bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Implementation of Dongba Character Font Style Transfer Model Based on AFGAN
Authors: Bao Congwang , Li Yuan , Lu En
Published: May 2024

Dongba characters are ancient ideographic scripts with abstract expressions that differ greatly from modern Chinese characters; directly applying existing methods cannot achieve the font style transfer of Dongba characters. This paper proposes an Attention-based Font style transfer Generative Adversarial Network (AFGAN) method. Based on the characteristics of Dongba character images, two core modules are set up in the proposed AFGAN, namely void constraint and font stroke constraint. In addition, in order to enhance the feature learning ability of the network and improve the style transfer effect, the Convolutional Block Attention Module (CBAM) mechanism is added in the down-sampling stage to help the network better adapt to input font images with different styles. The quantitative and qualitative analyses of the generated font and the real font were conducted by consulting with professional artists based on the newly built small seal script, slender gold script, and Dongba character dataset, and the styles of the small seal script and slender gold script were transferred to Dongba characters. The results indicate that the proposed AFGAN method has advantages in evaluation indexes and visual quality compared to existing networks. At the same time, this method can effectively learn the style features of small seal script and slender gold script, and transfer them to Dongba characters, indicating the effectiveness of this method.
Construction of Chitosan-Modified Naphthalimide Fluorescence Probe for Selective Detection of Cu2+
Authors: Yu Chunwei , Huang Jin , Yang Mei , Zhang Jun
Published: May 2024

A chitosan-based Cu2+ fluorescent probe was designed and synthesized independently using the C-2-amino group of chitosan with 1, 8-naphthalimide derivatives. A series of experiments were conducted to characterize the optical properties of the grafted probe. The fluorescence quenching effect was investigated based on the interactions between the probe and common metals. It was found that the proposed probe displayed selective interaction with Cu2+ over other metal ions and anions, reaching equilibrium within 5 min.
Cervical Spondylosis Diagnosis Based on Convolutional Neural Network with X-ray Images
Authors: Xie Yang , Nie Yali , Lundgren Jan , Yang Mingliang , Zhang Yuxuan , Chen Zhenbo
Published: May 2024

The increase in Cervical Spondylosis cases and the expansion of the affected demographic to younger patients have escalated the demand for X-ray screening. Challenges include variability in imaging technology, differences in equipment specifications, and the diverse experience levels of clinicians, which collectively hinder diagnostic accuracy. In response, a deep learning approach utilizing a ResNet-34 convolutional neural network has been developed. This model, trained on a comprehensive dataset of 1235 cervical spine X-ray images representing a wide range of projection angles, aims to mitigate these issues by providing a robust tool for diagnosis. Validation of the model was performed on an independent set of 136 X-ray images, also varied in projection angles, to ensure its efficacy across diverse clinical scenarios. The model achieved a classification accuracy of 89.7%, significantly outperforming the traditional manual diagnostic approach, which has an accuracy of 68.3%. This advancement demonstrates the viability of deep learning models to not only complement but enhance the diagnostic capabilities of clinicians in identifying Cervical Spondylosis, offering a promising avenue for improving diagnostic accuracy and efficiency in clinical settings.
An Optimal, Power Efficient, Internet of Medical Things Framework for Monitoring of Physiological Data Using Regression Models
Authors: Mishra Amitabh , Liberman Lucas S. , Brahamanpally Nagaraju
Published: May 2024

The sensors used in the Internet of Medical Things (IoMT) network run on batteries and need to be replaced, replenished or should use energy harvesting for continuous power needs. Additionally, there are mechanisms for better utilization of battery power for network longevity. IoMT networks pose a unique challenge with respect to sensor power replenishment as the sensors could be embedded inside the subject. A possible solution could be to reduce the amount of sensor data transmission and recreate the signal at the receiving end. This article builds upon previous physiological monitoring studies by applying new decision tree-based regression models to calculate the accuracy of reproducing data from two sets of physiological signals transmitted over cellular networks. These regression analyses are then executed over three different iteration varieties to assess the effect that the number of decision trees has on the efficiency of the regression model in question. The results indicate much lower errors as compared to other approaches indicating significant saving on the battery power and improvement in network longevity.
Context-Enhanced Network with Spatial-Aware Graph for Smartphone Screen Defect Detection
Authors: Liang Aili , Wang Qishan , Wu Xiaofeng
Published: May 2024

