bluuebunny/crossref_metadata_2025 huggingface dataset:
The Household Context of In Situ Conservation in a Center of Crop Diversity: Self-Reported Practices and Perceptions of Maize and Phaseolus Bean Farmers in Oaxaca, Mexico
Authors: Soleri Daniela , Aragón Cuevas Flavio , Castro García Humberto , Cleveland David A. , Smith Steven E.
Published: June 2022

Crop diversity conservation in situ is an ecosystem service with benefits at household, community, and global scales. These include risk reduction and adaptation to changing physical and sociocultural environments—both important given the accelerating changes in climate, human migration, and the industrialization of agriculture. In situ conservation typically occurs as part of small-scale, traditionally based agriculture and can support cultural identity and values. Although decisions regarding crop diversity occur at the household level, few data detail the household context of in situ crop diversity management. Our research addressed this data gap for maize and Phaseolus bean in Oaxaca, Mexico, a major center of diversity for those crops. We defined diversity as farmer-named varieties and interviewed 400 farming households across eight communities in two contrasting socioecological regions. Our research asked, “In a major center of maize and Phaseolus diversity, what are the demographic, production, and consumption characteristics of the households that are stewarding this diversity?” We describe the context of conservation and its variation within and between communities and regions and significant associations between diversity and various independent variables, including direct maize consumption, region, and marketing of crops. These results provide a benchmark for communities to understand and strengthen their maize and bean systems in ways they value and for scientists to support those communities in dynamically stewarding locally and globally significant diversity.
Dynamic Differential Game Strategy of the Energy Big Data Ecosystem Considering Technological Innovation
Authors: Dong Jun , Bao A-Ru-Han , Liu Yao , Dou Xi-Hao , Liu Dong-Ran , Xue Gui-Yuan
Published: June 2022

This study discusses how to create strategic value through energy big data and how to promote stakeholder interaction mechanisms in the evolution of the energy big data ecosystem. We use differential game methods to study the interaction between one power grid enterprise (PG) and one technology supplier (TS) under three different cost-sharing contracts: without cost-sharing contract, cost-sharing contract, and two-way subsidy contract. The effectiveness of the dynamic equilibrium strategies under different contracts is verified via numerical simulations. The results show that under the centralized decision scenario, the technological innovation investment, the degree of technological advancement of PG and TS, and the total profit of the supply chain system are superior to the decentralized decision scenario. The extent of TS technology innovation investment depends on the share rate of PG. Technology innovation investment and the profits of energy big data service supply chain stakeholders will increase with the sensitivity coefficient of technological advancement. Compared with contracts without cost-sharing and with cost-sharing, the two-way subsidy contract can provide the Pareto optimal solution for the investment trajectory of technological innovation and long-term profits. Theoretically, this study reveals a new perspective in the research on the relationship between power grid enterprises and technology suppliers under dynamic technology innovation. In practice, this study facilitates power grid enterprises and technology suppliers to form a closer cooperative relationship in the energy big data ecosystem. More importantly, it is helpful for power grid enterprises to make optimal transaction decisions at different stages of energy big data ecosystem evolution.
Stability of the Anaerobic Digestion Process during Switch from Parallel to Serial Operation—A Microbiome Study
Authors: Walter Andreas , Hanser Maria , Ebner Christian , Insam Heribert , Markt Rudolf , Hupfauf Sebastian , Probst Maraike
Published: June 2022

Anaerobic digestion is a common procedure of treating sewage sludge at wastewater treatment plants. However, plants differ in terms of the number of reactors and, in case of several reactors, their operation mode. To confirm the flexibility of well adapted, full-scale anaerobic digestion plants, we monitored the physicochemical process conditions of two continuously stirred tank reactors over one hydraulic retention time before and after the operation mode was switched from parallel to serial operation. To investigate changes in the involved microbiota, we applied Illumina amplicon sequencing. The rapid change between operation modes did not affect the process performance. In both parallel and serial operation mode, we detected a highly diverse microbial community, in which Bacteroidetes, Firmicutes, Proteobacteria and Claocimonetes were high in relative abundance. While a prominent core microbiome was maintained in both configurations, changes in the involved microbiota were evident at a lower taxonomical level comparing both reactors and operation modes. The most prominent methanogenic Euryarchaeota detected were Methanosaeta and cand. Methanofastidiosum. Volatile fatty acids were degraded immediately in both reactors, suggesting that the second reactor could be used to produce methane on demand, by inserting easily degradable substrates.
Travel Motivation during COVID-19: A Case from Nepal
Authors: Bhatta Kumar , Gautam Prakash , Tanaka Toshinori
Published: June 2022

