bluuebunny/crossref_metadata_2025 huggingface dataset:
ROBINA: Rotational Orbit-Based Inter-Node Adjustment for Acoustic Routing Path in the Internet of Underwater Things (IoUTs)
Authors: Draz Umar , Yasin Sana , Ali Tariq , Ali Amjad , Faheem Zaid Bin , Zhang Ning , Jamal Muhammad Hasan , Suh Dong-Young
Published: September 2021

The Internet of Underwater Things (IoUTs) enables various underwater objects be connected to accommodate a wide range of applications, such as oil and mineral exportations, disaster detection, and tracing tracking systems. As about 71% of our earth is covered by water and one-fourth of the population lives around this, the IoUT expects to play a vital role. It is imperative to pursue reliable communication in this vast domain, as human beings’ future depends on water activities and resources. Therefore, there is a urgent need for underwater communication to be reliable, end-to-end secure, and collision/void node-free, especially when the routing path is established between sender and sonobuoys. The foremost issue discussed in this area is its routing path, which has high security and bandwidth without simultaneous multiple reflections. Short communication range is also a problem (because of an absence of inter-node adjustment); the acoustic signals have short ranges and maximum-scaling factors that cause a delay in communication. Therefore, we proposed Rotational Orbit-Based Inter Node Adjustment (ROBINA) with variant Path-Adjustment (PA-ROBINA) and Path Loss (PL-ROBINA) for IoUTs to achive reliable communication between the sender and sonobuoys. Additionally, the mathematical-based path loss model was discussed to cover the PL-ROBINA strategy. Extensive simulations were conducted with various realistic parameters and the results were compared with state-of-the-art routing protocols. Extensive simulations proved that the proposed routing scheme outperformed different realistic parameters; for example, packet transmission 45% increased with an average end-to-end delay of only 0.3% respectively. Furthermore, the transmission loss and path loss (measured in dB) were 25 and 46 dB, respectively, compared with other algorithms, for example, EBER2 54%, WDFAD-BDR 54%, AEDG 49%, ASEGD 55%, AVH-AHH-VBF 54.5%, and TANVEER 39%, respectively. In addition, the individual parameters with ROBINA and TANVEER were also compared, in which ROBINA achieved a 98% packet transmission ratio compared with TANVEER, which was only 82%.
Wavelength-Tunable, Ultra-Broadband, Biconical, Long-Period Fiber Grating Mode Converter Based on the Dual-Resonance Effect
Authors: Zheng Yu , Guo Huiyi , Feng Mao , Wang Zhi , Liu Yange
Published: September 2021

We demonstrated a wavelength-tunable, ultra-wideband, biconical, long-period fiber grating (BLPFG) mode converter in a two-mode fiber based on fusion taper technology and CO2 laser writing technology. Theoretical and experimental results show that after changing the diameter of the two-mode fiber by fusing and tapering, the dispersion turning point of the fiber is adjusted and wavelength-tunable broadband mode conversion is achieved efficiently. Theoretical simulation shows that the mode conversion bandwidth can cover the O + E + S + C band. In the experiment, we fabricated adiabatic tapers with cladding diameters of 113 μm and 121 μm and wrote gratings on these tapers to achieve dual-resonance coupling, thus realizing mode conversion from LP01 to LP11, with a 15 dB bandwidth of 148.8 nm from 1229.0 nm to 1377.8 nm and of 168.5 nm from 1319.7 nm to 1488.2 nm, respectively. As far as we know, this is the first time that fusion taper technology has been used to adjust the window of the dual-resonant coupling of an optical fiber. This work broadens the scope of application of the dual-resonance effect and proposes a general method for widening the bandwidth of a fiber grating with tunable wavelength.
Feasibility of Novel Rear-Side Mirage Deflection Method for Thermal Conductivity Measurements
Authors: Kim Gwantaek , Kim Moojoong , Kim Hyunjung
Published: September 2021

Among the noncontact measurement technologies used to acquire thermal property information, those that use the photothermal effect are attracting attention. However, it is difficult to perform measurements for new materials with different optical and thermal properties, owing to limitations of existing thermal conductivity measurement methods using the photothermal effect. To address this problem, this study aimed to develop a rear-side mirage deflection method capable of measuring thermal conductivity regardless of the material characteristics based on the photothermal effect. A thin copper film (of 20 µm thickness) was formed on the surfaces of the target materials so that measurements could not be affected by the characteristics of the target materials. In addition, phase delay signals were acquired from the rear sides of the target materials to exclude the influence of the pump beam, which is a problem in existing thermal conductivity measurement methods that use the photothermal effect. To verify the feasibility of the proposed measurement technique, thermal conductivity was measured for copper, aluminum, and stainless steel samples with a 250 µm thickness. The results were compared with literature values and showed good agreement with relative errors equal to or less than 0.2%.
The Effect of Synergistic Approaches of Features and Ensemble Learning Algorithms on Aboveground Biomass Estimation of Natural Secondary Forests Based on ALS and Landsat 8
Authors: Du Chunyu , Fan Wenyi , Ma Ye , Jin Hung-Il , Zhen Zhen
Published: September 2021