Interactive devices such as touch screens have gained widespread usage in daily life; this has directed the attention of researchers to the quality of screen glass. Consequently, defect detection in screen glass is essential for improving the quality of smartphone screens. In recent years, defect detection methods based on deep learning have played a crucial role in improving detection accuracy and robustness. However, challenges have arisen in achieving high-performance detection due to the small size, irregular shapes and low contrast of defects. To address these challenges, this paper proposes CE-SGNet, a Context-Enhanced Network with a Spatial-aware Graph, for smartphone screen defect detection. It consists of two novel components: the Adaptive Receptive Field Attention Module (ARFAM) and the Spatial-aware Graph Reasoning Module (SGRM). The ARFAM enhances defect features by adaptively extracting contextual information to capture the most relevant contextual region of defect features. The SGRM constructs a region-to-region graph and encodes region features with spatial relationships. The connections among defect regions are enhanced during the propagation process through a graph attention network. By enriching the feature representations of defect regions, the CE-SGNet can accurately identify and locate defects of various shapes and scales. Experimental results demonstrate that the CE-SGNet achieves outstanding performance on two public datasets.
Investigation of Security Threat Datasets for Intra- and Inter-Vehicular Environments
Authors: Haddaji Achref , Ayed Samiha , Chaari Fourati Lamia , Merghem Boulahia Leila
Published: May 2024

Vehicular networks have become a critical component of modern transportation systems by facilitating communication between vehicles and infrastructure. Nonetheless, the security of such networks remains a significant concern, given the potential risks associated with cyberattacks. For this purpose, artificial intelligence approaches have been explored to enhance the security of vehicular networks. Using artificial intelligence algorithms to analyze large datasets can enable the early identification and mitigation of potential threats. However, developing and testing effective artificial-intelligence-based solutions for vehicular networks necessitates access to diverse datasets that accurately capture the various security challenges and attack scenarios in this context. In light of this, the present survey comprehensively examines the vehicular network environment, the associated security issues, and existing datasets. Specifically, we begin with a general overview of the vehicular network environment and its security challenges. Following this, we introduce an innovative taxonomy designed to classify datasets pertinent to vehicular network security and analyze key features of these datasets. The survey concludes with a tailored guide aimed at researchers in the vehicular network domain. This guide offers strategic advice on selecting the most appropriate datasets for specific research scenarios in the field.
Label-Free Three-Dimensional Morphological Characterization of Cell Death Using Holographic Tomography
Authors: Huang Chung-Hsuan , Lai Yun-Ju , Chen Li-Nian , Hung Yu-Hsuan , Tu Han-Yen , Cheng Chau-Jern
Published: May 2024

This study presents a novel label-free approach for characterizing cell death states, eliminating the need for complex molecular labeling that may yield artificial or ambiguous results due to technical limitations in microscope resolution. The proposed holographic tomography technique offers a label-free avenue for capturing precise three-dimensional (3D) refractive index morphologies of cells and directly analyzing cellular parameters like area, height, volume, and nucleus/cytoplasm ratio within the 3D cellular model. We showcase holographic tomography results illustrating various cell death types and elucidate distinctive refractive index correlations with specific cell morphologies complemented by biochemical assays to verify cell death states. These findings hold promise for advancing in situ single cell state identification and diagnosis applications.
Kinematic and Physiological Analysis of Medieval Combat Sport Using Motion Analysis, Blood Lactate Measurement, and Heart Rate Monitoring: A Case Study
Authors: Mohammadalizadeh Mojtaba , Jaiswal Suraj , Semken Scott , Mikkola Aki
Published: May 2024

Medieval combat sport is a form of mixed martial art in which combatants engage in fighting using offensive and defensive equipment while dressed in full armor. The sport is considered extremely taxing, making it nearly impossible to maintain the same level of performance. However, this form of sport has not been thoroughly analyzed, and its impact on human physical response is largely unknown. To address this gap, the study reported here aimed to introduce and test a procedure for analyzing human physical responses within the framework of the sport. To accomplish this, two experienced combatants were asked to engage in a series of strikes, performed in the form of a set duel simulating a professional fight competition. The kinematic aspect of the procedure was examined using motion analysis with the help of an IMU suit, while the physiological aspect was evaluated based on blood lactate levels and heart rate measurements. Furthermore, an ergometer test conducted in a laboratory setting aimed to determine the lactate threshold. The duel results showed noticeable decreases in the kinematic aspects of the strikes, such as the velocity of impact, and a dramatic rise in physiological aspects, such as heart rate and blood lactate levels. During the duel sets, the blood lactate surpassed the threshold level, and at the end, the heart rate exceeded the maximum age-related level. Practicing medieval combat sport has been shown to impose an extreme physical load on the bodies of combatants, noticeably affecting their performance levels.
Multi-Scenario Validation and Assessment of a Particulate Matter Sensor Monitor Optimized by Machine Learning Methods
Authors: Tang Hao , Cai Yunfei , Gao Song , Sun Jin , Ning Zhukai , Yu Zhenghao , Pan Jun , Zhao Zhuohui
Published: May 2024

