bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comparative Study on the Vertical Structures and Microphysical Properties of Stratiform Precipitation over South China and the Tibetan Plateau
Authors: He Jingshu , Zheng Jiafeng , Zeng Zhengmao , Che Yuzhang , Zheng Min , Li Jianjie
Published: July 2021

Under different water vapor and dynamic conditions, and the influence of topographies and atmospheric environments, stratiform precipitation over South China and the Tibetan Plateau can produce different features. In this study, stratiform precipitation vertical characteristics, bright-band (BB) microstructures, and the vertical variations of the raindrop size distribution (DSD) over a low-altitude site (Longmen site, 86 m) in South China and a high-altitude site (Nagqu site, 4507 m) on the Tibetan Plateau were comprehensively investigated and compared using measurements from a Ka-band millimeter-wave cloud radar (CR), a K-band microrain radar (MRR), and a Parsivel disdrometer (disdrometer). A reliable BB identification scheme was proposed on the basis of CR variables and used for stratiform precipitation sample selection and further statistics and analysis. Results indicate that melting layers over the Longmen are much higher and slightly thicker than those over the Nagqu due to significant differences in atmospheric conditions. For stratiform precipitation, vertical air motions and radar variables over the two sites show different variation trends from cloud top to the ground. Vertical air motions are very weak in the stratiform precipitation over the Longmen, whereas updrafts are more active over the Nagqu. Above the melting layer, radar equivalent reflectivity factor Ze (mean Doppler velocity VM) gradually increases (decreases) as height decreases over the two sites, but the aggregation rate for ice particles over the Longmen can be faster. In the melting layer, Ze (VM) at the BB bottom/center over the Longmen is larger (smaller) than those over the Nagqu for the reason that melted raindrops in the melting layers over the Longmen are larger than those over the Nagqu. Below the melting layer, profiles of radar variables and DSDs show completely different behaviors over the two sites, which reflects that the collision, coalescence, evaporation, and breakup processes of raindrops are different between the two sites. Over the Longmen, collision and coalescence dominate the precipitation properties; in particular, from 2.0–2.8 km, the breakup process competes with collision–coalescence processes but later is overpowered. In contrast, due to the lower BB heights over the Nagqu, collision and coalescence dominate raindrop properties. Comparisons of raindrop spectra suggest that the concentration of small (medium-to-large) raindrops over the Nagqu is much higher (slightly lower) than that over the Longmen. Therefore, the mass-weighted mean diameter Dm (the generalized intercept parameter Nw) over the Nagqu is smaller (larger) than that over the Longmen.
Limitations of Foot-Worn Sensors for Assessing Running Power
Authors: Baumgartner Tobias , Held Steffen , Klatt Stefanie , Donath Lars
Published: July 2021

Running power as measured by foot-worn sensors is considered to be associated with the metabolic cost of running. In this study, we show that running economy needs to be taken into account when deriving metabolic cost from accelerometer data. We administered an experiment in which 32 experienced participants (age = 28 ± 7 years, weekly running distance = 51 ± 24 km) ran at a constant speed with modified spatiotemporal gait characteristics (stride length, ground contact time, use of arms). We recorded both their metabolic costs of transportation, as well as running power, as measured by a Stryd sensor. Purposely varying the running style impacts the running economy and leads to significant differences in the metabolic cost of running (p < 0.01). At the same time, the expected rise in running power does not follow this change, and there is a significant difference in the relation between metabolic cost and power (p < 0.001). These results stand in contrast to the previously reported link between metabolic and mechanical running characteristics estimated by foot-worn sensors. This casts doubt on the feasibility of measuring running power in the field, as well as using it as a training signal.
Real-Time In-Vehicle Air Quality Monitoring System Using Machine Learning Prediction Algorithm
Authors: Goh Chew Cheik , Kamarudin Latifah Munirah , Zakaria Ammar , Nishizaki Hiromitsu , Ramli Nuraminah , Mao Xiaoyang , Syed Zakaria Syed Muhammad Mamduh , Kanagaraj Ericson , Abdull Sukor Abdul Syafiq , Elham Md. Fauzan
Published: July 2021

This paper presents the development of a real-time cloud-based in-vehicle air quality monitoring system that enables the prediction of the current and future cabin air quality. The designed system provides predictive analytics using machine learning algorithms that can measure the drivers’ drowsiness and fatigue based on the air quality presented in the cabin car. It consists of five sensors that measure the level of CO2, particulate matter, vehicle speed, temperature, and humidity. Data from these sensors were collected in real-time from the vehicle cabin and stored in the cloud database. A predictive model using multilayer perceptron, support vector regression, and linear regression was developed to analyze the data and predict the future condition of in-vehicle air quality. The performance of these models was evaluated using the Root Mean Square Error, Mean Squared Error, Mean Absolute Error, and coefficient of determination (R2). The results showed that the support vector regression achieved excellent performance with the highest linearity between the predicted and actual data with an R2 of 0.9981.
Towards Measuring Terahertz Photon Statistics by a Superconducting Bolometer
Authors: Prudkovskii Pavel , Leontyev Andrey , Kuznetsov Kirill , Kitaeva Galiya
Published: July 2021

