bluuebunny/crossref_metadata_2025 huggingface dataset:
Beyond Diffusion: A Systematic Literature Review of Innovation Scaling
Authors: Breaugh Jessica , McBride Keegan , Kleinaltenkamp Moritz , Hammerschmid Gerhard
Published: December 2021

Innovation is essential for our ability to overcome global issues such as climate change, natural resource depletion, and inequality. A central aspect of innovation is the scaling process. While an abundance of studies on innovation scaling exist in many different disciplines, there is a lack of shared understanding of what scaling means and how it can be successfully achieved. This systematic literature review addresses both these issues by reviewing 147 articles on “innovation scaling” making several contributions to research on innovations and innovation scaling. First, in outlining the ontological differences between “diffusion” and “scaling”, clear conceptual boundaries are established, which provide clarity and support cross-disciplinary consilience. Second, based on the analysis of articles, eleven common modal contextual factors that influence the outcomes of innovation scaling across contexts and disciplines are presented. Third, an initial theoretical framework of the innovation scaling process is developed, outlining four theoretical propositions. As a fourth contribution, the article establishes a research agenda for the future development of innovation scaling research across many research domains.
Government Environmental Pressure and Market Response to Carbon Disclosure: A Study of the Early Chinese ETS Implementation
Authors: Jin Ling , Choi Jun-Hyeok , Kim Saerona , Yang Dong-Hoon
Published: December 2021

We studied how companies’ carbon disclosures affect the cost of capital under the Chinese government’s introduction of the Emissions Trading Scheme (ETS) regulation. We also tested how much the effect varied between state-owned and private enterprises, and between polluting and non-polluting industries. Since, at its early stage, the market may perceive signals and implementations of environmental regulation as a cost burden, the effect of environmental disclosure, which is traditionally known to reduce the cost of capital, may be different. Using a comprehensive index through content analysis and targeting companies in China’s pilot ETS regions between 2011 and 2016, our study showed the following test results. First, for the companies in regions where the ETS regulation was introduced, while carbon disclosure was below a certain level, disclosure raised the cost of capital, and after carbon disclosure was sufficiently high, disclosure decreased the cost of capital. Second, this inverted-U-shaped relationship appeared in non-state-owned enterprises only, and state-owned enterprises showed a traditional linear relationship that disclosure lowers the cost of capital. Third, this non-linear relationship was statistically significant only in the non-heavy pollution industries. This study contributes to the literature in that there are limited studies on the market effects of China’s early introduction of the ETS regulation.
New Results of the Time-Space Fractional Derivatives of Kortewege-De Vries Equations via Novel Analytic Method
Authors: Sultana Mariam , Arshad Uroosa , Alam Md. Nur , Bazighifan Omar , Askar Sameh , Awrejcewicz Jan
Published: December 2021

Symmetry performs an essential function in finding the correct techniques for solutions to time space fractional differential equations (TSFDEs). In this article, we present the Novel Analytic Method (NAM) for approximate solutions of the linear and non-linear KdV equation for TSFDs. To enunciate the non-integer derivative for the aforementioned equation, the Caputo operator is manipulated. Furthermore, the formula implemented is a numerical way that is postulated from Taylor’s series, which confirms an analytical answer in the form of a convergent series. For delineation of the efficiency and functionality of the method in question, four applications are exemplified along with graphical interpretation and numerical solutions to finitely illustrate the behavior of the solution to this equation. Moreover, the 3D graphs of some of these numerical examples are plotted with specific values. Observing the effectiveness of this process, we can easily decide that this process can be implemented to other TSFDEs applied in the mathematical modeling of a real-world aspect.
Families of Generalized Quasisymmetry Models: A ϕ-Divergence Approach
Authors: Kateri Maria
Published: December 2021

The quasisymmetry (QS) model for square contingency tables is revisited, highlighting properties and features on the basis of its alternative definitions. More parsimonious QS-type models, such as the ordinal QS model for ordinal classification variables and models based on association models (AMs) with homogeneous row and column scores, are discussed. All these models are linked to the local odds ratios (LOR). QS-type models and AMs were extended in the literature for generalized odds ratios other than LOR. Furthermore, in an information-theoretic context, they are expressed as distance models from a parsimonious reference model (the complete symmetry for QS and the independence for AMs), while they satisfy closeness properties with respect to Kullback–Leibler (KL) divergence. Replacing the KL by ϕ divergence, flexible classes of QS-type models for LOR, AMs for LOR, and AMs for generalized odds ratios were generated. However, special QS-type models that are based on homogeneous AMs for LOR have not been extended to ϕ-divergence-based classes so far, or the QS-type models for generalized odds ratios. In this work, we develop these missing extensions, and discuss QS-type models and their generalizations in depth. These flexible families enrich the modeling options, leading to models of better fit and sound interpretation, as illustrated by representative examples.
Photophysical Properties and Electronic Structure of Symmetrical Curcumin Analogues and Their BF2 Complexes, Including a Phenothiazine Substituted Derivative
Authors: Gál Emese , Nagy Levente Csaba
Published: December 2021