Objective: The aim was to evaluate and optimize the performance of sensor monitors in measuring PM2.5 and PM10 under typical emission scenarios both indoors and outdoors. Method: Parallel measurements and comparisons of PM2.5 and PM10 were carried out between sensor monitors and standard instruments in typical indoor (2 months) and outdoor environments (1 year) in Shanghai, respectively. The optimized validation model was determined by comparing six machining learning models, adjusting for meteorological and related factors. The intra- and inter-device variation, measurement accuracy, and stability of sensor monitors were calculated and compared before and after validation. Results: Indoor particles were measured in a range of 0.8–370.7 μg/m3 and 1.9–465.2 μg/m3 for PM2.5 and PM10, respectively, while the outdoor ones were in the ranges of 1.0–211.0 μg/m3 and 0.0–493.0 μg/m3, correspondingly. Compared to machine learning models including multivariate linear model (ML), K-nearest neighbor model (KNN), support vector machine model (SVM), decision tree model (DT), and neural network model (MLP), the random forest (RF) model showed the best validation after adjusting for temperature, relative humidity (RH), PM2.5/PM10 ratios, and measurement time lengths (months) for both PM2.5 and PM10, in indoor (R2: 0.97 and 0.91, root-mean-square error (RMSE) of 1.91 μg/m3 and 4.56 μg/m3, respectively) and outdoor environments (R2: 0.90 and 0.80, RMSE of 5.61 μg/m3 and 17.54 μg/m3, respectively), respectively. Conclusions: Sensor monitors could provide reliable measurements of PM2.5 and PM10 with high accuracy and acceptable inter and intra-device consistency under typical indoor and outdoor scenarios after validation by RF model. Adjusting for both climate factors and the ratio of PM2.5/PM10 could improve the validation performance.
Novel Response Surface Technique for Composite Structure Localization Using Variable Acoustic Emission Velocity
Authors: Bhandari Binayak , Maung Phyo Thu , Prusty Gangadhara B.
Published: May 2024

The time difference of arrival (TDOA) method has traditionally proven effective for locating acoustic emission (AE) sources and detecting structural defects. Nevertheless, its applicability is constrained when applied to anisotropic materials, particularly in the context of fiber-reinforced composite structures. In response, this paper introduces a novel COmposite LOcalization using Response Surface (COLORS) algorithm based on a two-step approach for precise AE source localization suitable for laminated composite structures. Leveraging a response surface developed from critical parameters, including AE velocity profiles, attenuation rates, distances, and orientations, the proposed method offers precise AE source predictions. The incorporation of updated velocity data into the algorithm yields superior localization accuracy compared to the conventional TDOA approach relying on the theoretical AE propagation velocity. The mean absolute error (MAE) for COLORS and TDOA were found to be 6.97 mm and 8.69 mm, respectively. Similarly, the root mean square error (RMSE) for COLORS and TODA methods were found to be 9.24 mm and 12.06 mm, respectively, indicating better performance of the COLORS algorithm in the context of source location accuracy. The finding underscores the significance of AE signal attenuation in minimizing AE wave velocity discrepancies and enhancing AE localization precision. The outcome of this investigation represents a substantial advancement in AE localization within laminated composite structures, holding potential implications for improved damage detection and structural health monitoring of composite structures.
Direction-of-Arrival Estimation for Unmanned Aerial Vehicles and Aircraft Transponders Using a Multi-Mode Multi-Port Antenna
Authors: Almasri Sami Alkubti , Johannsen Nils L. , Hoeher Peter A.
Published: May 2024

Increasing airspace safety is an important challenge, both for unmanned aerial vehicles (UAVs) as well as manned aircraft. Future developments of collision avoidance systems are supposed to utilize information from multiple sensing systems. A compact sensing system could employ a multi-mode multi-port antenna (M 3PA). Their ability to radiate multiple orthogonal patterns simultaneously makes them suitable for communication applications as well as bearing and ranging applications. Furthermore, they can be designed to flexibly originate near-omnidirectional and/or directional radiation patterns. This option of flexibility with respect to the radiation characteristic is desired for antennas integrated in collision avoidance systems. Based on the aforementioned properties, M 3PAs represent a compelling option for aircraft transponders. In this paper, direction-of-arrival (DoA) estimation using an M 3PA designed for aerial applications is put to the test. First, a DoA estimation scheme suitable to be employed with M 3PAs is introduced. Next, the validity of the proposed method is confirmed through numerical simulations. Lastly, practical experiments are conducted in an antenna measurement chamber to verify the numerical results.
Using Inertial Measurement Units to Examine Selected Joint Kinematics in a Road Cycling Sprint: A Series of Single Cases
Authors: Morbey Simon , Tronslien Marius , Kong Kunho , Chapman Dale W. , Netto Kevin
Published: May 2024

