bluuebunny/crossref_metadata_2025 huggingface dataset:
A Field-Programmable Gate Array-Based Adaptive Sleep Posture Analysis Accelerator for Real-Time Monitoring
Authors: Sravanthi Mangali , Gunturi Sravan Kumar , Chinnaiah Mangali Chinna , Lam Siew-Kei , Divya Vani G. , Basha Mudasar , Janardhan Narambhatla , Hari Krishna Dodde , Dubey Sanjay
Published: November 2024

This research presents a sleep posture monitoring system designed to assist the elderly and patient attendees. Monitoring sleep posture in real time is challenging, and this approach introduces hardware-based edge computation methods. Initially, we detected the postures using minimally optimized sensing modules and fusion techniques. This was achieved based on subject (human) data at standard and adaptive levels using posture-learning processing elements (PEs). Intermittent posture evaluation was performed with respect to static and adaptive PEs. The final stage was accomplished using the learned subject posture data versus the real-time posture data using posture classification. An FPGA-based Hierarchical Binary Classifier (HBC) algorithm was developed to learn and evaluate sleep posture in real time. The IoT and display devices were used to communicate the monitored posture to attendant/support services. Posture learning and analysis were developed using customized, reconfigurable VLSI architectures for sensor fusion, control, and communication modules in static and adaptive scenarios. The proposed algorithms were coded in Verilog HDL, simulated, and synthesized using VIVADO 2017.3. A Zed Board-based field-programmable gate array (FPGA) Xilinx board was used for experimental validation.
Validation of a 3D Markerless Motion Capture Tool Using Multiple Pose and Depth Estimations for Quantitative Gait Analysis
Authors: D’Haene Mathis , Chorin Frédéric , Colson Serge S. , Guérin Olivier , Zory Raphaël , Piche Elodie
Published: November 2024

Gait analysis is essential for evaluating walking patterns and identifying functional limitations. Traditional marker-based motion capture tools are costly, time-consuming, and require skilled operators. This study evaluated a 3D Marker-less Motion Capture (3D MMC) system using pose and depth estimations with the gold-standard Motion Capture (MOCAP) system for measuring hip and knee joint angles during gait at three speeds (0.7, 1.0, 1.3 m/s). Fifteen healthy participants performed gait tasks which were captured by both systems. The 3D MMC system demonstrated good accuracy (LCC > 0.96) and excellent inter-session reliability (RMSE < 3°). However, moderate-to-high accuracy with constant biases was observed during specific gait events, due to differences in sample rates and kinematic methods. Limitations include the use of only healthy participants and limited key points in the pose estimation model. The 3D MMC system shows potential as a reliable tool for gait analysis, offering enhanced usability for clinical and research applications.
Identification of Spin Bowling Deliveries with an Advanced Smart Cricket Ball
Authors: Fuss Franz Konstantin , Doljin Batdelger , Ferdinands René E. D.
Published: November 2024

The type of throw of a spin bowler can be analysed in the laboratory using a motion analysis system. However, there is still no method to determine the type of throw using other means and less effort. To solve this problem, we revised the traditional classification of spin bowling throws and analysed whether spin bowling throws are separate entities or continuous concepts. We used an advanced smart cricket ball with high-speed gyroscopes to record the bowling actions and mathematically transformed the spin axis from the ball coordinate system (BCS) to the global coordinate system (GCS). We developed a visualisation method to map spin bowling throws from the yaw and pitch angles of the ball’s spin axis in the GCS. We compared the data from the smart ball with the data from the motion analysis system and profiled seven spin bowlers using the new method. The results of this study have shown that spin bowling throws are continuous concepts and that all differences between the two spin axis measurement methods were within 95% limits of agreement. The Smart Ball is sufficiently accurate to measure the direction of the ball’s spin axis in the GCS and is therefore well suited for profiling spin bowlers. Hybrid deliveries between sidespin, top/backspin, and swerve maximise the deviations of the ball in flight from the straight flight path in all three planes of the GCS. Hybrid throws between sidespin, top/backspin, and spin maximise the ball’s deviation from the straight trajectory in all three planes of the GCS.
Detecting Emotional Arousal and Aggressive Driving Using Neural Networks: A Pilot Study Involving Young Drivers in Duluth
Authors: Nahid Md Sakibul Hasan , Tila Tahrim Zaman , Seecharan Turuna S.
Published: November 2024

