bluuebunny/crossref_metadata_2025 huggingface dataset:
Shear Bond Strength of Clear Aligner Attachment Using 4-META/MMA-TBB Resin Cement on Glazed Monolithic Zirconia
Authors: Nitasnoraset Kasidit , Riddhabhaya Apiwat , Sessirisombat Chidchanok , Hotokezaka Hitoshi , Yoshida Noriaki , Sirisoontorn Irin
Published: July 2024

Increasing demand for adult orthodontic treatment using clear aligners has highlighted challenges in bonding clear aligner attachments to various restorations. Specifically, the bond strength of clear aligner attachments to glazed monolithic zirconia has not been extensively studied. This study aims to compare the shear bond strength (SBS) and mode of failure (MOF) of conventional bonding methods versus Superbond C&B (4-META/MMA-TBB resin cement) for clear aligner attachments on glazed monolithic zirconia. Fifty sintered and glazed zirconia samples were divided into five groups and attached with clear aligner attachments: Si (silane), B (bonding agent), SiB (bonding agent and silane), SU (Superbond C&B), and SiSU (silane and Superbond C&B). SBS and MOF of these samples were analyzed. Results indicated a significant difference in bond strength among the groups. SiSU exhibited the highest bond strength, followed by SU, while B had the lowest bond strength. SEM analysis revealed that SiSU and SU predominantly exhibited mixed failure, indicating high bond strength without affecting the glazed layers of the zirconia. In contrast, B exhibited only adhesive failure at the interface, resulting in insufficient bond strength for effective orthodontic treatment. In conclusion, using 4-META/MMA-TBB resin cement provides high bond strength for clear aligner attachments on glazed zirconia with minimal material damage during debonding.
A Comprehensive Review on Starch-Based Hydrogels: From Tradition to Innovation, Opportunities, and Drawbacks
Authors: Koshenaj Katerina , Ferrari Giovanna
Published: July 2024

Natural hydrogels based on renewable and inexpensive sources, such as starch, represent an interesting group of biopolymeric materials with a growing range of applications in the biomedical, cosmeceutical, and food sectors. Starch-based hydrogels have traditionally been produced using different processes based on chemical or physical methods. However, the long processing times, high energy consumption, and safety issues related to the synthesis of these materials, mostly causing severe environmental damage, have been identified as the main limitations for their further exploitation. Therefore, the main scientific challenge for research groups is the development of reliable and sustainable processing methods to reduce the environmental footprint, as well as investigating new low-cost sources of starches and individuating appropriate formulations to produce stable hydrogel-based products. In the last decade, the possibility of physically modifying natural polysaccharides, such as starches, using green or sustainable processing methods has mostly been based on nonthermal technologies including high-pressure processing (HPP). It has been demonstrated that the latter exerts an important role in improving the physicochemical and techno-functional properties of starches. However, as for surveys in the literature, research activities have been devoted to understanding the effects of physical pre-treatments via high-pressure processing (HPP) on starch structural modifications, more so than elucidating its role and capacity for the rapid formation of stable and highly structured starch-based hydrogels with promising functionality and stability, utilizing more sustainable and eco-friendly processing conditions. Therefore, the present review addresses the recent advancements in knowledge on the production of sustainable starch-based hydrogels utilizing HPP as an innovative and clean-label preparation method. Additionally, this manuscript has the ambition to give an updated overview of starch-based hydrogels considering the different types of structures available, and the recent applications are proposed as well to critically analyze the main perspectives and technological challenges for the future exploitation of these novel structures.
Modeling and Optimizing Biocontrol in Wines: pH as a Modulator of Yeast Amensalism Interaction
Authors: Kuchen Benjamín , Groff María Carla , Pantano María Nadia , Pedrozo Lina Paula , Vazquez Fabio , Scaglia Gustavo
Published: July 2024