Sprinting plays a significant role in determining the results of road cycling races worldwide. However, currently, there is a lack of systematic research into the kinematics of sprint cycling, especially in an outdoor, environmentally valid setting. This study aimed to describe selected joint kinematics during a cycling sprint outdoors. Three participants were recorded sprinting over 60 meters in both standing and seated sprinting positions on an outdoor course with a baseline condition of seated cycling at 20 km/h. The participants were recorded using array-based inertial measurement units to collect joint excursions of the upper and lower limbs including the trunk. A high-rate GPS unit was used to record velocity during each recorded condition. Kinematic data were analyzed in a similar fashion to running gait, where multiple pedal strokes were identified, delineated, and averaged to form a representative (average ± SD) waveform. Participants maintained stable kinematics in most joints studied during the baseline condition, but variations in ranges of movement were recorded during seated and standing sprinting. Discernable patterns started to emerge for several kinematic profiles during standing sprinting. Alternate sprinting strategies emerged between participants and bilateral asymmetries were also recorded in the individuals tested. This approach to studying road cycling holds substantial potential for researchers wishing to explore this sport.
Surfing Time–Motion Characteristics Possible to Gain Using Global Navigation Satellite Systems: A Systematic Review
Authors: Mejuto Gaizka , Gómez-Carmona Carlos David , Gracia Jokin , Rico-González Markel
Published: May 2024

The popularity of surfing has increased exponentially, reaching its recent debut in the Olympic Games. However, surfing suffers from a relative immature technological market, while in other sports some technologies such as global navigation satellite systems (GNSSs) have become an essential work material for strength and conditioning and head coaches. This article aims to systematically review surfers’ time–motion demands based on GNSSs. A systematic review of relevant articles was carried out using five main databases (PubMed, ProQuest Central, SCOPUS, SPORTDiscus, and FECYT (Web of Sciences, CCC, CIDW, KJD, MEDLINE, RSCI, and SCIELO)) until 23 March 2024. From the 238 studies initially found, 9 were included in the qualitative synthesis. In these, GNSS devices were employed with male (n = 143) and female (n = 28) surfers from different levels during competition and training situations. The studies show that the intermittent nature of the sport is evident, with substantial periods spent paddling and waiting punctuated by relatively brief high-intensity efforts when riding waves at high speeds. Notable differences emerged between competition and training demands, suggesting potential mismatches in how athletes currently prepare compared to event requirements. These novel insights allow quantifying surfing’s harsh physiological requirements and could guide conditioning practices to better meet the sport’s unique characteristics across populations. Therefore, training should emulate the lengthy aerobic capabilities needed for the paddling volumes observed, while also targeting the anaerobic systems to meet the repeated high-intensity surf riding efforts. However, inconsistencies in methods and reporting practices limit direct comparisons and comprehensive profiling of the sport’s physical characteristics.
Towards Stabilized Few-Shot Object Detection with Less Forgetting via Sample Normalization
Authors: Ren Yang , Yang Menglong , Han Yanqiao , Li Weizheng
Published: May 2024

Few-shot object detection is a challenging task aimed at recognizing novel classes and localizing with limited labeled data. Although substantial achievements have been obtained, existing methods mostly struggle with forgetting and lack stability across various few-shot training samples. In this paper, we reveal two gaps affecting meta-knowledge transfer, leading to unstable performance and forgetting in meta-learning-based frameworks. To this end, we propose sample normalization, a simple yet effective method that enhances performance stability and decreases forgetting. Additionally, we apply Z-score normalization to mitigate the hubness problem in high-dimensional feature space. Experimental results on the PASCAL VOC data set demonstrate that our approach outperforms existing methods in both accuracy and stability, achieving up to +4.4 mAP@0.5 and +5.3 mAR in a single run, with +4.8 mAP@0.5 and +5.1 mAR over 10 random experiments on average. Furthermore, our method alleviates the drop in performance of base classes. The code will be released to facilitate future research.
Carwash Oily Wastewater Separated by Ultrafiltration
Authors: Woźniak Piotr , Gryta Marek
Published: May 2024

In the present study, oily wastewater generated during car washing was separated using ultrafiltration (UF). Wastewater was collected from the settling tank of two manual car washes. In addition to pollutants removed from cars, such wastewater contains surfactants, the impact of which on the process of ultrafiltration has been analyzed. For this purpose, the application of commercial UF polyethersulfone (PES) membranes (10 and 100 kDa) and polyvinylidene fluoride (PVDF) tubular membranes (100 kDa) was comprehensively examined. Almost 100% removal of oil contaminants was achieved; however, intensive fouling was noticed. The membrane morphology and deposit composition were studied using a scanning electron microscope coupled with energy dispersion spectrometry. The fouling phenomenon was reduced by washing the membranes with an alkaline cleaning agent (pH = 11.5), which is used in car washes to remove insects. The filtration/membrane washing cycle was repeated many times to achieve stable operation of the membrane modules. The UF process was carried out for 120–140 h, and the separation efficiency was analyzed based on the rejection of dextrans, COD, BOD, total N and P, turbidity, and anionic surfactants. It has been found that cyclic repeated washing did not deteriorate the membrane’s performance, and a permeate with a turbidity of 0.12–0.35 NTU was obtained. Thus, cleaning agents used for washing cars can also be used for membrane cleaning.
The Interplay between Binge Watching and Suicide Risk: Daytime Sleepiness and Maladaptive Daydreaming as Mediators
Authors: Saladino Valeria , Calaresi Danilo , Cuzzocrea Francesca , Verrastro Valeria
Published: May 2024