Although the combination of Airborne Laser Scanning (ALS) data and optical imagery and machine learning algorithms were proved to improve the estimation of aboveground biomass (AGB), the synergistic approaches of different data and ensemble learning algorithms have not been fully investigated, especially for natural secondary forests (NSFs) with complex structures. This study aimed to explore the effects of the two factors on AGB estimation of NSFs based on ALS data and Landsat 8 imagery. The synergistic method of extracting novel features (i.e., COLI1 and COLI2) using optimal Landsat 8 features and the best-performing ALS feature (i.e., elevation mean) yielded higher accuracy of AGB estimation than either optical-only or ALS-only features. However, both of them failed to improve the accuracy compared to the simple combination of the untransformed features that generated them. The convolutional neural networks (CNN) model was much superior to other classic machine learning algorithms no matter of features. The stacked generalization (SG) algorithms, a kind of ensemble learning algorithms, greatly improved the accuracies compared to the corresponding base model, and the SG with the CNN meta-model performed best. This study provides technical support for a wall-to-wall AGB mapping of NSFs of northeastern China using efficient features and algorithms.
Wavelength-Tunable L-Band High Repetition Rate Erbium-Doped Fiber Laser Based on Dissipative Four-Wave Mixing
Authors: Li Kai , Huang Qianqian , Jiang Junjie , Huang Zinan , Mou Chengbo
Published: September 2021

A wavelength-tunable high repetition rate (HRR) erbium-doped fiber laser in L-band based on dissipative four-wave mixing (DFWM) mechanism is demonstrated. The cavity can generate a single-soliton train and bound-soliton train with a fixed repetition rate of ~126 GHz, which is determined by the free spectral range of the intra-cavity Lyot filter. A wide wavelength-tuning operation can also be obtained by rotating the polarization controllers. The wavelength-tuning ranges of the HRR single-soliton state and HRR bound-soliton state are ~38.3 nm and ~22.6 nm, respectively. This laser provides useful references for the area of a wavelength-tunable fiber laser with high repetition rate. The laser may also find useful applications in high-speed communication, sensing, etc.
Small-Angle Particle Counting Coupled Photometry for Real-Time Detection of Respirable Particle Size Segmentation Mass Concentration
Authors: Zhang Rongrui , Zhao Heng
Published: September 2021

Respirable particulate matter air pollution is positively associated with SARS-CoV-2 mortality. Real-time and accurate monitoring of particle concentration changes is the first step to prevent and control air pollution from inhalable particles. In this research, a new light scattering instrument has been developed to detect the mass concentration of inhalable particles. This instrument couples the forward small-angle single particle counting method with the lateral group particle photometry method in a single device. The mass concentration of four sizes of inhalable particles in the environment can be detected simultaneously in a large area in real-time without using a particle impactor. Different from the traditional light scattering instrument, this new optical instrument can detect darker particles with strong light absorption, and the measurement results mainly depend on the particle size and ignore the properties of the particles. Comparative experiments have shown that the instrument can detect particles with different properties by simply calibrating the environmental density parameters, and the measurement results have good stability and accuracy.
Optical Angular Sensor for Space Applications
Authors: Dabsch Alexander , Rosenberg Christoph , Trimmel Majesa , Keplinger Franz
Published: September 2021

This paper describes a silicon/glass sensing structure for axial angle measurements. The presented optical angular sensor can statically measure the angle φ of any apparatus depending on the torsion of the optical component against the sensor housing. Core element of the sensor is an optical medium with an etched structure, which diffracts light from an LED according to the Fresnel equation. Two photodiodes, one for angle determination and one as reference, conduct the measurement. Hence, the signal splits up into two parts: one part transmits trough the optical system and the second part (the reflected wave) is used as reference signal. For self-referencing purposes, the wavelength spectrum of the LED has its maximum in the infrared regime near to the wavelength where silicon gets transparent (l~1000 nm). More precisely, torsion angle and light intensity show a dependency given by Tstot if a straight etching structure (refraction profile) is used. To avoid multiple reflections of light, a coating layer restricts the illuminated area in the optical medium. With this setting a resolution of 0.05-degree rotation angle has been achieved and by stacking the construction, the sensor can measure an angular range from 30° up to 270°.
A Novel Machine Learning-Based Methodology for Tool Wear Prediction Using Acoustic Emission Signals
Authors: Ferrando Chacón Juan Luis , Fernández de Barrena Telmo , García Ander , Sáez de Buruaga Mikel , Badiola Xabier , Vicente Javier
Published: September 2021

