG19 verify the effectiveness of the scheme.
Decisions for Blockchain Adoption and Information Sharing in a Low Carbon Supply Chain
Authors: Yang Tianjian , Li Chunmei , Yue Xiongping , Zhang Beibei
Published: June 2022

Enterprises in low-carbon supply chains have been exploring blockchain technology in order to make carbon data transparent. However, there is still some opaque information in the market, such as the value-added service efficiency. How do supply chain members make decisions between information sharing and blockchain adoption? This study considers blockchain adoption and information sharing in a low-carbon supply chain with a single manufacturer and a single retailer. The retailer has private information about value-added services and decides how to share it with the manufacturer. We examine six combined strategies comprised of blockchain scenarios and information sharing formats (no sharing, voluntary sharing, and mandatory sharing). The results indicate that supply chain members prefer blockchain technology under no sharing and voluntary sharing. Under mandatory sharing, supply chain members have incentives to participate in blockchain when the value-added service efficiency exceeds a threshold value. While the manufacturer prefers to obtain the value-added service information, the retailer decides to share information depending on the value-added service efficiency. Besides, supply chain members’ attitude toward the sharing contract also depends on the value-added service efficiency.
Analysis of a Stochastic Inventory Model on Random Environment with Two Classes of Suppliers and Impulse Customers
Authors: Vinitha V. , Anbazhagan N. , Amutha S. , Jeganathan K. , Shrestha Bhanu , Song Hyoung-Kyu , Joshi Gyanendra Prasad , Moon Hyeonjoon
Published: June 2022

This paper explores the random environment with two classes of suppliers and impulse customers. The system’s greatest inventory size is S, and it has an infinitely large orbit. In this case, there are two categories of suppliers: temporary suppliers and regular suppliers. Whenever the inventory approaches r, we place on order Q1 (=S−r) unit items to a temporary supplier. Similarly, when the inventory level drops to s (<Q1s+1) units of items to our regular supplier. Two types of suppliers’ lead times are considered to be exponentially distributed. Here, the customers who arrive from different states of the random environment (RE) are followed by the Markovian arrival process. If there is no inventory in the system when the customer arrives, they are automatically assigned to an orbit. The model was examined in steady state by using the matrix-analytic approach. Finally, the numerical examples for our structural model are discussed.
A VIKOR-Based Linguistic Multi-Attribute Group Decision-Making Model in a Quantum Decision Scenario
Authors: Xiao Jingmei , Cai Mei , Gao Yu
Published: June 2022

Quantum decision theory has been successfully applied to multi-attribute group decision-making (MAGDM) to model decision-makers’ interference and superposition effects in recent years. Existing quantum models assume that interference effects among decision-makers are symmetric. However, asymmetric interference effects have been ignored. We propose a VIKOR-based linguistic distribution assessments (LDAs) model considering asymmetric interference effects in a quantum decision scenario. Firstly, we combine VIKOR with LDAs to obtain a compromise solution in a fuzzy multi-attribute decision scenario with conflicting attributes. Secondly, an aggregation framework based on quantum probability theory is constructed to explore group preferences considering asymmetric interference effects among decision-makers. Finally, the model is compared with other methods to confirm its validity and stability.
Natural Lacunae Method and Schatten–Von Neumann Classes of the Convergence Exponent
Authors: Kukushkin Maksim V.
Published: June 2022

Our first aim is to clarify the results obtained by Lidskii devoted to the decomposition on the root vector system of the non-selfadjoint operator. We use a technique of the entire function theory and introduce a so-called Schatten–von Neumann class of the convergence exponent. Considering strictly accretive operators satisfying special conditions formulated in terms of the norm, we construct a sequence of contours of the power type that contrasts the results by Lidskii, where a sequence of contours of the exponential type was used.
Revisiting the Polynomial-Time Equivalence of Computing the CRT-RSA Secret Key and Factoring
Authors: Zheng Mengce
Published: June 2022

The Rivest–Shamir–Adleman (RSA) cryptosystem is currently the most influential and commonly used algorithm in public-key cryptography. Whether the security of RSA is equivalent to the intractability of the integer factorization problem is an interesting issue in mathematics and cryptography. Coron and May solved the above most fundamental problem and proved the polynomial-time equivalence of computing the RSA secret key and factoring. They demonstrated that the RSA modulus N=pq can be factored in polynomial time when given RSA key information (N,e,d). The CRT-RSA variant is a fast technical implementation of RSA using the Chinese Remainder Theorem (CRT), which aims to speed up the decryption process. We focus on the polynomial-time equivalence of computing the CRT-RSA secret key and factoring in this paper. With the help of the latest partial key exposure attack on CRT-RSA, we demonstrate that there exists a polynomial-time algorithm outputting the factorization of N=pq for edp,edq<N3/2 when given the CRT-RSA key information (N,e,dp,dq). We apply Coppersmith’s lattice-based method as a basic mathematical tool for finding the small root solutions of modular polynomial equations. Furthermore, we provide validation experiments to illustrate the correctness of the CRT-RSA modulus factorization algorithm, and show that computing the CRT-RSA secret key and factoring its modulus is polynomial-time equivalent by using concrete numerical examples.
A Lindley-Type Distribution for Modeling High-Kurtosis Data
Authors: Rojas Mario A. , Iriarte Yuri A.
Published: June 2022

This article proposes a heavy-tailed distribution for modeling positive data. The proposal arises with the ratio of independent random variables, specifically, a Lindley distribution divided by a beta distribution. This leads to a three-parameter extension of the Lindley distribution capable of modeling high levels of kurtosis. The main structural properties of the proposed distribution are derived. The skewness and kurtosis behavior of the distribution are described. Parameter estimation is discussed under consideration of the moment and maximum likelihood methods. Finally, in order to avoid the parameter non-identifiability problem, a two-parameter version of the proposed distribution is derived. The usefulness of this special case is illustrated by fitting data in two real scenarios.
Yamaguchi -Noshiro Type Bi-Univalent Functions Associated with Sălăgean-Erdély–Kober Operator
Authors: Alharbi Asma , Murugusundaramoorthy Gangadharan , El-Deeb Sheza. M.
Published: June 2022

We defined two new subclasses of analytic bi-univalent function class Σ, in the open unit disk related with the Sălăgean–Erdély–Kober operator. The bounds on initial coefficients |a2|,|a3| and |a4| for the functions in these new subclasses of Σ are investigated. Using the estimates of coefficients a2,a3, we also discuss the Fekete-Szegö inequality results for the function classes defined in this paper. Relevant connections of these results, presented here as corollaries, are new and not studied in association with Sălăgean-Erdély–Kober operator for the subclasses defined earlier.