bluuebunny/crossref_metadata_2025 huggingface dataset:
Landsat-8 Sea Ice Classification Using Deep Neural Networks
Authors: Cáceres Alvaro , Schwarz Egbert , Aldenhoff Wiebke
Published: April 2022

Knowing the location and type of sea ice is essential for safe navigation and route optimization in ice-covered areas. In this study, we developed a deep neural network (DNN) for pixel-based ice Stage of Development classification for the Baltic Sea using Landsat-8 optical satellite imagery to provide up-to-date ice information for Near-Real-Time maritime applications. In order to train the network, we labeled the ice regions shown in the Landsat-8 imagery with classes from the German Federal Maritime and Hydrographic Agency (BSH) ice charts. These charts are routinely produced and distributed by the BSH Sea Ice Department. The compiled data set for the Baltic Sea region consists of 164 ice charts from 2014 to 2021 and contains ice types classified by the Stage of Development. Landsat-8 level 1 (L1b) images that could be overlaid with the available BSH ice charts based on the time of acquisition were downloaded from the United States Geological Survey (USGS) global archive and indexed in a data cube for better handling. The input variables of the DNN are the individual spectral bands: aerosol coastal, blue, green, red and near-infrared (NIR) out of the Operational Land Imager (OLI) sensor. The bands were selected based on the reflectance and emission properties of sea ice. The output values are 4 ice classes of Stage of Development and Ice Free. The results obtained show significant improvements compared to the available BSH ice charts when moving from polygons to pixels, preserving the original classes. The classification model has an accuracy of 87.5% based on the test data set excluded from the training and validation process. Using optical imagery can therefore add value to maritime safety and navigation in ice- infested waters by high resolution and real-time availability. Furthermore, the obtained results can be extended to other optical satellite imagery such as Sentinel-2. Our approach is promising for automated Near-Real-Time (NRT) services, which can be deployed and integrated at a later stage at the German Aerospace Center (DLR) ground station in Neustrelitz.
Cooperative Navigation for Low-Cost UAV Swarm Based on Sigma Point Belief Propagation
Authors: Chen Mingxing , Xiong Zhi , Song Fengyi , Xiong Jun , Wang Rong
Published: April 2022

As navigation is a key to task execution of micro unmanned aerial vehicle (UAV) swarm, the cooperative navigation (CN) method that integrates relative measurements between UAVs has attracted widespread attention due to its performance advantages. In view of the precision and efficiency of cooperative navigation for low-cost micro UAV swarm, this paper proposes a sigma point belief propagation-based (SPBP) CN method that can integrate self-measurement data and inter-UAV ranging in a distributed manner so as to improve the absolute positioning performance of UAV swarm. The method divides the sigma point filter into two steps: the first is to integrate local measurement data; the second is to approximate the belief of position based on the mean and covariance of the state, and pass message by augmentation, resampling and cooperative measurement update of the state to realize a low-complexity approximation to traditional message passing method. The simulation results and outdoor flight test results show that with similar performance, the proposed CN method has a calculation load more than 20 times less than traditional BP algorithms.
PRISMA L1 and L2 Performances within the PRISCAV Project: The Pignola Test Site in Southern Italy
Authors: Pignatti Stefano , Amodeo Aldo , Carfora Maria Francesca , Casa Raffaele , Mona Lucia , Palombo Angelo , Pascucci Simone , Rosoldi Marco , Santini Federico , Laneve Giovanni
Published: April 2022

In March 2019, the PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyperspectral satellite was launched by the Italian Space Agency (ASI), and it is currently operational on a global basis. The mission includes the hyperspectral imager PRISMA working in the 400–2500 nm spectral range with 237 bands and a panchromatic (PAN) camera (400–750 nm). This paper presents an evaluation of the PRISMA top-of-atmosphere (TOA) L1 products using different in situ measurements acquired over a fragmented rural area in Southern Italy (Pignola) between October 2019 and July 2021. L1 radiance values were compared with the TOA radiances simulated with a radiative transfer code configured using measurements of the atmospheric profile and the surface spectral characteristics. The L2 reflectance products were also compared with the data obtained by using the ImACor code atmospheric correction tool. A preliminary assessment to identify PRISMA noise characteristics was also conducted. The results showed that: (i) the PRISMA performance, as measured at the Pignola site over different seasons, is characterized by relative mean absolute differences (RMAD) of about 5–7% up to 1800 nm, while a decrease in accuracy was observed in the SWIR; (ii) a coherent noise could be observed in all the analyzed images below the 630th scan line, with a frequency of about 0.3–0.4 cycles/pixel; (iii) the most recent version of the standard reflectance L2 product (i.e., Version 2.05) matched well the reflectance values obtained by using the ImACor atmospheric correction tool. All these preliminary results confirm that PRISMA imagery is suitable for an accurate retrieval of the bio-geochemical variables pertaining to a complex fragmented ecosystem such as that of the Southern Apennines. Further studies are needed to confirm and monitor PRISMA data performance on different land-cover areas and on the Radiometric Calibration Network (RadCalNet) targets.
Recognition of Attentional States in VR Environment: An fNIRS Study
Authors: Zapała Dariusz , Augustynowicz Paweł , Tokovarov Mikhail
Published: April 2022