Driving is integral to many people’s daily existence, but aggressive driving behavior increases the risk of road traffic collisions. Young drivers are more prone to aggressive driving and danger perception impairments. A driver’s physiological state (e.g., fatigue, anger, or stress) can negatively affect their driving performance. This is especially true for young drivers who have limited driving experience. This research focuses on examining the connection between emotional arousal and aggressive driving behavior in young drivers, using predictive analysis based on electrodermal activity (EDA) data through neural networks. The study involved 20 participants aged 18 to 30, who completed 84 driving sessions. During these sessions, their EDA signals and driving behaviors, including acceleration and braking, were monitored using an Empatica E4 wristband and a telematics device. This study conducted two key analyses using neural networks. The first analysis used a comprehensive set of EDA features to predict emotional arousal, achieving an accuracy of 65%. The second analysis concentrated on predicting aggressive driving behaviors by leveraging the top 10 most significant EDA features identified from the arousal prediction model. Initially, the arousal prediction was performed using the complete set of EDA features, from which feature importance was assessed. The top 10 features with the highest importance were then selected to predict aggressive driving behaviors. Another aggressive driving behavior prediction with a refined set of difference features, representing the changes from baseline EDA values, was also utilized in this analysis to enhance the prediction of aggressive driving events. Despite moderate accuracy, these findings suggest that EDA data, particularly difference features, can be valuable in predicting emotional states and aggressive driving, with future research needed to incorporate additional physiological measures for enhanced predictive performance.
Aerodynamic Analysis of Rotor Spacing and Attitude Transition in Tilt-Powered Coaxial Rotor UAV
Authors: Wu Wei , Tan Xinyu , Liu Xing , Luo Angang , Niu Lanjie
Published: November 2024

Complex aerodynamic characteristics and optimal control during the attitude transition of tilt-powered coaxial twin-rotor unmanned aerial vehicles (UAVs) represent key challenges in flight control design. This study investigates aerodynamic mechanisms and control parameter optimization during the transition of UAVs from vertical to forward flight. By establishing a dynamic model and combining theoretical and numerical analyses, the optimal rotor spacing is determined to be h = 0.5 R. The load distribution and aerodynamic characteristics of the aircraft are analyzed at different initial tilt angles during attitude transitions. At an initial tilt angle of δ = 9°, the thrust force increases by 439% compared with that at δ = 3°, and the tip speed increases by 15% and 35% compared with that at δ = 3° and δ = 13°, respectively. The results indicate that a tilt angle of δ = 9° results in a higher turbulent dissipation rate and rotor layout efficiency, with a smoother vortex flow and more orderly distribution. The interference between the twin-rotor tip vortices is relatively weak, resulting in excellent symmetry and aerodynamic stability. Through the improvement of the theoretical model and parameter optimization of a novel tilt-powered coaxial twin-rotor UAV, this study enhances UAV flight stability and provides valuable insights and validation for the further development of UAV technology.
Evaluation of a Temperature/Humidity Data Logger for the Usage in Cattle Barns
Authors: Flessner Malina , König Felix , Guse Christian , Iwersen Michael , Klein-Jöbstl Daniela
Published: November 2024

Climate change is a worldwide problem that is manifested in livestock farming with a decrease in animal health and welfare and economic losses due to heat stress. Therefore, a precise and continuous recording of the barn climate is essential to be able to implement actions at a certain threshold. The aim of this study was to evaluate a logger for temperature and humidity (Kestrel Drop D2) marketed for on-farm use in comparison to various other temperature/humidity data loggers under field conditions. Four different sensors were used and placed in different settings in cattle barns to correlate temperature and humidity measurements. Data were recorded for over a year in total. The data were very highly correlated. Furthermore, the area under the curve for the evaluated logger in comparison to the other ones was 0.99 to 1.0, using a temperature–humidity index cut-off of 72, often set to define heat stress. In conclusion, the evaluated logger performed equally well as the other used devices. For on-farm use, it is suitable.
Feasibility of Backscattering Coefficient Evaluation of Soft Tissue Using High-Frequency Annular Array Probe
Authors: Choi Jungtaek , Ketterling Jeffrey A. , Mamou Jonathan , Hoerig Cameron , Hirata Shinnosuke , Yoshida Kenji , Yamaguchi Tadashi
Published: November 2024

The objective of this work is to address the need for versatile and effective tissue characterization in abdominal ultrasound diagnosis using a simpler system. We evaluated the backscattering coefficient (BSC) of several tissue-mimicking phantoms utilizing three different ultrasonic probes: a single-element transducer, a linear array probe for clinical use, and a laboratory-made annular array probe. The single-element transducer, commonly used in developing fundamental BSC evaluation methods, served as a benchmark. The linear array probe provided a clinical comparison, while the annular array probe was tested for its potential in high-frequency and high-resolution ultrasonic observations. Our findings demonstrate that the annular array probe meets clinical demands by providing accurate BSC measurements, showcasing its capability for high-frequency and high-resolution imaging with a simpler, more versatile system.
Evaluation of the Effects of Cultivar and Location on the Interaction of Lentil Seed Characteristics with Optimal Cooking Time
Authors: Sarakatsianos Dimitrios , Polyzou Dimitra , Mavromatis Athanasios , Vlachostergios Dimitrios N. , Gerasopoulos Dimitrios
Published: November 2024