Symmetrically substituted curcumin analogue compounds possess electron donor moieties at both ends of the conjugated systems; their difluoroboron complexes were synthesized, and their structures were fully characterized. A novel compound with enhanced photophysical properties bearing phenothiazine moieties is reported. The introduction of BF2 into the molecular structures resulted in bathochromic shifts both in the absorption and emission spectra, indicating that the π-conjugation was more extended than the one in the initial compounds. The solvatochromic effects were studied, which in case of the phenothiazinyl-curcumin BF2 complex was the most notable. Theoretical study of the investigated compounds was carried out using DFT and TD-DFT methods to evaluate the ground state geometries and vertical excitation energies.
An Investigation on Weak Concepts in Ordered Hyperstructures
Authors: Rao Yongsheng , Zhao Jietong , Khan Aysha , Akhoundi Maryam , Omidi Saber
Published: December 2021

The class of weak pseudoorders and left weak interior hyperideals in ordered hyperstructures is a generalization of pseudoorders and interior hyperideals. In this work, we study the concept of weak pseudoorders and left weak interior hyperideals in ordered hyperstructures and explore some results concerning the new defined concepts for ordered hyperrings and ordered Γ-semihypergroups. In this regards, we intend to concentrate our efforts on the relationship between the left weak interior hyperideal and interior hyperideal of an ordered hyperstructure. A characterization of a regular ordered hyperstructure via a left weak interior hyperideal is given. Finally, we characterize the notion of left weak interior simple ordered hyperstructures in terms of left weak interior hyperideals.
Modulation Recognition of Communication Signal Based on Convolutional Neural Network
Authors: Jiang Kaiyuan , Qin Xvan , Zhang Jiawei , Wang Aili
Published: December 2021

In the noncooperation communication scenario, digital signal modulation recognition will help people to identify the communication targets and have better management over them. To solve problems such as high complexity, low accuracy and cumbersome manual extraction of features by traditional machine learning algorithms, a kind of communication signal modulation recognition model based on convolution neural network (CNN) is proposed. In this paper, a convolution neural network combines bidirectional long short-term memory (BiLSTM) with a symmetrical structure to successively extract the frequency domain features and timing features of signals and then assigns importance weights based on the attention mechanism to complete the recognition task. Seven typical digital modulation schemes including 2ASK, 4ASK, 4FSK, BPSK, QPSK, 8PSK and 64QAM are used in the simulation test, and the results show that, compared with the classical machine learning algorithm, the proposed algorithm has higher recognition accuracy at low SNR, which confirmed that the proposed modulation recognition method is effective in noncooperation communication systems.
Nonlocal Neumann Boundary Value Problem for Fractional Symmetric Hahn Integrodifference Equations
Authors: Dumrongpokaphan Thongchai , Patanarapeelert Nichaphat , Sitthiwirattham Thanin
Published: December 2021

In this article, we present a nonlocal Neumann boundary value problems for separate sequential fractional symmetric Hahn integrodifference equation. The problem contains five fractional symmetric Hahn difference operators and one fractional symmetric Hahn integral of different orders. We employ Banach fixed point theorem and Schauder’s fixed point theorem to study the existence results of the problem.
Correction: Iriarte et al. A Unimodal/Bimodal Skew/Symmetric Distribution Generated from Lambert’s Transformation. Symmetry 2021, 13, 269
Authors: Iriarte Yuri A. , de Castro Mário , Gómez Héctor W.
Published: December 2021

In the original article [...]
Effective Intrusion Detection System to Secure Data in Cloud Using Machine Learning
Authors: Aldallal Ammar , Alisa Faisal
Published: December 2021

When adopting cloud computing, cybersecurity needs to be applied to detect and protect against malicious intruders to improve the organization’s capability against cyberattacks. Having network intrusion detection with zero false alarm is a challenge. This is due to the asymmetry between informative features and irrelevant and redundant features of the dataset. In this work, a novel machine learning based hybrid intrusion detection system is proposed. It combined support vector machine (SVM) and genetic algorithm (GA) methodologies with an innovative fitness function developed to evaluate system accuracy. This system was examined using the CICIDS2017 dataset, which contains normal and most up-to-date common attacks. Both algorithms, GA and SVM, were executed in parallel to achieve two optimal objectives simultaneously: obtaining the best subset of features with maximum accuracy. In this scenario, an SVM was employed using different values of hyperparameters of the kernel function, gamma, and degree. The results were benchmarked with KDD CUP 99 and NSL-KDD. The results showed that the proposed model remarkably outperformed these benchmarks by up to 5.74%. This system will be effective in cloud computing, as it is expected to provide a high level of symmetry between information security and detection of attacks and malicious intrusion.
On the Semi-Analytical Solutions in Hydrodynamics of Ideal Fluid Flows Governed by Large-Scale Coherent Structures of Spiral-Type
Authors: Ershkov Sergey V. , Rachinskaya Alla , Prosviryakov Evgenii Yu. , Shamin Roman V.
Published: December 2021