Binge watching, which entails consecutively viewing numerous episodes of a TV series or a selection of movies over an extended timeframe, often without pause, is notably widespread among young adults skilled in digital media usage. Nevertheless, this escalating habit can lead to problematic and addictive behavior, with potential associations including disruptions in sleep patterns, dreaming, and an elevated risk of suicide. The primary objective of this research was to assess whether daytime sleepiness and maladaptive daydreaming may impact the connection between binge watching and suicide risk and whether the hypothesized model is gender invariant. Self-report questionnaires were administered to a sample of 1012 emerging adults (50% girls) aged 18–25 (M = 21.73, SD = 2.28). Multivariate analysis of covariance (MANCOVA), structural equation modeling (SEM) with latent variables, and multiple-group path analysis (MGPA) were conducted. All direct and indirect paths were found to be statistically significant, and gender was found to be invariant. Specifically, the findings highlighted that higher binge watching, coupled with daytime sleepiness and maladaptive daydreaming, heightened suicide risk in both genders. Binge watching and sleep and dream issues are important factors to consider in the assessment of suicide risk, particularly among emerging adults who are already at a higher risk. It is thus important to prioritize the promotion of healthy media habits.
Reading Refugee/(Im)Migrant Education Diffractively: Transdisciplinary Exploration of Matters That Matter and Matter That Matters in Refugee/(Im)Migrant Education
Authors: Kasper Julie
Published: May 2024

This paper is a conceptual exploration and diffractive reading of refugee/(im)migrant education through multiple lenses, including data-driven decision making, critical refugee studies, new materialism and critical feminist and posthumanist studies, and trans theorizations such as Black trans feminism. After a brief introduction to “the field” of refugee/(im)migrant education, the paper turns to diffractive readings of refugee/(im)migrant education as means of exploring what is the matter, as in the material and discursive substance, in refugee/(im)migrant education, and why and how (including when, where, and by whom) does that matter come to matter? The paper concludes with discoveries, or findings, from this diffractive, transdisciplinary exploration and considerations for educators, policymakers, researchers, activists, and other actors (co)constituting and “becoming with” refugee/(im)migrant education.
Internal Communication Quality in a Telecommuting Context: A Phenomenological Exploration of Telecommuters’ Communication Experiences
Authors: Kilson Gabriel A. , Tavares Patrícia
Published: May 2024

Information and Communication Technologies (ICT) mediated interactions, such as audio and video calls, are part of all companies’ routines. Despite technological advances, no current ICT can perfectly mimic the unique characteristics of face-to-face interactions. As good-quality internal communication is critical to companies’ operations, the increased demand for work-from-home jobs raises relevant questions regarding employees’ capability to communicate properly. To better understand if the physical and temporal distance associated with the work-from-home represents a threat to employees’ capacity to establish clear communications, this study explores the internal communication experiences of full-time home-based telecommuters. Adopting a transcendental phenomenological strategy and based on a mix of purposeful and snowball sampling, 23 employees were interviewed online. Two additional interviews with top managers from a company where all employees work from home were also performed. Following a thematic analysis, results did not reveal a direct relationship between physical and temporal distance and the quality of internal communication. Indeed, the increased media options adopted by employees after starting to work from home contributed to improving internal communication quality. The main identified communication issues, such as information segregation, are related to how internal communications are managed, and may happen whether employees work side-by-side or physically apart.
Exploring Marital Quality in Parents of Children with Autism: Identifying Barriers and Facilitators
Authors: Gur Ayelet , Golan Bayazy Yifat
Published: May 2024

The current study aims to examine the factors that facilitate or act as barriers to the marital relationships of parents of children with ASD. In total, 150 parents of children with ASD participated in this study. An online qualitative survey tool was utilized to collect data, which were subsequently subjected to thematic analysis. Through qualitative analysis, three major themes emerged: (1) Psychological and Emotional Experiences, (2) Sense of Partnership, and (3) The Rich get Richer, including sub-themes such as formal support systems, a strong marital relationship prior to ASD diagnosis, and limited family resources. The findings suggest that elements of the marital relationship can serve as valuable resources for parents of children with ASD in coping with the challenges of parenthood. Conversely, the study highlights certain factors that act as barriers to the marital relationship.
Autonomic Rebound Following Maximal Exercise in Bodybuilders and Recreationally Active Participants
Authors: Kliszczewicz Brian , Wilner Gabe , Canino Andre , Chung Pedro , Nickel Abigail , Vaughan Keilah , McLester Cherilyn , Buresh Robert
Published: May 2024