The most important product of the lentil crop (Lens culinaris Medik) is the seeds. The main seed characteristics are their size, color, and the cooking time required to make them edible. Cultivar, location of cultivation, and their interaction are the primary factors of raw or cooked seed characteristics. The study examined the impact of five different lentil cultivars (Dimitra, Elpida, Thessalia, Samos, and 03-24L), as influenced by the cultivation environment in four different zones or nine different locations in Central-Northern Greece, on cooking time. The optimal cooking time (OCT) was calculated by cooking the seeds for 0–60 min to determine the percentage of cooked seeds using the penetration test. OCT was associated with the characteristics of both raw (mass of 1000 seeds, external color, and the percentage of mature/immature seeds) and cooked (color and organoleptic characteristics of the cooking media as well as mass increase and hardness and organoleptic characteristics of the seeds) seeds for 30 min. Depending on location, each cultivar had a different mass of 1000 seeds; Elpida had the highest mass (63.9 g), and Dimitra had the lowest (33.1 g). This was linked to OCT, which was among the highest (57.5 min) for Elpida, lowest (49 min) for Dimitra, and intermediate for Thessalia, Samos, or 03-24L. The average OCT was 55.9 min for all samples. The seed from the five locations with the shortest OCT was considered appropriate for human consumption. Two locations yielded seeds with intermediate OCT, while the other two produced the highest OCT; these were recommended for processing or propagation. In this study, the cultivar factor had a greater effect on raw seed characteristics, while the location factor had a greater effect on cooked seed characteristics and OCT than either the location, the cultivar factor, or the cultivar x location interaction.
A Novel Light-Weight Machine Learning Classifier for Intrusion Detection in Controller Area Network in Smart Cars
Authors: Kousar Anila , Ahmed Saeed , Altamimi Abdullah , Khan Zafar A.
Published: November 2024

The automotive industry has evolved enormously in recent years, marked by the proliferation of smart vehicles furnished with avant-garde technologies. These intelligent automobiles leverage cutting-edge innovations to deliver enhanced connectivity, automation, and convenience to drivers and passengers. Despite the myriad benefits of smart vehicles, their integration of digital systems has raised concerns regarding cybersecurity vulnerabilities. The primary components of smart cars within smart vehicles encompass in-vehicle communication and intricate computation, in addition to conventional control circuitry. In-vehicle communication is facilitated through a controller area network (CAN), whereby electronic control units communicate via message transmission across the CAN-bus, omitting explicit destination specifications. This broadcasting and non-delineating nature of CAN makes it susceptible to cyber attacks and intrusions, posing high-security risks to the passengers, ultimately prompting the requirement of an intrusion detection system (IDS) accepted for a wide range of cyber-attacks in CAN. To this end, this paper proposed a novel machine learning (ML)-based scheme employing a Pythagorean distance-based algorithm for IDS. This paper employs six real-time collected CAN datasets while studying several cyber attacks to simulate the IDS. The resilience of the proposed scheme is evaluated while comparing the results with the existing ML-based IDS schemes. The simulation results showed that the proposed scheme outperformed the existing studies and achieved 99.92% accuracy and 0.999 F1-score. The precision of the proposed scheme is 99.9%, while the area under the curve (AUC) is 0.9997. Additionally, the computational complexity of the proposed scheme is very low compared to the existing schemes, making it more suitable for the fast decision-making required for smart vehicles.
Accessibility Measures to Evaluate Public Transport Competitiveness: The Case of Rome and Turin
Authors: Zini Alessandro , Roberto Roberta , Corrias Patrizia , Felici Bruna , Noussan Michel
Published: November 2024

The transport sector worldwide relies heavily on oil products, and private cars account for the largest share of passenger mobility in several countries. Public transport could represent an interesting alternative under many perspectives, including a decrease in traffic, pollutants, and climate emissions. However, for public transport to succeed, it should be attractive for final users, representing a viable alternative to private mobility. In this work, we analyse the spatial distribution of public transport service provision within two metropolitan cities, considering the three key dimensions of mobility, competitiveness, and accessibility of public transport. The results show that private car performs better than public transport in all scopes considered, and that performance indicators are highly variable among city areas, indicating inequalities in social and environmental sustainability in urban systems. The outcomes of the analysis provide interesting insights for policy makers and researchers that deal with similar topics, and can also be extended to other cities and countries.
Bias Analysis and Correction in Weighted-L1 Estimators for the First-Order Bifurcating Autoregressive Model
Authors: Elbayoumi Tamer , Mostafa Sayed
Published: November 2024

This study examines the bias in weighted least absolute deviation (WL1) estimation within the context of stationary first-order bifurcating autoregressive (BAR(1)) models, which are frequently employed to analyze binary tree-like data, including applications in cell lineage studies. Initial findings indicate that WL1 estimators can demonstrate substantial and problematic biases, especially when small to moderate sample sizes. The autoregressive parameter and the correlation between model errors influence the volume and direction of the bias. To address this issue, we propose two bootstrap-based bias-corrected estimators for the WL1 estimator. We conduct extensive simulations to assess the performance of these bias-corrected estimators. Our empirical findings demonstrate that these estimators effectively reduce the bias inherent in WL1 estimators, with their performance being particularly pronounced at the extremes of the autoregressive parameter range.
Sherlock Holmes Between Homogeneity Tests: Detection Power Based on Profitability Ratios in the V4 Region
Authors: Durana Pavol , Blazek Roman , Kovalova Erika
Published: November 2024