An improvement in ecological validity is one of the significant challenges for 21st-century neuroscience. At the same time, the study of neurocognitive processes in real-life situations requires good control of all variables relevant to the results. One possible solution that combines the capability of creating realistic experimental scenarios with adequate control of the test environment is virtual reality. Our goal was to develop an integrative research workspace involving a CW-fNIRS and head-mounted-display (HMD) technology dedicated to offline and online cognitive experiments. We designed an experimental study in a repeated-measures model on a group of BCI-naïve participants to verify our assumptions. The procedure included a 3D environment-adapted variant of the classic n-back task (2-back version). Tasks were divided into offline (calibration) and online (feedback) sessions. In both sessions, the signal was recorded during the cognitive task for within-group comparisons of changes in oxy-Hb concentration in the regions of interest (the dorsolateral prefrontal cortex-DLPFC and middle frontal gyrus-MFG). In the online session, the recorded signal changes were translated into real-time feedback. We hypothesized that it would be possible to obtain significantly higher than the level-of-chance threshold classification accuracy for the enhanced attention engagement (2-back task) vs. relaxed state in both conditions. Additionally, we measured participants′ subjective experiences of the BCI control in terms of satisfaction. Our results confirmed hypotheses regarding the offline condition. In accordance with the hypotheses, combining fNIRS and HMD technologies enables the effective transfer of experimental cognitive procedures to a controlled VR environment. This opens the new possibility of creating more ecologically valid studies and training procedures.
On-Body Placement of Wearable Safety Promotion Devices Based on Wireless Communication for Construction Workers-on-Foot: State-of-the-Art Review
Authors: Yadav Neeraj , Sadeghi Neda , Kang Julian
Published: April 2022

High auditory noise levels and limited visibility are often considered among the main factors that hinder seamless communication on construction sites. Many previous research studies have leveraged technology to overcome these obstacles and communicate using the hearing, sight and touch senses. However, the technological efficacy does not secure the users’ perceptivity of the wireless communication devices. Statistical data regarding the number of fatal accidents on construction sites have remained steady despite regular efforts. This study analyzed prior research on wearable safety promotion devices for personnel that move around the jobsite on foot. A seven-point checklist was utilized to shortlist prior studies (2005–2021) attempting to provide safety information wirelessly to the construction workers-on-foot. The reasoning behind various on-body placements was investigated along with the information conveyed using the three communication modalities. A novel communication network is also introduced to visualize the technical details. Lastly, limitations and future recommendations have been presented to gain insights about the factors that might affect the placement of the wearable safety promotion devices.
Intelligent Bus Platoon Lateral and Longitudinal Control Method Based on Finite-Time Sliding Mode
Authors: Yu Lingli , Bai Yu , Kuang Zongxv , Liu Chongliang , Jiao Hao
Published: April 2022

Considering the rapid convergence of the longitudinal and lateral tracking errors of the platoon, a finite-time tracking control method for the longitudinal and lateral directions of the intelligent bus platoon is proposed. Based on the bus platoon model and desired motion trajectory, a distributed longitudinal and lateral finite-time sliding mode tracking control framework of the platoon is designed. Considering the finite-time convergence of the sliding mode of the system, a nonsingular integral terminal sliding mode (NITSM) is designed. An adaptive power integral reaching law (APIRL) is proposed for the finite-time accessibility of the system approaching mode. Based on NITSM-APIRL, a distributed longitudinal and lateral finite-time sliding mode tracking controller for the bus platoon is designed, and a Lyapunov function is created to analyze the finite-time stability and string stability of the system. Based on the Trucksim/Simulink joint simulation experiment platform, the control performance of the method is contrasted with the existing methods, and the actual vehicle test verification is completed by relying on the National Intelligent Connected Vehicle testing zone, which proves the practicability of the method.
Strongest Angle-of-Arrival Estimation for Hybrid Millimeter Wave Architecture with 1-Bit A/D Equipped at Transceivers
Authors: Li Ruihan , Zhao Lou , Liu Chunshan , Bi Meihua
Published: April 2022

This paper proposes an effective strongest angles of arrival (AoAs) estimation algorithm for a hybrid millimeter wave (mmWave) communication system with 1-bit analog-to-digital/digital-to-analog converters (A/Ds) equipped at transceivers. The proposed algorithm aims to reduce the required number of estimation overheads, while maintaining the root mean square error (RMSE) of strongest AoA estimates at the base station. We obtain the quantization thresholds of A/Ds for different signal-to-noise ratios (SNRs) and numbers of antennas via numerical simulations, based on which, the strongest AoAs can be estimated with a small amount of overheads. The proposed algorithm is compared with conventional schemes including 1-bit FFT and 1-bit exhaustive search, as well as 1-bit Cramér-Rao lower bound. Simulation results verify the effectiveness of our proposed algorithm in terms of reducing estimation overheads while maintaining reasonable estimation performance in low SNRs.
Monitoring Various Bioactivities at the Molecular, Cellular, Tissue, and Organism Levels via Biological Lasers
Authors: Shan Hongrui , Dai Hailang , Chen Xianfeng
Published: April 2022