The control of spoilage yeasts in wines is crucial to avoid organoleptic deviations in wine production. Traditionally, sulfur dioxide (SO2) was used to control them; nevertheless, SO2 influence on human health and its use is criticized. Biocontrol emerges as an alternative in wine pre-fermentation, but there is limited development in its applicability. Managing kinetics is relevant in the microbial interaction process. pH was identified as a factor affecting the interaction kinetics of Wickerhamomyces anomalus killer biocontrol on Zygosaccharomyces rouxii. Mathematical modeling allows insight into offline parameters and the influence of physicochemical factors in the environment. Incorporating submodels that explain manipulable factors (pH), the process can be optimized to achieve the best-desired outcomes. The aim of this study was to model and optimize, using a constant and a variable pH profile, the interaction of killer biocontrol W. anomalus vs. Z. rouxii to reduce the spoilage population in pre-fermentation. The evaluated biocontrol was W. anomalus against the spoilage yeast Z. rouxii in wines. The kinetic interactions of yeasts were studied at different pH levels maintained constant over time. The improved Ramón-Portugal model was adopted using the AMIGO2 toolbox for Matlab. A static optimization of a constant pH profile was performed using the Monte Carlo method, and a dynamic optimization was carried out using a method based on Fourier series and orthogonal polynomials. The model fit with an adjusted R2 of 0.76. Parametric analyses were consistent with the model behavior. Variable vs. constant optimization achieved a lower initial spoilage population peak (99% less) and reached a lower final population (99% less) in a reduced time (100 vs. 140 h). These findings reveal that control with a variable profile would allow an early sequential inoculation of S. cerevisiae. The models explained parameters that are difficult to quantify, such as general inhibitor concentration and toxin concentration. Also, the models indicate higher biocontrol efficiency parameters, such as toxin emission or sensitivity to it, and lower fitness of the contaminant, at pH levels above 3.7 during biocontrol. From a technological standpoint, the study highlights the importance of handling variable profiles in the controller associated with the pH management actuators in the process without incurring additional costs.
Special Issue “Recent Advances in Processing Technologies for Substance Extraction, Separation, and Enrichment”
Authors: Zhang Yanlin , Sarswat Prashank K.
Published: July 2024

Substance separation has always been the foundation of production processes in a variety of industrial sectors such as hydrometallurgy, natural compounds extraction, food industry, pharmaceutical industry, and environmental engineering [...]
Temperature Control Effect on Cheese Whey Anaerobic Digestion with Low-Cost Tubular Digesters
Authors: Ramos-Suárez Juan Luis , Álvarez-Méndez Sergio J. , Padrón Tejera Eseró , Ritter Axel , Mata González Javier
Published: July 2024

Cheese whey (CW) is a worldwide abundant by-product of the cheese industry, which can be used for biogas production if further processing is not performed to produce other valuable food products. This study evaluates biogas production from CW in low-cost, tubular reactors, thus comparing the effect of temperature control. CW was monodigested in two tubular reactors at the pilot scale: one of them with temperature control (30 ± 3 °C) and the other one working at environmental conditions. The results show that CW could be monodigested in pilot scale tubular reactors, thus yielding high methane. Temperature control (30 ± 3 °C) at the pilot scale led to higher methane yields under all tested operating conditions, thus reaching 565.8 ± 20.9 L kg−1VS at an Organic Loading Rate (OLR) of 0.416 ± 0.160 kgVS L−1 d−1, which was higher than the maximum yield obtained without temperature control (445.6 ± 21.9 L kg−1VS) at 0.212 ± 0.020 kgVS L−1 d−1. Methane yield differences were attributed to the increase in temperature, thus leading to a more stable process and a higher degradation capacity. The increase in temperature is only worthwhile if adequate thermal insulation is used between the digester and the soil; otherwise, the increase in biogas production will not meet the digester’s heat demand. The anaerobic monodigestion of CW in low-cost tubular reactors is a promising alternative for CW valorization, thus leading to high biogas yields, which can be used in several energy applications replacing fossil fuels.
Development, Experimental, and Numerical Characterisation of Novel Flexible Strain Sensors for Soft Robotics Applications
Authors: Nnadi Sylvester Ndidiamaka , Ajadalu Ivor , Rahmani Amir , Aliyu Aliyu , Elgeneidy Khaled , Montazeri Allahyar , Sohani Behnaz
Published: July 2024

Medical and agricultural robots that interact with living tissue or pick fruit require tactile and flexible sensors to minimise or eliminate damage. Until recently, research has focused on the development of robots made of rigid materials, such as metal or plastic. Due to their complex configuration, poor spatial adaptability and low flexibility, rigid robots are not fully applicable in some special environments such as limb rehabilitation, fragile objects gripping, human–machine interaction, and locomotion. All these should be done in an accurate and safe manner for them to be useful. However, the design and manufacture of soft robot parts that interact with living tissue or fragile objects is not as straightforward. Given that hyper-elasticity and conductivity are involved, conventional (subtractive) manufacturing can result in wasted materials (which are expensive), incompatible parts due to different physical properties, and high costs. In this work, additive manufacturing (3D printing) is used to produce a conductive, composite flexible sensor. Its electrical response was tested based on various physical conditions. Finite element analysis (FEA) was used to characterise its deformation and stress behaviour for optimisation to achieve functionality and durability. Also, a nonlinear regression model was developed for the sensor’s performance.
The Impact of Glacial Shrinkage on Future Streamflow in the Urumqi River Source Region of Eastern Tien Shan, Central Asia
Authors: Zhao Weibo , Li Zhongqin , Li Hongliang , Xu Chunhai , Mu Jianxin , Yang Yefei
Published: July 2024

