bluuebunny/crossref_metadata_2025 huggingface dataset:
Consolidating ICESat-2 Ocean Wave Characteristics with CryoSat-2 during the CRYO2ICE Campaign
Authors: Nilsson Bjarke , Andersen Ole Baltazar , Ranndal Heidi , Rasmussen Mikkel Lydholm
Published: March 2022

Using the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) global high-resolution elevation measurements, it is possible to distinguish individual surface ocean waves. With the vast majority of ocean surveying missions using radar satellites, ICESat-2 observations are an important addition to ocean surveys. ICESat-2 can also provide additional observations not possible with radar. In this paper, we consolidate the ICESat-2 ocean observations by comparing the significant wave height (SWH) with coincident CryoSat-2 radar observations during the CRYO2ICE campaign from August 2020 to August 2021. We use 136 orbit segments, constrained to the Pacific and Atlantic oceans as well as the Bering Sea, to compare observations to show the level of agreement between these systems. Three models based on ICESat-2 are used in the comparison: the standard ocean data output (ATL12), a method of modeling the individual surface waves using the geolocated photons and, functioning as a baseline, an approach using the standard deviation of the ocean surface. We find the following correlations between the SWHs from the models and the SWHs from CryoSat-2: 0.97 for ATL12, 0.95 for the observed waves model, and 0.97 for the standard deviation model. In the same comparison, we find mean differences relative to the observed SWHs for each model, as well as errors, which increase as the SWH increases. The SWH observed from ICESat-2 is found to agree with observations from CryoSat-2, with limitations due to changes in the sea state between the satellite observations. Observing the individual surface waves from ICESat-2 can therefore provide additional observed properties of the sea state that can be used alongside other global observations.
A Fast and Robust Algorithm with Reinforcement Learning for Large UAV Cluster Mission Planning
Authors: Zuo Lei , Gao Shan , Li Yachao , Li Lianghai , Li Ming , Lu Xiaofei
Published: March 2022

Large Unmanned Aerial Vehicle (UAV) clusters, containing hundreds of UAVs, have widely been used in the modern world. Therein, mission planning is the core of large UAV cluster collaborative systems. In this paper, we propose a mission planning method by introducing the Simple Attention Model (SAM) into Dynamic Information Reinforcement Learning (DIRL), named DIRL-SAM. To reduce the computational complexity of the original attention model, we derive the SAM with a lightweight interactive model to rapidly extract high-dimensional features of the cluster information. In DIRL, dynamic training conditions are considered to simulate different mission environments. Meanwhile, the data expansion in DIRL guarantees the convergence of the model in these dynamic environments, which improves the robustness of the algorithm. Finally, the simulation experiment results show that the proposed method can adaptively provide feasible mission planning schemes with second-level solution speed and that it exhibits excellent generalization performance in large-scale cluster planning problems.
Susceptibility Prediction of Post-Fire Debris Flows in Xichang, China, Using a Logistic Regression Model from a Spatiotemporal Perspective
Authors: Jin Tao , Hu Xiewen , Liu Bo , Xi Chuanjie , He Kun , Cao Xichao , Luo Gang , Han Mei , Ma Guotao , Yang Ying , Wang Yan
Published: March 2022

The post-fire debris flow (PFDF) is a commonly destructive hazard that may persist for several years following the wildfires. Susceptibility mapping is an effective method for mitigating hazard risk. Yet, the majority of susceptibility prediction models only focus on spatial probability in the specific period while ignoring the change associated with time. This study improves the predictive model by introducing the temporal factor. The area burned by the 30 March 2020 fire in Xichang City, China is selected as an illustrative example, and the susceptibility of the PFDF was predicted for different periods of seven months after the wildfires. 2214 hydrological response events, including 181 debris flow events and 2033 flood events from the 82 watersheds are adopted to construct the sample dataset. Seven conditioning factors consist of temporal factors and spatial factors are extracted by the remote sensing interpretation, field investigations, and in situ tests, after correlation and importance analysis. The logistic regression (LR) is adopted to establish prediction models through 10 cross-validations. The results show that the susceptibility to PFDF has significantly reduced over time. After two months of wildfire, the proportions of very low, low, moderate, high, and very high susceptibility are 1.2%, 3.7%, 24.4%, 23.2%, and 47.6%, respectively. After seven months of wildfire, the proportions of high and very high susceptibility decreased to 0, while the proportions of very low to medium susceptibility increased to 35.4%, 35.6%, and 28.1%, respectively. The reason is that the drone seeding of grass seeds and artificial planting of trees accelerated the natural recovery of vegetation and soil after the fire. This study can give insight into the evolution mechanism of PFDF over time and reflect the important influence of human activity after the wildfire.
Multi-Unit Serial Polynomial Multiplier to Accelerate NTRU-Based Cryptographic Schemes in IoT Embedded Systems
Authors: Sánchez-Solano Santiago , Camacho-Ruiz Eros , Martínez-Rodríguez Macarena C. , Brox Piedad
Published: March 2022