Statistical distributions of the analog readings of an antenna-coupled THz superconducting bolometer were measured and analyzed under a special type of irradiation by low-energy fluxes of THz photons with Poisson photon statistics and controllable mean photon numbers. The photons were generated via low-gain parametric down-conversion in pulse-pumped Mg:LiNbO3 crystal placed to a cooled cryostat together with the bolometer NbN film. Results of theoretical approximation of experimental histograms reveal the discrete nature of THz detection by superconducting bolometers and open a way for studying their quantum characteristics. It is shown that bolometer readings per pulse consist of discrete counts (“single charges”), with the mean number linearly dependent on the number of input photons. Contributions of single counts to a total analog reading are statistically distributed according to the normal law, with average values slightly depending on the number of counts in each reading. A general formula is proposed to describe the relationship between continuous statistical distribution of the bolometer readings and discrete quantum statistics of the incident photons.
A Deep Dive of Autoencoder Models on Low-Contrast Aquatic Images
Authors: Lee Rich C. , Chen Ing-Yi
Published: July 2021

Public aquariums and similar institutions often use video as a method to monitor the behavior, health, and status of aquatic organisms in their environments. These video footages take up a sizeable amount of space and require the use of autoencoders to reduce their file size for efficient storage. The autoencoder neural network is an emerging technique which uses the extracted latent space from an input source to reduce the image size for storage, and then reconstructs the source within an acceptable loss range for use. To meet an aquarium’s practical needs, the autoencoder must have easily maintainable codes, low power consumption, be easily adoptable, and not require a substantial amount of memory use or processing power. Conventional configurations of autoencoders often provide results that perform beyond an aquarium’s needs at the cost of being too complex for their architecture to handle, while few take low-contrast sources into consideration. Thus, in this instance, “keeping it simple” would be the ideal approach to the autoencoder’s model design. This paper proposes a practical approach catered to an aquarium’s specific needs through the configuration of autoencoder parameters. It first explores the differences between the two of the most widely applied autoencoder approaches, Multilayer Perceptron (MLP) and Convolution Neural Networks (CNN), to identify the most appropriate approach. The paper concludes that while both approaches (with proper configurations and image preprocessing) can reduce the dimensionality and reduce visual noise of the low-contrast images gathered from aquatic video footage, the CNN approach is more suitable for an aquarium’s architecture. As an unexpected finding of the experiments conducted, the paper also discovered that by manipulating the formula for the MLP approach, the autoencoder could generate a denoised differential image that contains sharper and more desirable visual information to an aquarium’s operation. Lastly, the paper has found that proper image preprocessing prior to the application of the autoencoder led to better model convergence and prediction results, as demonstrated both visually and numerically in the experiment. The paper concludes that by combining the denoising effect of MLP, CNN’s ability to manage memory consumption, and proper image preprocessing, the specific practical needs of an aquarium can be adeptly fulfilled.
Printed Circuit Board Defect Detection Using Deep Learning via A Skip-Connected Convolutional Autoencoder
Authors: Kim Jungsuk , Ko Jungbeom , Choi Hojong , Kim Hyunchul
Published: July 2021

As technology evolves, more components are integrated into printed circuit boards (PCBs) and the PCB layout increases. Because small defects on signal trace can cause significant damage to the system, PCB surface inspection is one of the most important quality control processes. Owing to the limitations of manual inspection, significant efforts have been made to automate the inspection by utilizing high resolution CCD or CMOS sensors. Despite the advanced sensor technology, setting the pass/fail criteria based on small failure samples has always been challenging in traditional machine vision approaches. To overcome these problems, we propose an advanced PCB inspection system based on a skip-connected convolutional autoencoder. The deep autoencoder model was trained to decode the original non-defect images from the defect images. The decoded images were then compared with the input image to identify the defect location. To overcome the small and imbalanced dataset in the early manufacturing stage, we applied appropriate image augmentation to improve the model training performance. The experimental results reveal that a simple unsupervised autoencoder model delivers promising performance, with a detection rate of up to 98% and a false pass rate below 1.7% for the test data, containing 3900 defect and non-defect images.
An Economic Analysis of the Shading Effects of Transmission Lines on Photovoltaic Power Plant Investment Decisions: A Case Study
Authors: Zsiborács Henrik , Baranyai Nóra Hegedűsné , Vincze András , Pintér Gábor
Published: July 2021