Understanding changes in runoff due to climate variations in glacier-dominated headwaters is key to managing water resources and dryland watersheds effectively and rationally. The continuous glacier shrinkage caused by climate warming has significantly impacted the water supply and ecological systems in the vast arid regions of Central Asia, attracting extensive public concern. The study results indicate an increase in total runoff at the Urumqi River source region during both the baseline (1997–2016) and mid-century (2040–2059) periods, encompassing rain, glacier meltwater, and snowmelt components. Compared to the baseline period, the temperature increases by the mid-century under the three climate scenarios (SSP1−26, SSP2−45, and SSP5−85) range from 0.98 to 1.48 °C. In this region, during the period from 1997 to 2016, glacier meltwater was the dominant component of runoff, comprising 42.10–43.79% of the total, followed by snowmelt at 29.64–30.40% and rainfall contributions of 26.56–27.49%. Additionally, glacier storage in this typical catchment responds quickly to temperature fluctuations, significantly impacting runoff. The Urumqi River source region’s runoff exhibits heightened sensitivity to these temperature shifts compared to precipitation effects. We hypothesized three glacier coverage scenarios: unchanged at 100% glaciation, reduced by half to 50%, and fully retreated to 0% glaciation. Analysis of these scenarios demonstrated that glaciers are pivotal in runoff formation. Under the SSP1−26, SSP2−45, and SSP5−85 climate scenarios, glaciers contributed additional runoff increases of 51.61%, 57.64%, and 62.07%, respectively. Generally, glaciers play a critical role in supplying water in dry areas. Thus, accurately forecasting future water resource shifts in high-altitude glacier regions is crucial for downstream water resource management and utilization.
Remote Sensing Classification and Mapping of Forest Dominant Tree Species in the Three Gorges Reservoir Area of China Based on Sample Migration and Machine Learning
Authors: Zhang Wenbo , Liu Xiaohuang , Xu Bin , Liu Jiufen , Li Hongyu , Zhao Xiaofeng , Luo Xinping , Wang Ran , Xing Liyuan , Wang Chao , Zhao Honghui
Published: July 2024

The distribution of forest-dominant tree species is crucial for ecosystem assessment. Remote sensing monitoring requires annual ground sample data, but consistent field surveys are challenging. This study addresses this by combining sample migration learning and machine learning for multi-year tree species classification in the Three Gorges Reservoir area in China. Using the continuous change detection and classification (CCDC) algorithm, sample data from 2023 were successfully migrated to 2018–2022, achieving high migration accuracy (R2 = 0.8303, RMSE = 4.64). Based on migrated samples, random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB) algorithms classified forest tree species with overall accuracies above 70% and Kappa coefficients above 0.6. XGB. They outperformed other algorithms, with classification accuracy of over 80% and Kappa above 0.75 in almost all years. The final map indicates stable distribution from 2018 to 2023, with eucalyptus covering over 40% of the forest area, followed by horsetail pine, fir, cypress, and wetland pine.
Data Matters: Rethinking the Data Distribution in Semi-Supervised Oriented SAR Ship Detection
Authors: Yang Yimin , Lang Ping , Yin Junjun , He Yaomin , Yang Jian
Published: July 2024