The off-season for natural bodybuilders (BB) is characterized by increased training loads and fluctuations in caloric intake, which may lead to insufficient recovery. The autonomic nervous system (ANS) plays a pivotal role in recovery. The purpose of this study was to evaluate resting ANS activity and recovery following a maximal exercise bout in off-season BB and compare them to those of recreationally active individuals. Fifteen males participated; 7 recreationally active (RA) (24.6 ± 2.1 years, 81.1 ± 10.8 kg) and 8 BB (21.8 ± 2.9 years, 89.3 ± 13.0 kg). Each performed a graded exercise test. Heart rate variability (HRV) was measured at rest and during a 45 min recovery period. HRV was analyzed as: root mean square of successive differences (lnRMSSD), standard deviation of normal-to-normal sinus beats (lnSDNN), high frequency (lnHF), low frequency (lnLF), and the ratio of low frequency to high frequency (lnLF/lnHF). A one-way ANOVA showed no differences for any resting marker of HRV, HR, and HR recovery. A significant depression in all markers of HRV was observed in the BB group at the 15 min point, and no recovery was observed before 45 min when compared to RA. The results of this study demonstrated depressed HRV recovery following the graded exercise test in BB when compared to the RA group.
Exploring the Impact of Gamified Role-Playing on Climate Change Knowledge and Nature Relatedness: Evidence from an Online Undergraduate Course on Environmental Health
Authors: Runnerstrom Miryha Gould , Denaro Kameryn , DiVincenzo Janet
Published: May 2024

In an online environmental health course, undergraduate students worked in teams of five and were immersed in a team-based climate change case study set in the Amazon rainforest. Each student was assigned a character role—a logger, a farmer, a conservation biologist, an environmental activist, and a policymaker. We aimed to understand whether student character assignments influenced their climate change knowledge, environmental concern, and connection to nature. Regression models were generated to test for differences in the outcome variables between characters at pre- and post-test. We observed higher gains in the nature relatedness scores for students assigned the logger role. After controlling for previous climate change knowledge, first-generation college students had lower climate change knowledge at the end of the course compared to non-first-generation students, but low-income students had higher climate change knowledge at the end of the course compared to non-low-income students. Environmental concern had no change over the term; scores were high during the pre- and post-survey for all students. There may be potential to develop a connection to nature by assigning students to play specific characters. Also, despite ongoing work to support first-generation college students, there remain opportunities to develop academic support programs for these students.
Environmental Assessment of Incorrect Automated Pedestrian Detection and Common Pedestrian Timing Treatments at Signalized Intersections
Authors: Gavric Slavica , Erdagi Ismet Goksad , Stevanovic Aleksandar
Published: May 2024

Existing research has primarily focused on the accuracy of automated pedestrian detection systems, overlooking the consequential environmental impacts arising from false or missed pedestrian detections. To fill these research gaps, this study investigates the emissions and fuel consumption resulting from incorrect pedestrian detection at signalized intersections in microsimulation. To carry out experiments, the authors employ Vissim microsimulation software and the Comprehensive Modal Emission Model (CMEM). For the first time in the literature, missed and false calls are modeled in microsimulation and their environmental impacts are accurately measured. The research highlights the limitations of current automated pedestrian (video) detection systems (APVDSs) technologies in reducing emissions and fuel consumption effectively. While APVDSs offer potential benefits for traffic management, their inability to accurately detect pedestrians undermines their environmental efficacy. This study emphasizes the importance of considering environmental impacts of APVDSs, and challenges the belief that pedestrian recall treatment is the least eco-friendly. Also, the study showed that coupling APVDS or push-button treatments with pedestrian recycle features increases fuel consumption and CO2 by 10% at the intersections with higher pedestrian demand. By understanding the emissions and fuel consumption associated with incorrect detections, transportation agencies can make more informed decisions regarding the implementation and improvement of APVDS technologies.
Environmental and Economic Performance of Greenhouse Cropping in the Mediterranean Basin: Lessons Learnt from a Cross-Country Comparison
Authors: Sturiale Sara , Gava Oriana , Gallardo Marisa , Buendía Guerrero Dolores , Buyuktas Dursun , Aslan Gulcin Ece , Laarif Asma , Bouslama Thameur , Navarro Alejandra , Incrocci Luca , Bartolini Fabio
Published: May 2024

