bluuebunny/crossref_metadata_2025 huggingface dataset:
Econometric Assessment of Institutional Quality in Mitigating Global Climate-Change Risk
Authors: Javaid Anam , Arshed Noman , Munir Mubbasher , Amani Zakaria Zahrahtul , Alamri Faten S. , Abd El-Wahed Khalifa Hamiden , Hanif Uzma
Published: January 2022

Background: Environmental deterioration is the alarming situation that results from rapid urbanization and development. The rising temperature and climate volatility are accounted for by the massive carbon dioxide (CO2) emissions. The research on climate-change mitigation is trying to curtail the situations before they become irreversible and unmanageable. This study explores the role of institutions in mitigating climate change by moderating the impact of environmental quality on climate change risk. Methodology: Global data sets have been collected from world big data depositories like the World Economic Forum (WEF), the World Development Indicators (WDI), and the International Country Risk Guide (ICRG). Countries that are listed in WEF were used as the sample of the study. An analysis was based on 114 countries that are based on the availability of data. For estimation, descriptive statistics, correlation analysis, change effects, and a Panel Feasible Generalized Least Squares (FGLS) model were used for estimating the results. Results: The global assessment indicates that CO2 emissions increase the climate risk, but its impact can be reduced by increasing the quality of institutions. Additionally, an increase in renewable energy consumption and economic growth reduces the climate risk. Implications: It is an instrumental study that empirically investigated the role of institutions in reducing climate risk by moderating CO2 emissions. The results of this study will help policymakers to formulate policies regarding environmental protection.
Growing Inequality in the Coffee Global Value Chain: A Complex Network Assessment
Authors: Utrilla-Catalan Rebeca , Rodríguez-Rivero Rocío , Narvaez Viviana , Díaz-Barcos Virginia , Blanco Maria , Galeano Javier
Published: January 2022

Following the liberalization of the coffee sector, governance and power balance in the international coffee trade has changed, with associated impacts on livelihoods in producing countries, most of which are middle- and low-income countries. Drawing on trade data for the period 1995–2018, we examine the dynamics and evolution of the international green coffee market to shed light on the re-distribution of value in the coffee supply chain. Data analysis shows that, over the studied period, the green coffee trade has increased considerably while the number of countries with a relevant role in trade has decreased, so that large exporting countries cover a higher share of trade, to the detriment of small exporting countries. We analyzed various properties of the global coffee trade network to provide insight on the relative contribution of countries not only in terms of their export value but also in terms of other selected features. The green coffee trade has gone from being distributed in many traditionally coffee-producing countries to concentrating mainly on the major coffee producers, as well as in some non-producing countries. These changes in the structure of the international green coffee market have led to greater inequality between producing and importing countries.
Exploring Potential of Seed Endophytic Bacteria for Enhancing Drought Stress Resilience in Maize (Zea mays L.)
Authors: Siddique Sulman , Naveed Muhammad , Yaseen Muhammad , Shahbaz Muhammad
Published: January 2022

Water scarcity is abiotic stress that is becoming more prevalent as a result of human activities, posing a threat to agriculture and food security. Recently, endophytic bacteria have been proven to reduce drought stress and increase crop productivity. Here, we explored the efficacy of seed endophytic bacteria in maize crops under water deficit conditions. For this purpose, twenty-seven endophytic bacteria have been isolated from three distinct maize cultivars seeds (Malka 2016, Sahiwal Gold and Gohar-19) and evaluated for desiccation tolerance of −0.18, −0.491, and −1.025 MPa induced by polyethylene glycol (PEG) 6000. The nine isolates were chosen on the basis of desiccation tolerance and evaluated for maize growth promotion and antioxidant activity under normal and drought conditions. Results showed that drought stress significantly decreased the growth of maize seedlings. However, isolates SM1, SM4, SM19, and SM23 significantly improved the root and shoot length, plant biomass, leaf area, proline content, sugar, and protein content under normal and drought conditions. Antioxidant enzymes were significantly decreased at p-value < 0.05 with inoculation of seed endophytic bacteria under drought conditions. However, further experiments of seed endophytic bacteria (SM1, SM4, SM19, and SM23) should be conducted to validate results.
Climate Data to Predict Geometry of Cracks in Expansive Soils in a Tropical Semiarid Region
Authors: Ribeiro Filho Jacques Carvalho , de Andrade Eunice Maia , Guerreiro Maria Simas , de Queiroz Palácio Helba Araujo , Brasil José Bandeira
Published: January 2022