The tourism industry is one of the most affected industries by the COVID-19 pandemic. Understanding travel motivation is necessary for the tourism movement, even in the COVID-19 pandemic. Thus, this quantitative study aimed to explore travel motivation and its determinants. We collected 181 samples through a web-based questionnaire survey of the Nepali people in January and February 2021. The data were analyzed using a probit regression model through two different travel companion perspectives, i.e., traveling with friends and traveling with family members. We found that travel motivation, attributes, travel purpose, and transport mode preferences differed in companion groups. Specifically, those who want to travel with friends are government employees, 20–29 years of age, set health and wellness purposes, choose the bike for transportation, are less willing to visit homestay and agritourism, and want to travel for around one week. Those who plan to travel with family members use the coach to travel, choose rural destinations, including villages, and spend around two weeks. Based on these findings, we suggest that the Nepalese tourism destination and public transport companies make tourism packages targeting the groups. Since both groups showed interest in visiting rural destinations, we can say that tourism in rural destinations may revive earlier than urban tourism after the pandemic. However, a low-risk travel environment should be ensured for traveling to attract more tourists during and the post-disaster.
Sustainability of Local Labour Market in South Africa: The Implications of Imports Competition from China
Authors: Faraj Muftah , Bein Murad
Published: June 2022

Using South African manufacturing and non-manufacturing industry employment, imports from China, growth in manufacturing and non-manufacturing industry, and workers’ earning data, we examined the impact of imports from China, growth in manufacturing and non-manufacturing industry on manufacturing and non-manufacturing industry employment and workers’ earnings. This study employed a Bayer and Hanck cointegration test to examine the cointegration among the variables, which found the existence of cointegration. In addition, the ARDL approach was employed to ascertain the long-run effect of the import from China, growth in manufacturing and non-manufacturing industry on the manufacturing and non-manufacturing industry employment and workers’ earning, while “Fully Modified Ordinary Least Square (FMOLS)”, “Dynamic Ordinary Least Square (DOLS)”, and “Canonical Cointegrated Regression (CRR)” estimators were employed for robustness. We found a negative long-run effect of imports from China on manufacturing sectors’ employment and workers’ earnings, while a positive of its effect was found on service industry employment. Moreover, growth in the manufacturing industry was found to have a positive long-run effect on manufacturing industry employment and workers’ earnings, while it has a negative long-run effect on service industry employment. As for the growth in the service industry, it was demonstrated to have a negative and positive long-run effect on manufacturing industry employment and non-manufacturing industry employment.
Social Housing and Affordable Rent: The Effectiveness of Legal Thresholds of Rents in Two Italian Metropolitan Cities
Authors: Napoli Grazia , Trovato Maria Rosa , Barbaro Simona
Published: June 2022

Social housing is an instrument of housing policies to support those groups of people who are disadvantaged due to particular economic weaknesses and/or social relational fragility. Consequently, to achieve the objective of social sustainability, the rents of social housing must be below the market rents and low enough to be affordable. Italian law has set several rent thresholds which are based on local territorial agreements between landlords and renters associations. This article aims to examine whether these thresholds generate social fairness and housing affordability within each city and between different cities, or instead inequalities and spatial asymmetries. A cluster analysis is applied to study whether the goal of fairness is achieved, while the effectiveness of providing housing affordability is assessed by comparing the benchmarked rents with those of the national ministerial Real Estate Market Observatory. Two metropolitan cities—one in the north and another in the south of Italy—with different social and economic characteristics were chosen as case studies. The results show that variations in rents, location, and housing quality are fairly consistent within urban areas and cities. However, the benchmarked rents are not consistently related to the market rents and are often higher than the latter, failing to meet the provision of affordable housing that was the primary goal of the law.
Spatiotemporal Evaluation of the Built Environment’s Impact on Commuting Duration
Authors: Hatami Faizeh , Thill Jean-Claude
Published: June 2022

Upward trends in commuting duration and distance due to urban sprawl in the United States have raised concerns about the ensuing environmental, social and economic problems. Various urban planning approaches have been developed, hypothesizing that built environment variables such as density, diversity, design, distance to transit and destination accessibility contribute to reducing travel consumption. This study evaluates the impact of the built environment on commuting duration in Mecklenburg County, North Carolina, in two steps. First, the built environment is classified into four types of exurban, suburban, urban, and compact and transit-accessible development (CTAD). Second, the impact of built environment types on commuting duration is evaluated for 2000 and 2015 using spatial panel data models controlling for selection bias. Results show that CTAD areas have shorter commuting durations than other areas in 2015; however, the commuting duration in both CTAD and urban areas has increased over time. Given the multifaceted nature of urban transportation-built environment interactions and their importance for sustainable futures, this calls for further attention from urban researchers and planners to more comprehensively consider the various dimensions of this matter, with an explicit focus on the changing nature of urban environments.
Nitrogen Reduction Combined with Organic Materials Can Stabilize Crop Yield and Soil Nutrients in Winter Rapeseed and Maize Rotation in Yellow Soil
Authors: Wei Quan-Quan , Gou Jiu-Lan , Zhang Meng , Zhang Bang-Xi , Rao Yong , Xiao Hua-Gui
Published: June 2022