In today’s photovoltaic (PV) power plants, traditional crystalline PV modules are the prevalent technology, which is highly susceptible to partial shading due to the risk of irreversible damage. Therefore, it is advisable to explore potential construction sites for objects that might cause shading, including high-voltage transmission towers, whose shading effects can be significant due to their height. By means of innovative simulation, using a model, validated with actual data, this study endeavored to deliver novel information related to the problems of shading by high-voltage transmission lines. In the context of Hungary, it examined the risk factors, technical and economic aspects, and possible solutions important for PV projects. It provides new insight, much needed also at the international level, considering the fact that the extent of the shadows cast by conductors on the surface at low Sun elevations is not known at present and neither are the shading characteristics of conductors between two transmission towers, depending on their height, in winter, when the Sun is low. An added practical benefit of the study is that its technical and economic approaches and the software solutions are all based on the practice of PV system design and construction. Related to the investigated issues, this can facilitate the formulation of the technical and economic aspects of suitable PV power plant building strategies in Hungary.
Fractional Derivative Modification of Drude Model
Authors: Karpiński Karol , Zielińska-Raczyńska Sylwia , Ziemkiewicz David
Published: July 2021

A novel, two-parameter modification of a Drude model, based on fractional time derivatives, is presented. The dielectric susceptibility is calculated analytically and simulated numerically, showing good agreement between theoretical description and numerical results. The absorption coefficient and wave vector are shown to follow a power law in the frequency domain, which is a common phenomenon in electromagnetic and acoustic wave propagation in complex media such as biological tissues. The main novelty of the proposal is the introduction of two separate parameters that provide a more flexible model than most other approaches found in the literature. Moreover, an efficient numerical implementation of the model is presented and its accuracy and stability are examined. Finally, the model is applied to an exemplary soft tissue, confirming its flexibility and usefulness in the context of medical biosensors.
Retrospective IP Address Geolocation for Geography-Aware Internet Services
Authors: Komosny Dan
Published: July 2021

The paper deals with the locations of IP addresses that were used in the past. This retrospective geolocation suffers from continuous changes in the Internet space and a limited availability of past IP location databases. I analyse the retrospective geolocation of IPv4 and IPv6 addresses over five years. An approach is also introduced to handle missing past IP geolocation databases. The results show that it is safe to retrospectively locate IP addresses by a couple of years, but there are differences between IPv4 and IPv6. The described parametric model of location lifetime allows us to estimate the time when the address location changed in the past. The retrospective geolocation of IP addresses has a broad range of applications, including social studies, system analyses, and security investigations. Two longitudinal use cases with the applied results are discussed. The first deals with geotargeted online content. The second deals with identity theft prevention in e-commerce.
E-Tongues/Noses Based on Conducting Polymers and Composite Materials: Expanding the Possibilities in Complex Analytical Sensing
Authors: Sierra-Padilla Alfonso , García-Guzmán Juan José , López-Iglesias David , Palacios-Santander José María , Cubillana-Aguilera Laura
Published: July 2021

Conducting polymers (CPs) are extensively studied due to their high versatility and electrical properties, as well as their high environmental stability. Based on the above, their applications as electronic devices are promoted and constitute an interesting matter of research. This review summarizes their application in common electronic devices and their implementation in electronic tongues and noses systems (E-tongues and E-noses, respectively). The monitoring of diverse factors with these devices by multivariate calibration methods for different applications is also included. Lastly, a critical discussion about the enclosed analytical potential of several conducting polymer-based devices in electronic systems reported in literature will be offered.
Digital Hologram Watermarking Based on Multiple Deep Neural Networks Training Reconstruction and Attack
Authors: Kang Ji-Won , Lee Jae-Eun , Choi Jang-Hwan , Kim Woosuk , Kim Jin-Kyum , Kim Dong-Wook , Seo Young-Ho
Published: July 2021

This paper proposes a method to embed and extract a watermark on a digital hologram using a deep neural network. The entire algorithm for watermarking digital holograms consists of three sub-networks. For the robustness of watermarking, an attack simulation is inserted inside the deep neural network. By including attack simulation and holographic reconstruction in the network, the deep neural network for watermarking can simultaneously train invisibility and robustness. We propose a network training method using hologram and reconstruction. After training the proposed network, we analyze the robustness of each attack and perform re-training according to this result to propose a method to improve the robustness. We quantitatively evaluate the results of robustness against various attacks and show the reliability of the proposed technique.
Use of Long Short-Term Memory for Remaining Useful Life and Degradation Assessment Prediction of Dental Air Turbine Handpiece in Milling Process
Authors: Huang Yi-Cheng , Chen Yu-Hsien
Published: July 2021