Data, in deep learning (DL), are crucial to detect ships in synthetic aperture radar (SAR) images. However, SAR image annotation limitations hinder DL-based SAR ship detection. A novel data-selection method and teacher–student model are proposed in this paper to effectively leverage sparse labeled data and improve SAR ship detection performance, based on the semi-supervised oriented object-detection (SOOD) framework. More specifically, we firstly propose a SAR data-scoring method based on fuzzy comprehensive evaluation (FCE), and discuss the relationship between the score distribution of labeled data and detection performance. A refined data selector (RDS) is then designed to adaptively obtain reasonable data for model training without any labeling information. Lastly, a Gaussian Wasserstein distance (GWD) and an orientation-angle deviation weighting (ODW) loss are introduced to mitigate the impact of strong scattering points on bounding box regression and dynamically adjusting the consistency of pseudo-label prediction pairs during the model training process, respectively. The experiments results on four open datasets have demonstrated that our proposed method can achieve better SAR ship detection performances on low-proportion labeled datasets, compared to some existing methods. Therefore, our proposed method can effectively and efficiently reduce the burden of SAR ship data labeling and improve detection capacities as much as possible.
Sub-Aperture Synthetic Aperture Radar Imaging of Fixed-Platform Beam-Steering Radar for Blast Furnace Burden Surface Detection
Authors: Deng Lifu , Chen Xianzhong , Hou Qingwen
Published: July 2024

Due to the scheme of fixed-platform beam-steering radar and the space of the blast furnace being subjected to harsh environmental influences, the traditional detection methods of burden surface are limited by geometric distortion, noncoherent clutter, and noise interference, which leads to an increase in the image entropy value and the equivalent number of views, makes the density distribution of burden surface show a diffuse state, and greatly affects the stability and accuracy. In this paper, a new fixed-platform beam-steering radar synthetic aperture radar imaging method (FPBS-SAR) is proposed in the sensory domain of the blast furnace environment. From the perspective of fixed-platform beam-steering radar motion characteristics, the target range–azimuth coupled distance history model under the sub-aperture is established, the azimuthal Doppler variation characteristics of the fixed-platform beam-steering process are analyzed, and the compensation function of the transform domain for geometric disturbance correction is proposed. For noncoherent noise suppression in blast furnaces, the trimmed geometric mean-order-likelihood CFAR method is proposed to take into account the information of burden surface and clutter suppression. To verify the method, point target simulation and imaging for the industrial field measurement data are carried out. The results indicate that geometric distortion is well eliminated, the image entropy value and the equivalent number of views have decreased, and noncoherent noise in blast furnaces is suppressed.
Assessing the Presence of Pithomyces chartarum in Pastureland Using IoT Sensors and Remote Sensing: The Case Study of Terceira Island (Azores, Portugal)
Authors: Ávila Mariana , Pinelo João , Casas Enrique , Capinha César , Pabst Rebecca , Szczesniak Iga , Domingues Elizabeth , Pinto Carlos , Santos Valentina , Gil Artur , Arbelo Manuel
Published: July 2024

Spores from the fungus Pithomyces chartarum are commonly found on Azorean pastures. When consumed by cattle along with the grass, these spores cause health issues in the cattle, resulting in animal suffering and financial losses. For approximately two years, we monitored meteorological parameters using weather stations and collected and analyzed grass samples in a laboratory to control for the presence of spores. The data confirmed a connection between meteorology and sporulation, enabling the prediction of sporulation risk. To detect the presence of spores in pastures rather than predict it, we employed field spectrometry and Sentinel-2 reflectance data to measure the spectral signatures of grass while controlling for spores. Our findings indicate that meteorological variables from the past 90 days can be used to predict sporulation, which can enhance the accuracy of a web-based alert system used by farmers to manage the risk. We did not detect significant differences in spectral signatures between grass with and without spores. These studies contribute to a deeper understanding of P. chartarum sporulation and provide actionable information for managing cattle, ultimately improving animal welfare and reducing financial losses.
A Novel Method for Identifying Frailty and Quantifying Muscle Strength Using the Six-Minute Walking Test
Authors: Zhang Yunjin , Morita Minoru , Hirano Tsunahiko , Doi Keiko , Han Xin , Matsunaga Kazuto , Jiang Zhongwei
Published: July 2024

The six-minute walking test (6MWT) is an essential test for evaluating exercise tolerance in many respiratory and cardiovascular diseases. Frailty and sarcopenia can cause rapid aging of the cardiovascular system in elderly people. Early detection and evaluation of frailty and sarcopenia are crucial for determining the treatment method. We aimed to develop a wearable measuring system for the 6MWT and propose a method for identifying frailty and quantifying walking muscle strength (WMS). In this study, 60 elderly participants were asked to wear accelerometers behind their left and right ankles during the 6MWT. The gait data were collected by a computer or smartphone. We proposed a method for analyzing walking performance using the stride length (SL) and step cadence (SC) instead of gait speed directly. Four regions (Range I–IV) were divided by cutoff values of SC = 2.0 [step/s] and SL = 0.6 [m/step] for a quick view of the frail state. There were 62.5% of frail individuals distributed in Range III and 72.4% of non-frail individuals in Range I. A concept of a WMS score was proposed for estimating WMS quantitatively. We found that 62.5% of frail individuals were scored as WMS1 and 41.4% of the non-frail elderly as WMS4. The average walking distances corresponding to WMS1–4 were 207 m, 370 m, 432 m, and 462 m, respectively. The WMS score may be a useful tool for quantitatively estimating sarcopenia or frailty due to reduced cardiopulmonary function.
A Blockchain Copyright Protection Scheme Based on CP-ABE Scheme with Policy Update
Authors: Jiang Jian , Gao Yulong , Gong Yufei , Jiang Zhengtao
Published: July 2024