Objective: To investigate the effect of nitrogen reduction combined with organic materials on crop growth of winter rapeseed and maize rotation in yellow soil. Methods: A 2-year, four-season winter rapeseed and maize rotation experiment using three organic materials (biochar (B), commercial organic fertilizer (O) and straw (S), 3000 kg·hm−2) and three nitrogen application rates (100%, 85% and 70%) was carried out from 2018 to 2020 in Guizhou Province, China. By comprehensively analyzing the crop yield, biomass and nutrient absorption, soil nutrients indicators, and the efficiency of nitrogen fertilizer was calculated. Results: All organic materials could increase the yield of both crops, and 100% N + O treatment was the best, and the 2-year winter rapeseed and maize yields reached 3069 kg·hm−2, 3215 kg·hm−2 and 11,802 kg·hm−2, 11,912 kg·hm−2, respectively. When nitrogen application was reduced by 15%, the addition of the three organic materials could stabilize or increase the yield and biomass, and nitrogen, phosphorus and potassium absorption in both crops showed an increasing trend, which could improve or maintain soil nutrients. When nitrogen application was reduced by 30%, the yields of two crops with organic materials addition were lower than those of 100% N treatment. Through the interaction, it was found that nitrogen and organic material were the main reasons for the increase in yield, respectively. Conclusions: The addition of three organic materials can replace 15% of nitrogen fertilizer. It is recommended to apply 153.0 kg·hm−2 and 127.5 kg·hm−2 of nitrogen fertilizer in winter rapeseed and maize seasons, respectively, in the rotation area of Guizhou yellow soil, with the addition of 3000 kg·hm−2 organic materials, most appropriately commercial organic fertilizer.
Potential of Biomass Frond Fiber on Mechanical Properties of Green Foamed Concrete
Authors: Othuman Mydin Md Azree , Nawi Mohd Nasrun Mohd , Odeh Ruba A. , Salameh Anas A.
Published: June 2022

Currently, the cost of construction rises along with the ongoing impact on the environment, and it has led the researchers to the acceptance of biomass natural fibers, such as biomass frond fiber (BFF), for the improvement of the mechanical properties of cement-based materials. BFF is abundantly accessible, making it relatively pertinent as a reinforcing material in foamed concrete (FC). In addition, natural fiber-reinforced concrete has been progressively employed in construction for several decades to reduce the crack growth under the static load. This paper intends to experimentally investigate the effectiveness of the addition of BFF to FC to improve its mechanical properties. The FC samples were strengthened with BFF at the weight fractions of 0.12%, 0.24%, 0.36%, 0.48%, and 0.60%. This study used three FC densities: 600 kg/m3, 800 kg/m3, and 1000 kg/m3, with fixed constitutions with 0.45 and 1:1.5 cement-to-water and cement-to-sand ratios, respectively. The evaluated strength characteristics included bending, splitting tensile, and compressive strengths. The experimental outcomes indicated that adding 0.36% BFF to FC facilitates optimal splitting tensile, compressive, and bending strength results. BFF enhances material strength by filling the spaces, microcracks, and gaps inside the FC structure. The BFF helped to reduce crack spreading when the plastic state of the FC cementitious matrix was loaded. Furthermore, the optimum level of BFF inclusion and the accumulation and the non-uniform distribution of BFF were detected, which caused the lowering of the strengths of the FC significantly. Beyond the optimum level of BFF, the agglomeration and the non-uniform dispersion of the BFF were seen, which resulted in a drop in mechanical properties. The output from this research will give a better insight into the potential utilization of plant fiber in FC. It is of profound significance to guide the sustainable development and application of FC material and infrastructures.
Banning Vs Taxing, Reviewing the Potential Opportunities and Challenges of Plastic Products
Authors: Desalegn Goshu , Tangl Anita
Published: June 2022

Plastic products are used for a variety of services and are then dumped into the earth after use. These dumped plastics affect our health, socioeconomic conditions, coastal and marine environments, as well as our climate. The purpose of this study is to systematically review the potential opportunities and challenges of plastic products under the umbrella of banning and taxing. The discourse analysis approach was used in this study to critically analyze and summarize 42 relevant studies. The study developed two different storylines. The first storyline (S1) used taxing plastic products as an alternative strategy. The second storyline (S2) used banning plastic products as an opposing alternative strategy. The findings of the study show that taxing plastic products is frequently observed in developed countries, whereas banning plastic products is frequently observed in developing countries. Benefits in regards to revenue generation, creating public awareness, employment opportunities, industrial processes, construction processes, and recycling growth are highlighted under the taxing policy. On the other hand, a cleaner environment, tourism attraction, eco-friendly shopping, and a reduced ecological footprint are highlighted under the banning policy. Governments and policymakers play a critical role in developing and implementing the necessary legislative framework for dealing with plastic products.
Impact of Social Media, Extended Parallel Process Model (EPPM) on the Intention to Stay at Home during the COVID-19 Pandemic
Authors: Tsoy Diana , Godinic Danijela , Tong Qingyan , Obrenovic Bojan , Khudaykulov Akmal , Kurpayanidi Konstantin
Published: June 2022

