bluuebunny/crossref_metadata_2025 huggingface dataset:
Differential Impact Analysis for Climate Change Adaptation: A Case Study from Nepal
Authors: Khadka Chiranjeewee , Upadhyaya Anju , Edwards-Jonášová Magda , Dhungana Nabin , Baral Sony , Cudlin Pavel
Published: August 2022

Following a case study, community adaptation plans are a bottom-up approach that focus on increasing climate-vulnerable communities’ engagement in local adaptation planning and policy design, prioritization, and implementation in Nepal. This paper explains how Community-Based Adaptation Action Plan (CAPA) groups are being studied to assess the climate vulnerability of the local socio-ecosystem and to develop community-level adaptation measures. However, there is insufficient research to differentiate local vulnerabilities caused by climate change. This paper, therefore, examines climate change vulnerability with respect to community vulnerability and potential adaptation measures to increase community resilience and adaptive capacity through CAPAs. The study compares differences by gender, caste/ethnicity, and wealth in relation to specific climate-related hazards (exposure, sensitivity, and adaptive capacity) of communities. The study draws on secondary sources of information along with field observations, 73 household interviews, 13 key-informant interviews, consultations, and 9 interactive meetings in 3 districts of Nepal. Differential impact analysis refers to the exposure, sensitivity, and adaptive capacity of local socio-ecological systems. In addition, multivariate analysis was conducted using the Canoco program to analyze the role of actors with respect to climate vulnerability. The results conclude that the degree of vulnerability varies widely at the household level and is strongly influenced by socio-economic characteristics such as gender, caste/ethnicity, and wealth. Immediate and focused attention is needed to improve access to government resources for vulnerable households, requiring positive support from decision makers. Equally important is improving the chain of communication, which includes information, skills, knowledge, capacity, and institutional arrangements. Analysis of the differential vulnerability and the adaptive capacity of a vulnerable community is more appropriate for the design of local adaptation plans. Therefore, the study suggests that engagement of local partners, including local authorities, in addressing vulnerability and adaptation is required to confront the social process, new institutional arrangements, local adaptation, and capacity-building with technical solutions.
Automated Analysis of Australian Tropical Cyclones with Regression, Clustering and Convolutional Neural Network
Authors: Sufi Fahim , Alam Edris , Alsulami Musleh
Published: August 2022

Tropical cyclones take precious lives, damage critical infrastructure, and cause economic losses worth billions of dollars in Australia. To reduce the detrimental effect of cyclones, a comprehensive understanding of cyclones using artificial intelligence (AI) is crucial. Although event records on Australian tropical cyclones have been documented over the last 4 decades, deep learning studies on these events have not been reported. This paper presents automated AI-based regression, anomaly detection, and clustering techniques on the largest available cyclone repository covering 28,713 records with almost 80 cyclone-related parameters from 17 January 1907 to 11 May 2022. Experimentation with both linear and logistic regression on this dataset resulted in 33 critical insights on factors influencing the central pressure of cyclones. Moreover, automated clustering determined four different clusters highlighting the conditions for low central pressure. Anomaly detection at 70% sensitivity identified 12 anomalies and explained the root causes of these anomalies. This study also projected parameterization and fine-tuning of AI-algorithms at different sensitivity levels. Most importantly, we mathematically evaluated robustness by supporting an enormous scenario space of 4.737 × 108234. A disaster strategist or researcher can use the deployed system in iOS, Android, or Windows platforms to make evidence-based policy decisions on Australian tropical cyclones.
A Study of the Relationship between Lithuanian International Migration Flows and Transport Sector Performance Indicators
Authors: Ševčenko-Kozlovska Galina , Čižiūnienė Kristina
Published: August 2022

Migration, emigration and immigration are processes directly related to transport and have a significant impact on the performance of this field. On the other hand, extensive movement of people inevitably relates to issues of sustainability, their assurance, etc. Migrants settle in large cities where public transport is well developed. Migrants usually commute by means other than driving their own cars (choosing public transport, walking, cycling or car sharing). Many researchers in the USA (United States of America) have linked this to migrants’ choice of a place of residence, which are well served by public transport, as they mainly travel for work. However, with passing time and improving living standards, the need for immigrants to not only use public transport, but to also own their own, becomes similar to that of the locals. This also increases the need for the analysis of sustainable transport issues. The correlation and regression analyses used in the article and the application of the ALM (automatic linear modelling) modelling led to the following results: a significant positive correlation was found between emigration and passenger carriage by all modes of transport|Maritime transport, and a significant negative correlation was found between emigration and passenger carriage by all modes of transport|Rail transport, suggesting that these indicators have a mutually significant relationship with one another. The conducted regression analysis and applied modelling showed that the regression model was insignificant and therefore cannot be used. However, the results suggest that the relationship between immigration and transport indicators can be used as a direction for further research.
Remote Sensing for Surface Coal Mining and Reclamation Monitoring in the Central Salt Range, Punjab, Pakistan
Authors: Ali Nafees , Fu Xiaodong , Ashraf Umar , Chen Jian , Thanh Hung Vo , Anees Aqsa , Riaz Muhammad Shahid , Fida Misbah , Hussain Muhammad Afaq , Hussain Sadam , Hussain Wakeel , Ahmed Awais
Published: August 2022