The laser is considered one of the greatest inventions of the 20th century. Biolasers employ high signal-to-noise ratio lasing emission rather than regular fluorescence as the sensing signal, directional out-coupling of lasing and excellent biocompatibility. Meanwhile, biolasers can also be micro-sized or smaller lasers with embedded/integrated biological materials. This article presents the progress in biolasers, focusing on the work done over the past years, including the molecular, cellular, tissue, and organism levels. Furthermore, biolasers have been utilized and explored for broad applications in biosensing, labeling, tracking, bioimaging, and biomedical development due to a number of unique advantages. Finally, we provide the possible directions of biolasers and their applications in the future.
Effects of Fe Staple-Fiber Spun-Yarns and Correlation Models on Textile Pressure Sensors
Authors: Choi Minki , Vu Chi Cuong , Kim Jooyong
Published: April 2022

As an aspect of intelligent clothing, e-textile sensors can flexibly sense and transmit information about human bodies and environments. However, difficulties relating to their technology and the variation in textile materials employed in their manufacture still limit their ability to analyze and be applied. The authors’ previous publication deployed a pressure sensor with warp-knitted spacer fabrics, wet-knitted fabrics, Ag-yarns, and Fe-yarns. An equivalent circuit analyzed the resistance behavior with some effects of the Ag-coated twisted yarns. In the present paper, the authors continue to evaluate the correlation model R-ε and the effects of the Fe staple-fiber spun yarns in detail. Together, the two studies provide an extensive understanding of the textile-related elements that affect pressure sensors. In addition, the process and the analysis (correlation model) could bring the textile sensors here developed close to the manufacturing stage, particularly for high precision/adjustable applications. We also develop a simple touch sensor matrix to demonstrate the potential of the sensor and the analyzing method.
Biometric Identification Based on Keystroke Dynamics
Authors: Kasprowski Pawel , Borowska Zaneta , Harezlak Katarzyna
Published: April 2022

The purpose of the paper is to study how changes in neural network architecture and its hyperparameters affect the results of biometric identification based on keystroke dynamics. The publicly available dataset of keystrokes was used, and the models with different parameters were trained using this data. Various neural network layers—convolutional, recurrent, and dense—in different configurations were employed together with pooling and dropout layers. The results were compared with the state-of-the-art model using the same dataset. The results varied, with the best-achieved accuracy equal to 82% for the identification (1 of 20) task.
Time-of-Flight Imaging in Fog Using Polarization Phasor Imaging
Authors: Zhang Yixin , Wang Xia , Zhao Yuwei , Fang Yujie
Published: April 2022

Due to the light scattered by atmospheric aerosols, the amplitude image contrast is degraded and the depth measurement is greatly distorted for time-of-flight (ToF) imaging in fog. The problem limits ToF imaging to be applied in outdoor settings, such as autonomous driving. To improve the quality of the images captured by ToF cameras, we propose a polarization phasor imaging method for image recovery in foggy scenes. In this paper, optical polarimetric defogging is introduced into ToF phasor imaging, and the degree of polarization phasor is proposed to estimate the scattering component. A polarization phasor imaging model is established, aiming at separating the target component from the signal received by ToF cameras to recover the amplitude and depth information. The effectiveness of this method is confirmed by several experiments with artificial fog, and the experimental results demonstrate that the proposed method significantly improves the image quality, with robustness in different thicknesses of fog.
Extending MQTT with Real-Time Communication Services Based on SDN
Authors: Shahri Ehsan , Pedreiras Paulo , Almeida Luis
Published: April 2022

MQTT is one of the most popular application-layer protocols used in the scope of the Internet-of-Things (IoT) and Industrial-Internet-of-Things (IIoT), given its suitability for resource-constrained embedded systems. However, MQTT Quality-of-Service policies do not support timeliness requirements, which is common in IIoT. The literature reports several research works that address this limitation, but they are limited in scope (e.g., improvements in the broker’s internal operation, control of the publisher’s data rate, and path optimizations). Conversely, this paper presents a comprehensive architectural approach, proposing a set of extensions to the MQTT protocol that allow applications to explicitly specify real-time requirements and instantiate corresponding network reservations to enforce the desired temporal behavior. Such reservations are enforced via Software Defined Networking, specifically the OpenFlow protocol, but other protocols that allow bandwidth reservations, e.g., TSN, can also be used. This paper presents the proposed system architecture together with extensive emulation and implementation results that validate the feasibility of the approach, showing that time-sensitive MQTT traffic can be effectively segregated and prioritized to meet application-defined real-time requirements. Using several combinations of network topologies and load levels and comparing to the absence of the proposed real-time mechanisms, both average and worst-case latencies of the time-sensitive traffic decreased to approximately half, while for the normal traffic, they increased by approximately 10%.
A Smart Multi-Rate Data Fusion Method for Displacement Reconstruction of Beam Structures
Authors: Zhang Qing , Fu Xing , Sun Zhiguo , Ren Liang
Published: April 2022