Considering how communities perceive the threat and risks of COVID-19, it is essential to examine how emotional regulation stimulated through intrinsic and extrinsic incentive mechanisms via social media can reinforce ‘Stay at home’ intentions. The conceptual framework was developed using the elements of the Extended Parallel Process Model (EPPM). A self-reported questionnaire was used to measure individuals’ intention to stay at home during the pandemic based on the perceived locus of causality as a part of self-determination theory. The empirical research was conducted on a sample of 306 USA respondents. The study results indicate that both components of the EPPM—efficacy and threat—positively affect ‘stay at home’ intentions. Moreover, a positive effect of efficacy on threats was found, as was a moderating effect of threats on the relationship between efficacy and the intention to stay at home. Meanwhile, the influence of social media exposure on threats and behavioral intentions was not significant. People are likely to stay at home as a preventive measure during COVID-19 if there is enough threats and efficacy. However, the abundance of information and opinions in social media can lead to a decreased perceived threat and might disrupt the acceptance of preventive actions.
Modification of Nutrient Requirements for a Four Crop-Based Cropping System to Increase System Productivity, Maintain Soil Fertility, and Achieve Sustainable Intensification
Authors: Quddus Md. Abdul , Anwar Md. Babul , Alam Md. Khairul , Ahmed Razu , Sarker Khokan Kumer , Islam Md. Anarul , Islam Md. Torikul , Kobeasy Mohamed I. , Gaber Ahmed , Ahmed Sharif
Published: June 2022

Sustainable and resilient cropping intensity is now a global focus to address the food demand and nutrition security of the growing population. For sustainable intensification, maintaining soil fertility is a key concern. The nutrient management for the recently developed four crop-based cropping system in Bangladesh has not yet been studied. Hence, field experiments were conducted on the nutrient management of the four crop-based cropping system [Aus (pre-monsoon rice), Aman (monsoon rice), lentil, and mungbean] in calcareous soil in Bangladesh during the years of 2016/17 and 2017/18 to determine the appropriate fertilizer management package to improve crop productivity and sustain soil fertility. The experiment had six treatments assigned in a randomized complete block design with three replications. The treatments included T1 = control (without synthetic fertilizer), T2 = 50% recommended dose of fertilizer (RDF), T3 = 75% RDF, T4 = 100% RDF, T5 = 125% RDF, and T6 = farmers’ practice (FP). The results revealed that the 125% RDF significantly contributed to higher yields of all four crops. The rice equivalent yield (REY) was the highest for the fertilizer management of 125% RDF, which was 45.5%, 9.4%, and 12.2% higher than the control (T1), 100% RDF (T4), and FP, respectively. Considering the uptake of nutrients (N, P, K, S, Zn, and B) by the crops in the cropping system, the 125% RDF was superior to the other treatments. The nutrient management practices had a positive influence on the apparent nutrient recovery (ANR) efficiency of the cropping system. The fertilizer management of 125% RDF was also economically more profitable due to the increment in the cost–benefit ratio of 26.8%, 4.4%, and 4.9% over the control, 100% RDF, and FP, respectively. The results indicate that the current fertilizer recommendations and FP for aus, aman, lentil, and mungbean are not adequate for the change from the three crop to the four crop-based pattern, and an increased dose of fertilizer is required to increase the yield of each individual crop as well as the total system’s productivity. The fertilizer use efficiency is also higher for 125% RDF than the 100% RDF and FP indicating that to sustain the soil fertility in the four crop-based system, the current RDF and FP are not sufficient. This finding will help intensive cropping areas in preventing nutrient deficiencies that would lead to a reduction in the crop yield.
Shareholder Option Valuation in Mezzanine Financing Applied to CO2 Reduction in Sustainable Infrastructure Projects: Application to a Tunnel Road in Medellin, Colombia
Authors: Aguilar Luis , González-Ruiz Juan David , Botero Sergio
Published: June 2022

This research uses real options analysis (ROA) to examine a lender’s conversion option in a mezzanine debt for a sustainable infrastructure project. We examine a transport infrastructure case in Medellin, Colombia, called “Tunel del Oriente” (Eastern tunnel), which meets sustainable criteria to allow the access to credit through a sustainable bond. This study proposes a model to evaluate the right to exercise the conversion option by employing ROA with a binomial approach under the concept of a call option. The underlying assets are based on revenues from the forecast of estimated demand and the alternative sales of carbon credits as the sustainable factor. The results indicated that the financial captured value (FCV), with one as the conversion ratio, could be up to 39.10% of the investment when the lender decides to become a shareholder. Furthermore, the FCV can increase by 6% more if the project sells TonCO2e saved by the sustainable factor, highlighting that the tax benefits are approximately 11% of the FCV if the project is sustainable. Additionally, the option value is 39.09% of the debt amount. Finally, this study demonstrates that project finance using mezzanine debt proves to be an effective and attractive method for any lender wanting to boost profit while supporting stakeholders and the environment with sustainable projects and responsible investment.
Assessment of Biophysical Properties of Faecal Pellets from Channel Catfish (Ictalurus punctatus) and Bighead Carp (Aristichthys nobilis)
Authors: Yuan Ting , Wang Qidong , Li Shiqi , Huang Geng , Zhang Tanglin , Li Zhongjie , Liu Jiashou
Published: June 2022