The complexity of the internal components of dental air turbine handpieces has been increasing over time. To make operations reliable and ensure patients’ safety, this study established long short-term memory (LSTM) prediction models with the functions of learning, storing, and transmitting memory for monitoring the health and degradation of dental air turbine handpieces. A handpiece was used to cut a glass porcelain block back and forth. An accelerometer was used to obtain vibration signals during the free running of the handpiece to identify the characteristic frequency of these vibrations in the frequency domain. This information was used to establish a health index (HI) for developing prediction models. The many-to-one and many-to-many LSTM frameworks were used for machine learning to establish prediction models for the HI and degradation trajectory. The results indicate that, in terms of HI predicted for the testing dataset, the mean square error of the many-to-one LSTM framework was lower than that that of a logistic regression model, which did not have a memory framework. Nevertheless, high accuracies were achieved with both of the two aforementioned approaches. In general, the degradation trajectory prediction model could accurately predict the degradation trend of the dental handpiece; thus, this model can be a useful tool for predicting the degradation trajectory of real dental handpieces in the future.
Measurement and Estimation of Spectral Sensitivity Functions for Mobile Phone Cameras
Authors: Tominaga Shoji , Nishi Shogo , Ohtera Ryo
Published: July 2021

Mobile phone cameras are often significantly more useful than professional digital single-lens reflex (DSLR) cameras. Knowledge of the camera spectral sensitivity function is important in many fields that make use of images. In this study, methods for measuring and estimating spectral sensitivity functions for mobile phone cameras are developed. In the direct measurement method, the spectral sensitivity at each wavelength is measured using monochromatic light. Although accurate, this method is time-consuming and expensive. The indirect estimation method is based on color samples, in which the spectral sensitivities are estimated from the input data of color samples and the corresponding output RGB values from the camera. We first present an imaging system for direct measurements. A variety of mobile phone cameras are measured using the system to create a database of spectral sensitivity functions. The features of the measured spectral sensitivity functions are then studied using principal component analysis (PCA) and the statistical features of the spectral functions extracted. We next describe a normal method to estimate the spectral sensitivity functions using color samples and point out some drawbacks of the method. A method to solve the estimation problem using the spectral features of the sensitivity functions in addition to the color samples is then proposed. The estimation is stable even when only a small number of spectral features are selected. Finally, the results of the experiments to confirm the feasibility of the proposed method are presented. We establish that our method is excellent in terms of both the data volume of color samples required and the estimation accuracy of the spectral sensitivity functions.
Construction of Fluorescent Immunosensor Quenchbody to Detect His-Tagged Recombinant Proteins Produced in Bioprocess
Authors: Ning Xuerao , Yasuda Takanobu , Kitaguchi Tetsuya , Ueda Hiroshi
Published: July 2021

With the widespread application of recombinant DNA technology, many useful substances are produced by bioprocesses. For the monitoring of the recombinant protein production process, most of the existing technologies are those for the culture environment (pH, O2, etc.). However, the production status of the target protein can only be known after the subsequent separation and purification process. To speed up the monitoring of the production process and screening of the higher-yield target protein variants, here we developed an antibody-based His-tag sensor Quenchbody (Q-body), which can quickly detect the C-terminally His-tagged recombinant protein produced in the culture medium. Compared with single-chain Fv-based Q-body having one dye, the Fab-based Q-body having two dyes showed a higher response. In addition, not only was fluorescence response improved but also detection sensitivity by the mutations of tyrosine to tryptophan in the heavy chain CDR region. Moreover, the effect of the mutations on antigen-binding was successfully validated by molecular docking simulation by CDOCKER. Finally, the constructed Q-body was successfully applied to monitor the amount of anti-SARS CoV-2 nanobody secreted into the Brevibacillus culture media.
Post-Drive Standing Balance of Vehicle Passengers Using Wearable Sensors: The Effect of On-Road Driving and Task Performance
Authors: Le Victor C. , Jones Monica L. H. , Sienko Kathleen H.
Published: July 2021

Postural sway has been demonstrated to increase following exposure to different types of motion. However, limited prior studies have investigated the relationship between exposure to normative on-road driving conditions and standing balance following the exposure. The purpose of this on-road study was to quantify the effect of vehicle motion and task performance on passengers’ post-drive standing balance performance. In this study, trunk-based kinematic data were captured while participants performed a series of balance exercises before and after an on-road driving session in real-time traffic. Postural sway for all balance exercises increased following the driving session. Performing a series of ecologically relevant visual-based tasks led to increases in most post-drive balance metrics such as sway position and velocity. However, the post-drive changes following the driving session with a task were not significantly different compared to changes observed following the driving session without a task. The post-drive standing balance performance changes observed in this study may increase vulnerable users’ risk of falling. Wearable sensors offer an opportunity to monitor postural sway following in-vehicle exposures.
Continuous Fusion of Motion Data Using an Axis-Angle Rotation Representation with Uniform B-Spline
Authors: Hu Haohao , Beck Johannes , Lauer Martin , Stiller Christoph
Published: July 2021