The nonlinear dynamics of the determining factors of the morphometric characteristics of cracks in expansive soils make their typification a challenge, especially under field conditions. To overcome this difficulty, we used artificial neural networks to estimate crack characteristics in a Vertisol under field conditions. From July 2019 to June 2020, the morphometric characteristics of soil cracks (area, depth and volume), and environmental factors (soil moisture, rainfall, potential evapotranspiration and water balance) were monitored and evaluated in six experimental plots in a tropical semiarid region. Sixty-six events were measured in each plot to calibrate and validate two sets of inputs in the multilayer neural network model. One set was comprised of environmental factors with significant correlations with the morphometric characteristics of cracks in the soil. The other included only those with a significant high and very high correlation, reducing the number of variables by 35%. The set with the significant high and very high correlations showed greater accuracy in predicting crack characteristics, implying that it is preferable to have fewer variables with a higher correlation than to have more variables of lower correlation in the model. Both sets of data showed a good performance in predicting area and depth of cracks in the soils with a clay content above 30%. The highest dispersion of modeled over predicted values for all morphometric characteristics was in soils with a sand content above 40%. The model was successful in evaluating crack characteristics from environmental factors within its limitations and may support decisions on watershed management in view of climate-change scenarios.
Effect of Agricultural Employment and Export Diversification Index on Environmental Pollution: Building the Agenda towards Sustainability
Authors: Jiang Guirong , Alvarado Rafael , Murshed Muntasir , Tillaguango Brayan , Toledo Elisa , Méndez Priscila , Isik Cem
Published: January 2022

Agricultural activities have a significant impact on environmental quality, because they generate waste that pollutes water and soil. In parallel, the supply of products has diversified in recent years to meet growing demand, exerting strong pressure on nature’s capacity for regeneration and absorption of waste. This research aims to examine the impact of agricultural employment and the export diversification index on ecological footprints, using advanced techniques of panel data econometrics. This relationship is moderated by population density and real per capita product. Cross-section dependence and slope homogeneity were included in the econometric models. The cointegration and causality analysis was reinforced by estimating the short- and long-term elasticities, using the AMG, CCE-MG, FMOLS, and DOLS models. Using annual data for 96 countries, we found a heterogeneous impact of agricultural employment and the export diversification index on ecological footprint, between the short and long term. The findings reveal that the increase of the product increases the pressure on the ecological footprint. The achievement of SDGs must include joint efforts between countries, and not in isolation. Those responsible for environmental policy should promote the idea that production must be friendly to the environment and promote the green growth of countries. The adoption of new technology, higher productivity agricultural employment, and the regulation of exports of sustainable products can contribute to achieving environmental sustainability.
Polarization of Living Standards among Administrative Units Engaged in Cross-Border Cooperation—The Example of Polish Municipalities of Euroregion Baltic
Authors: Janusz Marcin
Published: January 2022

The present work examines the standard of living among the Polish municipalities of the Euroregion Baltic—an institution engaged in cross-border cooperation which is striving to improve the standard of living in border areas. The time span of the study extended to the first full year after Poland’s EU accession (2004), and to the 15th anniversary of the accession and the 20th anniversary of the establishment of the Euroregion Baltic (2019 in both cases). All 38 Polish municipalities (NUTS 5) of the Euroregion were covered by the study. Using a synthetic index of standard of living based on Hellwig’s development pattern method, the municipalities were grouped into four classes according to their index value. Hierarchical methods were used to identify which municipalities had the most similar standards of living. The highest standard of living was recorded for the small, tourism-oriented town of Jastarnia and for strong urban centers (Gdańsk, Gdynia, Olsztyn, and Elbląg). Rural municipalities, especially those situated near the Polish-Russian border (Kaliningrad Oblast), had lower standards of living. The results show a progressing polarization in the standard of living, manifested by a widening gap between first-class municipalities and the other classes. This stratification was attributed to multiple factors, including the endogenous potential of the communities.
Application of Artificial Intelligence for Predicting Erosion of Biochar Amended Soils
Authors: Garg Ankit , Wani Insha , Kushvaha Vinod
Published: January 2022

Recently, incentives have been provided in developed countries by the government for commercial production of biochar for soil treatment, and other construction uses with an aim to reduce a significant amount of carbon emissions by 2030. Biochar is an important material for the development of circular economy. This study aims to develop a simple Artificial Neural Network (ANN) based model to predict erosion of biochar amended soils (BAS) under varying conditions (slope length, slope gradient, rainfall rate, degree of compaction (DoC), and percentage of biochar amendments). Accordingly, a model has been developed to estimate the total erosion rate and total water flow rate as a function of the above conditions. The model was developed based on available data from flume experiments. Based on ANN modelling results, it was observed that slope length was the most important factor in determining total erosion rate, followed by slope gradient, DoC, and percentage of biochar amendment. The percentage of biochar amendment was a leading factor in the total water flow rate determination as compared to other factors. It was also found that the reduction in erosion is relatively minimal during an increase in slope length up to 1.55 m, reducing sharply beyond that. At a slope length of 2 m, erosion is found to be reduced by 33% (i.e., 2.6 to 1.75), whereas the total flow rate decreases linearly from 1250 mL/m2/min to 790 mL/m2/min. The ANN model developed shows that soil biochar composite (SBC) with 5% biochar amendment gave the best results in reducing soil erosion. This study can be a helpful tool in providing preliminary guidelines for using biochar in erosion control.
Forecasting Amazon Rain-Forest Deforestation Using a Hybrid Machine Learning Model
Authors: Dominguez David , del Villar Luis de Juan , Pantoja Odette , González-Rodríguez Mario
Published: January 2022