Dynamic displacement plays an essential role in structural health monitoring. To overcome the shortcomings of displacement measured directly, such as installation difficulty of monitoring devices, this paper proposes a smart reconstruction method, which can realize real-time intelligent online reconstruction of structural displacement. Unlike the existing approaches, the proposed algorithm combines the improved mode superposition methods that is suitable for complex beam structures with the Kalman filtering approach using acceleration and strain data. The effectiveness of the proposed multi-rate data fusion method for dynamic displacement reconstruction is demonstrated by both numerical simulation and model vibration experiment. Parametric analysis shows that the reconstruction error is only 5% when the noise signal to noise ratio is 5 dB, illustrating that the proposed algorithm has excellent anti-noise performance. The results also indicate that both the high-frequency and low-frequency components of the dynamic displacements can be accurately reconstructed through the proposed method, which has good robustness.
Digital Twin for Civil Engineering Systems: An Exploratory Review for Distributed Sensing Updating
Authors: Bado Mattia Francesco , Tonelli Daniel , Poli Francesca , Zonta Daniele , Casas Joan Ramon
Published: April 2022

We live in an environment of ever-growing demand for transport networks, which also have ageing infrastructure. However, it is not feasible to replace all the infrastructural assets that have surpassed their service lives. The commonly established alternative is increasing their durability by means of Structural Health Monitoring (SHM)-based maintenance and serviceability. Amongst the multitude of approaches to SHM, the Digital Twin model is gaining increasing attention. This model is a digital reconstruction (the Digital Twin) of a real-life asset (the Physical Twin) that, in contrast to other digital models, is frequently and automatically updated using data sampled by a sensor network deployed on the latter. This tool can provide infrastructure managers with functionalities to monitor and optimize their asset stock and to make informed and data-based decisions, in the context of day-to-day operative conditions and after extreme events. These data not only include sensor data, but also include regularly revalidated structural reliability indices formulated on the grounds of the frequently updated Digital Twin model. The technology can be even pushed as far as performing structural behavioral predictions and automatically compensating for them. The present exploratory review covers the key Digital Twin aspects—its usefulness, modus operandi, application, etc.—and proves the suitability of Distributed Sensing as its network sensor component.
Dynamic Seat Assessment for Enabled Restlessness of Children with Learning Difficulties
Authors: Stanić Valentina , Žnidarič Taja , Repovš Grega , Geršak Gregor
Published: April 2022

Children with Attention-Deficit/Hyperactivity Disorder (ADHD) face a range of learning difficulties in the school environment, thus several strategies have been developed to enhance or optimise their performance in school. One possible way is to actively enable appropriate restlessness using dynamic seats. In this paper, an assessment of the efficacy of a dynamic seat while solving school task is presented and compared to classic chair and therapy ball. To test the effectiveness of active seat, a study that examined task solving performance while observing the intensity of movement, in-seat behaviour and psychophysiological responses (electrodermal activity, facial temperature) was designed. A total of 23 school-aged children participated in the study, 11 children with a combined type of ADHD and 12 children without disorders. Children with ADHD achieved the best results when sitting in the active seat, where the most intense movement and best in-seat behaviour was observed. At the same time, psychophysiological parameters indicate that when performing better at the task children with ADHD were not too challenged and were consequently less agitated. Results have suggested that for a better cognitive performance of children with ADHD, it is crucial to provide a comfortable and pleasant workspace that enables them the right amount of restlessness.
Binding of GS-461203 and Its Halogen Derivatives to HCV Genotype 2a RNA Polymerase Drug Resistance Mutants
Authors: Arba Muhammad , Wahyudi Setyanto Tri , Zubair Muhammad Sulaiman , Brunt Dylan , Singh Mursalin , Wu Chun
Published: April 2022

Hepatitis C Virus (HCV) is reported to develop GS-461203 resistance because of multiple mutations within the RNA-dependent RNA Polymerase (RdRp) of HCV. The lack of a high-resolution structure of these RdRp mutants in complex with GS-461203 hinders efforts to understand the drug resistance. Here we decipher the binding differences of GS-461203 in the wild type and mutated systems T179A or M289L of HCV RdRp Genotype 2a using homology modeling, molecular docking, and molecular dynamics simulation. Key residues responsible for GS-461203 binding were identified to be Arg48, Arg158, Asp318, Asp319, and Asp220, and that mutations T179A or M289L have caused conformational changes of GS-461203 in the RdRp active site. The affinities of GS-461203 were reduced in T179A system, but it became slightly stronger in the M289L system. Furthermore, we designed two new analogues of GS-461203 which encouragingly induced more stable interactions than GS-461203, and thus resulted in much better binding energies. This present study reveals how a single mutation, T179A or M289L, will modulate GS-461203 binding in HCV RdRp Genotype 2a, while introducing two novel analogues to overcome the drug resistance which may be good candidate for further experimental verification.
Towards a Better Understanding of Social-Ecological Systems for Basin Governance: A Case Study from the Weihe River Basin, China
Authors: Wang Bo , Wang Heng , Zeng Xianfeng , Li Baojun
Published: April 2022