The fusion of motion data is key in the fields of robotic and automated driving. Most existing approaches are filter-based or pose-graph-based. By using filter-based approaches, parameters should be set very carefully and the motion data can usually only be fused in a time forward direction. Pose-graph-based approaches can fuse data in time forward and backward directions. However, pre-integration is needed by applying measurements from inertial measurement units. Additionally, both approaches only provide discrete fusion results. In this work, we address this problem and present a uniform B-spline-based continuous fusion approach, which can fuse motion measurements from an inertial measurement unit and pose data from other localization systems robustly, accurately and efficiently. In our continuous fusion approach, an axis-angle is applied as our rotation representation method and uniform B-spline as the back-end optimization base. Evaluation results performed on the real world data show that our approach provides accurate, robust and continuous fusion results, which again supports our continuous fusion concept.
Measurements of Excavation Damaged Zone by Using Fiber Bragg Grating Stress Sensors
Authors: Wan Xiaorong , Li Chuan , Zhao Zhengang , Zhang Dacheng , Li Yingna , Zhang Jiahong
Published: July 2021

In this paper, a Fiber Bragg Grating (FBG) stress sensor is developed to measure the stress variation between the lower Excavation Damaged Zone (EDZ) and the upper undistributed rock. The disturbance brought by the environmental temperature can be differentially compensated with two FBGs mounted symmetrically on the spokes. Through finite element analysis, it can be known that the direct stress and shear stress are pointed at the angles of 45° and 60° on both sides of the coal mine roadway, respectively. The anchor ends of the sensors are installed into the upper undistributed rock and the bolt tails of the mine roadway with a depth of 700 m and fastened by nuts to secure the load sensing device on the surface of the rock. When the shallow foundation of surrounding rock is pressed and deformed toward the coal mining road, the structural modifications can be converted into the stress of rock bolt and the strain of spoke. Thus, the FBG mounted on the surface of the spoke receives the shift information of the Bragg wavelength. The monitoring results indicate that the FBG stress sensors are sensitive to the variation of the EDZ. During the blasting, the stress amplitude varies from 40.256 to 175.058 kPa, and the creep time changes from 21 to 74 min. The proposed method can be applied in the field of underground coal mines for safety condition monitoring of the EDZ and forecasting the coal mine roadway stability.
A Scoping Review of Pressure Measurements in Prosthetic Sockets of Transfemoral Amputees during Ambulation: Key Considerations for Sensor Design
Authors: Ko Siu-Teing , Asplund Fredrik , Zeybek Begum
Published: July 2021

Sensor systems to measure pressure at the stump–socket interface of transfemoral amputees are receiving increasing attention as they allow monitoring to evaluate patient comfort and socket fit. However, transfemoral amputees have many unique characteristics, and it is unclear whether existing research on sensor systems take these sufficiently into account or if it is conducted in ways likely to lead to substantial breakthroughs. This investigation addresses these concerns through a scoping review to profile research regarding sensors in transfemoral sockets with the aim of advancing and improving prosthetic socket design, comfort and fit for transfemoral amputees. Publications found from searching four scientific databases were screened, and 17 papers were found relating to the aim of this review. After quality assessment, 12 articles were finally selected for analysis. Three main contributions are provided: a de facto methodology for experimental studies on the implications of intra-socket pressure sensor use for transfemoral amputees; the suggestion that associated sensor design breakthroughs would be more likely if pressure sensors were developed in close combination with other types of sensors and in closer cooperation with those in possession of an in-depth domain knowledge in prosthetics; and that this research would be facilitated by increased interdisciplinary cooperation and open research data generation.
Working for the Welfare: Support and Supervision Needs of Indigenous Australian Child Protection Practitioners
Authors: Oates Fiona , Malthouse Kaylene
Published: July 2021