The present work aims to carry out an analysis of the Amazon rain-forest deforestation, which can be analyzed from actual data and predicted by means of artificial intelligence algorithms. A hybrid machine learning model was implemented, using a dataset consisting of 760 Brazilian Amazon municipalities, with static data, namely geographical, forest, and watershed, among others, together with a time series data of annual deforestation area for the last 20 years (1999–2019). The designed learning model combines dense neural networks for the static variables and a recurrent Long Short Term Memory neural network for the temporal data. Many iterations were performed on augmented data, testing different configurations of the regression model, for adjusting the model hyper-parameters, and generating a battery of tests to obtain the optimal model, achieving a R-squared score of 87.82%. The final regression model predicts the increase in annual deforestation area (square kilometers), for a decade, from 2020 to 2030, predicting that deforestation will reach 1 million square kilometers by 2030, accounting for around 15% compared with the present 1%, of the between 5.5 and 6.7 millions of square kilometers of the rain-forest. The obtained results will help to understand the impact of man’s footprint on the Amazon rain-forest.
Analysis of Sustainable Business Models: Exploratory Study in Two Brazilian Logistics Companies
Authors: Gomes Jaqueline Geisa Cunha , Okano Marcelo Tsuguio , Guerra Rodrigo Salgado , Cordeiro Denilson de Sousa , Santos Henry Castro Lobo dos , Fernandes Marcelo Eloy
Published: January 2022

Over the years, researchers have presented different concepts regarding business models. There is no unanimity, but there is a general agreement that a business model is the representation of how a company conducts its business. Subsequently, interest in the topic has increased and has come to be considered by companies that, driven to incorporate a positive contribution to sustainability into their values, began to face economic development that considers social and environmental aspects instead of worrying only about profit for the shareholders. The general objective of this research is to identify how the merger of two Brazilian logistics companies with different customer segments can positively contribute to the defense of sustainability, considering social and environmental aspects. As a methodology, a literature review on business models, conceptual business models, and sustainable business models was used to legitimize issues relevant to the themes. The case studies allowed for a measurement of the productivity of the areas of the chosen companies, and a survey of used business processes and technological systems, in addition to diagnosing the level of maturity of these areas. An analysis of the strengths and weaknesses in these areas, within the studied companies, resulted in a solution that allowed for the optimization of processes and savings in human and material resources, and the identification of qualitative benefits arising from mergers, improvements in productivity and services, the standardization of processes, and the implementation of innovative digital technologies.
Studies on Recycling Silane Controllable Recovered Carbon Fiber from Waste CFRP
Authors: Chin Kai-Yen , Shiue Angus , Wu Yi-Jing , Chang Shu-Mei , Li Yeou-Fong , Shen Ming-Yuan , Leggett Graham
Published: January 2022

During the production process of commercial carbon fiber reinforced polymers (CFRPs), a silane coupling agent is added to the carbon fiber at the sizing step as a binder to enhance the product’s physical properties. While improving strength, the silane coupling agent results in a silane residue on recovered carbon fibers (rCF) after recycling, which is a disadvantage when using recovered carbon fibers in the manufacture of new materials. In this study, the rCF is recovered from waste carbon fiber reinforced polymers (CFRPs) from the bicycle industry by a microwave pyrolysis method, applying a short reaction time and in an air atmosphere. Moreover, the rCF are investigated for their surface morphologies and the elements present on the surface. The silicon element content changes with pyrolysis temperature were 0.4, 0.9, and 0.2%, respectively, at 450, 550, and 650 °C. Additionally, at 950 °C, silicon content can be reduced to 0.1 ± 0.05%. The uniformity of microwave pyrolysis recycle treatment was compared with traditional furnace techniques used for bulk waste treatment by applying the same temperature regime. This work provides evidence that microwave pyrolysis can be used as an alternative method for the production of rCFs for reuse applications.
Sustainability of Serbian Villages in COVID-19 Pandemic Conditions
Authors: Lukić Tamara , Pivac Tatjana , Solarević Milica , Blešić Ivana , Živković Jelena , Penjišević Ivana , Golić Rajko , Kalenjuk Pivarski Bojana , Bubalo-Živković Milka , Pandžić Ana
Published: January 2022