Concern for the security of embedded systems that implement IoT devices has become a crucial issue, as these devices today support an increasing number of applications and services that store and exchange information whose integrity, privacy, and authenticity must be adequately guaranteed. Modern lattice-based cryptographic schemes have proven to be a good alternative, both to face the security threats that arise as a consequence of the development of quantum computing and to allow efficient implementations of cryptographic primitives in resource-limited embedded systems, such as those used in consumer and industrial applications of the IoT. This article describes the hardware implementation of parameterized multi-unit serial polynomial multipliers to speed up time-consuming operations in NTRU-based cryptographic schemes. The flexibility in selecting the design parameters and the interconnection protocol with a general-purpose processor allow them to be applied both to the standardized variants of NTRU and to the new proposals that are being considered in the post-quantum contest currently held by the National Institute of Standards and Technology, as well as to obtain an adequate cost/performance/security-level trade-off for a target application. The designs are provided as AXI4 bus-compliant intellectual property modules that can be easily incorporated into embedded systems developed with the Vivado design tools. The work provides an extensive set of implementation and characterization results in devices of the Xilinx Zynq-7000 and Zynq UltraScale+ families for the different sets of parameters defined in the NTRUEncrypt standard. It also includes details of their plug and play inclusion as hardware accelerators in the C implementation of this public-key encryption scheme codified in the LibNTRU library, showing that acceleration factors of up to 3.1 are achieved when compared to pure software implementations running on the processing systems included in the programmable devices.
Probabilistic Maritime Trajectory Prediction in Complex Scenarios Using Deep Learning
Authors: Sørensen Kristian Aalling , Heiselberg Peder , Heiselberg Henning
Published: March 2022

Maritime activity is expected to increase, and therefore also the need for maritime surveillance and safety. Most ships are obligated to identify themselves with a transponder system like the Automatic Identification System (AIS) and ships that do not, intentionally or unintentionally, are referred to as dark ships and must be observed by other means. Knowing the future location of ships can not only help with ship/ship collision avoidance, but also with determining the identity of these dark ships found in, e.g., satellite images. However, predicting the future location of ships is inherently probabilistic and the variety of possible routes is almost limitless. We therefore introduce a Bidirectional Long-Short-Term-Memory Mixture Density Network (BLSTM-MDN) deep learning model capable of characterising the underlying distribution of ship trajectories. It is consequently possible to predict a probabilistic future location as opposed to a deterministic location. AIS data from 3631 different cargo ships are acquired from a region west of Norway spanning 320,000 sqkm. Our implemented BLSTM-MDN model characterizes the conditional probability of the target, conditioned on an input trajectory using an 11-dimensional Gaussian distribution and by inferring a single target from the distribution, we can predict several probable trajectories from the same input trajectory with a test Negative Log Likelihood loss of −9.96 corresponding to a mean distance error of 2.53 km 50 min into the future. We compare our model to both a standard BLSTM and a state-of-the-art multi-headed self-attention BLSTM model and the BLSTM-MDN performs similarly to the two deterministic deep learning models on straight trajectories, but produced better results in complex scenarios.
On-Orbit Absolute Radiometric Calibration and Validation of ZY3-02 Satellite Multispectral Sensor
Authors: Tang Hongzhao , Xie Junfeng , Tang Xinming , Chen Wei , Li Qi
Published: March 2022

This study described the on-orbit vicarious radiometric calibration of Chinese civilian high-resolution stereo mapping satellite ZY3-02 multispectral imager (MUX). The calibration was based on gray-scale permanent artificial targets, and multiple radiometric calibration tarpaulins (tarps) using a reflectance-based approach between July and September 2016 at Baotou calibration site in China was described. The calibration results reveal a good linear relationship between DN and TOA radiances of ZY3-02 MUX. The uncertainty of this radiometric calibration was 4.33%, indicating that radiometric coefficients of ZY3-02 MUX are reliable. A detailed discussion on the validation analysis of the comparison results between the different radiometric calibration coefficients is presented in this paper. To further validate the reliability of the three coefficients, the calibrated ZY3-02 MUX was compared with Landsat-8 Operational Land Imager (OLI). The results also indicate that radiometric characteristics of ZY3-02 MUX imagery are reliable and highly accurate for quantitative applications.
High Precision Visual Dimension Measurement Method with Large Range Based on Multi-Prism and M-Array Coding
Authors: Zhou Xiao , Zhou Cong , Zhang Tingting , Mou Xingang , Xu Jiaxin , He Yi
Published: March 2022