There is an increasing trend in the industry of knowing in real-time the condition of their assets. In particular, tool wear is a critical aspect, which requires real-time monitoring to reduce costs and scrap in machining processes. Traditionally, for the purpose of predicting tool wear conditions in machining, mathematical models have been developed to extract the information from the signal of sensors attached to the machines. To reduce the complexity of developing physical models, where an in-depth knowledge of the system being modelled is required, the current trend is to use machine-learning (ML) models based on data from the tool wear. The acoustic emission (AE) technique has been widely used to capture data from and understand the real-time condition of industrial assets such as cutting tools. However, AE signal interpretation and processing is rather complex. One of the most common features extracted from AE signals to predict the tool wear is the counts parameter, defined as the number of times that the amplitude of the signal exceeds a predefined threshold. A recurrent problem of this feature is to define the adequate threshold to obtain consistent wear prediction. Additionally, AE signal bandwidth is rather wide, and the selection of the optimum frequencies band for feature extraction has been pointed out as critical and complex by many authors. To overcome these problems, this paper proposes a methodology that applies multi-threshold count feature extraction at multiresolution level using wavelet packet transform, which extracts a redundant and non-optimal feature map from the AE signal. Next, recursive feature elimination is performed to reduce and optimize the vast number of predicting features generated in the previous step, and random forests regression provides the estimated tool wear. The methodology presented was tested using data captured when turning 19NiMoCr6 steel under pre-established cutting conditions. The results obtained were compared with several ML algorithms such as k-nearest neighbors, support vector machines, artificial neural networks and decision trees. Experimental results show that the proposed method can reduce the predicted root mean squared error by 36.53%.
Experimental Study on the Relationship between the Velocity of Surface Movements and Tilting Rate in Pre-Failure Stage of Rainfall-Induced Landslides
Authors: Xie Jiren , Uchimura Taro , Huang Chao , Maqsood Zain , Tian Jingli
Published: September 2021

With the development of deformation measuring technology at slope surfaces, prediction methods for rainfall-induced landslides based on the surface movements and tilting of slopes in the pre-failure stage have been recognized as a promising technique for risk reduction of slope failure triggered by rainfall. However, the correlation and possible mechanism for these prediction methods were rarely discussed. In this study, the comparison between the prediction methods of slope failure based on the time history of surface displacements and tilting in the acceleration stage was carried out by conducting a series of laboratory tests and field tests under rainfall, in which the movements and tilting behaviors at the slope surface were measured. The results show that the predicted failure time of tested slopes obtained by different prediction methods is consistent, and the correlation between these landslide prediction methods were also detected. A proportional relationship between the velocity of surface displacements and tilting rate was observed, and a possible mechanism for the sliding behavior was discussed based on this linear relationship as well. In addition, an expression for the linear relationship between the rate of the surface tilting and displacement was also established in this study, and the results could have significance for the understanding of the sliding behavior in the failure process in rainfall-induced landslides.
Wavelet Ridges in EEG Diagnostic Features Extraction: Epilepsy Long-Time Monitoring and Rehabilitation after Traumatic Brain Injury
Authors: Obukhov Yury Vladimirovich , Kershner Ivan Andreevich , Tolmacheva Renata Alekseevna , Sinkin Mikhail Vladimirovich , Zhavoronkova Ludmila Alekseevna
Published: September 2021

Interchannel EEG synchronization, as well as its violation, is an important diagnostic sign of a number of diseases. In particular, during an epileptic seizure, such synchronization occurs starting from some pairs of channels up to many pairs in a generalized seizure. Additionally, for example, after traumatic brain injury, the destruction of interneuronal connections occurs, which leads to a violation of interchannel synchronization when performing motor or cognitive tests. Within the framework of a unified approach to the analysis of interchannel EEG synchronization using the ridges of wavelet spectra, two problems were solved. First, the segmentation of the initial data of long-term monitoring of scalp EEG with various artifacts into fragments suspicious of epileptic seizures in order to reduce the total duration of the fragments analyzed by the doctor. Second, assessments of recovery after rehabilitation of cognitive functions in patients with moderate traumatic brain injury. In the first task, the initial EEG was segmented into fragments in which at least two channels were synchronized, and by the adaptive threshold method into fragments with a high value of the EEG power spectral density. Overlapping in time synchronized fragments with fragments of high spectral power density was determined. As a result, the total duration of the fragments for analysis by the doctor was reduced by more than 60 times. In the second task, the network of phase-related EEG channels was determined during the cognitive test before and after rehabilitation. Calculation-logical and spatial-pattern cognitive tests were used. The positive dynamics of rehabilitation was determined during the initialization of interhemispheric connections and connections in the frontal cortex of the brain.
Instructor’s Rating of Driver’s Performance during an Anti-Lock Braking Exercise on a Closed-Road Course
Authors: Mims Lauren , Brooks Johnell O. , Jenkins Timothy M. , Jenkins Casey , Neczek Joseph , Isley Donnie , Bormann Allison , Hayes Laura , Gubitosa Daniel
Published: September 2021