The subject of this paper is to determine how the COVID-19 virus pandemic affected the situation in Serbian villages. The task of the paper is to show the positive and negative consequences that resulted from the pandemic. This would indicate that some of them may represent a new idea, a chance, or would work in favor of the sustainability of the villages of Serbia. In support of objectivity, research was carried out among the population that inhabits the rural areas of Serbia. It examined the extent to which internationally recognized phenomena and consequences of the COVID-19 virus pandemic were present in the study area and considered the nature of their impact on sustainability. The results of the semi-structured questionnaire were processed using descriptive statistics, t-test, and analysis of variance (ANOVA). Respondents contributed to the conception of possible solutions with their comments. The obtained differences in the answers resulted from different socio-demographic characteristics of the respondents, but also from the fact that the villages of Serbia differ in natural and social characteristics. Respondents’ responses are in favor of economic and sociodemographic sustainability, but they do not think in terms of environmental sustainability. The paper reveals several development opportunities, which complement each other and contribute to different methods for sustainability of rural villages in Serbia.
An Assessment Approach to Circular Business Models within an Industrial Ecosystem for Sustainable Territorial Development
Authors: Gamidullaeva Leyla , Shmeleva Nadezhda , Tolstykh Tatyana , Shmatko Alexey
Published: January 2022

In this work, the authors have made an attempt to develop a methodological approach to substantiate the socio-economic efficiency of enterprise performance within an industrial ecosystem in the context of a circular economy. The proposed approach has been verified via a case study of the industrial ecosystem in Novokuznetsk city. Based on the calculations, it has been evidenced that the creation of an industrial ecosystem in the region where the city is located would eliminate area sources of pollution and improve the quality of life of the population, which would advance regional sustainable development and strengthen territorial attractiveness for citizens. Thus, having used the proposed methodology, the prospects for the implementation of circular business models by enterprises in order to increase the efficiency of resource use and balanced and sustainable economic development of a territory have been substantiated. The transition to a circular economy can support the creation of favorable environmental conditions and increase the local community resilience, well-being, and quality of life.
Investigation of Dynamic Characteristics of Liquid Nitrogen Droplet Impact on Solid Surface
Authors: Zhao Ke , Ding Yang
Published: January 2022

Liquid nitrogen spray cooling technology exhibits excellent heat transfer efficiency and environmental protection performance. The promotion of this technology plays an important role in improving the sustainable development of the refrigeration industry. In order to clarify its complex microscale behavior, the coupled Level Set-VOF method was adopted to study the dynamic characteristics of liquid nitrogen droplet impact on solid surface in this paper. The spreading behaviors under various factors (initial velocity, initial diameter, wall temperature, and We number) were systematically analyzed. The results show that the spreading behaviors of liquid nitrogen droplet share the same process with the normal medium, which are rebound, retraction, and splashing. For the droplet with smaller velocity and diameter, Rebound is the common phenomenon due to the smaller kinetic energy. With the increase of droplet diameter (0.2 mm to 0.5 mm) and velocity (0.1 m/s to 5 m/s), the spreading factor increases rapidly and the spreading behaviors evolve into retraction and splashing. The increase of wall temperature accelerates the droplets spreading, and the spreading factor increases accordingly. For the liquid nitrogen droplets hit the wall, the dynamic behaviors of rebound (We < 0.2), retraction (0.2 < We < 4.9), and splashing (We > 4.9) will occur with the droplet weber number increased, which are consistent with the common medium. However, due to liquid nitrogen having lower viscosity and surface tension, the conditions of morphological transformations are different from the common media. The maximum spreading diameter has a power correlation with We, the power index of We is 0.306 for liquid nitrogen, lager than common medium (0.25). The reasons are: (1) the better wettability of liquid nitrogen, and (2) the vapor generated by the violent phase change ejects along the axial direction. The article will provide a certain theoretical basis for liquid nitrogen spray cooling technology, and can also enrich the flow dynamics of cryogenic fluids.
Exact Solutions for Solitary Waves in a Bose-Einstein Condensate under the Action of a Four-Color Optical Lattice
Authors: Halder Barun , Ghosh Suranjana , Basu Pradosh , Bera Jayanta , Malomed Boris , Roy Utpal
Published: January 2022

We address dynamics of Bose-Einstein condensates (BECs) loaded into a one-dimensional four-color optical lattice (FOL) potential with commensurate wavelengths and tunable intensities. This configuration lends system-specific symmetry properties. The analysis identifies specific multi-parameter forms of the FOL potential which admits exact solitary-wave solutions. This newly found class of potentials includes more particular species, such as frustrated double-well superlattices, and bichromatic and three-color lattices, which are subject to respective symmetry constraints. Our exact solutions provide options for controllable positioning of density maxima of the localized patterns, and tunable Anderson-like localization in the frustrated potential. A numerical analysis is performed to establish dynamical stability and structural stability of the obtained solutions, which makes them relevant for experimental realization. The newly found solutions offer applications to the design of schemes for quantum simulations and processing quantum information.
Optimization of the Motion Algorithm and Reduction of the External Dynamic Load of the Machinery Actuator in Translational and Rotational Modes
Authors: Musiiko Volodymyr , Šťastniak Pavol , Honchar Mykhailo , Nikolaienko Volodymyr , Lazaruk Jurii , Korpach Anatolii , Suchánek Andrej
Published: January 2022