The visual dimension measurement method based on non-splicing single lens has the contradiction between accuracy and range of measurement, which cannot be considered simultaneously. In this paper, a multi-camera cooperative measurement method without mechanical motion is proposed for the dimension measurement of thin slice workpiece. After the calibration of the multi-camera imaging system is achieved through a simple and efficient scheme, the high-precision dimension measurement with a large field of view can be completed through a single exposure. First, the images of the edges of the workpiece are compressed and combined by splitting and merging light through the multi-prism system, and the results are distributed to multiple cameras by changing the light path. Then, the mapping relationship between the global measurement coordinates and the image coordinates of each camera is established based on the globally unique M-array coding, and the image distortion is corrected by the coding unit composed of black and white blocks. Finally, the edge is located accurately by edge point detection at the sub-pixel level and curve fitting. The results of measuring a test workpiece with the dimension of 24 mm × 12 mm × 2 mm through a single exposure show that the repeated measurement accuracy can reach 0.2 µm and the absolute accuracy can reach 0.5 µm. Compared with other methods, our method can achieve the large-field measurement through only one exposure and without the mechanical movement of cameras. The measurement precision is higher and the speed is faster.
A Machine Learning Study on Internal Force Characteristics of the Anti-Slide Pile Based on the DOFS-BOTDA Monitoring Technology
Authors: Wei Chaoqun , Deng Qinglu , Yin Yueming , Yan Mengyao , Lu Meng , Deng Kangqing
Published: March 2022

Long-term monitoring of constructed anti-slide piles can help in understanding the processes by which anti-slide piles are subjected to the thrust of landslides. This paper examined the landslide control project of Badong No. 3 High School. The internal force of an anti-slide pile subjected to long-term action of landslide thrust was studied by Distributed Optical Fiber Sensing (DOFS) technology. The BP neural network was used for model training on the monitored strain values and the calculated bending moment values. The results show the following: (1) The monitoring results of the sensor fibers reflect the actual situation more accurately than steel rebar meters do and can locate the position of the sliding zone more accurately. (2) The bending moments distributed along the anti-slide pile have staged characteristics under the long-term action of landslide thrust. Three stages can be summarized according to the development trend of the bending moment values. These three stages can be divided into two change periods of landslide thrust. (3) The model produced by the BP neural network training can predict the bending moment values. In this paper, the sensing fibers monitoring over a long time interval provides a basis for long-term performance analysis of anti-slide piles and stability evaluation of landslides. Using the BP neural network for training relevant data can provide directions for future engineering monitoring. More novel methods can be devised and utilized that will be both accurate and convenient.
EEG Channel Selection Based User Identification via Improved Flower Pollination Algorithm
Authors: Alyasseri Zaid Abdi Alkareem , Alomari Osama Ahmad , Papa João P. , Al-Betar Mohammed Azmi , Abdulkareem Karrar Hameed , Mohammed Mazin Abed , Kadry Seifedine , Thinnukool Orawit , Khuwuthyakorn Pattaraporn
Published: March 2022

The electroencephalogram (EEG) introduced a massive potential for user identification. Several studies have shown that EEG provides unique features in addition to typical strength for spoofing attacks. EEG provides a graphic recording of the brain’s electrical activity that electrodes can capture on the scalp at different places. However, selecting which electrodes should be used is a challenging task. Such a subject is formulated as an electrode selection task that is tackled by optimization methods. In this work, a new approach to select the most representative electrodes is introduced. The proposed algorithm is a hybrid version of the Flower Pollination Algorithm and β-Hill Climbing optimizer called FPAβ-hc. The performance of the FPAβ-hc algorithm is evaluated using a standard EEG motor imagery dataset. The experimental results show that the FPAβ-hc can utilize less than half of the electrode numbers, achieving more accurate results than seven other methods.
A UWB-Based Lighter-Than-Air Indoor Robot for User-Centered Interactive Applications
Authors: Naheem Khawar , Elsharkawy Ahmed , Koo Dongwoo , Lee Yundong , Kim Munsang
Published: March 2022

Features such as safety and longer flight times render lighter-than-air robots strong candidates for indoor navigation applications involving people. However, the existing interactive mobility solutions using such robots lack the capability to follow a long-distance user in a relatively larger indoor space. At the same time, the tracking data delivered to these robots are sensitive to uncertainties in indoor environments such as varying intensities of light and electromagnetic field disturbances. Regarding the above shortcomings, we proposed an ultra-wideband (UWB)-based lighter-than-air indoor robot for user-centered interactive applications. We developed the data processing scheme over a robot operating system (ROS) framework to accommodate the robot’s integration needs for a user-centered interactive application. In order to explore the user interaction with the robot at a long-distance, the dual interactions (i.e., user footprint following and user intention recognition) were proposed by equipping the user with a hand-held UWB sensor. Finally, experiments were conducted inside a professional arena to validate the robot’s pose tracking in which 3D positioning was compared with the 3D laser sensor, and to reveal the applicability of the user-centered autonomous following of the robot according to the dual interactions.
Pix2Pix-Based Monocular Depth Estimation for Drones with Optical Flow on AirSim
Authors: Shimada Tomoyasu , Nishikawa Hiroki , Kong Xiangbo , Tomiyama Hiroyuki
Published: March 2022