Rear-end crashes are a common crash scenario, which contribute to many traffic related injuries and fatalities. A performance driving center offers adult car control classes focused on defensive driving skills, which include both classroom and behind-the-wheel instruction on a closed-road course. One focus of the class is activation of the anti-lock braking system (ABS), which was designed to help drivers during emergency braking situations. In the classroom, participants learn what ABS is as well as how and when it functions. On the closed-road course, participants learn how to activate ABS and how the system feels when it is activated. The goal of this study was to understand how knowledge of and experience with ABS prior to the class relates to a driver’s ability to activate ABS. The participants’ ability to activate ABS was evaluated by the driving instructor using a behaviorally anchored rating scale. Participants completed a survey before and after the class to gain knowledge of and experience with ABS. The results of the study showed that participants who previously knew what ABS felt like or had prior practice/training activating ABS performed significantly better activating ABS than those who simply knew what ABS means or had previously experienced ABS activation during their first of multiple attempts.
Effects of the Traditional Mediterranean Diet in Childhood Recurrent Acute Rhinosinusitis
Authors: Calatayud-Sáez Fernando M. , Calatayud Blanca , Calatayud Ana
Published: September 2021

Introduction: There are more and more studies that demonstrate the anti-inflammatory effects of the traditional Mediterranean diet (TMD). The aim of the study was to assess the effects of an intervention with the TMD in patients with recurrent acute and chronic rhinosinusitis. Material and Methods: We performed a pretest–posttest comparison study in 114 patients (56 girls and 58 boys) aged one to five years who had three or more acute rhinosinusitis episodes in the period of 1 year. They were included for a year in the nutritional program “Learning to eat from the Mediterranean”. The anthropometric, clinical, and therapeutic characteristics were studied. Results: All the studied indicators showed a positive and statistically significant evolution. Of the patients, 53.5% did not have any episode of acute rhinosinusitis, and 26.3% had only one, compared to the 3.37 they had on average in the previous year. The use of antibiotics decreased by 87.6%. The degree of satisfaction of the families was very high. The Mediterranean Diet Quality Index (KIDMED) that assesses the quality of the TMD rose from 7.7 to 11 points. Conclusions: The adoption of the TMD could have promising effects in the prevention and treatment of recurrent acute and chronic rhinosinusitis, limiting the pharmacological and surgical intervention in many of these patients.
Data Co-Operatives through Data Sovereignty
Authors: Calzada Igor
Published: September 2021

Against the widespread assumption that data are the oil of the 21st century, this article offers an alternative conceptual framework, interpretation, and pathway around data and smart city nexus to subvert surveillance capitalism in light of emerging and further promising practical cases. This article illustrates an open debate in data governance and the data justice field related to current trends and challenges in smart cities, resulting in a new approach advocated for and recently coined by the UN-Habitat programme ‘People-Centred Smart Cities’. Particularly, this feature article sheds light on two intertwined notions that articulate the technopolitical dimension of the ‘People-Centred Smart Cities’ approach: data co-operatives and data sovereignty. Data co-operatives are emerging as a way to share and own data through peer-to-peer (p2p) repositories and data sovereignty is being claimed as a digital right for communities/citizens. Consequently, this feature article aims to open up new research avenues around ‘People-Centred Smart Cities’ approach: First, it elucidates how data co-operatives through data sovereignty could be articulated as long as co-developed with communities connected to the long history and analysis of the various forms of co-operatives (technopolitical dimension). Second, it prospectively anticipates the city–regional dimension encompassing data colonialism and data devolution.
Some New Tests of Conformity with Benford’s Law
Authors: Cerqueti Roy , Lupi Claudio
Published: September 2021

This paper presents new perspectives and methodological instruments for verifying the validity of Benford’s law for a large given dataset. To this aim, we first propose new general tests for checking the statistical conformity of a given dataset with a generic target distribution; we also provide the explicit representation of the asymptotic distributions of the relevant test statistics. Then, we discuss the applicability of such novel devices to the case of Benford’s law. We implement extensive Monte Carlo simulations to investigate the size and the power of the introduced tests. Finally, we discuss the challenging theme of interpreting, in a statistically reliable way, the conformity between two distributions in the presence of a large number of observations.
Trading Macro-Cycles of Foreign Exchange Markets Using Hybrid Models
Authors: Ling Joseph Zhi Bin , Tsui Albert K. , Zhang Zhaoyong
Published: September 2021