Promoting sustainable development of the river basin ecosystem is important for improving human ecological environment. Thus, prior knowledge of natural and social sciences on the integration of natural, economic, and social factors related to rivers should be assimilated to improve river basin governance. This study uses a social-ecological systems (SES) framework to diagnose key factors affecting the governance of the Weihe River Basin, ranging from the social, economic, and political context to related ecosystems, watershed resource systems, watershed management system, and watershed governance actors’ five subsystems. Further, corresponding countermeasures are proposed for the problems found during our diagnosis. The results of this study show that applying an SES framework to the diagnosis and analysis of river basin governance integrates the research results of different disciplines and fields. Thus, this study is helpful in identifying and proposing the key impact variables related to river basin management to establish a comprehensive management counterplan.
Heterogeneous Impact of Economic Policy Uncertainty on Provincial Environmental Pollution Emissions in China
Authors: Yang Wei , Zhang Yifu , Hu Yuan
Published: April 2022

With China’s proposal of carbon peak and carbon neutral goals, its trend of economic development has shifted from pursuing high-speed economic development to high-quality development. However, for the past few years, with the increasing global economic policy uncertainty, fluctuations in the world economy, especially emergent through public events such as COVID-19, affect investment and consumption, and thus indirectly affect the realization of the dual carbon target. Economic policy uncertainty plays an increasingly important role in many factors affecting environmental pollution. We conducted an empirical test on sample data, which are from 30 provinces and autonomous regions in China from 2008 to 2020, to further study the impact of economic policy uncertainty on environmental pollution emissions. We found that: (1) Economic policy uncertainty is inversely related to the emission of environmental pollution, and the consumption effect brought by economic policy uncertainty is more than the investment effect. This means that, with the economic policy uncertainty index increasing, the comprehensive index of environmental pollution emissions is lower, and the environmental pollution emissions are lower; (2) Compared with provinces with an average level of economic development, the impact of economic policy uncertainty on environmental emissions is deeper in developed provinces.
Bibliometric Analysis of Global Research on Ecological Networks in Nature Conservation from 1990 to 2020
Authors: Lu Zhonggui , Li Wei , Wang Yidi , Zhou Siyang
Published: April 2022

As a nature-based solution to land-use sustainability, ecological networks (ENs) have received substantial attention from researchers, planners, and decision-makers worldwide. To portray the global research on ENs in nature conservation during the period of 1990–2020, 1371 papers in 53 subject categories were reviewed with bibliometric methods and CiteSpace. The results showed a successive growth of publications at an annually averaged rate of 18.9% during the past three decades. Co-citation analysis indicated that the most popular topic was connectivity, on which the studies concentrated on quantifying connectivity, identifying priority areas, and integrating conservation planning. A recent hotspot is to study the landscape fragmentation effects on natural habitats or biodiversity under land-use changes in urbanized areas. Multidisciplinary approaches have been increasingly used to tackle more complex interplays among economic, social, ecological, and cultural factors, with the aim of alleviating ecological service losses attributed to human activities. Spatiotemporal dynamics and participatory design of ENs at different scales have become an emerging trend. In order to address increasing pressures on biodiversity or landscape connectivity brought about by land use and climate change, it is suggested to develop more research on the evaluation and management of the resilience of ENs.
Seasonal Variation of Vegetation and Its Spatiotemporal Response to Climatic Factors in the Qilian Mountains, China
Authors: Duan Hanchen , Qi Yuan , Kang Wenping , Zhang Jinlong , Wang Hongwei , Jiang Xiaofang
Published: April 2022

The purpose of this study is to reveal the seasonal difference in vegetation variation and its seasonal response to climate factors in the Qilian Mountains (QM) under the background of global warming. Based on the MOD13 A2 normalized difference vegetation index (NDVI) data and meteorological data, this study analyzed the spatiotemporal dynamics and stability of vegetation in different seasons by using the mean value method, trend analysis and stability analysis method, and discussed their seasonal responses to climatic factors based on the correlation analysis method. The results show that the vegetation cover in the QM experienced a significant upward trend in the past 21 years, but there were obvious spatial differences in vegetation change in different seasons. The growth rate of vegetation in summer was the fastest, and summer vegetation provided the most significant contribution to the growing season vegetation. The order of vegetation stability in the QM among the seasons was growing season > summer > spring > autumn. The vegetation change was obviously affected by temperature in spring, while it was mainly controlled by precipitation in the growing season and summer. The response of vegetation to climatic factors was not significant in autumn. Our results can provide important data support for ecological protection in the QM and socioeconomic development in the Hexi Corridor.
The Importance of Individual Actor Characteristics and Contextual Aspects for Promoting Industrial Symbiosis Networks
Authors: Harfeldt-Berg Lovisa , Broberg Sarah , Ericsson Karin
Published: April 2022