In the Mediterranean region, the expansion of greenhouse horticulture has enabled the year-round supply of fresh vegetables. Compared to open field horticulture, this farming method can generate higher returns for farmers. However, it is often associated with significant environmental pressures. This research aims to pinpoint important opportunities for improvement of the environmental and economic performance of greenhouse farming in the Mediterranean region by showing the life cycle’s environmental and economic impacts and by highlighting life cycle hotspots. This is achieved through the combined application of life cycle assessment and life cycle costing to four case studies (commercial greenhouses) spanning the Mediterranean Basin (Italy, Spain, Tunisia, and Turkey). The case study findings highlight the following environmental hotspots and related impacts: (i) fertigation management can generate up to 11,283 m3/ha/year of water use impact; (ii) fertilizer leaching can generate up to 27 kg of N eq marine eutrophication impact; and (iii) crop protection treatments can generate up to 130,037 kg 1,4-DCB of terrestrial ecotoxicity impact. The large use of plastic materials (greenhouse and fertigation infrastructures) is an additional critical aspect due to manufacturing and disposal, contributing to eutrophication impact categories. Economic hotspots are related to greenhouse management (up to 35% total costs of production) and hired labor (up to 40% total costs of production). The lessons learnt from these case studies offer valuable insights into the sustainability challenges of greenhouse horticulture across the Mediterranean region. The hotspot analysis points to the need for targeted interventions to mitigate the most critical impacts while ensuring economic viability. This study enriches scientific understanding by examining different production and socioeconomic contexts, offering crucial insights for the advancement of sustainable practices in greenhouse agriculture such as the use of decision support systems to optimize input use.
Intentionality and Decision-Making in Impact Investing—Understanding Investment Motivation and Selection Criteria of Impact Investors
Authors: Heinz David C. , Velamuri Vivek K.
Published: May 2024

The opacity of the impact investment decision-making process is one of the main constraints hampering further growth in the impact investing ecosystem. This paper takes a differentiated view on why (investment motivation) and how (investment decision criteria) the major private impact investor types allocate funding to investees. We incorporate insights from 34 interviews with the five major impact investor types: social business angels, foundations, social banks, impact investment funds, and crowdvesting platforms. We find that motivation and decision-making significantly differ between the impact investor types, especially concerning strict vs. ambiguous impact definitions, active vs. passive investment approaches, and return requirements reaching from capital preservation to market-driven returns. By providing a differentiated overview of the investor type-specific motivations and most important investment criteria, our study offers social entrepreneurs a roadmap to identify the most appropriate impact investors for their business model.
Influence of Psychological Factors on Dairy Farmers’ Intentions to Adopt Environmental Sustainability Practices in Paraná State, Brazil
Authors: Sangali Jessica Ortega de Jesus , Bánkuti Ferenc Istvan , Damasceno Julio Cesar , Perez Henrique Leal
Published: May 2024

Efforts worldwide have been dedicated to developing strategies for reducing the environmental impacts arising from agricultural production. In developing countries, such as Brazil, where agricultural production stands as one of the most important economic sectors, meeting institutional and market requirements for sustainability is essential for ensuring the country’s competitiveness. This study investigated the intention of Brazilian dairy farmers to adopt environmental sustainability practices. The sample comprised 100 dairy farms in Paraná State, Brazil. The data were analyzed using structural equation models and discussed from the perspective of the Theory of Planned Behavior. The results showed that farmers’ intentions to adopt sustainability practices is not associated with socioeconomic or production characteristics. Structural equation modeling identified three constructs explaining farmers’ intentions to adopt sustainability practices, namely attitude (ATT), subjective norms (SN), and perceived behavioral control (PBC). ATT and SN had a positive and significant influence, explaining 90% (R2 = 0.90) of the farmers’ intentions toward sustainability adoption. The lack of influence of the PBC construct suggests that farmers perceive themselves as having limited ability to adopt sustainability practices, mainly attributed to a lack of knowledge and financial resources, low self-confidence, and a heavy reliance on others for the implementation of sustainability actions.
Exploring the Value Co-Creation of Cultural Creative Hotels: From the Perspective of Social Innovation
Authors: Wang Mai-Rong , Chen Chun-Liang
Published: May 2024

Social innovation has emerged as a transformative force in businesses, particularly in the context of cultural and creative hotels. This study aims to explore the relationship between social innovation and value co-creation in cultural and creative hotels, compare the intrinsic characteristics of social innovation and value co-creation within these hotels, and investigate the key factors driving social innovation in this sector. Employing a qualitative research methodology based on the theory of social innovation, this paper examines the process of value co-creation and analyzes the three key drivers within the social innovation ecosystem: establishing interdependence and identity among organizations; enhancing cognitive and value exchanges between organizations; and generating consensus through the role transformation of participants. The findings suggest that the key drivers of the social innovation ecosystem not only enhance the innovation capabilities of businesses but also motivate them to collaboratively create mutually beneficial and symbiotic value.
Progress towards the 2030 Sustainable Development Goals for EU Urban Communities (SDG11)
Authors: Ionescu George H. , Firoiu Daniela , Manda Andra-Maria , Pîrvu Ramona , Jianu Elena , Antoniu Maria-Eliza
Published: May 2024