Most existing studies on forecasting exchange rates focus on predicting next-period returns. In contrast, this study takes the novel approach of forecasting and trading the longer-term trends (macro-cycles) of exchange rates. It proposes a unique hybrid forecast model consisting of linear regression, multilayer neural network, and combination models embedded with technical trading rules and economic fundamentals to predict the macro-cycles of the selected currencies and investigate the predicative power and market timing ability of the model. The results confirm that the combination model has a significant predictive power and market timing ability, and outperforms the benchmark models in terms of returns. The finding that the government bond yield differentials and CPI differentials are the important factors in exchange rate forecasts further implies that interest rate parity and PPP have strong influence on foreign exchange market participants.
Green Attributes in Young Consumers’ Purchase Intentions: A Cross-Country, Cross-Product Comparative Study Using a Discrete Choice Experiment
Authors: Dinh Chi Thao , Uehara Takuro , Tsuge Takahiro
Published: September 2021

As consumption behavior is one of the key human activities destabilizing the Earth system, green consumption is expected to increase. However, although consumers often show interest in green consumption, they tend to choose non-green alternatives. Presuming that one of the reasons for their inconsistency lies in the trade-offs between green attributes and other attributes (e.g., brand, performance, and price), this study adopted a discrete choice experiment to understand how green attributes play a role in consumers’ purchase decisions. To obtain a deeper understanding, the study conducted a cross-country (young Japanese [n = 370] and Vietnamese [n = 403] consumers) and product (water bottles and T-shirts) comparative analysis. The findings showed that for both products, Japanese respondents were less appreciative of green attributes in both relative and absolute terms than Vietnamese respondents. Furthermore, the marginal willingness to pay (MWTP) for a low environmental impact was the highest among the other attributes in both products for Vietnamese respondents, while this was not the case for Japanese respondents. Utilizing the findings obtained from the conditional logit models and MWTP, this study proposes several policy implications for the promotion of green purchases suitable for each country’s unique situation.
Effects of Flipped Learning Approaches on Students’ Learning Performance in Software Engineering Education
Authors: Lin Yen-Ting
Published: September 2021

Software engineering education plays an important role in keeping students educated with software technologies, processes, and practices that are needed by industries. Nevertheless, the nature of software engineering learning activities in traditional classrooms is limited in scope and time, making it more difficult to achieve a proper balance between theory and practice and address industrial demands. This makes scant provision for assisting students in keeping their software engineering knowledge current. To support software engineering education, flipped learning is a suitable strategy. Prior studies have shown that students’ perceptions in flipped learning environments are better than those in traditional learning environments. Nevertheless, in flipped learning, students may not have sufficient ability to conduct learning out of class. Therefore, the flipped learning strategy should aim to meet the needs of students to ensure that they get the appropriate support or feedback during the learning process before the class. The aim of this study was to propose a flipped learning diagnosis approach to promote students’ learning out of class in the flipped classroom. To explore students’ learning performance in software engineering courses, three classes of students were invited to learn with three different learning approaches (traditional learning approach, flipped learning approach, and flipped learning diagnosis approach). The results showed that the students who learned with the flipped learning diagnosis approach outperformed those students who learned with the flipped learning approach or the traditional learning approach.
Redesigning the Municipal Solid Waste Supply Chain Considering the Classified Collection and Disposal: A Case Study of Incinerable Waste in Beijing
Authors: Yang Xiaoyu , Guo Xiaopeng , Yang Kun
Published: September 2021

The output of municipal solid waste is growing rapidly, which has brought tremendous pressure to urban development. The supply chain of municipal solid waste (MSW) in China mainly contains three processes: collection, transportation, and disposal. The waste is sorted at the collection and disposed of according to the classification. However, it is mixed at the transportation stage. Mixed transportation remixes the separately collected waste, which seriously affects the disposal effect. The supply chain of MSW urgently needs to be redesigned to improve the MSW disposal effect. First of all, on the ground of the waste treatment situation, we redesigned the supply chain of MSW in China. Secondly, combined with the redesign of the MSW supply chain, this paper established the function allocation model for collection stations, making a collection station only gather one type of waste, and built the transportation path planning model for vehicles, reducing the impact of waste storage on residents. Finally, based on the data of Xuanwu District in Beijing, the supply chain redesigning practical example of incinerable waste was given. The supply chain redesigning model in this paper not only makes full use of the existing infrastructure but also improves the disposal effect of waste. The supply chain redesigning model has practical application value.
Corporate Social Responsibility and the Renewable Energy Development in the Baltic States
Authors: Strielkowski Wadim , Tarkhanova Elena , Baburina Natalia , Streimikis Justas
Published: September 2021