In this work, we propose a method for estimating depth for an image of a monocular camera in order to avoid a collision for the autonomous flight of a drone. The highest flight speed of a drone is generally approximate 22.2 m/s, and long-distant depth information is crucial for autonomous flights since if the long-distance information is not available, the drone flying at high speeds is prone to collisions. However, long-range, measurable depth cameras are too heavy to be equipped on a drone. This work applies Pix2Pix, which is a kind of Conditional Generative Adversarial Nets (CGAN). Pix2Pix generates depth images from a monocular camera. Additionally, this work applies optical flow to enhance the accuracy of depth estimation. In this work, we propose a highly accurate depth estimation method that effectively embeds an optical flow map into a monocular image. The models are trained with taking advantage of AirSim, which is one of the flight simulators. AirSim can take both monocular and depth images over a hundred meter in the virtual environment, and our model generates a depth image that provides the long-distance information than images captured by a common depth camera. We evaluate accuracy and error of our proposed method using test images in AirSim. In addition, the proposed method is utilized for flight simulation to evaluate the effectiveness to collision avoidance. As a result, our proposed method is higher accuracy and lower error than a state of work. Moreover, our proposed method is lower collision than a state of work.
3D Poisson-Based Neighborhood Capacity Analysis for Millimeter Wave Communications
Authors: Comisso Massimiliano , Buttazzoni Giulia , Pastore Stefano , Vatta Francesca , Babich Fulvio
Published: March 2022

This paper proposes a theoretical model for evaluating the capacity of a millimeter wave (mmWave) source destination link when the nodes are distributed according to a three-dimensional (3D) homogeneous Poisson point process. In the presented analysis, different from the existing approaches, the destination lies in an arbitrary location with respect to the source; thus, the link performance can be evaluated for a neighbor of any order. Moreover, the developed model relies on a realistic propagation environment, characterized by path loss attenuation and shadowing in line of sight (LoS), non-LoS, and outage link state conditions. The derived formulas, which are calculated in closed-form and validated by independent Monte Carlo simulations, are used to investigate the influence of the intensity parameter, of the antenna gain, and of the mmWave frequency band on the link capacity for any possible neighbor in a practical 3D scenario.
Effect of the Dynamic Response of a Side-Wall Pressure Measurement System on Determining the Pressure Step Signal in a Shock Tube Using a Time-of-Flight Method
Authors: Svete Andrej , Hernández Castro Francisco Javier , Kutin Jože
Published: March 2022

Technological progress demands accurate measurements of rapidly changing pressures. This, in turn, requires the use of dynamically calibrated pressure meters. The shock tube enables the dynamic characterization by applying an almost ideal pressure step change to the pressure sensor under calibration. This paper evaluates the effect of the dynamic response of a side-wall pressure measurement system on the detection of shock wave passage times over the side-wall pressure sensors installed along the shock tube. Furthermore, it evaluates this effect on the reference pressure step signal determined at the end-wall of the driven section using a time-of-flight method. To determine the errors in the detection of the shock front passage times over the centers of the side-wall sensors, a physical model for simulating the dynamic response of the complete measurement chain to the passage of the shock wave was developed. Due to the fact that the use of the physical model requires information about the effective diameter of the pressure sensor, special attention was paid to determining the effective diameter of the side-wall pressure sensors installed along the shock tube. The results show that the relative systematic errors in the pressure step amplitude at the end-wall of the shock tube due to the errors in the detection of the shock front passage times over the side-wall pressure sensors are less than 0.0003%. On the other hand, the systematic errors in the phase lag of the end-wall pressure signal in the calibration frequency range appropriate for high-frequency dynamic pressure applications are up to a few tens of degrees. Since the target phase measurement uncertainty of the pressure sensors used in high-frequency dynamic pressure applications is only a few degrees, the corrections for the systematic errors in the detection of the shock front passage times over the side-wall pressure sensors with the use of the developed physical dynamic model are, therefore, necessary when performing dynamic calibrations of pressure sensors with a shock tube.
Relationships among Bicycle Rider Behaviours, Anger, Aggression, and Crashes in Finland
Authors: O’Hern Steve , Willberg Elias , Fink Christoph , Useche Sergio
Published: March 2022