We have presented here a clearly formulated algorithm or semi-analytical solving procedure for obtaining or tracing approximate hydrodynamical fields of flows (and thus, videlicet, their trajectories) for ideal incompressible fluids governed by external large-scale coherent structures of spiral-type, which can be recognized as special invariant at symmetry reduction. Examples of such structures are widely presented in nature in “wind-water-coastline” interactions during a long-time period. Our suggested mathematical approach has obvious practical meaning as tracing process of formation of the paths or trajectories for material flows of fallout descending near ocean coastlines which are forming its geometry or bottom surface of the ocean. In our presentation, we explore (as first approximation) the case of non-stationary flows of Euler equations for incompressible fluids, which should conserve the Bernoulli-function as being invariant for the aforementioned system. The current research assumes approximated solution (with numerical findings), which stems from presenting the Euler equations in a special form with a partial type of approximated components of vortex field in a fluid. Conditions and restrictions for the existence of the 2D and 3D non-stationary solutions of the aforementioned type have been formulated as well.
UAV-Assisted Three-Dimensional Spectrum Mapping Driven by Spectrum Data and Channel Model
Authors: Du Xiaofu , Zhu Qiuming , Ding Guoru , Li Jie , Wu Qihui , Lan Tianxu , Lin Zhipeng , Zhong Weizhi , Han Lu
Published: December 2021

As the number of civil aerial vehicles increase explosively, spectrum scarcity and security become an increasingly challenge in both the airspace and terrestrial space. To address this difficulty, this paper presents an unmanned aerial vehicle-assisted (UAV-assisted) spectrum mapping system and a spectrum data reconstruction algorithm driven by spectrum data and channel model are proposed. The reconstruction algorithm, which includes a model-driven spectrum data inference method and a spectrum data completion method with uniformity decision mechanism, can reconstruct limited and incomplete spectrum data to a three-dimensional (3D) spectrum map. As a result, spectrum scarcity and security can be achieved. Spectrum mapping is a symmetry-based digital twin technology. By employing an uniformity decision mechanism, the proposed completion method can effectively interpolate spatial data even when the collected data are unevenly distributed. The effectiveness of the proposed mapping scheme is evaluated by comparing its results with the ray-tracing simulated data of the campus scenario. Simulation results show that the proposed reconstruction algorithm outperforms the classical inverse distance weighted (IDW) interpolation method and the tensor completion method by about 12.5% and 92.3%, respectively, in terms of reconstruction accuracy when the collected spectrum data are regularly missing, unevenly distributed and limited.
Dynamics of Characteristic and One-Point Correlation Functions of Multi-Mode Bosonic Systems: Exactly Solvable Model
Authors: Kiselev Alexei D. , Ali Ranim , Rybin Andrei V.
Published: December 2021

In this communication we study dynamics of the open quantum bosonic system governed by the generalized Lindblad equation with both dynamical and environment induced intermode couplings taken into account. By using the method of characteristics we deduce the analytical expression for the normally ordered characteristic function. Analytical results for one-point correlation functions describing temporal evolution of the covariance matrix are obtained.
Starlikeness of New General Differential Operators Associated with q-Bessel Functions
Authors: Andrei Loriana , Caus Vasile-Aurel
Published: December 2021

Owning to the importance and great interest of differential operators, two generalized differential operators, which may be symmetric or assymetric, are newly introduced in the present paper. Motivated by the familiar Jackson’s second and third Bessel functions, we derive necessary and sufficient conditions for which the new generalized operators belong to the class of q-starlike functions of order alpha. Several corollaries and consequences of the main results are also pointed out.
Developing an Optical Measuring System for Hole Saw Caps
Authors: Lu Chien-Yu , Chang Tsung-Chieh , Lee Lian-Wang , Sung Rong-Chu , Su Te-Jen
Published: December 2021

This paper developed a set of size detection systems with a computer vision method based on the accuracy requirements of the hole saw caps to meet the needs of the accuracy detection machine. The results allow manufacturers to build a digitalized hole saw cap detection system at a low cost. We have designed a measurement system for the hole saw caps with the computer vision method to measure the dimensions of the hole saw caps. However, a valid measurement value of the hole saw caps must be positioned symmetrically. However, in fact, when the measurement system is positioned accurately asymmetrically, it will cause a problem in the measurement data. Therefore, the dark box environment made of a light source and the back plate of the hole saw caps material and two cameras are employed to observe the hole saw caps from both above and the side views. Then, personal desktop computers calculate the size of the hole saw caps based on the camera screen vision with a Python program. The results of the proposed methodology are obtained by measuring 10 workpieces of different sizes, and all the errors within a range of 2 pixels (pixel, px) met the detection standards. Therefore, the developed hole saw cap detection system is in line with expectations.
A Possible Neutron-Antineutron Oscillation Experiment at PF1B at the Institut Laue Langevin
Authors: Gudkov Vladimir , Klinby Esben , Meirose Bernhard , Milstead David , Nesvizhevsky Valery V. , Protasov Konstantin V. , Rizzi Nicola , Santoro Valentina , Snow William Michael , Wagner Richard , Yiu Sze-Chun
Published: December 2021