Aboriginal and Torres Strait Islander children are disproportionately represented in all parts of the child protection system in Australia. The recruitment of Aboriginal and Torres Strait Islander practitioners into child protection systems to work with Indigenous families at risk underpins the government strategy to reduce this over-representation. However, little is known about the experiences of Indigenous people who undertake child protection work or what their support and supervision needs may be. This research is centered on Indigenous Australian child protection practitioners as experts in their own experiences and as such includes large excerpts of their own narratives throughout. Practitioner narratives were collected via qualitative semi-structured in-depth interviews. Critical theory and decolonising frameworks underpinned the research design. The study found that Indigenous child protection practitioners have a unique place in the families, communities and profession. Many viewed their work in the child protection field as an extension of their Indigeneity. This coupled with the historical experience of state-sanctioned removal of Indigenous children during colonisation and contemporarily, informs the need for child protection workplaces to re-think the support and supervision afforded to Indigenous practitioners.
“Divide, Divert, & Conquer” Deconstructing the Presidential Framing of White Supremacy in the COVID-19 Era
Authors: Louie Vivian , Viladrich Anahí
Published: July 2021

Based on the analysis of President Donald J. Trump’s social media, along with excerpts from his speeches and press releases, this study sheds light on the framing of white supremacy during the first months of the COVID-19 pandemic in the United States. Our findings reveal that the triad of divide, divert, and conquer was crucial to Trump’s communications strategy. We argue that racist nativism—or racialized national threats to American security—is key to comprehending the external divisiveness in this strategy. When Trump bitterly cast China as the cause of America’s pandemic fallout and Mexico as the source of other key American problems (i.e., crime and low-paid jobs for U.S.-born Americans), he sowed clear racialized divisions between the United States (U.S.). and these two nations. We further argue that nativist racism—or the framing of descendants from those nations as incapable of ever being American—is key to comprehending the internal divisiveness in the former President’s pandemic rhetoric. Trump’s framing of China and Mexico as enemies of America further found its culprits in Asian and Latino Americans who were portrayed as COVID-19 carriers. Trump’s narrative was ultimately geared to diverting attention from his administration’s mishandling of COVID-19, the dismal structural conditions faced by detained and undocumented Latinos, and the anti-Asian bias faced by some of his Asian American constituents. In the conclusions, this article makes a call for countering white supremacy by developing comparative approaches that pay more attention to how different racisms play out for different groups.
Determinants of the Arab Spring Protests in Tunisia, Egypt, and Libya: What Have We Learned?
Authors: Barakat Zahraa , Fakih Ali
Published: July 2021

This paper provides empirical evidence on the determinants of protest participation in Arab Spring countries that witnessed major uprisings and in which social unrest was most pronounced. Namely, this paper investigates the latter in Tunisia, Egypt, and Libya using a micro-level data survey, the Arab Transformation Survey (2015). The findings of our probit regression analysis reveal that gender, trust in government, corruption concern, and social media usage have influenced the individual’s perception of protest activism. We find evidence that the role of economic factors was inconsistent, whereas political grievances were more clearly related to the motive to participate in the uprisings. We then control for country-specific effects whereby results show that citizens in each country showed different characteristics of participation. The findings of this research would set the ground for governments to better assess the health of their societies and be a model of governance in the Middle East.
The Diffusion Mechanism of Megaproject Citizenship Behavior: The Role of Institutional Isomorphism
Authors: Yang Delei , Zhu Jun , Cui Qingbin , He Qinghua , Zheng Xian
Published: July 2021

Megaproject citizenship behavior (MCB) has been confirmed to a play vital role on megaproject performance. Although current research has argued that institution elements have had an impact on MCB diffusion, limited studies have empirically investigated the distinct effectiveness of various institution elements on driving MCB’s widespread diffusion in construction megaprojects. Based on institution theory, this study proposes a theoretical model comprising institutional elements (i.e., normative and mimetic isomorphism), owner’s support, relationship-based trust, and their effect or impact on MCB’s diffusion. Based on 171 industrial questionnaires collected from managers of contractors and designers in megaprojects. Partial least squares structural equation modeling (PLS-SEM) was used to validate the established model. The results indicated that both normative and mimetic isomorphism have positive effects on facilitating MCB diffusion, and owner’s support has shown partial mediation in promoting MCB diffusion through normative isomorphism, as well as full mediation in the promoting of MCB diffusion through mimetic isomorphism. Meanwhile, relationship-based trust exerts a positive moderating effect on the relationship between mimetic isomorphism and MCB. This study extends current literature on driving MCB diffusion from the perspective of institutional theory, contributing by providing four implications for megaprojects managers to “buy in” more extensive MCB.
Non-Chemical Control of Annual Bluegrass (Poa annua) in Bermudagrass (Cynodon spp.) via Fraise Mowing: Efficacy and Barriers to Adoption
Authors: Carroll Devon E. , Brosnan James T. , Unruh J. Bryan , Stephens Carrie A. , McKeithen Chase , Boeri Pablo A.
Published: July 2021