Fish faeces are a crucial component of solid wastes from cage culture systems. In order to investigate the environmental impacts of faeces from channel catfish (Ictalurus punctatus) and bighead carp (Aristichthys nobilis), certain biophysical characteristics during faecal sinking at three temperatures (10, 20 and 30 °C for winter, spring-autumn and summer conditions, respectively) were assessed in the present study. Settling velocities of faeces from channel catfish (1.72–13.33 cm/s) and bighead carp (4.16–13.83 cm/s) accelerated with an increase in water temperature. For channel catfish faeces, there were positive correlations between settling velocity and physical properties, i.e., weight, volume, length and diameter; however, for bighead carp faeces, no linear relationship between settling velocity and length was found. The main faecal water absorption period for these two species occurred after 2.5 min of immersion. The main leaching period of faecal carbon and nitrogen was 0–2.5 min, and the leaching period of faecal phosphorus was 0–10 min. The nutrient contents in channel catfish faeces were significantly higher than those in bighead carp faeces. These results suggest that co-culturing channel catfish with bighead carp can effectively reduce the discharge of nutrients from aquaculture. The biophysical properties of these two types of fish faeces can also provide guidance in particle waste collection.
The Impact of Family Factors on Children’s Mental Health during Home Quarantine: An Empirical Study in Northwest China
Authors: Jin Xiaoyi , Dong Yitong , Du Wei
Published: June 2022

(1) Aims: This paper aims to analyze the factors affecting children’s mental health during home quarantine from the perspective of family composition in a specific Chinese context where historically, families are small in size. (2) Methods: Here, 10,210 online questionnaires from 3 junior high schools in Xi’an and Hanzhong from 23 to 27 February 2020, were collected to explore the impact of family factors on children’s mental health in Northwest China during home quarantine based on the ecosystem theory, by using OLS, logit regression models, and the Shapley value decomposition method. (3) Results: The mental health of northwestern Chinese children changed significantly after home quarantine. We also found that during home quarantine, some factors, such as a high-income family, lack of siblings, living with parents, mothers with middle- or high-level occupations, frequent parent–child communication, and better parent–child relationships, were positively related to children’s mental health. (4) Conclusions: Different from previous studies, this paper found that the psychological condition of children in Northwest China tended to be improved during the epidemic. In addition, family factors, especially the parent–child interaction, played an important role in the mental health of children during the epidemic.
Nexus between Leader–Member Exchange, Paternalistic Leadership, and Creative Behavior in the Construction Industry
Authors: Maqsoom Ahsen , Zahoor Ifra , Ashraf Hassan , Ullah Fahim , Alsulami Badr T. , Salman Alaa , Alqurashi Muwaffaq
Published: June 2022

Effective leadership and creative performance are the predominant factors for the success of modern projects in the global construction industry. However, rigorous research has not explored the nexus between such factors and the leader–member exchange (LMX). To address this gap, this study explores the relationship between dimensions of paternalistic leadership and employee creativity achieved through LMX in the context of the construction industry. Based on social exchange theory (SET), six relevant hypotheses were proposed in this study. The data were collected through a structured questionnaire. An online survey form was used for data collection, through which 288 responses were collected from the construction industry employees working in Pakistan. The collected data were analyzed using Smart PLS in two stages, i.e., measurement model evaluation (reliability analysis, convergent and discriminant validity) and structural model evaluation (R2, F2, and path coefficient). The findings of the current study reveal a positive association of authoritarian, benevolent, and moral leadership with employee creativity. In addition, LMX significantly mediates the relationship between the two dimensions of paternalistic leadership (benevolent and moral leadership) and creativity, except for authoritarian leadership. Based on the results, this study contributes to the body of knowledge related to the appropriate leadership style in the local construction industry that can be extended to other developing countries with similar dynamics. It also helps the managers target and develops relevant skills to acquire positive outcomes from their team members.
Research on Real-Time Communication Algorithm of Substation Based on Time-Sensitive Network
Authors: Wang Beilei , Liu Yang , Guo Chenyang , Song Yan , Wang Jidong , Xiao Jinchao , Chen Xiaoguang
Published: June 2022

A time-sensitive network (TSN) extends the conventional Ethernet to support time-sensitive data flow. Thus, it enables simultaneous transmission of high reliability (HR) flow, medium reliability (MR) flow, and low reliability (LR) flow on the same network, thereby improving the reliability of data transmission. A TSN is a symmetric network that connects sensors and other facilities. As a backbone network, it can efficiently connect the underlying sensors and other levels of facilities, as well as ensure the quality of service of the network. For modern supervisory control and data acquisition (SCADA) systems, several types of sensors are widely used. The acquisition cycle of sensors for different purposes varies significantly from milliseconds to seconds. Moreover, these data also have different real-time requirements. Based on satisfiability modulo theories (SMT), this study proposes a TSN routing and scheduling method by adding related scheduling constraints. Compared with other methods, the proposed method can realize the routing and scheduling of hybrid flow in a hyper period and consider MR flow and LR flow, which improves the feasibility and certainty of data flow interaction between substations.
Location Information-Assisted Robust Beamforming Design for Ultra-Wideband Communication Systems
Authors: Yang Lei , Zhang Zhi , Fang Xiao , Cao Shiyu , Shangguan Zhegong , Li Shiyin
Published: June 2022