We consider a possible neutron–antineutron (n−n¯) oscillation experiment at the PF1B instrument at Institut Laue Langevin. It can improve the best existing constraint on the transition rate and also allow the testing of the methods and instrumentation which would be needed for a later larger-scale experiment at ESS. The main gain factors over the most competitive experiment, performed earlier at PF1 instrument at ILL, are: a more intense neutron beam and a new operating mode based on coherent n and n¯ mirror reflections. The installation of such an experiment would need a temporary replacement of the existing ballistic neutron guide by a specially designed n/n¯ guide with a gradually increasing cross section and a specially selected coating as well as the development and construction of an advanced n¯ annihilation detector with a high efficiency and low background. The overall gain factor could reach up to an order of magnitude and depends on the chosen experiment configuration.
A Relativistic Toda Lattice Hierarchy, Discrete Generalized (m,2N−m)-Fold Darboux Transformation and Diverse Exact Solutions
Authors: Qin Meng-Li , Wen Xiao-Yong , Yuen Manwai
Published: December 2021

This paper investigates a relativistic Toda lattice system with an arbitrary parameter that is a very remarkable generalization of the usual Toda lattice system, which may describe the motions of particles in lattices. Firstly, we study some integrable properties for this system such as Hamiltonian structures, Liouville integrability and conservation laws. Secondly, we construct a discrete generalized (m,2N−m)-fold Darboux transformation based on its known Lax pair. Thirdly, we obtain some exact solutions including soliton, rational and semi-rational solutions with arbitrary controllable parameters and hybrid solutions by using the resulting Darboux transformation. Finally, in order to understand the properties of such solutions, we investigate the limit states of the diverse exact solutions by using graphic and asymptotic analysis. In particular, we discuss the asymptotic states of rational solutions and exponential-and-rational hybrid solutions graphically for the first time, which might be useful for understanding the motions of particles in lattices. Numerical simulations are used to discuss the dynamics of some soliton solutions. The results and properties provided in this paper may enrich the understanding of nonlinear lattice dynamics.
New Self-Adaptive Inertial-like Proximal Point Methods for the Split Common Null Point Problem
Authors: Tang Yan , Zhang Yeyu , Gibali Aviv
Published: December 2021

Symmetry plays an important role in solving practical problems of applied science, especially in algorithm innovation. In this paper, we propose what we call the self-adaptive inertial-like proximal point algorithms for solving the split common null point problem, which use a new inertial structure to avoid the traditional convergence condition in general inertial methods and avoid computing the norm of the difference between xn and xn−1 before choosing the inertial parameter. In addition, the selection of the step-sizes in the inertial-like proximal point algorithms does not need prior knowledge of operator norms. Numerical experiments are presented to illustrate the performance of the algorithms. The proposed algorithms provide enlightenment for the further development of applied science in order to dig deep into symmetry under the background of technological innovation.
Approximations of Symmetric Functions on Banach Spaces with Symmetric Bases
Authors: Martsinkiv Mariia , Zagorodnyuk Andriy
Published: December 2021

This paper is devoted to studying approximations of symmetric continuous functions by symmetric analytic functions on a Banach space X with a symmetric basis. We obtain some positive results for the case when X admits a separating polynomial using a symmetrization operator. However, even in this case, there is a counter-example because the symmetrization operator is well defined only on a narrow, proper subspace of the space of analytic functions on X. For X=c0, we introduce ε-slice G-analytic functions that have a behavior similar to G-analytic functions at points x∈c0 such that all coordinates of x are greater than ε, and we prove a theorem on approximations of uniformly continuous functions on c0 by ε-slice G-analytic functions.
On Convex Functions Associated with Symmetric Cardioid Domain
Authors: Malik Sarfraz Nawaz , Raza Mohsan , Xin Qin , Sokół Janusz , Manzoor Rabbiya , Zainab Saira
Published: December 2021

The geometry of the image domain plays an important role in the characterization of analytic functions. Therefore, for a comprehensive and detailed study of these functions, a thorough analysis of the geometrical properties of their domains is of prime interest. In this regard, new geometrical structures are introduced and studied as an image domain and then their subsequent analytic functions are defined. Inspired and motivated by ongoing research, Malik et al. introduced a very innovative domain named the cardioid domain, which is symmetric about a real axis. Extending the same work on this symmetric cardioid domain, in this article, we provide a deeper analysis and define and study the convex functions associated with the symmetric cardioid domain, named cardio-convex functions.
Some Single-Valued Neutrosophic Uncertain Linguistic Maclaurin Symmetric Mean Operators and Their Application to Multiple-Attribute Decision Making
Authors: Song Hongbing , Geng Yushui
Published: December 2021

The Maclaurin symmetric mean (MSM) operator has a good aggregation effect. It can capture the relationships between multiple input parameters, and the neutrosophic uncertain linguistic numbers can well represent some indeterminate and incomplete information. In this paper, we combine the MSM operator with the singled-valued neutrosophic uncertain linguistic set and propose some MSM operators based on single-valued neutrosophic uncertain linguistic environment, such as single-valued neutrosophic uncertain linguistic Maclaurin symmetric mean(SVNULMSM) operator and single-valued neutrosophic uncertain linguistic generalized Maclaurin symmetric mean(SVNULGMSM) operator. First of all, according to the neutrosophic set and uncertain linguistic numbers, we propose the single-valued neutrosophic uncertain linguistic numbers and give some operating rules. Furthermore, considering the influence of attribute weight on the results, we introduce the weighted SVNULMSM operator and weighted SVNULGMSM operator. Then, we propose a method to deal with MSDM problems and give the specific steps to solve the problem. Finally, an investment example is used to verify the effectiveness of our method, and the superiority of the method is proved by comparing with other methods.
Quantum Coherence of Atoms with Dipole–Dipole Interaction and Collective Damping in the Presence of an Optical Field
Authors: Algarni Mariam , Berrada Kamal , Abdel-Khalek Sayed , Eleuch Hichem
Published: December 2021