Profitability reveals the key financial ratios that ensure the long-term sustainability of an enterprise’s ability to invest in further growth. Without knowledge of the course of development, particularly changes in profitability, enterprises face financial difficulties that threaten their existence. Although the homogeneity tests serve as a reliable tool for identifying changes, their application in financial management often receives insufficient attention. The aim of this research is to evaluate the detection power of homogeneity tests and identify the one with the highest ability based on testing changes in the development of profitability ratios across sectors in the Visegrad Four. Buishand’s test, Pettitt’s test, the SNHT, and the von Neumann test were run for 8671 enterprises during 2016–2021 and gained from Moody’s Orbis. Comparison tables for ROA, ROC, ROE, ROS, ROR, and ROW using Monte Carlo simulation with a million replications identified the number of Slovak, Czech, Polish, and Hungarian enterprises in which heterogeneity was divided according to the Nomenclature of Economic Activities, NACE. The SNHT disclosed the greatest number of changes in the development of all profitability ratios. The results validate the use of selected tests for ratio assessment. Furthermore, business agencies may replicate this approach to determine the economic situation and sector performance.
Some Notes on the Gini Index and New Inequality Measures: The nth Gini Index
Authors: Gavilan-Ruiz José Manuel , Ruiz-Gándara África , Ortega-Irizo Francisco Javier , Gonzalez-Abril Luis
Published: November 2024

A new family of inequality indices based on the deviation between the expected maximum and the expected minimum of random samples, called the nth Gini index is presented. These indices generalize the Gini index. At the same time, this family of indices and the S-Gini index are generalized by proposing the uv-Gini index, which turns out to be a convex combination of the S-Gini index and the Lorenz family of inequality measures. This family of Gini indices provides a methodology for achieving perfect equality in a given distribution of incomes. This is achieved through a series of successive and equal increases in the incomes of each individual.
Rice Responses to the Stem Borer Diatraea saccharalis (Lepidoptera: Crambidae) by Infrared-Thermal Imaging: Implications for Field Management
Authors: Rocha Rodrigo de Almeida , dos Santos Pedro Valasco , Pazini Juliano de Bastos , Almeida André Cirilo de Sousa , Silva Anderson Rodrigo da
Published: November 2024

Diatraea saccharalis (Fabricius) is a major pest of rice crops, and its early detection—before any visible plant damage occurs—is crucial to prevent yield losses and establish effective, rational control methods. This study aimed to model the infrared-thermal responses of rice cultivars to D. saccharalis infestation levels. Between 2019 and 2020, two experiments were conducted in a controlled environment using the cultivars IR 40 and BR IRGA 409, previously identified as having different resistance reactions. Rice plants grown in pots were manually infested with first-instar larvae of D. saccharalis, ranging from 0 to 10 caterpillars per plant, with the plants maintained in cages covered with voile fabric throughout the trial. After 30 days of infestation, the number of live and dead caterpillars, the number of damaged and healthy stems, and the dry mass of the aerial parts were evaluated. A generalized linear mixed model was applied to the data obtained from leaf temperature as a function of infestation level throughout the infestation period, using the F-test to detect significant differences between cultivars. Generalized Additive Models for Location, Scale, and Shape (GAMLSS) were fitted to the variables related to resistance. It was observed that leaf surface temperature is related to the level of infestation and could be used to detect susceptibility in IR 40. In both cultivars, leaf temperatures were higher within the first 15 days post-infestation.
Service Robots in the Workplace: Fostering Sustainable Collaboration by Alleviating Perceived Burdensomeness
Authors: Almokdad Eeman , Lee Chung Hun
Published: November 2024

This study investigates the impact of job demands and perceived burdensomeness on employees’ willingness to collaborate with service robots (SRs) in the workplace, with a focus on the moderating effects of organizational support, self-esteem, and self-development. Conducted among 200 employees in South Korea, the results show that higher job demands significantly increase perceived burdensomeness, which negatively affects employees’ willingness to collaborate with SRs. Organizational support moderates the negative impact of job demands, reducing their detrimental effects, although it was less effective in buffering the reduction in social interaction. Self-esteem and self-development positively moderated the relationship between burdensomeness and collaboration. This study contributes to the understanding of sustainable workforce management by highlighting the importance of fostering personal and organizational resources to ensure that SR integration enhances both operational efficiency and employee well-being. The findings align with broader sustainability goals by promoting human–robot collaboration that optimizes resource use, enhances workforce adaptability, and maintains social and psychological balance in the workplace.
Correction: Vij et al. Application of Trichoderma viride and Pseudomonas fluorescens to Cabbage (Brassica oleracea L.) Improves Both Its Seedling Quality and Field Performance. Sustainability 2022, 14, 7583
Authors: Vij Shilpa , Sharma Neha , Sharma Meenakshi , Mohanta Tapan Kumar , Kaushik Prashant
Published: November 2024