Riding a bicycle is increasingly encouraged as a sustainable transport solution, especially in urban areas. However, safety concerns, both perceived and actual, can significantly lower the willingness to ride among the population. To support cycling planning and policy in the double task of increasing the levels of cycling while mitigating crash risk, there is a need to better understand the behaviours and attitudes of bicycle riders. In this manuscript, we study a cohort of Finnish bicycle riders through four questionnaires, the Cycling Behaviour Questionnaire (CBQ), Cyclist Risk Perception and Regulation Scale (RPRS), Cyclist Anger Scale (CAS), and Cyclist Aggression Expression Inventory (CAX). Our findings show low self-reported errors and violations, and high levels of knowledge regarding traffic rules among Finnish bicycle riders. Most participants report low levels of aggression, which is generally dealt with in constructive ways, while anger was most commonly a result of interactions with motor vehicles and less with other road users such as pedestrians. To further reduce the crash risk in cycling, our results point to the need for further separation between bicycle riders and motorised vehicles, and for the development of risk perception and positive behaviours among riders, particularly those engaging in risky behaviours.
Combating Ageism through Adult Education and Learning
Authors: Fragoso António , Fonseca Josélia
Published: March 2022

The demographic data and projections show that the world is ageing at a high pace and that this has transversal consequences to society. The available data on ageism show that it constitutes the most prevalent form of discrimination in Europe. Whilst this seems logical because ageism, potentially, affects everybody (unlike sexism or racism), public debates on the phenomenon are rare. The awareness of people of its importance is minimal, the resources and investigation devoted to understanding it are relatively small and the initiatives towards combating ageism are not enough. There is a mismatch between the dimension of the phenomenon and the attention that we have given it. Ageism has various negative consequences for the older adults themselves; for the institutions at large (but especially for the working world institutions) and for countries. In a fast-ageing world that will witness structural changes in age groups, ageism is a complex phenomenon that needs to be counteracted. So far, in Europe, combating ageism through law and public policy seems to have produced poor results. However, the literature shows that adult education and learning can provide very effective means to improve the mutual knowledge between generations, combat myths and prejudice and deconstruct age-based stereotypes.
Acceptance of New Formulations of Extruded Gluten Free Snacks Based on Pulse Flours by Spanish Millennial Consumers
Authors: Ciudad-Mulero Maria , Morales Patricia , Cámara Montaña , Fernández-Ruiz Virginia
Published: March 2022

Nowadays, the food industry has developed novel gluten free extruded snack type products made from pulses, which could be good candidates to promote pulse consumption as a sustainable food product, while also satisfying the consumer’s demand. Snack type products are a large part of the young people’s diets and impact health outcomes, so it is essential to offer them snacks with a better nutritional profile. In this study, 81 Spanish millennial consumers tasted “in situ” six different gluten free snacks based on pulse flour (lentil and chickpea) marketed in Spain. The aim of the present study was: (a) to evaluate the Spanish millennial consumers’ acceptance level of new pulse snack type products; (b) to evaluate the segmentation of the millennial consumers and understand the difference between the segments; (c) to evaluate the potential relationship between their nutrition food labelling and consumers’ acceptance. In general, the lentil formulations (with more protein, more fat and less fiber) obtained higher scores than those of the chickpea. In addition, a multidimensional statistical analysis, preference mapping, and a statistical analysis of agglomerative hierarchical clustering were performed. Consumers were grouped into three clusters based on their preferences, allowing a detailed study of consumer acceptance of the selected snacks. Cluster 1 like less the samples with less salt, and, on the contrary, these samples were preferred by Cluster 3. Cluster 2 is a group who like lentil snacks, regardless of their flavoring. It was observed that the consumer segments differ at least in their preference for saltiness. The findings of this study also showed that the nutritional composition of the analyzed snacks (as appears in nutrition labelling) was associated with Spanish millennial consumers’ acceptance and could provide valuable information to develop new snacks targeted at specific market niches, such as millennials. These data provide valuable insights when trying to anticipate Spanish millennial consumer acceptance of new gluten free pulse snacks.
Evaluation of the Varietal Impact of Two Citrus Species on Fluctuations of Tetranychus urticae (Acari: Tetranychidae) and Beneficial Phytoseiid Mites
Authors: Assouguem Amine , Farah Abdellah , Ullah Riaz , Korkmaz Yesim Bulak , Almeer Rafa , Sayed Amany A. , Najda Agnieszka , Lazraq Abderrahim
Published: March 2022

The activity of Tetranychus urticae Koch, 1836, and its predators (Euseius stipulatus Athias-Henriot, 1960, Typhlodromus sp., and Phytoseiulus persimilis Athias-Henriot, 1957) on two citrus varieties (Nules (Mandarin) and Valencia late (Orange)) was studied in citrus orchards in Machraa Belksiri at the Gharb region of Morocco in the years 2020–2021. In this trial, during the first year of monitoring, we detected that on the Valencia late variety (Citrus sinensis), the occupancy of leaves by T. urticae was important, with 3200 mobile forms (50%). The predator Typhlodromus sp. presented 1385 (22%), followed by E. stipilatus with 1186 mobile forms (18%), while P. persimilis presented the lowest number with 621 forms (10%). Conversely, on the Nules variety (Citrus Clementina), we found (52%) 2475 forms for the pest T. urticae. E. stipulatis was the most abandoning predator, with 1344 (28%), followed by Typhlodromus sp., with 944 (22%); however, the predator P. persimilis was absent. From our results, it can be concluded that synergistic control by these predators can reduce the rate of T. urticae and constitutes a sustainable alternative method in the absence of chemical control. Regarding the effect of the variety of the different mites studied, the varieties Nules and Valencia late showed no impact on the rates of E. 1tipulates and T. urticae, with relatively similar averages, while on the predator Typhlodromus sp. and P. persimilis, the varietal impact was important.
Landscape as a Scaling Strategy in Territorial Development
Authors: Plant Roel
Published: March 2022