We investigate the effect of the interatomic distances and thermal reservoir on the coherence dynamics of the atoms considering the dipole–dipole interaction (DDI) and collective damping effect (CDE). We show that the control and protection of the coherence are very sensitive to the interatomic distances and reservoir temperature. Furthermore, we explore the distance effect between atoms and reservoir temperature on the time evolution of the total quantum correlation between the two atoms. The obtained results could be useful to execute these quantum phenomena and also considered as a good indication to implement realistic experiments with optimal conditions.
Lateral-Torsional Buckling Analysis for Doubly Symmetric Tubular Flange Composite Beams with Lateral Bracing under Concentrated Load
Authors: Liu Yingchun , He Ziwen , Zhang Wenfu , Ji Jing , Liu Yuchen , Wang Zizhen , Wang Ruili , Yang Kailin , Zhang Zhichao
Published: December 2021

Tubular flange composite beams are increasingly applied in modern bridge structures. In order to investigate the overall stability behavior of doubly symmetric tubular flange composite beams with lateral bracing under concentrated load, the analysis of elastic lateral-torsional buckling is conducted by the energy variation method. The analytical solution of critical moment of doubly symmetric tubular flange composite beams with lateral bracing is obtained. Meanwhile, the simplified calculation formula of critical moment is fitted by 1stOpt software based on 26,000 groups of data, and the accuracy is verified by the finite element method. It is found that, the critical moment rises obviously with increasing lateral bracing stiffness, and adding lateral bracing to doubly symmetric tubular flange composite beams is beneficial to improve the overall stability in engineering practice. Finally, the influence of several parameters including concrete strength, span, steel ratio of flange and height-thickness ratio of web are studied. The results show that the concrete strength and the web height-thickness ratio have a weak influence on critical moment of elastic lateral-torsional buckling, while the influence of span-depth ratio and flange steel ratio is very significant.
Eigenvalue-Based Spectrum Sensing with Small Samples Using Circulant Matrix
Authors: Du Liping , Fu Yuting , Chen Yueyun , Wang Xiaojian , Zhang Xiaoyan
Published: December 2021

In cognitive radio (CR) networks, eigenvalue-based detectors (EBDs) have attracted much attention due to their good performance of detecting secondary users (SUs). In order to further improve the detection performance of EBDs with short samples, we propose two new detectors: average circulant matrix-based Roy’s largest root test (ACM-RLRT) and average circulant matrix-based generalized likelihood ratio test (ACM-GLRT). In the proposed method, the circulant matrix of samples at each time instant from SUs is calculated, and then, the covariance matrix of the circulant matrix is averaged over a short period of time. The eigenvalues of the achieved average circulant matrix (ACM) are used to build our proposed detectors. Using a circulant matrix can improve the dominant eigenvalue of covariance matrix of signals and also the detection performance of EBDs even with short samples. The probability distribution functions of the detectors undernull hypothesis are analyzed, and the asymptotic expressions for the false-alarm and thresholds of two proposed detectors are derived, respectively. The simulation results verify the effectiveness of the proposed detectors.
Incompatible Deformations in Additively Fabricated Solids: Discrete and Continuous Approaches
Authors: Lychev Sergey , Koifman Konstantin , Djuzhev Nikolay
Published: December 2021

The present paper is intended to show the close interrelationship between non-linear models of solids, produced with additive manufacturing, and models of solids with distributed defects. The common feature of these models is the incompatibility of local deformations. Meanwhile, in contrast with the conventional statement of the problems for solids with defects, the distribution for incompatible local deformations in additively created deformable body is not known a priori, and can be found from the solution of the specific evolutionary problem. The statement of the problem is related to the mechanical and physical peculiarities of the additive process. The specific character of incompatible deformations, evolved in additive manufactured solids, could be completely characterized within a differential-geometric approach by specific affine connection. This approach results in a global definition of the unstressed reference shape in non-Euclidean space. The paper is focused on such a formalism. One more common factor is the dataset which yields a full description of the response of a hyperelastic solid with distributed defects and a similar dataset for the additively manufactured one. In both cases, one can define a triple: elastic potential, gauged at stress-free state, and reference shape, and some specific field of incompatible relaxing distortion, related to the given stressed shape. Optionally, the last element of the triple may be replaced by some geometrical characteristics of the non-Euclidean reference shape, such as torsion, curvature, or, equivalently, as the density of defects. All the mentioned conformities are illustrated in the paper with a non-linear problem for a hyperelastic hollow ball.
Symmetric and Asymmetric Synapses Driving Neurodegenerative Disorders
Authors: Romaus-Sanjurjo Daniel , Custodia Antía , Aramburu-Núñez Marta , Posado-Fernández Adrián , Vázquez-Vázquez Laura , Camino-Castiñeiras Javier , Leira Yago , Pías-Peleteiro Juan Manuel , Aldrey José Manuel , Ouro Alberto , Sobrino Tomás
Published: December 2021