The future of mobile communication systems is evolving rapidly toward being more intelligent, while also having the ability to interconnect with everything and be aware of the current wireless environment. For complex scenarios, the asymmetry features of channel state information (CSI) will seriously restrict the performance of the communication system. With its accurate positioning technology and high-speed communication rate, ultra-wideband (UWB) has a promising future as a solution to integrate communication and positioning functions. The traditional CSI channel estimation usually requires channel training, which will greatly increase the overhead of the system. This paper proposes a location information-assisted beamforming to replace the traditional channel training process. First, we use the user location parameter information to reconstruct the channel model and derive the CSI error distribution based on the location distribution. Second, considering the uncertainty of the user positioning error, we model the robust beamforming optimization problem that minimizes the total transmit power. To solve this non-convex problem effectively, we design a new beamforming algorithm by using semidefinite relaxation (SDR) and Bernstein-type inequalities. Finally, simulation results verify the robustness of the proposed robust beamforming compared to the worst-case robust beamforming.
Early Detection of Abnormal Attacks in Software-Defined Networking Using Machine Learning Approaches
Authors: Chuang Hsiu-Min , Liu Fanpyn , Tsai Chung-Hsien
Published: June 2022

Recent developments have made software-defined networking (SDN) a popular technology for solving the inherent problems of conventional distributed networks. The key benefit of SDN is the decoupling between the control plane and the data plane, which makes the network more flexible and easier to manage. SDN is a new generation network architecture; however, its configuration settings are centralized, making it vulnerable to hackers. Our study investigated the feasibility of applying artificial intelligence technology to detect abnormal attacks in an SDN environment based on the current unit network architecture; therefore, the concept of symmetry includes the sustainability of SDN applications and robust performance of machine learning (ML) models in the case of various malicious attacks. In this study, we focus on the early detection of abnormal attacks in an SDN environment. On detection of malicious traffic in SDN topology, the AI module in the topology is applied to detect and act against the attack source through machine learning algorithms, making the network architecture more flexible. Under multiple abnormal attacks, we propose a hierarchical multi-class (HMC) architecture to effectively address the imbalanced dataset problem and improve the performance of minority classes. The experimental results show that the decision tree, random forest, bagging, AdaBoost, and deep learning models exhibit the best performance for distributed denial-of-service (DDoS) attacks. In addition, for the imbalanced dataset problem of multiclass classification, our proposed HMC architecture performs better than previous single classifiers. We also simulated the SDN topology and scenario verification. In summary, we concatenated the AI module to enhance the security and effectiveness of SDN networks in a practical manner.
Hesitant Fuzzy Variable and Distribution
Authors: Zhang Guofang , Yuan Guoqiang
Published: June 2022

In recent decades, the hesitant fuzzy set theory has been used as a main tool to describe the hesitant fuzzy phenomenon, which usually exists in multiple attributes of decision making. However, in the general case concerning numerous decision-making problems, values of attributes are real numbers, and some decision makers are hesitant about these values. Consequently, the possibility of taking a number contains several possible values in the real number interval [0, 1]. As a result, the hesitant possibility of hesitant fuzzy events cannot be inferred from the given hesitant fuzzy set which only presents the hesitant membership degree with respect to an element belonging to this one. To address this problem, this paper explores the axiomatic system of the hesitant possibility measure from which the hesitant fuzzy theory is constructed. Firstly, a hesitant possibility measure from the pattern space to the power set of [0, 1] is defined, and some properties of this measure are discussed. Secondly, a hesitant fuzzy variable, which is a symmetric set-valued function on the hesitant possibility measure space, is proposed, and the distribution of this variable and one of its functions are studied. Finally, two examples are shown in order to explain the practical applications of the hesitant fuzzy variable in the hesitant fuzzy graph model and decision-making considering hesitant fuzzy attributes. The relevant research results of this paper provide an important mathematical tool for hesitant fuzzy information processing from another new angle different from the theory of hesitant fuzzy sets, and can be utilized to solve decision problems in light of the hesitant fuzzy value of multiple attributes.
A Modified Stein Variational Inference Algorithm with Bayesian and Gradient Descent Techniques
Authors: Zhang Limin , Dong Jing , Zhang Junfang , Yang Junzi
Published: June 2022

This paper introduces a novel variational inference (VI) method with Bayesian and gradient descent techniques. To facilitate the approximation of the posterior distributions for the parameters of the models, the Stein method has been used in Bayesian variational inference algorithms in recent years. Unfortunately, previous methods fail to either explicitly describe the influence of its history in the tracing of particles (Q(x) in this paper) in the approximation, which is important information in the search for particles. In our paper, Q(x) is considered in design of the operator Bp, but the chance of jumping out of the local optimum may be increased, especially in the case of complex distribution. To address the existing issues, a modified Stein variational inference algorithm is proposed, which can make the gradient descent of Kullback–Leibler (KL) divergence more random. In our method, a group of particles are used to approximate target distribution by minimizing the KL divergence, which changes according to the newly defined kernelized Stein discrepancy. Furthermore, the usefulness of the suggested technique is demonstrated by using four data sets. Bayesian logistic regression is considered for classification. Statistical studies such as parameter estimate classification accuracy, F1, NRMSE, and others are used to validate the algorithm’s performance.
A New Class of Bertrand Curves in Euclidean 4-Space
Authors: Li Yanlin , Uçum Ali , İlarslan Kazım , Camcı Çetin
Published: June 2022