In the publication [...]
Barriers to the Effective Selection of Sustainable Materials for Residential Building Projects: A Qualitative Study
Authors: Mahame Constant , Kikwasi Geraldine J. , Baruti Modest Maurus
Published: November 2024

Although sustainability in Tanzania’s construction sector has been explored in areas such as energy efficiency and green building practices, little attention has been given to understanding the specific barriers to the selection of SBMs in residential projects. This study fills that gap by identifying and analyzing the critical barriers hindering the effective selection of SBMs in Tanzania’s residential construction sector. Through qualitative interviews with experts from regulatory bodies, public developers, and academic researchers, this research provides a comprehensive examination of these barriers. Using Atlas.ti 23 software for a qualitative data analysis, six key categories of barriers were identified: (1) Regulatory and Policy Barriers, (2) Financial Barriers, (3) Knowledge and Awareness Barriers, (4) Technical Barriers, (5) Market and Supply Chain Issues, and (6) Cultural and Social Barriers. Among these, lack of awareness and limited knowledge emerged as particularly significant, alongside regulatory and policy barriers, in hindering the effective selection of SBMs. This study’s novelty lies in its focus on the Tanzanian context, depth of the analysis of the unique challenges, and categorization of the barriers. The findings underscore the need for targeted policy interventions, particularly in raising awareness, offering financial incentives, and establishing comprehensive regulatory frameworks. Furthermore, this study presents a graphical representation to illustrate the categories and constructs of these barriers, adding a visual dimension to the understanding of the issues. Future research should expand the scope to include private developers and material suppliers, whose roles are critical in enhancing the availability and adoption of SBMs in Tanzania’s construction industry.
Correction: Kumar et al. Root System Architecture and Symbiotic Parameters of Summer Mung Bean (Vigna Radiata) under Different Conservation Agriculture Practices. Sustainability 2022, 14, 3901
Authors: Kumar Arun , Saini Kulvir Singh , Rolaniya Lalit Kumar , Singh Love Kumar , Kaushik Prashant
Published: November 2024

Affiliation Update: [...]
Non-Linear Effects of Economic Policy Uncertainty on Green Innovation: Evidence from BRICS Countries
Authors: Farooq Umar , Alam Mohammad Mahtab , Subhani Bilal Haider , Tabash Mosab I. , Shamansurova Zilola
Published: November 2024

This research investigates the influence of economic policy uncertainty (EPU) and its squared term (squared EPU) on the advancement of environmental technologies and the registration of environmental patents in the BRICS nations over the period from 2010 to 2022. Employing the cross-section autoregressive distributed lag (CS-ARDL) technique, the analysis reveals a significant negative relationship liaison between EPU and both environmental innovation and patent registrations, indicating that an increased uncertainty discourages investment in sustainable technologies. Conversely, a positive relationship was found with square EPU, suggesting that elevated levels of uncertainty may stimulate innovative responses as firms seek to differentiate themselves in a competitive market. These findings underscore the necessity for stable and transparent policy frameworks to foster long-term commitments to environmental innovation. This research enriches the literature by illustrating the dual nature of EPU and its differentiated effects on eco-innovation.
Evaluation of the Effects of Rainwater Infiltration on Slope Instability Mechanisms
Authors: Lira Bruna Silveira , dos Santos Junior Olavo Francisco , de Freitas Neto Osvaldo , Sousa Maria Natália de Melo
Published: November 2024

Mass movements can be caused by factors from different categories, such as geological factors and climate change. From a geological point of view, the soil profile and the geotechnical properties of the materials are crucial in influencing slope instability. From a climate change perspective, rainfall intensity is one of the main triggers of mass movements. Studies related to rainfall infiltration focus on saturated slope zones; therefore, areas of slope stability with infiltration in the unsaturated zone present large gaps. The Brazilian government environmental diagnostics company, the Mineral Resources Research Company (CPRM), identified the municipality of Areia/PB as a danger zone. The region has landslides that occur mostly during the rainy season. Such events lead to the presumption that rainwater infiltration is responsible for the failure of the municipality’s slopes. Thus, the studies proposed in this research aim to determine the influence of precipitation on the stability of the slopes present in the region. The results show that antecedent precipitation has a greater influence on stability, indicating that daily precipitation alone cannot be used as a determinant for landslides. It was concluded that the role of precipitation in slope stability will vary for different locations, with varying surface conditions, variable tropical rainfall, or different microclimatic conditions.
Environmental Justice Specialization and Corporate ESG Performance: Evidence from China Environmental Protection Court
Authors: Meng Yue , Yang Xiaolei
Published: November 2024