This article analyses how the established but still elusive concept of ‘landscape’ may strengthen territorial development processes in the face of complexity. In times of the Anthropocene, landscapes are best treated as spaces for experiential and relational being, rather than pure social constructs or rationalised physical objects. Using basic tenets of social-ecological and social-technical systems thinking, this article tests the hypothesis that landscape, considered as a socio-technical innovation, can be harnessed in territorial development as a scaling device to achieve resilient and adaptive territories. This approach opens the perspective that the transition towards landscape-territorial development and planning can proceed in three phases. Each phase reflects a society with different degrees of awareness of the landscape. The article reflects on ways to operationalise the proposed landscape-territorial approach. It is concluded that, rather than in calls for global landscape governance, it is ultimately in reconfigured place—that is, landscapes reclaimed, developed, protected, as the local actors require it—that new spheres of control and influence over the landscape emerge.
“Pop-Up Systems”—Innovative Sport and Exercise-Oriented Offerings for Promoting Physical Activity in All-Day Schools
Authors: Ferrari Ilaria , Schuler Patricia , Bretz Kathrin , Bär Jessica , Rast Marianne , Niederberger Lukas
Published: March 2022

In all-day schools and schools with extended education, children have the opportunity to spend the whole day at school. Full-day attendance at school requires a reorientation of extended time. Therefore, it is important to consider how children spend their time between lessons and identify conducive opportunities. As part of the project “Sport in the School Environment”, multiple mobile pop-up facilities were installed at several all-day schools in Zurich, Switzerland, for a period of 3–6 weeks. These facilities included “Parkour”, “Pumptrack”, “Skatepark”, and “Streetsoccer”. The aim was to find out whether these installations offer an opportunity for physical activity (PA). At the same time, social aspects of the students using these facilities as part of their all-day school attendance were observed. The following questions were investigated: How, by whom, and in which contexts are the installations used? The use of the facilities was evaluated content-analytically and descriptively. It was shown that the facilities are used intensively and in very different ways. The main focus of the pop-up facilities is on the use of the facilities and the creation of opportunities for children and young people to exercise and meet up with each other.
Sustainability as a Moral Discourse: Its Shifting Meanings, Exclusions, and Anxieties
Authors: Yamada Shoko , Kanoi Lav , Koh Vanessa , Lim Al , Dove Michael R.
Published: March 2022

As sustainability gains popularity in public discourse, scholars have noted its diverse uses, multiple meanings, and contradictory outcomes. This paper explores how the current proliferation of the concept of sustainability stems in part from its varied normative appeals, which in turn motivate, legitimate, and unsettle its diverse mobilizations. As the concept of sustainability calls for an extension of moral horizons beyond the immediate here and now, this redrawing of moral boundaries has simultaneously produced new externalities as well as enduring anxieties and responses within these moral bounds themselves. Drawing on ethnographic and historical materials, we argue that sustainability’s moral boundaries have become both an object of scholarly critique and their own productive site of anxiety and negotiation. Questions about sustainability’s moral horizons and externalities often surface in the concept’s public deployment itself. We suggest that these tensions can be made visible by attending to the intersections between sustainability and a broader range of moral concerns at work.
Depth-Wise Separable Convolution Attention Module for Garbage Image Classification
Authors: Liu Fucong , Xu Hui , Qi Miao , Liu Di , Wang Jianzhong , Kong Jun
Published: March 2022

Currently, how to deal with the massive garbage produced by various human activities is a hot topic all around the world. In this paper, a preliminary and essential step is to classify the garbage into different categories. However, the mainstream waste classification mode relies heavily on manual work, which consumes a lot of labor and is very inefficient. With the rapid development of deep learning, convolutional neural networks (CNN) have been successfully applied to various application fields. Therefore, some researchers have directly adopted CNNs to classify garbage through their images. However, compared with other images, the garbage images have their own characteristics (such as inter-class similarity, intra-class variance and complex background). Thus, neglecting these characteristics would impair the classification accuracy of CNN. To overcome the limitations of existing garbage image classification methods, a Depth-wise Separable Convolution Attention Module (DSCAM) is proposed in this paper. In DSCAM, the inherent relationships of channels and spatial positions in garbage image features are captured by two attention modules with depth-wise separable convolutions, so that our method could only focus on important information and ignore the interference. Moreover, we also adopt a residual network as the backbone of DSCAM to enhance its discriminative ability. We conduct the experiments on five garbage datasets. The experimental results demonstrate that the proposed method could effectively classify the garbage images and that it outperforms some classical methods.
The Evaluation of Business Tools for Encouraging Social Responsibility in Older Consumers
Authors: Jakunskiene Egle , Kazlauskiene Egle
Published: March 2022