This article deals with the theoretical preconditions for creating a high-performance, universal earthmoving vehicle with continuous motion that can create long grooves of different depths and widths in the soil using a single actuator. For this purpose, a new symmetrical rotor actuator was developed, which operates in translational and rotational modes due to the two-level actuator with a double-swivel mounting on the base chassis, instead of the traditional single-swivel mounting. Its use eliminates the possibility of leveling the thickness of the shavings when digging the soil. The rotor-actuator-movement algorithm at the front part was developed from a combination of vehicle movement and cyclic-lateral-actuator movement. In real practice, this means digging up the soil with even shavings. The implementation of the developed algorithm in the physical model of the symmetrical actuator confirmed the possibility of balancing the thickness of the shavings, which are cut by the rotor buckets with up to 10% accuracy. The difference between the results in determining the thickness of the shavings analytically and experimentally is 12% with a confidence interval of 0.95.
Neutrino Mass Spectrum: Present Indication and Future Prospect
Authors: Cao Son , Hong Van Nguyen T. , Ngoc Tran V. , Quyen Phan T.
Published: January 2022

The fact that neutrinos are massive has been the most crucial evidence of physics beyond the Standard Model of elementary particles. To date, we still do not know how neutrinos get mass and why their mass is much smaller than that of their charged fermion cousins. The precise determination of the neutrino mass spectrum has become one of the central tasks of neutrino physics, providing critical input for understanding the nature of neutrino mass and extending our model. The present landscape of the neutrino mass spectrum is reviewed and explored in this article using data from the neutrino oscillation, cosmology, and beta decay. In addition, we discuss the possibility of relevant programs elucidating the neutrino mass spectrum in the coming decades.
A Novel Axial-Flux Dual-Stator Toothless Permanent Magnet Machine for Flywheel Energy Storage
Authors: Zhao Yong , Lu Fangzhou , Fan Changxin , Yang Jufeng
Published: January 2022

This paper presents an alternative system called the axial-flux dual-stator toothless permanent magnet machine (AFDSTPMM) system for flywheel energy storage. This system lowers self-dissipation by producing less core loss than existing structures; a permanent magnet (PM) array is put forward to enhance the air–gap flux density of the symmetrical air gap on both sides. Moreover, its vertical stability is strengthened through the adoption of an axial-flux machine, so expensive active magnetic bearings can be replaced. The symmetry configuration of the AFDSTPMM system is shown in this paper. Then, several parts of the AFDSTPMM system are optimized thoroughly, including stator windings, number of pole pairs and the PM parameters. Further, the performance of the proposed PM array, including back-EMFs, air–gap flux density, average torque, torque ripple and over-load capacity, are compared with the Halbach PM array and spoke PM array, showing the superiority of proposed configuration. Finally, 3D simulations were made to testify for the 2D analyses.
Best Dominants and Subordinants for Certain Sandwich-Type Theorems
Authors: Cătaş Adriana , Borşa Emilia , Iambor Loredana
Published: January 2022

In this paper, we aim to present a survey on subordination and superordination theorems related to the class of analytic functions defined in a symmetric domain, which is the open unit disc. The results were deduced by making use of a new differential operator. We present two properties of this operator from which we constructed the final results. Moreover, based on the obtained outcomes, we give two sandwich-type theorems. Some interesting further consequences are also taken into consideration.
Towards Convergence of IoT and Blockchain for Secure Supply Chain Transaction
Authors: Hasan A S M Touhidul , Sabah Shabnam , Haque Rakib Ul , Daria Apubra , Rasool Abdur , Jiang Qingshan
Published: January 2022

Supply chain management (SCM) is essential for a company’s faster, efficient, and effective product life cycle. However, the current SCM systems are insufficient to provide product legitimacy, transaction privacy, and security. Therefore, this research proposes a secure SCM system for the authenticity of the products based on the Internet of Things (IoT) and blockchain technology. The IoT-enabled Quick Response (QR) scanner and the blockchain-integrated distributed system will allow all the SCM stakeholders to begin secure and private transactions for their products or services. Resulting, the consumer will receive an authentic and genuine product from the original producer. A lightweight asymmetric key encryption technique, i.e., elliptic curve cryptography (ECC) and Hyperledger Fabric-based blockchain technology with on-chain smart contracts are applied for distributed IoT devices to make the authentication process faster and lighter. Each SCM stakeholder is registered by the service provider and receives corresponding public and private keys, which will be used for the authentication process of the participants and IoT devices. The authenticated QR scanner records all transactions on the blockchain. Consequently, there will be no human intervention for the SCM transactions. The security and scalability analysis demonstrates that the proposed system is more secure and robust than other state-of-the-art techniques.
Electromagnetic Form Factor of Doubly-Strange Hyperon
Authors: Wang Xiongfei , Huang Guangshun
Published: January 2022