Although the copyright protection schemes supported by blockchain have significantly changed traditional copyright data management, there are still some data security challenges that cannot be ignored, especially the secure access and controllable management of copyright data. Quantum computing attacks also pose a threat to its security. Targeting these issues, we design and propose a blockchain copyright protection scheme based on attribute-based encryption (ABE). In this scheme, the security advantages of blockchain technology are utilized to ensure the authenticity and integrity of copyright data. Based on lattice cryptography and the decision ring learning with errors (R-LWE) problem, a new ABE algorithm that supports searchable ciphertext and policy updates is designed. Then, we introduce it into the blockchain copyright protection scheme, which enables secure access to copyright data and fine-grained control. In addition, the lattice cryptography can strengthen this scheme against quantum attacks. Through security analysis, our scheme can prove to be secure against adaptive chosen keyword attacks, selective chosen plaintext attacks, and adaptive chosen policy attacks in the random oracle model. More importantly, the comparison analysis and experimental results show that our proposed approach has lower computation costs and storage costs. Therefore, our scheme has better security and performance in copyright protection.
StarDICE II: Calibration of an Uncooled Infrared Thermal Camera for Atmospheric Gray Extinction Characterization
Authors: Sommer Kélian , Plez Bertrand , Cohen-Tanugi Johann , Dagoret-Campagne Sylvie , Moniez Marc , Neveu Jérémy , Betoule Marc , Bongard Sébastien , Feinstein Fabrice , Le Guillou Laurent , Juramy Claire , Sepulveda Eduardo , Souverin Thierry
Published: July 2024

The StarDICE experiment strives to establish an instrumental metrology chain with a targeted accuracy of 1 mmag in griz bandpasses to meet the calibration requirements of next-generation cosmological surveys. Atmospheric transmission is a significant source of systematic uncertainty. We propose a solution relying on an uncooled infrared thermal camera to evaluate gray extinction variations. However, achieving accurate measurements with thermal imaging systems necessitates prior calibration due to temperature-induced effects, compromising their spatial and temporal precision. Moreover, these systems cannot provide scene radiance in physical units by default. This study introduces a new calibration process utilizing a tailored forward modeling approach. The method incorporates sensor, housing, flat-field support, and ambient temperatures, along with raw digital response, as input data. Experimental measurements were conducted inside a climatic chamber, with a FLIR Tau2 camera imaging a thermoregulated blackbody source. The results demonstrate the calibration effectiveness, achieving precise radiance measurements with a temporal pixel dispersion of 0.09 W m−2 sr−1 and residual spatial noise of 0.03 W m−2 sr−1. We emphasize that the accuracy of scene radiance retrieval can be systematically affected by the camera’s close thermal environment, especially when the ambient temperature exceeds that of the scene.
Copper Micro-Flowers for Electrocatalytic Sensing of Nitrate Ions in Water
Authors: Farina Roberta , D’Arrigo Giuseppe , Alberti Alessandra , Scalese Silvia , Capuano Giuseppe E. , Corso Domenico , Screpis Giuseppe A. , Coniglio Maria Anna , Condorelli Guglielmo G. , Libertino Sebania
Published: July 2024