Factors that affect and influence industrial symbiosis (IS) collaborations have been researched extensively in the literature, where they are mostly reported at a network level or for IS in general, and lack the individual actor’s perspective. This review article contributes to and expands knowledge of influencing factors and their effect on the individual actor. In a systematic review, guided by the PRISMA 2020 guidelines, this study reviews 53 scientific papers examining planned or existing IS networks. It examines literature from 1 January 2000 to 28 March 2022, and it identifies drivers, barriers, and enablers influencing actors to participate in IS. It explores whether and how the perception and impact of these factors differs depending on the characteristics of individual actors and their specific context. The main findings of this study reveal that an actor’s specific characteristics and the network’s context have a significant impact on decision making and how actors both perceive and are affected by factors influencing collaboration. Furthermore, an additional novel contribution to this field of research is that the study identifies three underlying and recurring considerations that actors appear to find critical, namely, perceived business opportunities/risks, regulatory and political setting, and potential inequalities in the network. The results show that an actor’s take on these critical considerations determines whether the actor is willing to engage in IS.
A Water Footprint Management Construct in Agri-Food Supply Chains: A Content Validity Analysis
Authors: Barbosa Marcelo Werneck , Cansino José M.
Published: April 2022

Common problems when carrying out water footprint (WF) assessments are obtaining specific primary data, dealing with the complexity of its computation, and the availability of quality data. In a supply chain context, inconsistencies are even more exacerbated. In order to fill in this research gap, this study proposes and evaluates the content validity of a survey scale to assess WF management initiatives implemented by companies, with a focus on supply chains and the agriculture industry. In order to do so, a literature review was performed to identify candidate survey items whose content was later validated with experts in terms of their relevance, clarity, and essentiality to measure WF management. Content validity was assessed using several indices (items’ content validity index (I-CVI), Kappa’s coefficient, Aiken’ V coefficient, and content validity ratio (CVR)), which indicated high content validity for the selected items. This study provides a set of measurement survey items that can be used to evaluate WF management initiatives implemented in agri-food supply chains in future empirical studies.
Fire-YOLO: A Small Target Object Detection Method for Fire Inspection
Authors: Zhao Lei , Zhi Luqian , Zhao Cai , Zheng Wen
Published: April 2022

For the detection of small targets, fire-like and smoke-like targets in forest fire images, as well as fire detection under different natural lights, an improved Fire-YOLO deep learning algorithm is proposed. The Fire-YOLO detection model expands the feature extraction network from three dimensions, which enhances feature propagation of fire small targets identification, improves network performance, and reduces model parameters. Furthermore, through the promotion of the feature pyramid, the top-performing prediction box is obtained. Fire-YOLO attains excellent results compared to state-of-the-art object detection networks, notably in the detection of small targets of fire and smoke. Overall, the Fire-YOLO detection model can effectively deal with the inspection of small fire targets, as well as fire-like and smoke-like objects. When the input image size is 416 × 416 resolution, the average detection time is 0.04 s per frame, which can provide real-time forest fire detection. Moreover, the algorithm proposed in this paper can also be applied to small target detection under other complicated situations.
A Personalized Assistance System for the Location and Efficient Evacuation in Case of Emergency: TECuidamos, a Challenge-Based Learning Derived Project Designed to Save Lives
Authors: López-Caudana Edgar , Ruiz Sergio , Calixto Aaron , Nájera Brandon , Castro Diego , Romero Diego , Luna José , Vargas Vincent , Legorreta Iván , Lara-Prieto Vianney , Caratozzolo Patricia , Membrillo-Hernández Jorge
Published: April 2022

The uncertainty of the occurrence of a disaster is greater in places such as Mexico City, a city with one of the largest seismic activities in the world. This leads to a growing need for the population to be better educated in the application of security protocols. Challenge-Based Learning (CBL) is a didactic technique that brings students closer to real situations with the aim of developing the skills required to apply their knowledge in the design, study, and implementation of a solution to a given challenge. In this report, the authors apply this teaching technique to create a system capable of helping civil protection personnel monitor, guide, and record crucial data in an emergency. All of this is achieved through a web administrator and using route planning algorithms hosted within a cloud server to provide the user with an efficient route in real time. The result was a working prototype that performs these tasks. After several tests, the prototype showed the suitability of the system. Educating to prevent is essential to reduce the number of deaths in a disaster. CBL is a suitable technique for developing the necessary skills and integrating multidisciplinary knowledge.
Assessing the Spatial Mapping of Heat Vulnerability under Urban Heat Island (UHI) Effect in the Dhaka Metropolitan Area
Authors: Abrar Rakin , Sarkar Showmitra Kumar , Nishtha Kashfia Tasnim , Talukdar Swapan , Shahfahad  , Rahman Atiqur , Islam Abu Reza Md Towfiqul , Mosavi Amir
Published: April 2022