Being close to consumers, retail chains have a considerable influence on the formation of social responsibility in society. By applying various means of encouragement, these entities try to draw the attention of consumers to problems in the society and encourage them to contribute to socially responsible activities. The aim of this research was to evaluate whether the means of promoting social responsibility applied in the biggest retail chains of Lithuania selling alimentary products have an influence on a consumer and encourage them to contribute to the promotion of the idea of social responsibility. Analyses of scientific literature, qualitative approaches based on 482 in-depth interviews, analyses of data obtained during the survey, mathematical–statistical analyses and comparative analyses were applied in this research. This article represents the results of the obtained research and emphasizes the main factors promoting and limiting the social responsibility of consumers. It was identified that the social responsibility of consumers in the field of environmental protection is formed by information provided by business entities, company images and other people surrounding the consumer. Social responsibility in the field of charity and support was influenced by information provided by business entities and other people’s opinions. Furthermore, the article concludes with the development of models showing which elements business entities should orient towards in order to promote the social responsibility of consumers in the field of environmental protection or charity and support. The compiled model can be used by all business subjects acting in the retail trade and trying to encourage users to become involved in socially responsible activities.
Critical Success Factors for Concrete Recycling in Construction Projects
Authors: Badraddin Abdulmalek K. , Radzi Afiqah R. , Almutairi Saud , Rahman Rahimi A.
Published: March 2022

This study explores the success factors of concrete recycling in construction projects, using Malaysia as a case study. The objectives include (1) identifying the critical success factors for concrete recycling in construction projects, (2) comparing the critical success factors between large enterprises (LEs) and small–medium enterprises (SMEs), and (3) developing constructs that group the critical success factors. First, a list of success factors was identified through semi-structured interviews with fifteen construction industry professionals and a systematic literature review of journal articles. This list was then incorporated into a questionnaire and disseminated to industry professionals. Eighty-nine valid responses were collected and analyzed using mean score ranking, normalization, agreement analysis, and factor analysis techniques. The analyses showed ten critical success factors for concrete recycling. The critical success factors include the availability of uniform standards for concrete recycling, adequate awareness among project stakeholders on concrete recycling, appropriate construction waste management plans, government policies to support concrete recycling, good marketing strategy for concrete recycling, good communication among employees, applications for recycled concrete in sub-industries, provisions in work method statements on concrete recycling, positive legislation toward concrete recycling, and availability of concrete recycling infrastructure. However, the percentage of agreement between SMEs and LEs for the ten critical success factors was only 22%. In other words, there is no consensus on criticality across organizational sizes. Finally, the critical success factors can be categorized into two interrelated groups: external and internal. This study contributes to the literature by analyzing the necessary success factors for concrete recycling. The study findings allow researchers and practitioners to develop strategies to promote concrete recycling.
Can High Levels of Hindrance Demands Increase the Worker’s Intellectual Response?
Authors: Martín-Martín Francisco G. , Díaz-Fúnez Pedro A. , Durniat Katarzyna , Salvador-Ferrer Carmen María , Llopis-Marín Juan Manuel , Limbert Caroline , Mañas-Rodríguez Miguel Ángel
Published: March 2022

Job demands are factors that are associated with a physical and psychological cost when it comes to coping with them, but which can also positively affect the motivational process. Demands such as overload, defined as an excessive workload, have not presented positive results in any of the studies that have related it to employee engagement. The present study aims to delve into the possible positive effect of this demand on the intellectual bonding of employees. It is hypothesized that: (a) Initially, the increase in the perception of work overload will show a negative influence on the intellectual engagement of the employees; but (b) high perceptions of overload will change this effect, producing an increase in the intellectual dimension of engagement. The sample is made up of 706 employees of a Spanish multinational company. The results support this asymmetric curvilinear influence. The level of intellectual engagement is significantly reduced when the role overload increases from the lower values of the scale. However, upon reaching high levels of role overload, the intellectual engagement response begins to grow. These results challenge the conceptualization of overload as only negative and opens the door to consider that the positive response to a demand can also occur at high levels of it.
Evaluation of the Response of Grain Productivity to Different Arable Land Allocation Intensities in the Land Use Planning System of China
Authors: Yin Guanyi , Lou Yi , Xie Shuai , Wei Wei
Published: March 2022