Recently, the approaches of the Corporate Social Responsibility (CSR) in the renewable energy development have changed with the new global approach to sustainability. Today, CSR is an evolving and dominating business practice that integrates sustainable development into a company’s business model. The main focus of our paper is on the public relations of corporate social responsibility in renewable energy development. We show that a proper approach to public relations and resulting communication and dissemination of products and results should be sustained. This paper assesses the new pathways for executing public relations for CSR with relation to the renewable energy projects. The study analyses the impact of corporate social responsibility on energy companies, which are expected to make a positive contribution to the development of sustainable energy. We use both the overview of the theoretical concepts and literature as well as analyze the case of the “old” and “new” European Union Member countries represented by the Baltic States that yield many similarities but differ in their economic development to show the best practices of promoting CSR in sustainable energy development. Our results demonstrate that the implementation of corporate social responsibility can help to create more ethical and conscious sustainable companies and to build better relationships with the environmentally engaged citizens and loyal customers who are also concerned about the environment, health and well-being of their communities.
A Study into the Availability, Costs and GHG Reduction in Drop-In Biofuels for Shipping under Different Regimes between 2020 and 2050
Authors: van der Kroft Douwe F. A. , Pruyn Jeroen F. J.
Published: September 2021

In this study, various scenarios were developed that correspond to estimations of future biomass availability and biofuel demand from the maritime industry. These marine biofuel demand scenarios were based on the Greenhouse Gas (GHG) reduction targets of the Renewable Energy Directive II (RED II) and the International Maritime Organization (IMO). A multi-objective Mixed Integer Linear Programming (MILP) model was developed which is used to optimize the Well-to-Tank (WtT) phases of each studied scenario. This resulted in an overview of the most feasible use of feedstocks, deployment of new conversion technologies and trade flows between regions. Additionally, the results provided insight into the costs and emission reduction potential of marine biofuels. By analyzing the results from this study, improved insight into the potential of drop-in biofuels for reaching the proposed emission reduction targets for the maritime sector was developed. A trade-off between costs and emissions was found to result in potential GHG reductions between 68–95% compared to Heavy Fuel Oil (HFO) for 800–2300 EUR/ton. More specifically, 80% GHG reduction compared to HFO can be achieved at fuel costs of between 900–1050 EUR/ton over the studied time period.
Shared Taxonomy for the Implementation of Responsible Innovation Approach in Industrial Ecosystems
Authors: Valackienė Asta , Nagaj Rafał
Published: September 2021

Symbolic narratives, such as an “ivory tower”, a “grey zone”, or a “black box” tell us about the gap between university and society, and academia and industry. Recently, they have been replaced by the Quadruple Helix model, which closes the gap by connecting four main stakeholders—government, university, industry, and society, into an innovation ecosystem. However, the roles of the different stakeholders are often blurred and difficult to define, and it is difficult to develop a basic approach to implement responsible innovations in industrial ecosystems in general. On the other hand, the interactions between stakeholder groups, especially universities and industry, are not sufficiently demonstrated in both scientific literature and empirical studies. We note that the responsible research and innovation (RRI) approach should facilitate a framework of shared taxonomy among stakeholders. By highlighting this situation, we follow the paradigm of emerging thinking and we seek to fill this knowledge gap theoretically and empirically. Therefore, in this study, we combined several strategies and perspectives. First, we conducted survey research concerning social capital in Poland and Lithuania to understand the impact of social capital and trust on stakeholder cooperation. Second, we conducted interviews with scientists who actively work to transfer knowledge into industry. Third, we utilized field notes from working experiences in research management. This work has theoretical and practical implications. The theoretical contribution of the paper demonstrates the construction of methodology based on emerging perspectives, and new theoretical insights, on professional discourses for implementing the responsible innovation approach in industrial ecosystems, by highlighting the commitments of main stakeholder groups. Practical input: our insights and empirical research will contribute toward sustainability policymaking and achieving substantial results in industrial ecosystems. The results indicate that if there is trust, then the government, companies, and society (in Poland and Lithuania) would be willing to cooperate with each other. However, there is a lack of trust and cooperation between universities and businesses. Stakeholders have become increasingly aware of the emergence of a science and industry cooperation as an open platform, enlarged with society and policies. They note the problem of making research public and transparent as part of a new mode of cooperation; however, they articulate RRI as a framework of shared taxonomy.
Farmers’ Perceived Vulnerability and Proactive versus Reactive Climate Change Adaptation in Chile’s Maule Region
Authors: Engler Alejandra , Rotman Marieke L. , Poortvliet P. Marijn
Published: September 2021