In 1959, E. G. Gray described two different types of synapses in the brain for the first time: symmetric and asymmetric. Later on, symmetric synapses were associated with inhibitory terminals, and asymmetric synapses to excitatory signaling. The balance between these two systems is critical to maintain a correct brain function. Likewise, the modulation of both types of synapses is also important to maintain a healthy equilibrium. Cerebral circuitry responds differently depending on the type of damage and the timeline of the injury. For example, promoting symmetric signaling following ischemic damage is beneficial only during the acute phase; afterwards, it further increases the initial damage. Synapses can be also altered by players not directly related to them; the chronic and long-term neurodegeneration mediated by tau proteins primarily targets asymmetric synapses by decreasing neuronal plasticity and functionality. Dopamine represents the main modulating system within the central nervous system. Indeed, the death of midbrain dopaminergic neurons impairs locomotion, underlying the devastating Parkinson’s disease. Herein, we will review studies on symmetric and asymmetric synapses plasticity after three different stressors: symmetric signaling under acute damage—ischemic stroke; asymmetric signaling under chronic and long-term neurodegeneration—Alzheimer’s disease; symmetric and asymmetric synapses without modulation—Parkinson’s disease.
The Influence of Mental Imagery Expertise of Pen and Paper Players versus Computer Gamers upon Performance and Electrocortical Correlates in a Difficult Mental Rotation Task
Authors: Rodrigues Johannes , Marzban Dorna , Hewig Johannes
Published: December 2021

We investigated the influence of mental imagery expertise in 15 pen and paper role-players as an expert group compared to the gender-matched control group of computer role-players in the difficult Vandenberg and Kuse mental rotation task. In this task, the participants have to decide which two of four rotated figures match the target figure. The dependent measures were performance speed and accuracy. In our exploratory investigation, we further examined midline frontal theta band activation, parietal alpha band activation, and parietal alpha band asymmetry in EEG as indicator for the chosen rotation strategy. Additionally, we explored the gender influence on performance and EEG activation, although a very small female sample section was given. The expected gender difference concerning performance accuracy was negated by expertise in pen and paper role-playing women, while the gender-specific difference in performance speed was preserved. Moreover, gender differences concerning electro-cortical measures revealed differences in rotation strategy, with women using top-down strategies compared to men, who were using top-down strategies and active inhibition of associative cortical areas. These strategy uses were further moderated by expertise, with higher expertise leading to more pronounced activation patters, especially during successful performance. However, due to the very limited sample size, the findings of this explorative study have to be interpreted cautiously.
Base Point Freeness, Uniqueness of Decompositions and Double Points for Veronese and Segre Varieties
Authors: Ballico Edoardo
Published: December 2021

We prove a base point freeness result for linear systems of forms vanishing at general double points of the projective plane. For tensors we study the uniqueness problem for the representation of a tensor as a sum of terms corresponding to points and tangent vectors of the Segre variety associated with the format of the tensor. We give complete results for unions of one point and one tangent vector.
PURA-SCIS Protocol: A Novel Solution for Cloud-Based Information Sharing Protection for Sectoral Organizations
Authors: Putra Fandi Aditya , Ramli Kalamullah , Hayati Nur , Gunawan Teddy Surya
Published: December 2021

Over recent years, the incidence of data breaches and cyberattacks has increased significantly. This has highlighted the need for sectoral organizations to share information about such events so that lessons can be learned to mitigate the prevalence and severity of cyber incidents against other organizations. Sectoral organizations embody a governance relationship between cross-sector public and private entities, called public-private partnerships (PPPs). However, organizations are hesitant to share such information due to a lack of trust and business-critical confidentially issues. This problem occurs because of the absence of any protocols that guarantee privacy protection and protect sensitive information. To address this issue, this paper proposes a novel protocol, Putra-Ramli Secure Cyber-incident Information Sharing (PURA-SCIS), to secure cyber incident information sharing. PURA-SCIS has been designed to offer exceptional data and privacy protection and run on the cloud services of sectoral organizations. The relationship between organizations in PURA-SCIS is symmetrical, where the entities must collectively maintain the security of classified cyber incident information. Furthermore, the organizations must be legitimate entities in the PURA-SCIS protocol. The Scyther tool was used for protocol verification in PURA-SCIS. The experimental results showed that the proposed PURA-SCIS protocol provided good security properties, including public verifiability for all entities, blockless verification, data privacy preservation, identity privacy preservation and traceability, and private information sharing. PURA-SCIS also provided a high degree of confidentiality to protect the security and integrity of cyber-incident-related information exchanged among sectoral organizations via cloud services.
Lower Limb Perfusion Asymmetries in Humans at Rest and Following Activity—A Collective View
Authors: Rodrigues Luis Monteiro , Rocha Clemente Gomes , Florindo Margarida Esteves , Gregório João
Published: December 2021