The progressive increase in nitrate’s (NO3−) presence in surface and groundwater enhances environmental and human health risks. The aim of this work is the fabrication and characterization of sensitive, real-time, low-cost, and portable amperometric sensors for low NO3− concentration detection in water. Copper (Cu) micro-flowers were electrodeposited on top of carbon screen-printed electrodes (SPCEs) via cyclic voltammetry (with voltage ranging from −1.0 V to 0.0 V at a scan rate of 0.1 V s−1). The obtained sensors exhibited a high catalytic activity toward the electro-reduction in NO3−, with a sensitivity of 44.71 μA/mM. They had a limit of detection of 0.87 µM and a good dynamic linear concentration range from 0.05 to 3 mM. The results were compared to spectrophotometric analysis. In addition, the devices exhibited good stability and a maximum standard deviation (RSD) of 5% after ten measurements; reproducibility, with a maximum RSD of 4%; and repeatability after 10 measurements with the RSD at only 5.63%.
Connecting Soft and Hard: An Integrating Role of Systems Dynamics in Tsunami Modeling and Simulation
Authors: Zanker Marek , Alhasnawi Bilal Naji , Babič František , Bureš Vladimír , Čech Pavel , Husáková Martina , Mikulecký Peter , Nacházel Tomáš , Ponce Daniela , Iqbal Salman , Sedhom Bishoy E.
Published: July 2024

Modeling and simulation have been used to study tsunamis for several decades. We created a review to identify the software and methods used in the last decade of tsunami research. The systematic review was based on the PRISMA methodology. We analyzed 105 articles and identified 27 unique software and 45 unique methods. The reviewed articles can be divided into the following basic categories: exploring historical tsunamis based on tsunami deposits, modeling tsunamis in 3D space, identifying tsunami impacts, exploring relevant variables for tsunamis, creating tsunami impact maps, and comparing simulation results with real data. Based on the outcomes of this review, this study suggests and exemplifies the possibilities of system dynamics as a unifying methodology that can integrate modeling and simulation of most identified phenomena. Hence, it contributes to the development of tsunami modeling as a scientific discipline that can offer new ideas and highlight limitations or a building block for further research in the field of natural disasters.
Quantitative Analysis of Carbon Emissions from Highway Construction Based on Life Cycle Assessment
Authors: Gao Shuohan , Liu Xuexin , Lu Chunying , Zhang Haixiao , Wang Xinjun , Kong Yaping
Published: July 2024

Carbon dioxide (CO2) emissions from the construction of road infrastructure have been of growing interest in recent years. This paper proposes a binary statistical method for highway construction based on project cost control and a construction management system. A quantitative analysis of the CO2 emissions from highway construction activities was also conducted to guide the formulation of a carbon reduction strategy. Taking an expressway in central China as a case study, the CO2 emissions from different construction activities were calculated. The results revealed that the CO2 emissions for the whole construction project reached 10,605.2 t·km−1·lane−1, with the raw material production and on-site construction phases accounting for 95.2% and 4.8%, respectively. The values for bridge and tunnel engineering were much higher than those for other engineering types. In the raw material production phase, steel and cement production contributed the most to emissions (more than 99%). During the on-site construction phase, diesel and electricity consumption contributed 90% to CO2 emissions, especially from earthwork, subgrade protection, bridge engineering, tunnel excavation, and pavement surfacing. Accordingly, efforts should be focused on the key points and directed toward using recycled and low-carbon materials and improving working efficiency, machinery performance, and construction technology.
The Occurrence of Microplastics in the Marine Food Web in Latin America: Insights on the Current State of Knowledge and Future Perspectives
Authors: Terrazas-López Rafael , Guadarrama-Guzman Pedro , Sujitha Suresh Babu , Arreola-Mendoza Laura , Ponniah Jonathan Muthuswamy
Published: July 2024

Microplastics (MPs) pose a significant and increasing threat globally, with plastics accounting for around 60–80% of marine trash. Plastic particles with a size of 5000 µm or less are referred to as microplastics (MPs). These MPs can enter the marine organisms either through their diet or by trophic transfer. This can potentially expose people to these particles. According to the literature, around 21.9% of fish, 18.4% of seabirds, 11.7% of arthropods, and 7.8% of molluscs in marine systems are at risk from plastic pollution. The LATAM region experiences significant MP contamination that primarily originates from wastewater treatment plants, industrial effluents, maritime sources, and the decomposition of macro–mesoplastics. The majority of research conducted in the LATAM region focuses on MPs in natural habitats, specifically examining the presence of MPs in biota (such as fish, mussels, squids, turtles, and even insects) and sediments. In order to conduct a thorough analysis of the sources and spread of microplastics (MPs) in marine organisms, we conducted a comprehensive assessment of the available literature on microplastic research in Latin American countries. The objective was to evaluate the origin, destinations, and pathways via which MPs are transferred. An assessment of the prevalence of microplastics (MPs) in marine organisms would yield significant insights into the potential health hazards posed by plastic pollution to humans.
Effects of the Amount of Information from Navigation Voice Guidance on Driving Performance
Authors: Yang Liping , Zhao Xiaohua , Bian Yang , Zhang Mengmeng , Guo Yajuan
Published: July 2024