Changes in climatic conditions are unavoidable and irreversible and an early and effective adaptation in farming systems will be vital for resilient agriculture. Although the extant literature has described factors that explain climate change adaptation, the roles of proactive versus reactive adaptation related to perceived vulnerability are still underexplored. The aim of our study was to open a new angle of discussion by linking farmers’ perceptions of vulnerability with their adaptation response, and exploring the dynamic of such a relationship. Semi-structured interviews with farmers were held in the Maule Region of central Chile (n = 36). The interview included questions o about main agricultural challenges, perceptions of climate change and its impact, adaptation strategies, and perceptions of vulnerability, exposure, sensitivity, and ability to adapt. In order to interpret the interview data, a content analysis procedure was followed. The results indicate that farmers respond differently by either engaging in proactive or reactive adaptation behavior. Furthermore, the patterns of either proactive or reactive adaptation behavior can be explained by structural factors and social and human capital. While structural factors, such as production systems and financial capital, explain engaging in adaptation to climate change, social and human capital act as enhancing factors that explain proactive adaptation. Future policies on adaptation behavior should focus on promoting proactive forms of adaptation behavior by developing and enhancing social connections and access to information, as well as on the provision of financial schemes to enable efficient and effective adaptation within the agricultural sector.
Techno-Economic Assessment of Polysaccharide Extraction from Baobab: A Scale Up Analysis
Authors: Dimopoulou Maria , Offiah Vivian , Falade Kolawole , Smith Alan M. , Kontogiorgos Vassilis , Angelis-Dimakis Athanasios
Published: September 2021

This research studied the commercial exploitation of an indigenous African crop in order to formulate high value products, with a potential significant impact on the local economy. More specifically, the present work investigated the extraction of polysaccharides from baobab in a bench-scale unit, focusing on the overall yield and the techno-economic assessment of the extraction process. Preliminary technoeconomic analysis for two scenarios (with and without ethanol recycling) was performed to determine the economic viability of the process and the development of the baobab market both in Nigeria and the UK. A full economic analysis was undertaken for each of the two scenarios, considering all operating and capital costs, and the production cost of baobab polysaccharides was estimated based on a constant return on investment. Combining the operating cost with the average polysaccharide yield, the minimum profitable selling price in the UK was estimated to be between £23 and £35 per 100 g of polysaccharide, which is comparable to the commercial selling price of high purity polysaccharides. An assessment of a scaled-up plant was also performed under Nigerian conditions and the results showed that such an investment is potentially viable and profitable, with a minimum profitable selling price of £27 per 100 g, a value comparable to the UK-based scenarios.
Review of Research on Digital Supply Chain Management Using Network Text Analysis
Authors: Pyun Jebum , Rha Jin Sung
Published: September 2021

Studies that have examined the digital transformation’s association with supply chains have been actively conducted for over 10 years, and studies on digital supply chain management have been increasing. However, there is a lack of consensus on the definitions of or views about the digital supply chain; thus, researchers in the academic or industrial fields propound various concepts of digital supply chains, which results in confusion during the exchange of opinions or transmission of concepts in many cases. The purpose of this study is to identify the research trends from various articles on the digital supply chain that have been published so far, summarize and analyze the theories and concepts pertaining to it, and review future topics of research. Network text analysis was conducted by extracting information from unstructured text data to identify research trends. The results of the analysis showed that many studies have examined the digital supply chain in terms of sustainable management. “Sustainability” was the most influential word in the keyword network, and the digital transformation of supply chains is essential for the sustainable viability of firms in the era of Industry 4.0 and digital transformation. Many studies have focused on technology for big data analysis and the IoT as technologies to fulfill digital supply chains and maintained that COVID-19 has increased risk factors such as global supply chain disruptions, which is why global firms must monitor the supply chain in real time by securing end-to-end visibility and making corporate-level efforts to build a digital supply chain to instantly detect and deal with related risks. The common groups of keywords were related to “supply chain integration”, “resilience”, “digital technologies”, and “digital transformation”.
Population Flow Mechanism Study of Beijing-Tianjin-Hebei Urban Agglomeration from Industrial Space Supply Perspective
Authors: Chen Yuqi , Sun Zongyao , Cai Liangwa
Published: September 2021

The growing demographic dividend is declining worldwide due to global population shrinkage. However, with the enhancement of spatial connection, industry-oriented population flow is becoming more and more active. The floating demographic dividend will bring new opportunities to regional development. Population flow has become an important field of urban research. We selected the Beijing-Tianjin-Hebei urban agglomeration as the study area and conducted the study of the interaction relationship between population flow and industry space supply. Considering that it takes time for space supplies to be industrial entities and then to affect population flow, this study built a fixed-effects model with annual space supply and “t + 1” population flow to perform regression analysis. The main findings of the research can be concluded as below. The regional population flow was mainly rural population and floated mainly to rural areas. It is difficult to complete the urbanization of floating population through land urbanization due to China’s household registration system. The population flow is sensitive to industry space supply and its spatial development conditions. As the study area is an important global urban agglomeration and China’s political, economic, and cultural center, its regional population flow is representative and typical. Guiding its population flow to form a coordinated spatial and social network can provide scientific support for regional industry space supply and allocation, and can provide a reference for the development of other urban agglomerations.
Children and Youth Environmental Action: The Case of Children and Youth with Disabilities
Authors: Salvatore Chiara , Wolbring Gregor
Published: September 2021