The significance of lower limb perfusion asymmetries remains unknown in healthy individuals. Our study aims to understand how factors such as posture, sex, age, and body weight relate to perfusion. Data from studies previously published by our group, including experiments using laser Doppler flowmetry as the gold standard for perfusion measurements in baseline, (various) challenge, and recovery phases was assembled from a total of 139 healthy participants. Body position was shown to be a primary determinant of perfusion asymmetry, especially in women. Effects of sex and age were also analyzed. In a supine position, perfusion asymmetries seemed to relate negatively in the aged group of participants, where challenge and recovery seemed to follow different processes. In the upright position, young men and women have shown comparable distributions and asymmetry ratios at baseline and recovery. In the aged group, differences between sexes were observed at baseline, but again, the course of the asymmetry ratios with challenge was essentially similar in men and women. Our analysis suggests that ageing is a critical determinant in our upright study sample, as higher baseline asymmetries and longer recoveries after challenge were linked in older males with higher body mass index (BMI).
Differential Ageing of the Brain Hemispheres: Evidence from a Longitudinal Study of Hand Preferences in Common Marmosets
Authors: Rogers Lesley J.
Published: December 2021

This paper is concerned with decreasing asymmetry of motor control in ageing. It discusses age-related changes in humans and reports a longitudinal study of hand preferences in common marmosets. An annual assessment of hand preference for holding food was recorded throughout the lifespan of 19 marmosets that lived for at least 9 years, and half of those lived for at least 11 years. Those with a left-hand preference showed a gradual reduction in the strength of their hand preference throughout adult life. No significant change in the strength of hand preference was found in right-handed marmosets. Hence, ageing has a specific effect on motor control by the right hemisphere.
An Exploration into the Detection of COVID-19 from Chest X-ray Scans Using the xRGM-NET Convolutional Neural Network
Authors: Ackall Gabriel , Elmzoudi Mohammed , Yuan Richard , Chen Cuixian
Published: December 2021

COVID-19 has spread rapidly across the world since late 2019. As of December, 2021, there are over 250 million documented COVID-19 cases and over 5 million deaths worldwide, which have caused businesses, schools, and government operations to shut down. The most common method of detecting COVID-19 is the RT-PCR swab test, which suffers from a high false-negative rate and a very slow turnaround for results, often up to two weeks. Because of this, specialists often manually review X-ray images of the lungs to detect the presence of COVID-19 with up to 97% accuracy. Neural network algorithms greatly accelerate this review process, analyzing hundreds of X-rays in seconds. Using the Cohen COVID-19 X-ray Database and the NIH ChestX-ray8 Database, we trained and constructed the xRGM-NET convolutional neural network (CNN) to detect COVID-19 in X-ray scans of the lungs. To further aid medical professionals in the manual review of X-rays, we implemented the CNN activation mapping technique Score-CAM, which generates a heat map over an X-ray to illustrate which areas in the scan are most influential over the ultimate diagnosis. xRGM-NET achieved an overall classification accuracy of 97% with a sensitivity of 94% and specificity of 97%. Lightweight models like xRGM-NET can serve to improve the efficiency and accuracy of COVID-19 detection in developing countries or rural areas. In this paper, we report on our model and methods that were developed as part of a STEM enrichment summer program for high school students. We hope that our model and methods will allow other researchers to create lightweight and accurate models as more COVID-19 X-ray scans become available.
A Survey on Traffic Prediction Techniques Using Artificial Intelligence for Communication Networks
Authors: Chen Aaron , Law Jeffrey , Aibin Michal
Published: December 2021

Much research effort has been conducted to introduce intelligence into communication networks in order to enhance network performance. Communication networks, both wired and wireless, are ever-expanding as more devices are increasingly connected to the Internet. This survey introduces machine learning and the motivations behind it for creating cognitive networks. We then discuss machine learning and statistical techniques to predict future traffic and classify each into short-term or long-term applications. Furthermore, techniques are sub-categorized into their usability in Local or Wide Area Networks. This paper aims to consolidate and present an overview of existing techniques to stimulate further applications in real-world networks.
Isolation and Characterization of A2-EPTX-Nsm1a, a Secretory Phospholipase A2 from Malaysian Spitting Cobra (Naja sumatrana) Venom
Authors: Abdullah Nur Atiqah Haizum , Rusmili Muhamad Rusdi Ahmad , Zainal Abidin Syafiq Asnawi , Shaikh Mohd Farooq , Hodgson Wayne C. , Othman Iekhsan
Published: December 2021

Phospholipase A2 (PLA2) toxins are one of the main toxin families found in snake venom. PLA2 toxins are associated with various detrimental effects, including neurotoxicity, myotoxicity, hemostatic disturbances, nephrotoxicity, edema, and inflammation. Although Naja sumatrana venom contains substantial quantities of PLA2 components, there is limited information on the function and activities of PLA2 toxins from the venom. In this study, a secretory PLA2 from the venom of Malaysian N. sumatrana, subsequently named A2-EPTX-Nsm1a, was isolated, purified, and characterized. A2-EPTX-Nsm1a was purified using a mass spectrometry-guided approach and multiple chromatography steps. Based on LC-MSMS, A2-EPTX-Nsm1a was found to show high sequence similarity with PLA2 from venoms of other Naja species. The PLA2 activity of A2-EPTX-Nsm1 was inhibited by 4-BPB and EDTA. A2-EPTX-Nsm1a was significantly less cytotoxic in a neuroblastoma cell line (SH-SY5Y) compared to crude venom and did not show a concentration-dependent cytotoxic activity. To our knowledge, this is the first study that characterizes and investigates the cytotoxicity of an Asp49 PLA2 isolated from Malaysian N. sumatrana venom in a human neuroblastoma cell line.
Infant Botulism: Checklist for Timely Clinical Diagnosis and New Possible Risk Factors Originated from a Case Report and Literature Review
Authors: Dilena Robertino , Pozzato Mattia , Baselli Lucia , Chidini Giovanna , Barbieri Sergio , Scalfaro Concetta , Finazzi Guido , Lonati Davide , Locatelli Carlo Alessandro , Cappellari Alberto , Anniballi Fabrizio
Published: December 2021