Fraise mowing is a maintenance practice that may serve as a non-chemical means of controlling the problematic weed annual bluegrass (Poa annua L.) in bermudagrass (Cynodon spp.) given reports of efficacy on other turfgrass species. However, an understanding of practitioner decision-making in implementing fraise mowing as a weed-control measure remains unknown. A field study was conducted in Knoxville, TN and repeated in space in Jay, FL during summer 2019 to assess bermudagrass regrowth and subsequent annual bluegrass control, following fraise mowing at depths of 1.5 and 3.0 cm compared to a non-treated check (0 cm). Bermudagrass recovered more quickly at the 1.5 cm depth than the 3.0 cm depth and was the swiftest in Florida. Fraise mowing at either depth resulted in a 41–97% reduction in annual bluegrass populations. A qualitative study was conducted in spring 2021, which engaged eight turfgrass managers from Tennessee and Florida via individual interviews in order to understand barriers and challenges to fraise mowing application. Turfgrass managers had positive views of fraise mowing but described challenges in implementation for weed control including cost, labor, area closure, and debris removal.
Implementing Strategic Sustainable Supply Chain Management
Authors: Bratt Cecilia , Sroufe Robert , Broman Göran
Published: July 2021

Despite increasing business interest in sustainability in general and in sustainable supply chain management (SSCM), the ability to increase suppliers’ ecological and social performance is generally insufficient for many companies. In this study, we outline an implementation process model for sustainable supply chain management. We do so by synthesizing insights from a review of the sustainable supply chain management and organizational learning literature and a case study with a company aspiring to become a global leader in sustainable lighting. By combining these insights, we find that successful implementation of sustainable supply chain management requires sustainability to be anchored in a company’s vision and integrated into all functions. We also argue that organizational learning, especially learning with external stakeholders such as suppliers, an operational definition of socioecological sustainability among stakeholders, and procedural support for the cocreation of strategic plans for change are vital for achieving a truly sustainable supply chain. This definition and cocreation allow for attention to be directed toward strategic ecological and social practices, along with the joint handling of tradeoffs and economic considerations among stakeholders. As we build a foundation for an SSCM implementation process model, we use a science-based framework for strategic sustainable development. We call for more action-based research to uncover the complex nature of sustainable supply chain management, as there are unique challenges and dynamic relationships in every supply chain.
Macroecology of North European Wet Grassland Landscapes: Habitat Quality, Waders, Avian Predators and Nest Predation
Authors: Manton Michael , Angelstam Per
Published: July 2021

Wet grassland degradation is a global issue that involves both altered land cover patterns and ecological processes, which affect the distribution and abundance of species. The sharp decline in European wader bird (Charadrii) populations is a good example. The aim of this study is to test the hypothesis that the anthropogenic developmental stage of wet grassland habitats and landscapes drives avian nest predator abundance, and thus the predation pressure on nests, which is a major cause of wader bird declines. Using a macroecological approach we selected six wet grassland landscapes representing a gradient in both grassland habitat development and breeding wader population status in four European countries (Belarus, Iceland, Lithuania and Sweden). We (1) mapped wader and avian predator assemblages in multiple wet grassland patches in each landscape, (2) used artificial nests to estimate the relative rate of egg predation, and (3) analyzed relationships between nest predation pressure, corvid nest predators versus raptors, nest loss and the stage of wet grassland habitat and landscape development. We found (1) inverse relationships between the abundance of corvids and waders, as well as between wet grassland developmental stage and waders, and (2) a positive correlation between the probability of nest loss and the density of corvid birds. In conclusion, we found a clear macroecological pattern linking habitat quality, wader populations, nest predators and nest predation. These linkages stress the importance of including nest predation as a factor limiting wader bird populations, and that corvid control or management may be useful management tools.
Do Socially Responsible Investment Funds Sell Losses and Ride Gains? The Disposition Effect in SRI Funds
Authors: Boumda Beatrice , Duxbury Darren , Ortiz Cristina , Vicente Luis
Published: July 2021

An increasing percentage of the total net assets under professional management is devoted to ethical investments. Socially responsible investment (SRI) funds have a dual objective: building an investment strategy based on environmental, social, and corporate governance (ESG) screens and providing financial returns to investors. In the current study, we investigate whether this dual objective has an influence on the behavior of mutual fund managers in the realization of gains and losses. Evidence has shown that most investors in SRI funds invest in those funds primarily because of their social concerns. If the motivations of SRI managers align with those of SRI investors, SRI managers might then have more incentives than conventional managers to hold onto losing stocks if they feel their social value compensates for the economic loss. We hypothesize that SRI managers would be less prone to the disposition effect than conventional managers. Pertaining to the disposition effect, we do not find evidence of a difference in the behavior of SRI fund managers compared with that of conventional fund managers. Our results hold, even when considering market trends, management structure, gender, and prior performance.
Implementation of General Sustainability Objectives as Tools to Improve the Environmental Performance of Industry
Authors: Almgren Richard , Hjelm Olof
Published: July 2021