The expansion and exploitation of mining resources are essential for social and economic growth. Remote sensing provides vital tools for surface-mining monitoring operations as well as for reclamation efforts in the central Salt Range of the Indus River Basin, Pakistan. This research demonstrates the applicability of remote sensing techniques to the coal mining monitoring scheme to allow for effective and efficient monitoring and to offset the adverse consequences of coal mining activities. Landsat 8 OLI images from June 2019 and 2020, and a Landsat 7 ETM+ image from June 2002, were used for this study. A three-phase methodology including Normalized Difference Vegetation Index (NDVI) analysis, land cover mapping, and change detection approaches was adopted. Image classification based on Tasseled Cap Transformation and the brightness temperature At-satellite using the K-means algorithm was implemented in a GIS program to identify seven land cover classes within the study area. The results show some level of surface disturbance to the landscape due to the coal mining reclamation activities that had taken place over the 18-year time period. From 2019 to 2020, about 3.622 km2 of coal mines or barren land were converted into bare agricultural land. Over the years, it was also observed that reclamation areas exhibited higher values of NDVI than coal mining areas. The mean NDVI for coal mining areas was 0.252 km2, and for areas of reclamation, it was 0.292 km2 in 2020, while in 2019, the value for coal mining sites was 0.133 km2, and 0.163 km2 for reclamation sites. This trend suggests that coal-mining operations can be monitored using satellite data, and the progress of reclamation efforts can be assessed using satellite NDVI data from the target locations. This study is beneficial to agencies responsible for monitoring land cover changes in a coal mine because it provides a cost-effective, efficient, and robust scientific tool for making mine site allocation decisions and for monitoring the progress of reclamation efforts.
Exploring the Role of Environmental Regulation and Technological Innovation in Financial Performance: Evidence from Chinese Heavy-Polluting Industry
Authors: Zhu Yiling , Zhao Tong
Published: August 2022

Environmental regulation is an important guarantee to realize the balanced development of economy and environment, and is the policy guidance of the government to the resource utilization of companies. Environmental regulation will make companies increase costs, and also promote companies to explore technological innovation. How to reverse the negative cost effect of environmental regulation and improve financial performance is a problem that the government and companies need to think about together. Based on the data from 2015 to 2019 of China’s heavy-polluting industry of listed companies, this paper analyzes the impact of environmental regulation on financial performance. The results show that: (1) environmental regulation inhibits firms’ short-term and long-term financial performance. Environmental regulation has formed the negative effect of cost crowding out; (2) environmental regulation positively affects technological innovation. Environmental regulation can stimulate companies to actively explore technological reform to cope with the requirements and restrictions of environmental regulation policies; (3) technological innovation is not significantly negatively correlated with corporate financial performance. Technological innovation input cannot directly lead to the improvement of financial performance in the current period; and (4) technological innovation positively mediates the relationship between environmental regulation and financial performance. That verifies a weak “Porter Hypothesis”. “Innovation compensation effect” exists, and technological innovation can partially offset “cost crowding out effect” and slow down the inhibition relationship of environmental regulation on financial performance, but the innovation effect does not offset the environmental cost. According to the research results, environmental regulation still has a negative effect on the financial performance of listed companies in China’s heavy-polluting industries. The government should formulate strict and stringent environmental regulation policies, guide companies to rationally use resources and protect the environment. Instead of passively responding to policies, companies should actively seek new technologies and alternative sources of energy. Companies try to amplify the compensation effect of technological innovation, reduce the cost crowding out effect of environmental regulation, and improve their value.
The Impact of Family Socioeconomic Status on Learning Conformity among Chinese University Students: Self-Efficacy as Mediating Factor
Authors: Xiao Bin , Song Guandong
Published: August 2022

Background: At present, family socioeconomic status is a significant contributor to the differences in university students’ learning motivation, but few studies have examined the effects on different types of motivation to learn conformity. Thus, the present study investigates the effects of family socioeconomic status on different types of learning conformity and the mediating role of self-efficacy. Methods: 339 Chinese university students were surveyed using the general self-efficacy scale, the learning conformity scale, and the family socioeconomic status questionnaire. We analyzed the effect of family socioeconomic status on learning conformity and the mediating role of general self-efficacy through common bias tests, correlation analysis, structural equation modeling, and tests of mediating effects. Results: (1) There are three types of learning conformity, as follows: learning abidance, learning obedience, and learning compliance. (2) The mediation model concluded that family socioeconomic status had a positive and significant effect on learning abidance and learning obedience, and general self-efficacy played a partially mediating role, with an adequate ratio of 59.7% and 26.26%, respectively; family socioeconomic status had a negative and significant effect on learning compliance, and general self-efficacy played a partially mediating role, with an adequate ratio of 52.02%. Conclusions: This study provides first-hand empirical data to support studies of learning motivation, learning conformity behavior, and self-efficacy among Chinese university students. It also provides a theoretical basis for subsequent research on family socioeconomic status and learning conformity.
Techno-Economic Analysis of Hybrid Diesel Generators and Renewable Energy for a Remote Island in the Indian Ocean Using HOMER Pro
Authors: Riayatsyah T. M. I. , Geumpana T. A. , Fattah I. M. Rizwanul , Mahlia T. M. Indra
Published: August 2022