Infant botulism is a rare and underdiagnosed disease caused by BoNT-producing clostridia that can temporarily colonize the intestinal lumen of infants less than one year of age. The diagnosis may be challenging because of its rareness, especially in patients showing atypical presentations or concomitant coinfections. In this paper, we report the first infant botulism case associated with Cytomegalovirus coinfection and transient hypogammaglobulinemia and discuss the meaning of these associations in terms of risk factors. Intending to help physicians perform the diagnosis, we also propose a practical clinical and diagnostic criteria checklist based on the revision of the literature.
Evolution of the Ergot Alkaloid Biosynthetic Gene Cluster Results in Divergent Mycotoxin Profiles in Claviceps purpurea Sclerotia
Authors: Hicks Carmen , Witte Thomas E. , Sproule Amanda , Lee Tiah , Shoukouhi Parivash , Popovic Zlatko , Menzies Jim G. , Boddy Christopher N. , Liu Miao , Overy David P.
Published: December 2021

Research into ergot alkaloid production in major cereal cash crops is crucial for furthering our understanding of the potential toxicological impacts of Claviceps purpurea upon Canadian agriculture and to ensure consumer safety. An untargeted metabolomics approach profiling extracts of C. purpurea sclerotia from four different grain crops separated the C. purpurea strains into two distinct metabolomic classes based on ergot alkaloid content. Variances in C. purpurea alkaloid profiles were correlated to genetic differences within the lpsA gene of the ergot alkaloid biosynthetic gene cluster from previously published genomes and from newly sequenced, long-read genome assemblies of Canadian strains. Based on gene cluster composition and unique polymorphisms, we hypothesize that the alkaloid content of C. purpurea sclerotia is currently undergoing adaptation. The patterns of lpsA gene diversity described in this small subset of Canadian strains provides a remarkable framework for understanding accelerated evolution of ergot alkaloid production in Claviceps purpurea.
Sequence, Structure, and Binding Site Analysis of Kirkiin in Comparison with Ricin and Other Type 2 RIPs
Authors: Maiello Stefania , Iglesias Rosario , Polito Letizia , Citores Lucía , Bortolotti Massimo , Ferreras José M. , Bolognesi Andrea
Published: December 2021

Kirkiin is a new type 2 ribosome-inactivating protein (RIP) purified from the caudex of Adenia kirkii with a cytotoxicity compared to that of stenodactylin. The high toxicity of RIPs from Adenia genus plants makes them interesting tools for biotechnology and therapeutic applications, particularly in cancer therapy. The complete amino acid sequence and 3D structure prediction of kirkiin are here reported. Gene sequence analysis revealed that kirkiin is encoded by a 1572 bp open reading frame, corresponding to 524 amino acid residues, without introns. The amino acid sequence analysis showed a high degree of identity with other Adenia RIPs. The 3D structure of kirkiin preserves the overall folding of type 2 RIPs. The key amino acids of the active site, described for ricin and other RIPs, are also conserved in the kirkiin A chain. Sugar affinity studies and docking experiments revealed that both the 1α and 2γ sites of the kirkiin B chain exhibit binding activity toward lactose and D-galactose, being lower than ricin. The replacement of His246 in the kirkiin 2γ site instead of Tyr248 in ricin causes a different structure arrangement that could explain the lower sugar affinity of kirkiin with respect to ricin.
Transformation of Selected Fusarium Toxins and Their Masked Forms during Malting of Various Cultivars of Wheat
Authors: Ksieniewicz-Woźniak Edyta , Bryła Marcin , Michałowska Dorota , Waśkiewicz Agnieszka , Yoshinari Tomoya
Published: December 2021

This study investigated the impact of malting of six wheat cultivars inoculated with Fusarium culmorum on the dynamics of content changes of selected Fusarium toxins. The grains of all the tested cultivars showed a high content of deoxynivalenol (DON), zearalenone (ZEN), and their derivatives, whereas nivalenol (NIV) and its glucoside were found only in the Legenda cultivar. Our experiments confirmed that the malting process of wheat grain enables the secondary growth of Fusarium, and mycotoxin biosynthesis. The levels of toxins in malt were few-fold higher than those in grain; an especially high increase was noted in the case of ZEN and its sulfate as the optimal temperature and pH conditions for the biosynthesis of these toxins by the pathogen are similar to those used in the grain malting process. This is the first paper reporting that during the malting process, biosynthesis of ZEN sulfate occurs, instead of glycosylation, which is a typical modification of mycotoxins by plant detoxication enzymes.