In order to implement the dual-carbon strategy and achieve sustainable economic development, it is essential to guarantee environmental protection through the establishment of an effective environmental rule of law. This study employs a quasi-natural experiment, namely the establishment of environmental protection courts in China’s intermediate people’s courts, to investigate the impact on the ESG performance of A-share listed companies from 2010 to 2022. A double-difference model is utilized for this purpose. This study reveals that the specialization of environmental justice is an effective means of promoting the ESG performance of enterprises. The results of mechanism tests indicate that the specialization of environmental justice has a positive impact on the ESG performance of enterprises, primarily by enhancing external supervision and garnering greater media attention and analyst interest. Furthermore, heterogeneity analysis reveals that the influence of environmental justice specialization on corporate ESG performance is particularly pronounced in eastern regions, contexts characterized by high environmental uncertainty and heavily polluting enterprises. These findings offer invaluable insights into the development of environmental justice and the advancement of sustainable economic growth.
Strengthening Resilience and Sustainability for Post-Disaster Recovery: A Comparative Law and Economics Analysis on Smart Mixes Between Mechanisms
Authors: He Qihao , Faure Michael
Published: November 2024

This article advocates smart mixes of mechanisms of post-disaster recovery in terms of boosting resilience and sustainability through liability rules, government intervention, insurance, and their combinations. Liability rules can provide compensation to victims and, in theory, also reduce disaster risks, while they have their limits in practice. The government widely intervenes in disaster compensation in many countries, but it faces challenges in how it can intervene fairly and efficiently, whether through informal channels, such as ad hoc charity, or structured approaches, such as compensation funds. As governments may struggle to provide efficient and effective compensation ex post, insurance may offer proactive solutions with models of first-party catastrophe insurance and third-party liability insurance ex ante. Where market failure, liability failure, and government failure may all arise, a smart mix of mechanisms is often preferable from a law and economic perspective, rather than relying solely on one framework. However, upon examining empirical evidence regarding the effectiveness of these instruments in China, the UK, France, Germany, and Turkey, it becomes apparent that a mix of mechanisms is not always applied in an effective manner. Models of mandatory comprehensive disaster insurance, and Public–Private Partnership (PPP), which both receive government intervention as a last resort to the market and liability failures, can reach the goal of more effective compensation for disaster victims, risk prevention and resilience when faced with disaster recovery, and should therefore be substantially implemented beyond the current levels. To be clear, the proposed mix of solutions mainly focuses on legal and economic dimensions which are rather limited, ignoring, for example, building codes for structures and physical interventions.
Measurement, Characteristic Facts and Policy Recommendations for China’s City-Scale Manufacturing Value Chains
Authors: Ren Jinxin , He Shuquan , Ren Hang , Ren Gui
Published: November 2024

This paper constructs and optimizes, for the first time, the decomposition framework of inter-city outflow and export from the urban scale and analyzes the basic characteristics of China’s urban manufacturing industry’s participation in the global value chain and national value chain from the perspective of temporal and spatial evolution. The results show that the participation index of the manufacturing industry in coastal cities is higher than that in inland cities, and inland cities are more inclined to rely on the domestic value chain to obtain superior resources for the development of the manufacturing industry. The indicators of the manufacturing industry in the cities of the province show excellent performance, while the indicators of the peripheral cities show poor characteristics. At the same time, the length index of the global value chain of the coastal city manufacturing industry is also consistent with the actual development of the urban manufacturing industry in China. The performances of China’s urban manufacturing industry in participating in the global value chain and the domestic value chain are different. Under the background of the new development pattern, the effective docking of the double chains should be realized to achieve high-quality development in the manufacturing industry.
Research on Whether Quality Policies Can Promote the High-Quality Development of China’s Manufacturing Industry and Its Configuration Paths in the Context of Sustainable Development
Authors: Zhang Zhiqiang , Bai Yifan
Published: November 2024

High-quality development enhances economic quality and resource allocation efficiency through various effective and sustainable means, with particularly notable results in the manufacturing sector. Quality policies, through establishing standards, norms, and incentive measures, aim to foster technological innovation, efficient resource utilization, and quality improvement in manufacturing, thereby supporting its high-quality development. This study explores the impact of quality policies on high-quality development in manufacturing and their configurational pathways, providing theoretical foundations and practical guidance for optimizing policy combinations and promoting sustainable development. This analysis is based on quality policies released from 2013 to 2022 and sample data from 30 Chinese provinces. The findings reveal that quality policies significantly promote high-quality development in manufacturing, particularly through incentive, capacity building, and system changing instruments, while command instruments may exert certain pressures on high-quality development. Configuration analysis further indicates that a single instrument is insufficient to support high-quality development in manufacturing fully; the synergistic effect of multiple policy instruments is essential, and regions should optimize policy combinations according to their characteristics. This study provides valuable insights for sustainable development, offering a deeper understanding of the complex causal relationship between quality policies and high-quality development in manufacturing.
Emissions Reduction Effects and Carbon Leakage Risks of Carbon Emissions Trading Policy: An Empirical Study Based on the Spatial Durbin Model
Authors: Qiu Hannuo , Yang Bian , Liu Ying , Wang Linping
Published: November 2024