Bertrand curves are a pair of curves that have a common principal normal vector at any point and are related to symmetry properties. In the present paper, we define the notion of 1,3-V Bertrand curves in Euclidean 4-space. Then we find the necessary and sufficient conditions for curves in Euclidean 4-space to be 1,3-V Bertrand curves. Some related examples are given.
An Integrated Approach for Failure Mode and Effects Analysis Based on Weight of Risk Factors and Fuzzy PROMETHEE Ⅱ
Authors: Lian Xiaozhen , Hou Liang , Zhang Wenbo , Bu Xiangjian , Yan Huasheng
Published: June 2022

Design experts need to fully understand the failure risk of a product to improve its quality and reliability. However, design experts have different understandings of and concepts in the risk evaluation process, which will lead to cognitive asymmetry in the product’s redesign. This phenomenon of cognitive asymmetry prevents experts from improving the reliability of a product, increasing the risk of product development failure. Traditionally, failure mode and effects analysis (FMEA) has been widely used to identify the failure risk in redesigning products and a system’s process. The risk priority number (RPN), which is determined by the risk factors (RF), namely, the occurrence (O), severity (S), and detection (D), is the index used to determine the priority ranking of the failure modes (FM). However, the uncertainty about the evaluation information for the RF and the coupling relationship within the FM have not been taken into account jointly. This paper presents an integrated approach for FMEA based on an interval-valued intuitionistic fuzzy set (IVIFS), a fuzzy information entropy, a non-linear programming model, and fuzzy PROMETHEE Ⅱ to solve the problem of cognitive asymmetry between experts in the risk evaluation process. The conclusions are as follows: Firstly, an IVIFS is used to present the experts’ evaluation information of the RF with uncertainty, and the fuzzy information entropy is utilized to obtain the weight of the experts to integrate the collective decision matrix. Secondly, a simplified non-linear programming model is utilized to obtain the weight of the RF to derive the weighted preference index of the FM. Subsequently, the coupling relationship within the FM is estimated by fuzzy PROMETHEE Ⅱ, where the net flow is given to estimate the priority ranking of the FM. Finally, the proposed approach is elaborated on using a real-world case of a liquid crystal display. Methods comparison and sensitivity analyses are conducted to demonstrate the validity and feasibility of the proposed approach.
Fitness-Based Acceleration Coefficients Binary Particle Swarm Optimization (FACBPSO) to Solve the Discounted Knapsack Problem
Authors: Sulaiman Adel , Sadiq Marium , Mehmood Yasir , Akram Muhammad , Ali Ghassan Ahmed
Published: June 2022

The discounted {0-1} knapsack problem (D{0-1}KP) is a multi-constrained optimization and an extended form of the 0-1 knapsack problem. The DKP is composed of a set of item batches where each batch has three items and the objective is to maximize profit by selecting at most one item from each batch. Therefore, the D{0-1}KP is complex and has found many applications in real economic problems and other areas where the concept of promotional discounts exists. As DKP belongs to a binary class problem, so the novel binary particle swarm optimization variant with modifications is proposed in this paper. The acceleration coefficients are important parameters of the particle swarm optimization algorithm that keep the balance between exploration and exploitation. In conventional binary particle swarm optimization (BPSO), the acceleration coefficients of each particle remain the same in iteration, whereas in the proposed variant, fitness-based acceleration coefficient binary particle swarm optimization (FACBPSO), values of acceleration coefficients are based on the fitness of each particle. This modification enforces the least fit particles to move fast and best fit accordingly, which accelerates the convergence speed and reduces the computing time. Experiments were conducted on four instances of DKP having 10 datasets of each instance and the results of FACBPSO were compared with conventional BPSO and the new exact algorithm using a greedy repair strategy. The results demonstrate that the proposed algorithm outperforms PSO-GRDKP and the new exact algorithm in solving four instances of D{0-1}KP, with improved convergence speed and feasible solution time.
Special Issue on Quantum Information Applied in Neuroscience
Authors: Georgiev Danko D.
Published: June 2022

The rapid progress achieved by quantum information science in recent decades was made possible by the realization that genuine quantum phenomena, for which their occurrences are forbidden by classical physics, are not a defect of quantum theory but are useful physical resources [...]
A General Framework for Geometrically Uniform Codes and Signal Sets Matched to Groups
Authors: Gomes Eduardo Michel Vieira , de Carvalho Edson Donizete , Martins Carlos Alexandre Ribeiro , Brizola Evandro Mazetto , da Silva Eduardo Brandani
Published: June 2022