Youth environmental activism is on the rise. Children and youth with disabilities are disproportionally impacted by environmental problems and environmental activism. They also face barriers towards participating in activism, many of which might also apply to their participation in environmental activism. Using a scoping review approach, we investigated the engagement with children and youth with disabilities by (a) academic literature covering youth environmental activism and their groups and (b) youth environmental activism group (Fridays For Future) tweets. We downloaded 5536 abstracts from the 70 databases of EBSCO-HOST and Scopus and 340 Fridays For Future tweets and analyzed the data using directed qualitative content analysis. Of the 5536 abstracts, none covered children and youth with disabilities as environmental activists, the impact of environmental activism or environmental problems such as climate change on children and youth with disabilities. Fourteen indicated that environmental factors ‘caused’ the ‘impairments’ in children and youth with disabilities. One suggested that nature could be beneficial to children and youth with disabilities. The tweets did not mention children and youth with disabilities. Our findings suggest the need for more engagement with children and youth with disabilities in relation to youth environmental activism and environmental challenges.
Sediment Organic Carbon Sequestration of Balkhash Lake in Central Asia
Authors: Liu Wen , Ma Long , Abuduwaili Jilili , Issanova Gulnura , Saparov Galymzhan
Published: September 2021

As an important part of the global carbon pool, lake carbon is of great significance in the global carbon cycle. Based on a study of the sedimentary proxies of Balkhash Lake, Central Asia’s largest lake, changes in the organic carbon sequestration in the lake sediments and their possible influence over the past 150 years were studied. The results suggested that the organic carbon in the sediments of Lake Balkhash comes mainly from aquatic plants. The organic carbon burial rate fluctuated from 8.16 to 30.04 g·m−2·a−1 and the minimum appeared at the top of the core. The organic carbon burial rate continues to decline as it has over the past 150 years. Global warming, higher hydrodynamic force, and low terrestrial input have not been conducive to the improvement of organic carbon sequestration in Balkhash Lake; the construction of a large reservoir had a greater impact on the sedimentary proxy of total organic carbon content, which could lead to a large deviation for environmental reconstruction. This is the first study to assess the sediment organic carbon sequestration using the modern sediments of Central Asia’s largest lake, which is of great scientific significance. The results contribute to an understanding of organic carbon sequestration in Central Asia and may provide a scientific basis for carbon balance assessment in regional and global scales.
The 4.0 Industry Technologies and Their Impact in the Continuous Improvement and the Organizational Results: An Empirical Approach
Authors: Arredondo-Méndez Víctor Hugo , Para-González Lorena , Mascaraque-Ramírez Carlos , Domínguez Manuel
Published: September 2021

This study analyses the relationships between the technologies of Industry 4.0, continuous improvement, and the business results. To carry out this study, 109 questionnaires to companies of different sectors were collected, but an indispensable condition to take into account was the fact that these companies develop themselves their logistics management. The analysis of the results obtained through the Partial Least Squares (PLS) methodology argues that there is a positive relationship between 4.0 Industry and continuous improvement processes, as well as between continuous improvement processes and organizational results, although it cannot be concluded that a direct relationship between 4.0 Industry and organizational results exists, which means that there are other variables, such as continuous improvement, mediating between them. With this work, there is already an accredited reference of the relationship, which has been verified to exist, between the Industry 4.0, the continuous improvement, and the business results.
Corporate Social Responsibility and Earnings Management: Moderating Impact of Economic Cycles and Financial Performance
Authors: Gonçalves Tiago , Gaio Cristina , Ferro André
Published: September 2021

This study analyses the relationship between earnings management and corporate social responsibility. To this end, we use a sample of 568 listed companies from the European Union between 2010 and 2018. We use discretionary accruals as the measure of earnings management, under the Modified Jones model. Corporate social responsibility is proxied by the Combined Environmental, Social and Governance Score from the ASSET4 database. We find a negative relation between earnings management and corporate social responsibility, suggesting that managers from more socially responsible companies have a more ethical behavior and, thus, financial reporting of higher quality. Additional analysis provides evidence that economic cycles and financial performance play important roles in the relation between earnings management and corporate social responsibility. During periods of crisis or of losses, the relationship is positive, suggesting that under unfavorable economic conditions, management makes opportunistic use of a sustainable company’s status to manage earnings.