China’s carbon emissions trading policy represents a significant institutional innovation designed to advance the country’s economic and social development towards sustainability and low-carbon growth. This study investigates the effects of China’s carbon emissions trading policy by employing the difference-in-differences model and spatial Durbin model, using provincial panel data spanning from 2005 to 2020. We find that the carbon emissions trading policy can inhibit per capita carbon emissions in the pilot areas. This work is primarily driven by green technological innovation and the upgrade of industrial structure. Furthermore, the carbon emissions trading policy exhibits a positive spatial spillover effect, inhibits per capita carbon emissions in the areas adjacent to the pilot through demonstration effect and competition effect, and does not cause carbon leakage. These findings reveal the policy’s effectiveness in emissions reduction, and may be useful reference for promoting sustainable economic and social development. This is of great practical significance for exploring how to optimize environmental governance measures, avoid carbon leakage, and achieve balance and fairness in responsibilities in achieving low-carbon sustainable development. Our study proposes policy recommendations for synergizing the national trading market in China.
The Role of Influencers in Shaping the Economic Decisions of Consumers Using the Logistic Regression Approach—Does the Generation Factor Matter?
Authors: Mawad Jeanne Laure J. , Freiha Sibelle S.
Published: November 2024

This article explores the role of social media marketing in shaping economic decisions among consumers. This study aims to examine the characteristics influencing consumer intentions, with a strong emphasis on the role of influencers. In order to conduct this study, a logistic regression was employed. The sample reveals that individuals who view influencers as credible sources of information and experience, those who exhibit homophily with influencers, those who perceive the influencers’ content as high-quality, and those who develop strong parasocial relationships with influencers show higher consumption intentions. In contrast, older individuals tend to have lower consumption intentions. These consumption intention characteristics vary across genders and generations. The study concludes with recommendations targeting all relevant stakeholders, influencers, businesses, policy makers, and consumers.
Indulging in Tempting Yet Unhealthy Delights: Exploring the Moderating Influence of Gender and Motivation for Healthy and Sustainable Eating
Authors: Hansen Torben
Published: November 2024

Individuals frequently encounter alluring food temptations that can disrupt their efforts to follow a healthy diet. These temptations may trigger pleasurable thoughts and sensations, potentially leading to unhealthy eating habits and obesity, which misalign with the goals of sustainable food systems to promote overall well-being. However, there is limited knowledge regarding how individual differences such as gender and motivation for healthy eating might impact individuals’ responses to unhealthy food temptations. In an experimental investigation, 245 participants were exposed to a tasty but low-nutrient food product (potato crisps). The results provide several new insights: (a) when individuals’ motivation for healthy eating is low, pleasurable experiences have a positive impact on perceived dietary quality; (b) pleasurable feelings also directly reduce willingness to consume potato crisps; (c) gender influences the relationship between pleasure-feeling and willingness to eat, with a negative relationship for women and a non-significant relationship for men; and (d) among women, there is a positive relationship between arousal and willingness to eat, while this relationship is non-significant for men. This study adds to the body of knowledge already available on food temptations, nutrition, and sustainable eating.
The Role of Wild Food in Fostering Healthy, Sustainable, and Equitable Food Systems
Authors: Scott Madison M. , Carolan Michael S. , Long Michael A.
Published: November 2024

In this paper, we provide an overview of the research and literature on wild foods (i.e., edible plants that grow without human cultivation and/or animals harvested from their natural habit, i.e., food sourced from “hunting and gathering”) and their ability to assist food systems in becoming more sustainable and equitable. We begin with a discussion on the green revolution and the global capitalist food system that has been created and is dominated by large agribusinesses. Next, we turn to a brief discussion of how homogenizing the food system, as large agribusinesses have, leads to a corresponding loss of local culture. We then provide an overview of the main areas of wild food research, including nutrition, reducing food insecurity, the importance of cultural and shared knowledge, and sustainability. Our discussion stresses how focusing too heavily on the dichotomy of cultivated vs. wild food is problematic. Rather, lessons regarding health, sustainability, and equity can be learned from foragers, hunters and gathers.
Foundation Model Study on Inorganic and Biopolymer Nano Additives Treated Soil—A Step Forward in Nano Additive Soil Stabilization
Authors: Kannan Govindarajan , Sujatha Evangelin Ramani , Baldovino Jair de Jesús Arrieta , Rosa Yamid E. Nuñez de la
Published: November 2024

For almost a decade, various studies have been carried out to prove the suitability of nano additives in enhancing the geotechnical properties of soil. Yet, this line of research is still in its elementary stage, restricting itself to laboratory tests to determine soil’s index and engineering properties blended with varying dosages of nano additives. In other words, research on practical applications of nano additives for soil stabilization is scarce. The present work attempts to investigate the suitability of three different nanomaterials as a load-bearing stratum for shallow foundations. The nano additives were chosen in such a way that each of them is from a different origin. One of them is nano calcium carbonate (inorganic) whereas the other two are nano-sized varieties of natural biopolymers, namely nano chitosan (crustacean-based) and nano carboxymethyl cellulose (plant-based). A series of laboratory tests were initially conducted to determine the strength of all three nano-additive-treated soils at different dosages, which were investigated for 180 days to ensure their long-term performance. This was followed by a foundation model study on untreated soil and on soil treated with optimal dosages of nano additives. The results were validated using finite element software followed by a parametric study to optimize the depth of soil stabilization. It was observed that all three nano additives exhibited a better performance when the top layer had the optimal dosage and the subsequent layers had a relatively lesser dosage.
Prioritizing Criteria for Establishing a Green Shipping Corridor Between the Ports of Sines and Luanda Using Fuzzy AHP
Authors: Bengue Alberto Antonio , Alavi-Borazjani Seyedeh Azadeh , Chkoniya Valentina , Cacho José Luís , Fiore Mariantonietta
Published: November 2024