The standard model of particle physics is a well-tested theoretical framework, but there are still some issues that deserve experimental and theoretical investigation. The Ξ resonances with strangeness S=−2, the so-called doubly-strange hyperon, can provide important information to further test the standard model by studying their electromagnetic form factors, such as probing the limitation of the quark models and spotting unrevealed aspects of the QCD description of the structure of hadron resonances. In this work, we review some recent studies of the electromagnetic form factors on doubly-strange hyperons in pair production from positron–electron annihilation experiment.
Detection of Adversarial DDoS Attacks Using Generative Adversarial Networks with Dual Discriminators
Authors: Shieh Chin-Shiuh , Nguyen Thanh-Tuan , Lin Wan-Wei , Huang Yong-Lin , Horng Mong-Fong , Lee Tsair-Fwu , Miu Denis
Published: January 2022

DDoS (Distributed Denial of Service) has emerged as a serious and challenging threat to computer networks and information systems’ security and integrity. Before any remedial measures can be implemented, DDoS assaults must first be detected. DDoS attacks can be identified and characterized with satisfactory achievement employing ML (Machine Learning) and DL (Deep Learning). However, new varieties of aggression arise as the technology for DDoS attacks keep evolving. This research explores the impact of a new incarnation of DDoS attack–adversarial DDoS attack. There are established works on ML-based DDoS detection and GAN (Generative Adversarial Network) based adversarial DDoS synthesis. We confirm these findings in our experiments. Experiments in this study involve the extension and application of the GAN, a machine learning framework with symmetric form having two contending neural networks. We synthesize adversarial DDoS attacks utilizing Wasserstein Generative Adversarial Networks featuring Gradient Penalty (GP-WGAN). Experiment results indicate that the synthesized traffic can traverse the detection systems such as k-Nearest Neighbor (KNN), Multi-Layer Perceptron (MLP) and Random Forest (RF) without being identified. This observation is a sobering and pessimistic wake-up call, implying that countermeasures to adversarial DDoS attacks are urgently needed. To this problem, we propose a novel DDoS detection framework featuring GAN with Dual Discriminators (GANDD). The additional discriminator is designed to identify adversary DDoS traffic. The proposed GANDD can be an effective solution to adversarial DDoS attacks, as evidenced by the experimental results. We use adversarial DDoS traffic synthesized by GP-WGAN to train GANDD and validate it alongside three other DL technologies: DNN (Deep Neural Network), LSTM (Long Short-Term Memory) and GAN. GANDD outperformed the other DL models, demonstrating its protection with a TPR of 84.3%. A more sophisticated test was also conducted to examine GANDD’s ability to handle unseen adversarial attacks. GANDD was evaluated with adversarial traffic not generated from its training data. GANDD still proved effective with a TPR around 71.3% compared to 7.4% of LSTM.
On the Unique Solvability of Incomplete Cauchy Type Problems for a Class of Multi-Term Equations with the Riemann–Liouville Derivatives
Authors: Fedorov Vladimir E. , Du Wei-Shih , Turov Mikhail M.
Published: January 2022

Incomplete Cauchy-type problems are considered for linear multi-term equations solved with respect to the highest derivative in Banach spaces with fractional Riemann–Liouville derivatives and with linear closed operators at them. Some new existence and uniqueness theorems for solutions are presented explicitly and the analyticity of the solutions of the homogeneous equations are also shown. The asymmetry of the Cauchy-type problem under study is expressed in the presence of a so-called defect, which shows the number of lower-order initial conditions that should not be set when setting the problem. As applications, our abstract results are used in the study of a class of initial-boundary value problems for multi-term equations with Riemann–Liouville derivatives in time and with polynomials of a self-adjoint elliptic differential operator with respect to spatial variables.
Stability Evaluation Method of Hole Wall for Bored Pile under Blasting Impact
Authors: Yang Qiuwei , Ba Zhikun , Zhao Zhuo , Peng Xi , Sun Yun
Published: January 2022