This study is about the electrification of the remote islands in the Indian Ocean that were severely affected by the tsunami in the 2004 earth earthquake. To supply electricity to the islands, two diesel generators with capacities of 110 kW and 60 kW were installed in 2019. The feasibility of using renewable energy to supplement or replace the units in these two generators is investigated in this work. In 2019, two diesel generators with capacities of 110 kW and 60 kW were installed in the islands to supply electricity. This work analyses whether the viability of using renewable energy can be used to supplement or replace these two generators. Among the renewable energy options proposed here are a 100 kW wind turbine, solar PV, a converter, and batteries. As a result, the study’s goal is to perform a techno-economic analysis and optimise the proposed hybrid diesel and renewable energy system for a remote island in the Indian Ocean. The Hybrid Optimisation Model for Electric Renewable (HOMER) Pro software was used for all simulations and optimisation for this analysis. The calculation is based on the current diesel price of USD 0.90 per litre (without subsidy). The study found that renewable alone can contribute to 29.2% of renewable energy fractions based on the most optimised systems. The Net Present Cost (NPC) decreased from USD 1.65 million to USD 1.39 million, and the levelised Cost of Energy (CoE) decreased from 0.292 USD/kWh to 0.246 USD/kWh, respectively. The optimised system’s Internal Rate of Return (IRR) is 14% and Return on Investment (ROI) 10%, with a simple payback period of 6.7 years. This study shows that it would be technically feasible to introduce renewable energy on a remote island in Indonesia, where numerous islands have no access to electricity.
Runoff Estimation in Ungauged Watershed and Sensitivity Analysis According to the Soil Characteristics: Case Study of the Saint Blaise Vallon in France
Authors: Park Gue-Tae , An Song-Hee , Jang Dong-Woo
Published: August 2022

Water Resources Research announced that, as a result of global warming, the amount of extreme torrential rain globally has increased steadily since the middle of the last century. To cope effectively with climate change, it is important to use consistent and scientific water information of water resources. In this study, we use a hydrological analysis of the Saint Blaise Vallon area to indicate how the damage from natural disasters that may come in the future may be minimized. In addition, a hydrological analysis and a numerical simulation model were implemented to estimate runoff and runoff coefficients derived from a heavy rainfall event that caused serious damage to river flooding. A runoff sensitivity analysis was conducted according to the soil parameters. In particular, a method using the hydrological model and the hydrological sensitivity analysis were applied to the target watershed, and the results of the peak outlet discharge were analyzed in time series so that they could be used for flood prediction and disaster management. In addition, the flood discharge and runoff coefficients during the flooding of the target watershed were presented through the study.
The Compressive Properties and Deformation Mechanism of Closed-Cell Aluminum Foam with High Porosity after High-Temperature Treatment
Authors: Zhang Hu , Lei Mingfeng , Lin Zanquan , Gong Weipeng , Shen Jiajia , Zhang Yunbo
Published: August 2022

As a new type of structurally functional material, aluminum foam is widely used in civil engineering due to its excellent noise and energy reduction, thermal insulation, and fire protection properties. However, systematic research into the mechanical properties, application technology, and specification standards of aluminum foam materials in civil engineering application scenarios is lacking. In this work, a special experimental study on the mechanical properties and deformation mechanism of closed-cell aluminum foam materials in compression after fire was carried out. The mechanism of deformation and failure of closed-cell aluminum foam was revealed, and the variation in the mechanical properties of closed-cell aluminum foam with porosity, and heating temperature were investigated. On the basis of the experimental results, the correlation function between material parameters and material porosity in the Liu–Subhash constitutive model was established through multiparameter regression analysis. Then, an intrinsic structure model of aluminum foam that can consider porosity was proposed. The research results show that (1) the compression deformation process of closed-cell aluminum foam specimens exhibits significant stage characteristics: a quasi-elastic stage of quasi-elastic deformation of the matrix and cell structure → a plateau stage of cell structure destabilization and damage → a densification stage of cell collapse and stacking. (2) As the porosity decreases, the aluminum foam material becomes more resistant to compressive deformation and shows better compressive mechanical properties overall. With an increase in the heat treatment temperature, the elastic gradient, compressive proof strength, and plateau stress of the aluminum foam material show a small decrease in the overall trend. (3) The predicted values of the intrinsic structure model of closed-cell aluminum foam are in good agreement with the experimental results, indicating that the model can efficiently characterize the stress–strain process of the material and is referable.
The Philosophical Thought of Confucius and Mencius, and the Concept of the Community of a Shared Future for Mankind
Authors: Khan Uzma , Wang Huili , Cui Zhongliang , Begum Abida , Mohamed Abdullah , Han Heesup
Published: August 2022