This study measured the spatio-temporal change of the Arable Land Allocation Intensity (ALAI), and established a toughness index to evaluate the responses of grain productivities to the ALAIs in 31 provinces. The results show that the ALAI decreased in 31 provinces during 2005–2020, whereas the grain productivity responses differed. Though China’s Major Grain producing areas (CMGPA) experienced decreasing arable land allocation intensities compared with the non-CMGPAs, they still showed a robust toughness of grain productivity. The spatial barycenter of grain productivity moved towards Northeast China, which was much faster and further than the northwest movement of the ALAI, indicating a dislocated motion of grain production and ALAI. In all, both the toughness of grain productivity and the tightening arable land allocation intensities were apparent in the CMGPAs, especially in the northeastern CMGPAs in China. In order to improve the grain productivity on shrinking arable land resources, this study suggests that we tighten the quota of arable land transformed into construction land, improve the per-unit grain yield, and enhance the remote sensing technology and field surveys to better monitor the local governments’ performance in arable land management.
Intergenerational Occupational Mobility, Labor Migration and Sustained Demographic Dividends
Authors: Yu Anqi , Liu Guankun , Gao Yuning
Published: March 2022

Based on the 1% sample survey of the National Population Census (2015), this paper empirically analyzes the impact of intergenerational occupational mobility levels on labor migration in terms of push and pull factors. We found that increasing the degree of intergenerational occupational mobility has a significant “agglomeration effect” on registered and mobile labor: reducing the emigration willingness of household registered labor and increasing the immigration probability of labor from cities with a lower degree of intergenerational occupational mobility. Labor migration generally occurs from cities with lower intergenerational occupational mobility to cities with a higher degree of intergenerational occupational mobility. The heterogeneity analysis reveals that the agglomeration effect of a city on native labor is insignificant in east, northwest and northeast China. Rural laborers, highly educated laborers and rural laborers with high education levels are more likely to move from their registered cities. The mechanism analysis finds that improving the city’s comprehensive economic incremental competitiveness will enhance the city’s agglomeration effect on native labor, while increasing the degree of educational returns will strengthen the city’s agglomeration effect on mobile labor from cities with a lower degree of intergenerational mobility. Moreover, after using IV-probit, IV-2SLS and heteroscedasticity-based IVs to deal with endogenous problems, the above conclusions are still robust. Our findings may contribute to realizing sustained demographic dividends through internal migration.
Impact of Government Subsidy Strategies on Supply Chains Considering Carbon Emission Reduction and Marketing Efforts
Authors: Yuan Shengjun , Li Jie , Su Xin
Published: March 2022

This study analyzes the impact of different government subsidies on supply chain members under the low-carbon policy. Using the theory and the Stackelberg game method, we derive the equilibrium decision of diverse government subsidy models on the carbon emission reduction efforts and marketing efforts of supply chain members when manufacturers are dominant. We found that government subsidies positively influenced the carbon emission reduction efforts and marketing efforts of supply chain members and could increase the overall profit of the supply chain and the overall welfare of society. Meanwhile, social welfare increased first and then decreased with the subsidy, and there was a maximum value. Within a certain threshold, when the market demand was sensitive to carbon emission reduction efforts, it was more beneficial to subsidize manufacturers, and when it was sensitive to marketing efforts, subsidizing retailers was more beneficial. Regardless of the subsidy situation, an optimal subsidy rate exists among supply chain members. Meanwhile, adjusting government subsidy measures can decrease the profit gap between supply chain members, and it provides potential possibilities for cooperation among supply chain members.
Investigating Company’s Technical Development Directions Based on Internal Knowledge Inheritance and Inventor Capabilities: The Case of Samsung Electronics
Authors: Han Fang , Yoon Sejun , Raghavan Nagarajan , Park Hyunseok
Published: March 2022

This paper proposes a new method to analyze technical development directions of a company using knowledge persistence-based main path analysis and co-inventor network analysis. Main path analysis is used for identifying internal technical knowledge flows and inheritances over time within a company, and knowledge persistence-based main path analysis can well identify major knowledge streams of each sub-domain within a relatively small knowledge network generated by one company without omission of significant inventions. A co-inventor network analysis is used for identifying key inventors who can be represented as the major technical capabilities of a company. The method is a meaningful attempt in that it applies knowledge persistence-based main path analysis to analyzing a company’s internal technical development and combines the two approaches to provide the information on both base technical capabilities and new technical characteristics. To test the method, this paper conducted an empirical study of Samsung Electronics. The results show that the method generated major knowledge flows and identified key inventors of Samsung Electronics. In particular, the method can identify the base technical knowledge as the ‘backbone’ and newly injected knowledge as ‘fresh blood’ for forecasting future technical development. Based on the identified clue information, this paper forecasted the potential future technologies for each sub-domain of Samsung Electronics with technical keywords and descriptions.