Blasting impact load may be encountered during the construction of some pile foundation projects. Due to the effect of blasting impact, hole collapse can easily occur in the hole-forming stage of pile foundation construction. In order to prevent hole collapse, it is very necessary to evaluate the stability of a pile hole wall before pile foundation construction. The calculation of hole collapse can usually be attributed to an axisymmetric circular hole stress concentration problem. However, the existing collapse failure theory of pile hole hardly considers the effect of blasting impact load. In view of this, this paper proposes the stability evaluation method of a pile hole wall under blasting impact. Compared with the existing collapse failure theory, the proposed method fully considers the effect of blasting impact stress. Using Mohr–Coulomb strength theory and symmetry analysis, the strength condition of collapse failure is established in this work for accurate evaluation of the stability of a hole wall. The proposed stability evaluation method is demonstrated by a pile foundation construction project of a bridge. Moreover, a shaking table test on the pile hole model was performed to verify the proposed method by experimental data. The results indicate the effectiveness and usability of the proposed method. The proposed method provides a feasible way for the stability analysis of a pile hole wall under blasting impact.
Lie Group Classification of Generalized Variable Coefficient Korteweg-de Vries Equation with Dual Power-Law Nonlinearities with Linear Damping and Dispersion in Quantum Field Theory
Authors: Adeyemo Oke Davies , Khalique Chaudry Masood
Published: January 2022

Many physical phenomena in fields of studies such as optical fibre, solid-state physics, quantum field theory and so on are represented using nonlinear evolution equations with variable coefficients due to the fact that the majority of nonlinear conditions involve variable coefficients. In consequence, this article presents a complete Lie group analysis of a generalized variable coefficient damped wave equation in quantum field theory with time-dependent coefficients having dual power-law nonlinearities. Lie group classification of two distinct cases of the equation was performed to obtain its kernel algebra. Thereafter, symmetry reductions and invariant solutions of the equation were obtained. We also investigate various soliton solutions and their dynamical wave behaviours. Further, each class of general solutions found is invoked to construct conserved quantities for the equation with damping term via direct technique and homotopy formula. In addition, Noether’s theorem is engaged to furnish more conserved currents of the equation under some classifications.
Effect of Interlayer Coupling and Symmetry on High-Order Harmonic Generation from Monolayer and Bilayer Hexagonal Boron Nitride
Authors: Kim Dasol , Lee Yeon , Chacón Alexis , Kim Dong-Eon
Published: January 2022

High-order harmonic generation (HHG) is a fundamental process which can be simplified as the production of high energetic photons from a material subjected to a strong driving laser field. This highly nonlinear optical process contains rich information concerning the electron structure and dynamics of matter, for instance, gases, solids and liquids. Moreover, the HHG from solids has recently attracted the attention of both attosecond science and condensed matter physicists, since the HHG spectra can carry information of electron-hole dynamics in bands and inter- and intra-band current dynamics. In this paper, we study the effect of interlayer coupling and symmetry in two-dimensional (2D) material by analyzing high-order harmonic generation from monolayer and two differently stacked bilayer hexagonal boron nitrides (hBNs). These simulations reveal that high-order harmonic emission patterns strongly depend on crystal inversion symmetry (IS), rotation symmetry and interlayer coupling.
A Modified Van Der Pol Oscillator Model for the Unsteady Lift Produced by a Flapping Flat Plate for Different Positions of the Rotation Axis
Authors: Hafien Chedhli , Messaoudi Abdellatif
Published: January 2022

To understand the nonlinear interaction between unsteady aerodynamic forces and the kinematics of structures, we theoretically and numerically investigated the characteristics of lift coefficients produced by a flapping thin flat plate controlled by the rotation axis position. The flat plate was placed in a 2-D incompressible flow at a very low Reynolds number (Re = 300). We showed that the behavior of the unsteady aerodynamic forces suggests the existence of a limit cycle. In this context, we developed a Reduced Order Model (ROM) by resolving the modified van der Pol oscillator using the Taylor development method and computational fluid dynamics (CFD) solutions. A numerical solution was obtained by integrating the differential equation of the modified van der Pol oscillator using the fourth-order Runge–Kutta method (RK4). The model was validated by comparing this solution with the reformulated equation of the added mass lift coefficient. Using CFD and ROM solutions, we analyzed the dependency of the unsteady lift coefficient generation on the kinematics of the flapping flat plate. We showed that the evolution of the lift coefficient is influenced by the importance of the rotation motion of the Leading Edge (LE) or Trailing Edge (TE), according to the position of the rotation axis. Indeed, when the rotation axis is moved towards the LE, the maximum and the minimum values of the lift coefficient are proportional to the downward and upward motions respectively of the TE and the rotation axis. However, when the rotation axis is moved towards the TE, the maximum and the minimum values of the lift coefficient are proportional to the downward and upward motions respectively of the LE and the rotation axis.
Semi-Adaptive Evolution with Spontaneous Modularity of Half-Chaotic Randomly Growing Autonomous and Open Networks
Authors: Gecow Andrzej , Iantovics Laszlo Barna
Published: January 2022