This article examines the implementation of the Swedish national environmental quality objectives and discusses what can be learned for the equivalent process for the set of global UN 2030 goals (SDGs), established in 2015. The empirical basis is a study on 50 large companies in Sweden and their use of these objectives in their policy formulation. The SDGs are crafted with a broader approach than the Swedish national environmental quality objectives. Therefore, the SDGs probably better reflect the agenda of the business community since they have a global character, cover the whole spectrum of important sustainability issues and provide a mutual agenda for the business community worldwide. More than 90 percent of the large companies in the study have explicitly committed themselves to the SDGs, only 1–2 years after they were published, whereas similar commitments hardly exist for the national environmental quality objectives, even 20 years after their establishment. A large majority of the large companies in this study know about the SDGs, have actively endorsed them, and started to adjust their activities accordingly. In the end, the results of these endorsements remain to be seen.
Collective Identity Supporting Sustainability Transformations in Ecovillage Communities
Authors: Ulug Ciska , Horlings Lummina , Trell Elen-Maarja
Published: July 2021

Ecovillages are collective projects that attempt to integrate sustainability principles into daily community life, while also striving to be demonstration projects for mainstream society. As spaces of experimentation, they can provide valuable insights into sustainability transformations. Through shared values and interpersonal connections, ecovillages possess collective identities, which provide a platform for enacting their ideals. However, many ecovillage residents question how to best enhance their role as models, resource centers, and pieces of a greater movement toward sustainability transformations, while simultaneously preserving their unique community and identity. In relation to the above, this paper addresses the questions: What can collective identity in ecovillage communities teach us about the objective and subjective dimensions of sustainability transformations? Furthermore, how can the perspective of collective identity highlight challenges for ecovillages for initiating sustainability transformations? Sustainability transformations encompass objective (behaviors) and subjective (values) dimensions; however, the interactions between these spheres deserve more scholarly attention. Using ethnographic data and in-depth interviews from three ecovillages in the United States, this paper reveals the value in collective identity for underscoring belonging and interpersonal relationships in sustainability transformations. Furthermore, the collective identity perspective exposes paradoxes and frictions between ecovillages and the societal structures and systems they are embedded within.
Holistic Requirements Analysis for Specifying New Systems for 3D Media Production and Promotion
Authors: Mouzakis Christos , Ververidis Dimitrios , Girao Luis Miguel , Patz Nicolas , Nikolopoulos Spiros , Kompatsiaris Ioannis
Published: July 2021

This paper presents a requirements engineering process for driving the design of new systems that will allow for enhancing 3D media productivity, for lowering the entry barrier in 3D media creation, and for innovative media forms across many media types. This work has been carried out with the perspective of enhancing recovery and transformation as the pandemic has driven many professionals in culture to zero income. Toward this goal, we perform a requirements engineering process based on the IEEE 830 standard for requirements specification. It allows us to elucidate system requirements through existing (AS-IS) and envisioned (TO-BE) scenarios affected by the latest trends on design methodologies and content promotion in social media. A total of 30 tools for content creation, promotion, and monetization are reviewed and 10 TO-BE scenarios were engineered and validated. The validation was performed through a survey of 24 statements on a 5 Likert scale by 47 individuals from the domains of Media, Fine arts, Architecture, and Informatics. Useful evaluation results and comments have been collected that can be useful for future systems design.
Framework of Blockchain-Supported E-Commerce Platform for Small and Medium Enterprises
Authors: Jiang Ji , Chen Jin
Published: July 2021

Small and medium enterprises (SMEs) play an important role in promoting the national economy and providing employment opportunities. E-commerce platforms may facilitate transactions between these enterprises. However, transactions on the e-commerce platform are non-face-to-face, strongly virtual, and variable, resulting in SMEs often facing moral hazards and opportunistic behaviors. Blockchain is a distributed ledger consisting of an encryption algorithm, consensus mechanism, and smart contracts, having the characteristics of authenticity, security, transparency, and unforgeability. Thus, the problems faced by SMEs can be resolved by combining e-commerce platforms and blockchain technology. In this study, we first provide a conceptual framework for blockchain-supported e-commerce platforms for SMEs. Second, based on this conceptual framework, we build a total business architecture. Finally, we propose three key applications to illustrate how the platform facilitates SMEs in solving financing and trading problems. This study provides significant guidance for the operation and management of blockchain-supported e-commerce platforms for these enterprises.