The urban heat island (UHI) phenomenon gets intensified in the process of urbanization, which increases the vulnerability of urban dwellers to heatwaves. The UHI-induced vulnerability to heatwaves has increased in Bangladesh during past decades. Thus, this study aims to examine the UHI and vulnerability to heatwaves in the city of Dhaka using a heat vulnerability index (HVI). The HVI is constructed using various demographic, socioeconomic, and environmental risk variables at thana level. Principal component analysis (PCA) was applied to the 26 normalized variables for each of the 41 thanas of Dhaka to prepare the HVI. Result shows that more than 60% of the city is under built-up areas, while vegetation cover and water bodies are in low proportion. Analysis of HVI shows that the very high- and high-risk zones comprise 6 and 11 thanas, while low- and very low-risk zones comprise only 5 and 8 thanas. The correlation of HVI with variables such as exposure (0.62) and sensitivity (0.80) was found to be highly positive, while adaptive capacity had a negative correlation (−0.26) with the HVI. Findings of this study can be utilized in the mitigation of UHI phenomenon and maintaining the thermal comfort of Dhaka.
Environmental Competencies for Sustainability: A Training Experience with High School Teachers in a Rural Community
Authors: Moctezuma Teresa Luis Miguel , Aparicio López José Luis , Rodríguez Alviso Columba , Gervacio Jiménez Herlinda , Brito Carmona Rosa María
Published: April 2022

Solid teacher training can be a transcendental tool in solving the most pressing environmental problems of our time. The purpose of this study was to reinforce the competencies of in-service teachers through a training process on environmental and sustainability issues. The research was carried out during the 2020–2021 cycle in Preparatory School No. 47 of the Autonomous University of Guerrero. We sought to broaden the teachers’ knowledge of environmental education for sustainability, the sustainable development goals and methodological strategies. The information was collected through an initial questionnaire, as well as the record of teachers’ activities during the course, which was structured in four topics: socio-environmental problems, environmental education for sustainability, sustainable development goals 2030, and methodological strategies. The training process influenced the teachers’ perception, achieving a more complex vision of the topics studied. The didactic and pedagogical strategies proposed facilitated the integration of transversal activities in their discipline. The work carried out demonstrated the importance of strengthening training processes that include methodological strategies such as transversality taking advantage of the physical characteristics of the rural community. Teachers develop environmental competencies for sustainability in their educational practice, to contribute to the integral formation of their students.
Alternative Marine Fuel Research Advances and Future Trends: A Bibliometric Knowledge Mapping Approach
Authors: Moshiul Alam Md , Mohammad Roslina , Hira Fariha Anjum , Maarop Nurazean
Published: April 2022

While the marine sector contributes significantly to the global economy, its environmental impact is a cause for apprehension due to growing concerns about ship emissions. The International Maritime Organization (IMO) has set decarbonization strategies consistent with sustainable development goals. The impending legislation aimed at reducing greenhouse gas (GHG) emissions from maritime shipping by at least half by 2050 and to zero by the end of the century. A growing body of research has focused on alternative marine fuel selection; hence, this bibliometric review is timely. We assess the global scientific research on alternative marine fuel for knowledge mapping based on the articles available on the Scopus database since 1973. A total of 749 publications associated with alternative marine fuel has been subjected to a range of bibliometric analyses to explore this research field quantitatively and qualitatively. The study utilized the R-studio bibliometrics package and VOSviewer bibliometric tools to generate the results. The field of study has a growth rate of 7.05%, having a significant contribution to knowledge from the USA, the United Kingdom, India, and China. Recent trends indicate that researchers are increasingly focused on alternative fuel oil choices. By analyzing commonly used keywords, it was possible to trace a multi-criteria decision analysis process that might be utilized to construct decision support systems for alternative maritime fuel selection. According to relevant articles, the research community has concentrated on the possibility of alternative fuels being utilized in place of traditional marine fuels to reduce emissions from the shipping sector from an environmental, technological, and economic standpoint. The current study offers an updated and comprehensive overview of research trends on alternative marine fuels. Researchers interested in data mapping work in this area can begin with this endeavor.
A Model to Support Sustainable Resource Management in the “Etna River Valleys” Biosphere Reserve: The Dominance-Based Rough Set Approach
Authors: Scuderi Alessandro , Sturiale Luisa , Timpanaro Giuseppe , Matarazzo Agata , Zingale Silvia , Guarnaccia Paolo
Published: April 2022