Nowadays, navigation systems are widely used in public travel because they can instantly offer GPS-based route directions. Following the navigation prompt messages while driving is considered a secondary driving task, while vehicle control is regarded as a primary driving task. Navigation prompt messages with more information can deliver more cues to drivers, but they require a higher cognitive demand and vice versa. To systematically explore the effects of the amount of information from navigation voice prompts and further quantify the utility of voice prompts, four types of prompt messages with increasing amounts of information, denoted as a Single Message, Double Message, Triple Message, and Quadruple Message, were designed. A driving simulation experiment was conducted to obtain driving behavior data under different prompt messages. The one-way analysis of variance (ANOVA) and Kruskal–Wallis (KW) test were used to examine the differences in driving performance under the guidance of different prompt messages from multiple perspectives. Then, eight indicators were selected based on the functions of the navigation system and the driver’s response, and the grey near-optimal method was used to determine the utility of the four types of prompt messages. This study found that the four types of navigation prompt messages all began to take effect at about 200 m upstream of the stop bar. The differences between the four types of prompt messages were more significant in the zone from 100 m upstream and ended at 100 m downstream of the stop bar of the intersection. Drivers using Single and Double Messages exhibited more powerful deceleration than those using Triple and Quadruple Messages. The utility values of the four types of prompt messages increased with the increase in the amount of information. This study provides theoretical support for optimizing navigation information and lays a foundation for establishing navigation broadcast guidelines.
Depth and Width of Collaborative Innovation Networks and High-Quality Development
Authors: Dai Hongwei , Liu Yiwei , Li Heyang , Cao Aochen
Published: July 2024

The key driving force for high-quality development is innovation, and collaborative innovation is an important form of organizing and realizing innovation. However, the impact of collaborative innovation networks on high-quality regional development remains unclear. At the city cluster level, this study analyzes more than 300,000 patent data based on the data of prefecture-level cities in China from 2012 to 2020 using the crawler method and social network analysis. The results show that, first, collaborative innovation in China is characterized by growth, network, and structural stability. Second, collaborative innovation can significantly improve the high-quality development of urban economies by reducing human resource mismatch and increasing the “intensive margin” and “expansive margin” of innovation. Third, at the national level, increased urban collaboration in terms of width and depth has contributed to the economy’s high-quality development. However, the two have not yet demonstrated complementarity, although at the level of urban agglomerations, the two are significantly complementary. Fourth, heterogeneity analysis shows that collaborative innovation is more effective in promoting high-quality development for highly matured city clusters and cities with robust innovation capacity. It can considerably overcome geographical constraints. From the regional heterogeneity perspective, the promotion of high-quality development through collaborative innovation is stronger in southern and central China. It is recommended that emerging market countries and city clusters focus on constructing and developing collaborative innovation networks and promoting high-quality economic development through measures such as increasing network density, enhancing the breadth and depth of synergies among cities, and developing differentiated policies.
Indoor Air Quality Evaluation in Rural Houses Using Different Heating Methods in Northern Shanxi, China
Authors: Zhang Mengying , Dong Xujuan , Feng Jing
Published: July 2024

It has been shown that heating methods have a large impact on rural indoor air quality. Previous studies on indoor air quality in rural houses involved a limited number of heating methods and lacked comprehensive comparative research on the three heating methods: coal-fired boiler radiator heating, air-source heat pump radiator heating, and Chinese stove–kang heating. In this paper, subjective surveys and objective tests were conducted on indoor air quality in rural houses using these three heating methods in northern Shanxi, China. The gray relational analysis method and the comprehensive index method were used to evaluate the indoor air pollution levels of the three heating methods. The results were as follows: The subjective evaluations of most rural residents were overly optimistic about the indoor air quality of coal-fired boiler radiator heating and Chinese stove–kang heating. The indoor TVOC concentrations from these two heating methods far exceeded the standard limit of 0.6 mg/m3 at night. The indoor PM2.5 and PM10 concentrations from Chinese stove–kang heating varied greatly over a day and showed intermittent peak fluctuations that far exceeded the standard limits in the initial period of fuel combustion. The pollution levels from coal-fired boiler radiator heating, air-source heat pump radiator heating, and Chinese stove–kang heating were evaluated as light pollution, non-pollution, and medium or heavy pollution, respectively.
How Urban Block Form Affects the Vitality of the Catering Industry: Evidence from Jinan, China
Authors: Hou Yiming , Chen Yanbin , Zhang Xiaoqing
Published: July 2024