The Community of a Shared Future for Mankind seeks to mitigate the world’s current challenges, and to create a more sustainable future through better global governance. Some of the philosophical arguments of the Community of a Shared Future for Mankind, and its foundations, which this article traces, are grounded in the philosophical teachings of Confucius and Mencius. The five pillars of Confucianism are benevolence (Ren), righteousness (Yi), propriety (Li), wisdom (Zhi) and fidelity (Xin). The five pillars have their equivalents in the philosophy of the Community of a Shared Future for Mankind: benevolence has its equivalents in multilateral and bilateral agreements; righteousness shows justice; propriety’s equivalents are international standards and regulations; wisdom is the problem-solving dialogues; and trustworthiness is equated to international organizations that safeguard global integrity. The Confucian principle of harmony is congruent with the objective of the Community of a Shared Future for Mankind, of creating a world of harmony, peace and cooperation. The Golden Rule has been observed in the Community of a Shared Future for Mankind, through its insistence on reciprocal bilateral and multilateral cooperation. Mencius’ philosophical contribution to the Community of a Shared Future for Mankind is in his theory of human nature, where humaneness is seen as developmental—as would be the community built by the Community of a Shared Future for Mankind. Mencius’ principle of governance is congruent with the Community of a Shared Future for Mankind’s insistence on responsible governance. These congruences and similarities, between the Community of a Shared Future for Mankind and the philosophies of Confucius and Mencius, point to the foundations for the Community of a Shared Future for Mankind.
Fault Identification of Electric Submersible Pumps Based on Unsupervised and Multi-Source Transfer Learning Integration
Authors: Yang Peihao , Chen Jiarui , Wu Lihao , Li Sheng
Published: August 2022

The ratio between normal data and fault data generated by electric submersible pumps (ESPs) in production is prone to imbalance, and the information carried by the fault data generally as a minority sample is easily overwritten by the normal data as a majority sample, which seriously interferes with the fault identification effect. For the problem that data imbalance under different working conditions of ESPs causes the failure data to not be effectively identified, a fault identification method of ESPs based on unsupervised feature extraction integrated with migration learning was proposed. Firstly, new features were extracted from the data using multiple unsupervised methods to enhance the representational power of the data. Secondly, multiple samples of the source domain were obtained by multiple random sampling of the training set to fully train minority samples. Thirdly, the variation between the source domain and target domain was reduced by combining weighted balanced distribution adaptation (W-BDA). Finally, several basic learners were constructed and combined to integrate a stronger classifier to accomplish the ESP fault identification tasks. Compared with other fault identification methods, our method not only effectively enhances the performance of fault data features and improves the identification of a few fault data, but also copes with fault identification under different working conditions.
Using Explainable Artificial Intelligence to Identify Key Characteristics of Deep Poverty for Each Household
Authors: Zhang Wenguang , Lei Ting , Gong Yu , Zhang Jun , Wu Yirong
Published: August 2022

The first task for eradicating poverty is accurate poverty identification. Deep poverty identification is conducive to investing resources to help deeply poor populations achieve prosperity, one of the most challenging tasks in poverty eradication. This study constructs a deep poverty identification model utilizing explainable artificial intelligence (XAI) to identify deeply poor households based on the data of 23,307 poor households in rural areas in China. For comparison, a logistic regression-based model and an income-based model are developed as well. We found that our XAI-based model achieves a higher identification performance in terms of the area under the ROC curve than both the logistic regression-based model and the income-based model. For each rural household, the odds of being identified as deeply poor are obtained. Additionally, multidimensional household characteristics associated with deep poverty are specified and ranked for each poor household, while ordinary feature ranking methods can only provide ranking results for poor households as a whole. Taking all poor households into consideration, we found that common important characteristics that can be used to identify deeply poor households include household income, disability, village attributes, lack of funds, labor force, disease, and number of household members, which are validated by mutual information analysis. In conclusion, our XAI-based model can be used to identify deep poverty and specify key household characteristics associated with deep poverty for individual households, facilitating the development of new targeted poverty reduction strategies.
Strategic Sustainable Development in International Sport Organisations: A Delphi Study
Authors: Glibo Iva , Misener Laura , Koenigstorfer Joerg
Published: August 2022