The 2030 Agenda for sustainable development emphasizes the interconnectedness of environmental issues with socio-economic development, recognizing their fundamental role in human prosperity, while the sustainable development goals (SDGs) serve as a pivotal framework globally. This study provides a critical assessment of the progress made by EU Member States in pursuing the SDG 11 (sustainable cities and communities) targets as set out in the 2030 Agenda. The analysis is based on official data published by the EU Statistical Office—Eurostat—and uses the AAA (Holt-Winters) exponential smoothing algorithm for the trend analysis of specific indicators. The results show significant progress during the first seven years of implementation of the Agenda 2023, while indicating concerns about the achievement of the 2030 targets in some Member States. The mapping of potentially negative trends emphasizes the need for firm corrective actions, underlining the urgency of early interventions to address expected negative developments before they have potentially irreversible consequences.
Short Sea Shipping as a Sustainable Modal Alternative: Qualitative and Quantitative Perspectives
Authors: Izdebski Michael J. , Kalahasthi Lokesh Kumar , Regal-Ludowieg Andrés , Holguín-Veras José
Published: May 2024

This study investigated the possibility of using short sea shipping (SSS) as a sustainable freight modal alternative by analyzing data collected from shippers in the New York State Capital Region. To this end, qualitative and quantitative approaches were jointly used. The qualitative analysis focused on exploring in-depth interviews with the decision makers regarding the drivers and the barriers to firms shifting to SSS. The quantitative efforts included estimating discrete choice (ordinal logit) models to assess the influence of four key governing aspects (leadership buy-in, emergency logistics, public policy, and sustainability) on the probabilities of shifting to SSS supported by the findings from the qualitative part. This paper also includes a comprehensive description of various variables, factors influencing the current mode choice, shippers’ perceptions, and willingness to use SSS. The results showed that firms with higher truck shares had fewer chances to switch to SSS unless in emergencies. Unfortunately, sustainability was the least valued by most of the participants in choosing SSS. Hence, lower costs and better service were essential. The ordinal logit models provide a potential tool for policymakers and freight planners to estimate the probability of firms choosing SSS over the current mode.
Research on the Optimisation of Dual-Heat-Source Heating Systems in Nearly Zero-Energy Buildings
Authors: Hou Qingying , Xu Wendong , Zhang Zhizheng , Wang Yangyang , Zhang Hao , Tao Jin
Published: May 2024

A nearly zero-energy building is characterised by its low energy demand and enhanced thermal insulation, with great potential to integrate renewable energy systems to satisfy various demands and improve energy efficiency. Solar energy is a primary renewable energy resource that can be harnessed in different ways to provide electricity, heating, and cooling in building applications. In this study, a solar–ground-source heat pump system was designed and established in a nearly zero-energy building. The system’s performance was presented, and its control strategy was optimised. To evaluate and assess the operation of the solar energy system, an experimental setup was built, and the experiment was divided into two periods, taking into account the weather conditions. In the first experimental period, different parameters of the heating system were tested and evaluated. In this regard, the variation trends of the heat pump unit’s coefficient of performance, the system coefficient of performance, the collector start-up temperature difference, and the heat pump setting temperature were analysed under different parameter combinations. On this basis, the optimal operating parameters were identified for different heating periods. In the second period, the optimal operating parameters identified were used to carry out heating experiments. The results highlighted that the adoption of the preferred operating parameters increases the percentage of direct solar energy supply by 2.0%. Additionally, the system coefficient of performance increases by 8.9%, the unit coefficient of performance increases by 6.7%, the carbon emissions are reduced by 4.18 tonnes, the SO2 emissions are reduced by 0.143 tonnes, and the dust emissions are reduced by 0.1 tonnes. The findings of this study can provide useful data and a guiding reference for optimising and promoting the implementation of renewable-energy-driven heating systems for nearly zero-energy buildings in severe cold regions.
Green Business Model and Green Media Coverage for a Successful Initial Public Offering: Evidence from the Korean Firms
Authors: Kim Jungha , Ko Kyung Ryang , Choi Wonyong
Published: May 2024

With mounting concerns about sustainability, significant attention has been directed toward research within the green industry domain. However, existing literature on initial public offerings (IPOs) has overlooked a crucial distinction: investors do not perceive all firms operating in green industries equally. Firms with green business models (GBMs) are more attractive to investors by providing positive signals of future growth potential and sustainability. To reveal this, the study investigates the relationship between GBMs and IPO success by Ordinary Least Squares (OLS) regression analysis. As the Asia-Pacific IPO market accounts for about 60% of IPO volume and value, with Korea actively participating in this global surge, the study used a sample of 150 firms that underwent IPOs between 2016 and 2019 on the Korea Securities Dealers Automated Quotations (KOSDAQ) market. We find evidence that firms with GBMs are more likely to achieve successful IPO outcomes, and GMC also plays a positive moderating role, enhancing the positive link between GBMs and IPO success. However, GMC alone had no significant effect. These findings imply that green signals positively contribute to a successful IPO and that each green signal can have different signaling effects, ultimately contributing to the field of sustainability through signaling theory.