Up until now, studies of Kauffman network stability have focused on the conditions resulting from the structure of the network. Negative feedbacks have been modeled as ice (nodes that do not change their state) in an ordered phase but this blocks the possibility of breaking out of the range of correct operation. This first, very simplified approximation leads to some incorrect conclusions, e.g., that life is on the edge of chaos. We develop a second approximation, which discovers half-chaos and shows its properties. In previous works, half-chaos has been confirmed in autonomous networks, but only using node function disturbance, which does not change the network structure. Now we examine half-chaos during network growth by adding and removing nodes as a disturbance in autonomous and open networks. In such evolutions controlled by a ‘small change’ of functioning after disturbance, the half-chaos is kept but spontaneous modularity emerges and blurs the picture. Half-chaos is a state to be expected in most of the real systems studied, therefore the determinants of the variability that maintains the half-chaos are particularly important in the application of complex network knowledge.
Newton’s Third Law in the Framework of Special Relativity for Charged Bodies Part 2: Preliminary Analysis of a Nano Relativistic Motor
Authors: Yahalom Asher
Published: January 2022

(1) Background: In a recent paper discussing Newton’s third law in the framework of special relativity for charged bodies, it was suggested that one can construct a practical relativistic motor provided high enough charge and current densities are available. As on the macroscopic scale charge density is limited by the phenomena of dielectric breakdown, it was suggested to take advantage of the high charge densities which are available on the microscopic scale. (2) Methods: We use standard physical theories such as Maxwell electrodynamics and quantum mechanics, supplemented by tools from vector analysis and numerics. (3) Results: We show that a hydrogen atom either in the ground state or excited state will not produce a relativistic engine effect, but by breaking the symmetry or putting the electron in a wave packet state may produce relativistic motor effect. (4) Conclusions: A highly localized wave packet will produce a strong relativistic motor effect. The preliminary analysis of the current paper suggests new promising directions of research both theoretical and experimental.
High-Dimensional Radial Symmetry of Copula Functions: Multiplier Bootstrap vs. Randomization
Authors: Billio Monica , Frattarolo Lorenzo , Guégan Dominique
Published: January 2022

We use a recently proposed fast test of copula radial symmetry based on multiplier bootstrap and obtain an equivalent randomization test. The literature shows the statistical superiority of the randomization approach in the bivariate case. We extend the comparison of statistical performance focusing on the high-dimensional regime in a simulation study. We document radial asymmetry in the joint distribution of the percentage changes of sectorial industrial production indices of the European Union.
Spatial Decay Bounds for the Brinkman Fluid Equations in Double-Diffusive Convection
Authors: Chen Xuejiao , Li Yuanfei , Li Dandan
Published: January 2022

In this paper, we consider the Brinkman equations pipe flow, which includes the salinity and the temperature. Assuming that the fluid satisfies nonlinear boundary conditions at the finite end of the cylinder, using the symmetry of differential inequalities and the energy analysis methods, we establish the exponential decay estimates for homogeneous Brinkman equations. That is to prove that the solutions of the equation decay exponentially with the distance from the finite end of the cylinder. To make the estimate of decay explicit, the bound for the total energy is also derived.
Third-Order Differential Subordination Results for Analytic Functions Associated with a Certain Differential Operator
Authors: Darweesh Amal Mohammed , Atshan Waggas Galib , Battor Ali Hussein , Lupaş Alina Alb
Published: January 2022

In this research, we study suitable classes of admissible functions and establish the properties of third-order differential subordination by making use a certain differential operator of analytic functions in U and have the normalized Taylor–Maclaurin series of the form: f(z)=z+∑n=2∞anzn, (z∈U). Some new results on differential subordination with some corollaries are obtained. These properties and results are symmetry to the properties of the differential superordination to form the sandwich theorems.
An Anomaly-Based IDS Framework Using Centroid-Based Classification
Authors: Lin Iuon-Chang , Chang Ching-Chun , Peng Chih-Hsiang
Published: January 2022

Botnet is an urgent problem that will reduce the security and availability of the network. When the bot master launches attacks to certain victims, the infected users are awakened, and attacks start according to the commands from the bot master. Via Botnet, DDoS is an attack whose purpose is to paralyze the victim’s service. In all kinds of DDoS, SYN flood is still a problem that reduces security and availability. To enhance the security of the Internet, IDS is proposed to detect attacks and protect the server. In this paper, the concept of centroid-based classification is used to enhance performance of the framework. An anomaly-based IDS framework which combines K-means and KNN is proposed to detect SYN flood. Dimension reduction is designed to achieve visualization, and weights can adjust the occupancy ratio of each sub-feature. Therefore, this framework is also suitable for use on the modern symmetry or asymmetry architecture of information systems. With the detection by the framework proposed in this paper, the detection rate is 96.8 percent, the accuracy rate is 97.3 percent, and the false alarm rate is 1.37 percent.