The study aims to explore the consensus-level strategic priorities for sustainable development from the perspective of decision makers in organisations responsible for governing international sport and how they cluster within the Framework for Strategic Sustainable Development. We employed the three-round Delphi study with decision makers from international sport organisations. Based on the 29 semi-structured interviews in the first round, we inductively generated items for questionnaires for the subsequent two rounds. The process yielded 20 items representing strategic priorities determined by 20 experts in the last round. The highest ranked item was normative change, in which sustainability is prioritised throughout all organisational strategies and actions. Moreover, planned efforts that are part of a long-term strategy and embedding sustainability requirements at the bidding phase of sport events were considered with high priority. The 20 items clustered into four out of five levels of the Framework for Strategic Sustainable Development, namely system, success, strategic guidelines and actions. No items could be assigned to the framework’s tool level, potentially indicating gaps of strategic consideration. The findings from the Delphi study add a forecasting element to the research and practice of strategic sustainability in the management of sport by revealing consensus-level strategic priorities for the future.
Drivers of Environmental Conservation Agriculture in Sado Island, Niigata Prefecture, Japan
Authors: Maharjan Keshav Lall , Gonzalvo Clarisse Mendoza , Aala Wilson Jr. Florendo
Published: August 2022

Sado Island in the Niigata prefecture in Japan is one of the first Globally Important Agricultural Heritage Systems (GIAHS) among developed countries and has since been involved in environmental conservation agriculture (ECA). While ECA is still in its early stage in Japan, it has proven to be effective in mitigating climate change in the agricultural sector; hence, this study aimed to identify drivers of ECA among Sado Island paddy farmers. The data revealed the prevalence of farmers’ cognitive dissonance between ECA and its mitigating effects on climate change. Our findings confirmed the importance of perceived GIAHS involvement in the continuation of ECA. In addition, other identified drivers of ECA fall either on a macro-level (i.e., farmers’ awareness of their role in improving their environment) or micro-level (i.e., farmers’ differing farm optimizations). These perspectives highlighted the altruistic nature of the Sado Island ECA paddy farmers by valuing the improvement of their local and global environment as their main reason to continue ECA, whereas their various farm management optimizations support this observed farmer altruism by providing avenues to increase yield with only a moderate paddy land area. This study highlights the need to continuously develop sustainable strategies to maintain and improve a positive farmer mindset towards ECA.
Neighbor-Companion or Neighbor-Beggar? Estimating the Spatial Spillover Effects of Fiscal Decentralization on China’s Carbon Emissions Based on Spatial Econometric Analysis
Authors: Xu Xianpu , Li Shan
Published: August 2022

China’s rapid economic growth is associated with huge energy consumption and high carbon dioxide (CO2) emissions. Although the environmental effect of fiscal decentralization (FD) has been widely reported, its impact on CO2 is still a controversial subject. In this context, based on the panel data for China’s 30 provinces during 2003–2019, this paper uses a spatial autoregressive model to investigate the spatial spillover effects of revenue and expenditure decentralization on CO2 emissions, respectively. The results show that: (1) CO2 emissions exhibit spatial dependence, indicating that the rise of CO2 emissions in the region can lead to the rise of it in neighboring regions. (2) Both revenue and expenditure decentralization have significant positive spatial spillover effects on CO2 emissions, implying that higher FD in the province can significantly accelerate CO2 emissions in neighboring provinces. (3) There exists regional heterogeneity in the spatial spillover effect of FD on CO2 emissions. (4) Foreign direct investment (FDI) and technological innovation (R&D) can effectively mitigate the adverse effect of FD on CO2 emissions. (5) Industrial structure and human capital can significantly inhibit CO2 emissions, while economic development cannot. Therefore, it is important to optimize the system of fiscal decentralization and strengthen inter-regional cooperation on carbon emission reduction.
An Integrated Assessment of GIS-MCA with Logistics Analysis for an Assessment of a Potential Decentralized Bioethanol Production System Using Distributed Agricultural Residues in Thailand
Authors: Jusakulvijit Piradee , Bezama Alberto , Thrän Daniela
Published: August 2022

Crop residues derived from post-harvesting process have been problematic due to an on-field incineration, which caused air pollutants and greenhouse gas (GHG) emissions. An appropriate utilization of those biomasses can improve the environmental situation and provide a substitute for fossil fuels. Therefore, this study intends to analyze how left-over agricultural residues should be valorized in the decentralized bioethanol production configuration. With integrated techniques of geographical information system and multi-criteria analysis (GIS-MCA), we identify suitable locations for exhibiting decentralized sites matching the geographical backgrounds in each region. Under the precondition of a complete utilization of the agricultural residues, we found optimal installation numbers 71 units of decentralized production in total through suitability analysis. Conducting the location–allocation model, it is possible to determine production scales from the collectable spatially distributed biomass and transportation distances. Under the presumed conditions of installing 1 to 25 units, the logistics cost and total capital investment can reach USD 1.17–2.46 L−1 and USD 1.17–6.93 L−1, respectively. The results from examining the technical potential and economic feasibility aspects are key to designing decentralized bioethanol production facilities and maximizing the utilization of agricultural residues in Thailand.
Shared Cycling Demand Prediction during COVID-19 Combined with Urban Computing and Spatiotemporal Residual Network
Authors: Cao Yi , Wang Yixiao
Published: August 2022