Geometrically uniform codes are fundamental in communication systems, mainly for modulation. Typically, geometrically uniform codes are dependent on a given alphabet. The current work establishes the necessary and sufficient conditions for obtaining a matched labeling between a group G and a signal set S. It introduces the concept of the G-isometric signal set, allowing for the establishment of equivalences between different types of signal sets. In particular, we obtain isometries between groups and geometrically uniform codes with a minimal generator. We also draw attention to the influence of the environment metric space, the group metric, and the matched mapping on the labeling of a signal set. The results are valid for all environment metric spaces. The alphabet emerges naturally from the relationship between the signal set S and the label group derived from its symmetry group, Γ(S).
A Time-Symmetric Resolution of the Einstein’s Boxes Paradox
Authors: Heaney Michael B.
Published: June 2022

The Einstein’s Boxes paradox was developed by Einstein, de Broglie, Heisenberg, and others to demonstrate the incompleteness of the Copenhagen Formulation of quantum mechanics. I explain the paradox using the Copenhagen Formulation. I then show how a time-symmetric formulation of quantum mechanics resolves the paradox in the way envisioned by Einstein and de Broglie. Finally, I describe an experiment that can distinguish between these two formulations.
A New Aulacoseira Thwaites (Bacillariophyta) Species from Wyoming, USA
Authors: Greifenstein Jeremy , Shea Rachel , Kociolek John Patrick
Published: June 2022

A new species, Aulacoseira wyomingensis, is described from a small seep near Casper, Wyoming, USA, using light and scanning electron microscopy, in which it was the dominant diatom taxon. Valves have large areolae that cover the valve face. Spines, when present, are short and shield-like, precluding chain formation. Unlike most members of the genus, A. wyomingensis appears to lack rimoportulae. While we assign this species to the genus Aulacoseira within the Aulacoseiraceae based on the radial nature of its valve, its cingulum composed of fine ligulate bands, and presence of a ringleiste and collum, it does not appear to be easily assigned to any of the morphological groups within the genus.
Solving Dual-Channel Supply Chain Pricing Strategy Problem with Multi-Level Programming Based on Improved Simplified Swarm Optimization
Authors: Yeh Wei-Chang , Liu Zhenyao , Yang Yu-Cheng , Tan Shi-Yi
Published: June 2022

With the evolution of the Internet and the introduction of third-party platforms, a diversified supply chain has gradually emerged. In contrast to the traditional single sales channel, companies can also increase their revenue by selling through multiple channels, such as dual-channel sales: adding a sales channel for direct sales through online third-party platforms. However, due to the complexity of the supply chain structure, previous studies have rarely discussed and analyzed the capital-constrained dual-channel supply chain model, which is more relevant to the actual situation. To solve more complex and realistic supply chain decision problems, this paper uses the concept of game theory to describe the pricing negotiation procedures among the capital-constrained manufacturers and other parties in the dual-channel supply chain by applying the Stackelberg game theory to describe the supply chain structure as a hierarchical multi-level mathematical model to solve the optimal pricing strategy for different financing options to achieve the common benefit of the supply chain. In this study, we propose a Multi-level Improved Simplified Swarm Optimization (MLiSSO) method, which uses the improved, simplified swarm optimization (iSSO) for the Multi-level Programming Problem (MLPP). It is applied to this pricing strategy model of the supply chain and experiments with three related MLPPs in the past studies to verify the effectiveness of the method. The results show that the MLiSSO algorithm is effective, qualitative, and stable and can be used to solve the pricing strategy problem for supply chain models; furthermore, the algorithm can also be applied to other MLPPs.
Design Procedure of a Frequency Reconfigurable Metasurface Antenna at mmWave Band
Authors: Ledimo Bokamoso Kebatho , Moaro Pako , Ramogomana Reuben , Mosalaosi Modisa , Basutli Bokamoso
Published: June 2022

The use of the millimeter wave (mmWave) spectrum and further exploration of sub-mmWave has led to a new era in wireless communication, as the need for higher data rates grows. High frequencies, on the other hand, incur a higher path loss, requiring an increase in antenna gain requirements. Metasurfaces, which emerge as a promising technology for mitigating path loss effects by utilizing two dimensional (2D) arrays of engineered meta-atoms resembling metamaterials that control the surface’s electromagnetic response have been introduced. Currently, metasurfaces are primarily considered as passive reflecting devices in wireless communications, assisting conventional transceivers in shaping propagation environments. This paper presents an alternative application of metasurfaces for wireless communications as active reconfigurable antennas for next generation transceivers. A framework that demonstrates the design process of a metasurface antenna structure was introduced and further used to design a 4 × 4 array and its reconfigurable counterpart. In contrast to conventional phased array antennas, a reconfigurable metasurface (RMS) antenna does not require phase-shifters and amplifiers, which leads to reduced cost. Instead, each individual element achieves reconfigurability by shifting the resonating frequency using semiconductor devices such as PIN diodes. The proposed metasurface antenna is designed to operate at a frequency of 28 GHz and 40 GHz. In addition, an increase in gain and directivity was observed when diodes were added to the metasurface antenna array. However, due to PIN diodes being connected to metallic strips in the metasurface antenna array, loss can occur due to power dissipation, which results in a decrease in radiation efficiency.