For several decades, studies and conventions have highlighted the importance of the ecosystem services provided by natural resources and biodiversity for humanity and the need to move their management towards a sustainable model. Inthe United Nations 2030 Agenda for Sustainable Development (2015), among its 17 Sustainable Development Goals (SDGs), there isalsoSDG 15, “Life on Land”, specifically dedicated to biodiversity, forests and desertification. The aim is to “sustainably manage forests, combat desertification, halt and reverse land degradation, and halt the loss of bio-diversity”. The UNESCO “MAB—Man and Biosphere” Programme could achieve this goal by establishing Biosphere Reserves (BRs). Among them, the establishment of the BR “Etna river valleys” is an opportunity to adopt sustainable development models in the “Etna Park system” (UNESCO site since 2013) for the regeneration of virtuous relationships between cities and rural areas and the promotion of the conservation of natural resources and biodiversity through strategies of territorial enhancement with a multifunctional vision of agriculture and territory. This research aims to provide, through the methodology of “Rough Sets”, a useful tool to support the strategic choices that stakeholders will be called upon to make for the management of the complex environmental, cultural and economic mosaic that characterises the BR “Etna river valleys”.The results show both weaknesses and strengths in the transition towards a sustainable land management model, which will nonethelesshave to be supported and accompanied by information and financial support.
Decision Making in Green Supply Chain with Manufacturers’ Misreporting Behavior
Authors: Zong Shengliang , Shen Chunyang , Su Siping
Published: April 2022

To reduce the cost of energy conservation and emission reduction, some manufacturers will choose to misreport the green degree of their products, which may have some serious negative effects on the profit of the supply chain. To investigate the effects of the manufacturers’ misreporting strategy on the decisions and associated profit of the supply chain, we establish a two-period Stackelberg game model for a dual-channel manufacturer–retailer setting. Our results show that the manufacturers’ misreporting strategies lead to higher profits for them, which means that manufacturers tend to misreport the green degree of the products. However, the manufacturer’s misreporting strategy will put the retailer and the whole supply chain in a disadvantageous position and, hence, reduce the profit of the retailer and the whole supply chain. In addition, we also show that the manufacturer’s misreporting strategy only affects the greenness of the product and does not affect the pricing decisions of the manufacturer, the retailer and the whole supply chain. Finally, we design a revenue-sharing contract to achieve the coordination of the supply chain, which provides managerial insights for the decision makers of the supply chain.
Back and Forth on Sustainable Development: A Focus on Healthcare Organisations
Authors: Cavicchi Caterina , Oppi Chiara , Vagnoni Emidia
Published: April 2022

The sustainability of healthcare systems represents a relevant target of the 2030 Sustainable Development Goals Agenda. Nevertheless, academic research has neglected to study healthcare systems when focusing on the transition toward sustainable healthcare. This study addresses this gap by investigating the implementation of the sustainable development (SD) principle in the Italian healthcare system, in light of international and national institutional discourses on SD. A questionnaire-based survey has been directed to the General Directors (GDs) of government-funded healthcare orgsanisations to investigate their perceptions about the SD principle applied to healthcare, their strategic planning for SD, their implemented projects for sustainability and the intellectual capital factors that influence the latter’s implementation. The study was conducted in two waves: a first survey was administered in 2016, with a second one in 2021. We used content analysis to identify the potential differences emerging over time in GDs’ perceptions in light of the changes in the institutional discourse; we then assessed the differences over time in the perceived contribution of intellectual capital factors to the implementation of sustainability actions. Results show a substantial decrease in strategic planning for sustainability, as well as in the volume of sustainability projects implemented, as organisations were found to be less involved in implementing SD strategies and projects in 2021 than in 2016. Policies at the country level have mainly focused on balancing cost containment with quality targets, leaving the environmental dimension of sustainability and its connection with healthcare with limited guidelines. Regarding intellectual capital factors, organisational culture and technologies are increasingly perceived as enablers of SD; nevertheless, further studies are needed to deepen their effective contribution to sustainable healthcare.
Coordinated Development Relationship between Port Cluster and Its Hinterland Economic System Based on Improved Coupling Coordination Degree Model: Empirical Study from China’s Port Integration
Authors: Wang Chengsong , Yang Qian , Wu Shanhua
Published: April 2022

In recent years, the port integration in China has been carried out vigorously, and has basically covered all coastal provinces from south to north and some areas along the Yangtze River. In order to quantify the practical effects of the port integration, this paper conducts research investigating whether or not the port integration would be able to realize the coordinated development between the port cluster and its hinterland economic system more smoothly. This paper carries out the research by building the improved coupling coordination degree model for evaluating the coupling coordination degree between the port cluster and its hinterland economic system, and further by applying the improved model to the empirical analysis of three port clusters with different integration patterns. The empirical results reveal that: (1) the port integration may lead to a “Painful Period” for the coordinated development relationship between the port cluster and its hinterland economic system in the short term, especially at the beginning of the integration, and the coupling coordination degree of the whole system would fall into a drop temporally; (2) among different port clusters with different port integration purposes and patterns, there are evident differences in the change of the coupling coordination degree of the whole system at the beginning of the integration; and (3) in the long run, the port integration would be able to effectively improve the coupling coordination degree of the port cluster and its hinterland economic system, and thus the whole system can obtain a better relationship of coordinated development.