The regularity and demand predictions of shared cycling are very necessary and challenging for the management and development of urban pedestrian and bicycle traffic. The bicycle-sharing system has the problem of spatial and temporal demand fluctuations and presents a very complex nonlinear regularity. The demand for shared bicycles is affected by many factors, including time, space, weather and the situation of COVID-19. This study proposes a new bicycle-sharing demand forecasting model (USTARN) based on the impact of COVID-19, which combines urban computing and spatiotemporal attention residual network. USTARN consists of two parts. In the first part, a spatiotemporal attention residual network model is established to learn the temporal correlation and spatial correlation of shared bicycle demand. The temporal characteristic branches of each spatial small region are trained, respectively, to predict the shared bicycle demand in batches in different regions and periods according to the historical data. In order to improve the prediction accuracy of the model, the second part of the model adjusts and redistributes the prediction results of the first part by learning other information of the city, such as the severity of COVID-19, weather, temperature, wind speed and holidays. It can predict the demand for shared bicycles in different urban areas in different periods and different severities of COVID-19. This study uses the order data of shared bicycles during the period of COVID-19 in 2020 obtained from the open data platform of Shenzhen municipal government as verification, analyzes the spatiotemporal regularity of the system demand and discusses the impact of the number of newly diagnosed patients and the daily minimum temperature on the demand for shared bicycles. The results show that USTARN can fully reflect time, space, the epidemic situation, weather and temperature, and the prediction results of the impact of wind speed and other factors on the demand for shared bicycles are better than the classical methods.
Intuitionistic Fuzzy Topology Based on Intuitionistic Fuzzy Logic
Authors: Sayed Osama R. , Aly Ayman A. , Zhang Shaoyu
Published: August 2022

There are many symmetries in intuitionistic fuzzifying topology. In the present paper, the notion of intuitionistic fuzzifying topology as an extension of fuzzifying topology and a preliminary of the research on bi-intuitionistic fuzzy topology is introduced. A theory of intuitionistic fuzzy topology with the semantic method of intuitionistic fuzzy logic is established.
Robust Sparse Reduced-Rank Regression with Response Dependency
Authors: Liu Wenchen , Liu Guanfu , Tang Yincai
Published: August 2022

In multiple response regression, the reduced rank regression model is an effective method to reduce the number of model parameters and it takes advantage of interrelation among the response variables. To improve the prediction performance of the multiple response regression, a method for the sparse robust reduced rank regression with covariance estimation(Cov-SR4) is proposed, which can carry out variable selection, outlier detection, and covariance estimation simultaneously. The random error term of this model follows a multivariate normal distribution which is a symmetric distribution and the covariance matrix or precision matrix must be a symmetric matrix that reduces the number of parameters. Both the element-wise penalty function and row-wise penalty function can be used to handle different types of outliers. A numerical algorithm with a covariance estimation method is proposed to solve the robust sparse reduced rank regression. We compare our method with three recent reduced rank regression methods in a simulation study and real data analysis. Our method exhibits competitive performance both in prediction error and variable selection accuracy.
The kth Local Exponent of Doubly Symmetric Primitive Digraphs with d Loops
Authors: Chen Danmei
Published: August 2022

Let D be a primitive digraph of order n. The exponent of a vertex x in V(D) is denoted γD(x), which is the smallest integer q such that for any vertex y, there is a walk of length q from x to y. Let V(D)={v1,v2,⋯,vn}. We order the vertices of V(D) so that γD(v1)≤γD(v2)≤⋯≤γD(vn) is satisfied. Then, for any integer k satisfying 1≤k≤n, γD(vk) is called the kth local exponent of D and is denoted by expD(k). Let DSn(d) represent the set of all doubly symmetric primitive digraphs with n vertices and d loops, where d is an integer such that 1≤d≤n. In this paper, we determine the upper bound for the kth local exponent of DSn(d), where 1≤k≤n. In addition, we find that the upper bound for the kth local exponent of DSn(d) can be reached, where 1≤k≤n.
Some Fuzzy Inequalities for Harmonically s-Convex Fuzzy Number Valued Functions in the Second Sense Integral
Authors: Macías-Díaz Jorge E. , Khan Muhammad Bilal , Alrweili Hleil , Soliman Mohamed S.
Published: August 2022

Many fields of mathematics rely on convexity and nonconvexity, especially when studying optimization issues, where it stands out for a variety of practical aspects. Owing to the behavior of its definition, the idea of convexity also contributes significantly to the discussion of inequalities. The concepts of symmetry and convexity are related and we can apply this because of the close link that has grown between the two in recent years. In this study, harmonic convexity, also known as harmonic s-convexity for fuzzy number valued functions (F-NV-Fs), is defined in a more thorough manner. In this paper, we extend harmonically convex F-NV-Fs and demonstrate Hermite–Hadamard (H.H) and Hermite–Hadamard Fejér (H.H. Fejér) inequalities. The findings presented here are summaries of a variety of previously published studies.
Symmetry in Acid-Base Chemistry
Authors: Raczyńska Ewa D.
Published: August 2022