As port authorities and cargo operators seek strategies to reduce carbon emissions while ensuring operational efficiency, some are turning to the concept of green corridors. These solutions aim to establish formalized partnerships among ports, carriers, shippers, and countries. During the process, the stakeholders must consider four priority areas (alternative fuels, bunkering infrastructure, vessel decarbonization pathways, and cargo demand dynamics) from seven angles (environmental, economic, infrastructure, regulatory, operational, technological, and social). This study explores the prioritization of these criteria for establishing a green maritime corridor between two major ports in Portugal and Angola, which would be a significant step toward promoting sustainable global trade. Utilizing the fuzzy AHP, this research analyzes all these factors and their associated sub-criteria derived from a comprehensive literature review and consultations with stakeholders from the Ports of Sines and Luanda. The findings show the dominance of environmental compatibility and economic viability, while social acceptance shows the lowest score. This framework guides the decision-making process for developing a sustainable shipping corridor. The results offer valuable insights for policymakers which can guide them in fostering resilient maritime transport routes, accelerating the adoption of decarbonization strategies and playing a critical role in achieving the IMO’s zero-emission targets by 2050.
Enhancing Environmental Sensitivity and Vulnerability Assessments for Oil Spill Responses in the Caspian Sea
Authors: Iskakov Berik , Nurakynov Serik , Dabas Jagriti , Zhantayev Zhumabek , Balakay Larissa , Dedova Tatyana , Yelisseyeva Alena , Sydyk Nurmakhambet
Published: November 2024

Oil spills pose significant threats to marine and coastal ecosystems, necessitating advanced methodologies for environmental sensitivity and vulnerability assessments. This study enhances existing frameworks to better manage oil spill risks in the Caspian Sea, a region characterized by its ecological sensitivity and economic dependence on oil extraction. Utilizing the Environmental Sensitivity Index (ESI), we adapted global standards to the unique conditions of the Caspian Sea and built a sensitivity map of the coastline, which later became one of the components of the integral sensitivity map for the entire Caspian Sea, which includes several biotic and abiotic components. We also developed a comprehensive geodatabase incorporating topographic, infrastructural, and hydrodynamic data. Through the sophisticated modeling of oil spill scenarios using the Oil Spill model of the MIKE 21 software (Release 2016) suite, we simulated spills of varying magnitudes to analyze their potential impacts on the marine and coastal environment. The results enabled the creation of vulnerability maps, pinpointing areas at highest risk and facilitating strategic response planning. Our study demonstrates the critical importance of integrating advanced geospatial analyses and dynamic modeling techniques to improve oil spill preparedness and response strategies. The findings of this study suggest that enhanced monitoring and adaptive management strategies are essential for protecting the Caspian Sea from environmental risks posed by its oil industry.
Research on the Carbon Emission Reduction Effect of the Dual Pilot Policy of Low-Carbon Cities and New Energy Demonstration Cities
Authors: Li Yinlong , Zhang Jingjing
Published: November 2024

Achieving the “double carbon” goal and optimizing the energy structure necessitates strategic deployments such as low-carbon cities (LCCs) and new energy demonstration cities (NEDCs). Prior research has primarily examined the effectiveness of these two policies when implemented independently. Despite overlapping scopes, there remains a need for a definitive conclusion regarding whether the concurrent implementation of these policies will yield a synergistic effect, thereby further reducing carbon emissions. Employing panel data spanning 2007–2021 from 280 Chinese cities, this study investigates the carbon emission reduction (CER) effect of the dual pilot policy (DPP), focusing specifically on LCCs and NEDCs through a multi-period difference-in-differences (DID) analysis. The findings reveal a significant synergistic effect between LCCs and NEDCs on CER, with the sequence of policy implementation playing a crucial role in determining the effectiveness of CER. Notably, cities first become NEDCs and subsequently transition into LCCs, demonstrating a more pronounced CER effect. Further analysis of the impact mechanism underscores that the DPP fosters urban CER by elevating inventive and improved green technology innovation. Among these, the contribution of inventive green technology innovation is particularly prominent, accounting for as much as 24%, far surpassing the 20% contribution of improved green technology innovation. A heterogeneity analysis indicates that the DPP’s impact is more significant in western and non-resource-based cities. Given China’s status as one of the world’s foremost carbon emitters, exploring China’s CER pathways holds profound practical significance and offers invaluable empirical insights for advancing global CER efforts.