Most organic molecules, including natural products, drugs, and toxicants, contain functional groups that display acid-base properties [...]
Multi-Label Attribute Reduction Based on Neighborhood Multi-Target Rough Sets
Authors: Zheng Wenbin , Li Jinjin , Liao Shujiao , Lin Yidong
Published: August 2022

The rough set model has two symmetry approximations called upper approximation and lower approximation, which correspond to a concept’s intension and extension, respectively. Multi-label learning enforces the rough set model, which wants to be applied considering the correlations among labels, while the target concept should not be limited to only one. This paper proposes a multi-target model considering label correlation (Neighborhood Multi-Target Rough Sets, NMTRS) and proposes an attribute reduction approach based on NMTRS. First, some definitions of NMTRS are introduced. Second, some properties of NMTRS are discussed. Third, some discussion about the attribute significance measure is given. Fourth, the attribute reduction approaches based on NMTRS are proposed. Finally, the efficiency and validity of the designed algorithms are verified by experiments. The experiments show that our algorithm shows considerable performance when compared to state-of-the-art approaches.
Against All Odds: How Eindhoven Emerged as a Deeptech Ecosystem
Authors: Romme A. Georges L.
Published: August 2022

The Brainport-Eindhoven region has developed into a leading location for deeptech entrepreneurship in Europe. Against all odds, it has transformed itself from a region that heavily depended on the multinational company Philips, into a diverse and fast-growing deeptech ecosystem. While this success has not gone unnoticed, there is not yet a clear account of how and why the Eindhoven region emerged as a global hotspot for deeptech innovation and entrepreneurship. Moreover, such an account might provide an exemplary model of a collaborative ecosystem, one that provides an alternative to the “winner-takes-all” entrepreneurial culture of Silicon Valley. This essay explores the performance of the Eindhoven region in terms of three structural conditions. First, the focus on deeptech R&D and entrepreneurship appears to be deeply rooted in the region’s history as well as strong competencies in systems engineering, design thinking, and multidisciplinary collaboration. Second, a collaborative approach to regional policy gives industrial, academic, and governmental actors an equivalent position in its “triple helix” governance. Finally, the Eindhoven region benefits from a systemic approach toward co-locating R&D and entrepreneurial activities on five campuses. Overall, the huge complexity of deeptech systems and products apparently requires a truly collaborative approach at all levels of the entrepreneurial ecosystem.
Peritumoral Brain Edema in Relation to Tumor Size Is a Variable That Influences the Risk of Recurrence in Intracranial Meningiomas
Authors: Frati Alessandro , Armocida Daniele , Arcidiacono Umberto Aldo , Pesce Alessandro , D’Andrea Giancarlo , Cofano Fabio , Garbossa Diego , Santoro Antonio
Published: August 2022

Peritumoral brain edema (PBE) is common in intracranial meningiomas (IM) and can increase their morbidity. It is not uncommon for a neurosurgeon to confront meningiomas with a large proportion of PBE independently from the site and size of the contrast-enhancing lesion with increased surgical risks. We performed a retrospective review of 216 surgically-treated patients suffering from IM. We recorded clinical, biological, and radiological data based on the rate of tumor and edema volume and divided the patients into a group with high Edema/Tumor ratio and a group with a low ratio. We investigated how the ratio of edema/lesion may affect the outcome. Multivariate analysis was performed for the two groups. Smokers were found to be more likely to belong to the high-rate group. The edema/tumor ratio did not affect the surgical radicality; however, independently of the biological sub-type, WHO grading, and EOR, a higher frequency of recurrence is shown in patients with a high edema/tumor ratio (70.5% vs. 8.4%. p < 0.01). There is evidence to suggest that the blood-brain barrier (BBB) damage from smoke could play a role in an increased volume of PBE. The present study demonstrates that IMs showing a high PBE ratio to tumor volume at diagnosis are associated with a smoking habit and a higher incidence of recurrence independently of their biological type and grading.
Determinants of Cocoa Farmers’ Compliance with Agrochemical Safety Precautions in Ogun and Osun States, Nigeria
Authors: Oyekale Abayomi Samuel
Published: August 2022

Cocoa is one of the major cash crops in Nigeria and its production is directly related to the effective utilization of agrochemicals. This paper analysed the factors influencing cocoa farmers’ compliance with agrochemical safety regulations. The data were collected from 326 cocoa farmers from Ogun and Osun states, using multi-stage sampling procedures. The data were analysed with Principal Component Analysis (PCA) and an Endogenous Tobit Regression model. The results showed that majority of the farmers were primarily growing cocoa and average ownership of personal protective equipment (PPE) was less than two. Awareness of manufacturers’ instructions was high for insecticides and fungicides, while majority of the farmers were not eating or drinking while handling agrochemicals. Safety compliance indicators were significantly influenced (p < 0.10) by farmers’ ownership of PPE, education, age, awareness of manufacturers’ safety instructions and health status. It was concluded that utilization of PPE was very low among the farmers and efforts to facilitate safety training on the use of different agrochemicals will facilitate safety compliance through proper understanding of manufacturers’ instructions.
Fibrinogenolysis in Venom-Induced Consumption Coagulopathy after Viperidae Snakebites: A Pilot Study
Authors: Valenta Jiri , Hlavackova Alzbeta , Stach Zdenek , Stikarova Jana , Havlicek Marek , Michalek Pavel
Published: August 2022

Envenomations that are caused by Viperidae snakebites are mostly accompanied by venom-induced consumption coagulopathy (VICC) with defibrination. The clinical course of VICC is well described; however, reports about its detailed effects in the hemocoagulation systems of patients are sparse. In this pilot study, we prospectively analyzed the changes in plasma fibrinogen that were caused by the envenomation of six patients by five non-European Viperidae snakes. Western blot analysis was employed and fibrinogen fragments were visualized with the use of specific anti-human fibrinogen antibodies. All of the studied subjects experienced hypo- or afibrinogenemia. The western blot analysis demonstrated fibrinogenolysis of the fibrinogen chains in all of the cases. Fibrinogenolysis was considered to be a predominant cause of defibrination in Crotalus, Echis, and Macrovipera envenomation; while, in the cases of VICC that were caused by Atheris and Calloselasma envenomation, the splitting of the fibrinogen chains was present less significantly.
Non-Proteinogenic Amino Acid β-N-Methylamino-L-Alanine (BMAA): Bioactivity and Ecological Significance
Authors: Koksharova Olga A. , Safronova Nina A.
Published: August 2022

Research interest in a non-protein amino acid β-N-methylamino-L-alanine (BMAA) arose due to the discovery of a connection between exposure to BMAA and the occurrence of neurodegenerative diseases. Previous reviews on this topic either considered BMAA as a risk factor for neurodegenerative diseases or focused on the problems of detecting BMAA in various environmental samples. Our review is devoted to a wide range of fundamental biological problems related to BMAA, including the molecular mechanisms of biological activity of BMAA and the complex relationships between producers of BMAA and the environment in various natural ecosystems. At the beginning, we briefly recall the most important facts about the producers of BMAA (cyanobacteria, microalgae, and bacteria), the pathways of BMAA biosynthesis, and reliable methods of identification of BMAA. The main distinctive feature of our review is a detailed examination of the molecular mechanisms underlying the toxicity of BMAA to living cells. A brand new aspect, not previously discussed in any reviews, is the effect of BMAA on cyanobacterial cells. These recent studies, conducted using transcriptomics and proteomics, revealed potent regulatory effects of BMAA on the basic metabolism and cell development of these ancient photoautotrophic prokaryotes. Exogenous BMAA strongly influences cell differentiation and primary metabolic processes in cyanobacteria, such as nitrogen fixation, photosynthesis, carbon fixation, and various biosynthetic processes involving 2-oxoglutarate and glutamate. Cyanobacteria were found to be more sensitive to exogenous BMAA under nitrogen-limited growth conditions. We suggest a hypothesis that this toxic diaminoacid can be used by phytoplankton organisms as a possible allelopathic tool for controlling the population of cyanobacterial cells during a period of intense competition for nitrogen and other resources in various ecosystems.
Toxigenicity of F. graminearum Residing on Host Plants Alternative to Wheat as Influenced by Environmental Conditions
Authors: Janaviciene Sigita , Suproniene Skaidre , Kadziene Grazina , Pavlenko Romans , Berzina Zane , Bartkevics Vadims
Published: August 2022

Fusarium graminearum is an important pathogen that causes Fusarium head blight (FHB) in several cereal crops worldwide. The potential of this pathogen to contaminate cereals with trichothecene mycotoxins presents a health risk for both humans and animals. This study aimed to evaluate the potential of different trichothecene genotypes of F. graminearum isolated from an alternative host plant to produce mycotoxins under different spring wheat grain incubation conditions. Fourteen F. graminearum strains were isolated from seven alternative host plants and identified as 3-acetyl-deoxynivalenol (3-ADON) and 15-acetyl-deoxynivalenol (15-ADON) genotypes. These strains were cultivated on spring wheat grains at 25 °C and 29 °C for 5 weeks. The mycotoxins produced were analysed with a high-performance liquid chromatograph (HPLC) coupled to a Thermo Scientific TSQ Quantiva MS/MS detector. The obtained results showed that the F. graminearum strains from alternative host plants could produce nivalenol (NIV), deoxynivalenol (DON), fusarenon-X (FUS-X), 3-ADON, deoxynivalenol-3-ß-d-glucoside (D3G), 15-ADON, and zearalenone (ZEA). F. graminearum strains produced DON and ZEA under both temperatures, with the mean concentrations varying from 363 to 112,379 µg kg−1 and from 1452 to 44,816 µg kg−1, respectively. Our results indicated the possible role of dicotyledonous plants, including weeds, as a reservoir of inoculum sources of F. graminearum-induced Fusarium head blight, associated with the risk of mycotoxin contamination in spring wheat.