Existing research underscores the significance of block form in fostering urban vitality. However, there is a dearth of evidence on its influence on the catering industry’s vitality. Additionally, current studies investigating the correlation between block form and urban vitality have frequently neglected disparities among various types of blocks with dominant functions. We employ a multi-scale geographically weighted regression and a geographic detector to elucidate the effects of block form and the heterogeneity of blocks with dominant functions on the catering industry’s vitality. Our findings suggest that the suitable block form can mitigate the catering industry’s reliance on factors such as the regional population and public transportation infrastructure, to a certain degree. High-rise buildings and irregular block plans positively influence the catering industry’s vitality, while the effects of block area, building density, and functional density display considerable spatial heterogeneity. Commercial blocks are most influenced by block form, whereas public service blocks are least affected. The methodology of this study can be replicated globally to guide urban planners in judiciously allocating commercial facilities, based on the varying spatial form requirements of different blocks, thereby fostering a vibrant city.
The Role of Social Media Marketing in Green Product Repurchase Intention
Authors: Hu Tung-Lai , Chao Chuang-Min , Lin Chia-Hung
Published: July 2024

This study explores the impact of social media marketing activities and ESG green brand involvement on the repurchase intention of green products among members of Taiwan’s green product social media groups. Using the Theory of Reasoned Action, the study employs a quantitative approach, collecting data through an online survey from 438 valid responses. Structural equation modeling (SEM) was applied to analyze the relationships between social media marketing activities (independent variable), green values, environmental concerns, brand image, and brand involvement (mediating variables), and repurchase intention (dependent variable). The findings reveal that social media marketing activities significantly enhance green values, environmental concerns, and brand image, which positively influence brand involvement. Brand involvement significantly mediates the relationship between green values, environmental concerns, brand image, and repurchase intention. This confirms that effective social media marketing can strengthen consumer loyalty and repurchase intentions for green products. The study suggests that companies should integrate green values, environmental concerns, and brand image into their social media marketing strategies to enhance consumer engagement and repurchase intentions. Leveraging social media influencers and interactive content can effectively promote green products and foster a culture of sustainability, creating a win–win situation for companies, consumers, and the environment. This research contributes to the literature by highlighting the mediating roles of green values, environmental concerns, and brand involvement in social media marketing for green products. It provides practical insights for companies aiming to enhance green product repurchase intentions through targeted social media strategies and ESG initiatives, illustrating the strategic use of social media marketing to boost consumer loyalty and sustainable consumption.
Bridging Environmental Sustainability and Organizational Performance: The Role of Green Supply Chain Management in the Manufacturing Industry
Authors: Feng Tao , Qamruzzaman Md , Sharmin Syeda Samira , Karim Salma
Published: July 2024

This study aims to explore the complex connection between green supply chain Management (GSCM) practices, relational efficiency, Job satisfaction, and operational efficiency, as well as the overall organizational performance of manufacturing companies. Utilizing a qualitative model as the basis of our study is essential for navigating this terrain. The present study used carefully designed questionnaires for collecting responses from operational-level managers and applied structural equation modeling (SEM) for inferential analysis, offering a detailed insight into the variables affecting organizational performance in GSCM. This study revealed a significant finding about the role of GSCM practices in connecting business performance and environmental responsibility, highlighting the vital link between sustainable business practices and organizational success. Manufacturing companies should acknowledge and manage the intricate relationship between internal and external aspects of GSCM to achieve smooth operational integration while reducing environmental impact. Our study emphasizes the importance of comprehensively analyzing the connection between GSCM practices and organizational performance. It highlights the need to address challenges to implement sustainable practices. By confronting these challenges directly, organizations can realize the complete capabilities of GSCM and strengthen their dedication to environmental responsibility. The research highlights obstacles and proposes a strategic management approach, providing a roadmap for effectively integrating GSCM into organizational structures. Understanding the relationship between business practices and their environmental impacts is crucial as we address climate change and environmental degradation worldwide. This study illuminates the mediating role of GSCM practices. It emphasizes the importance of manufacturing companies adopting a comprehensive approach to incorporating sustainability into their operational framework and promoting environmental resilience and organizational success.
Olfactory Repellents in Road Ecology: What We Know and What to Focus on in the Future
Authors: Keken Zdeněk , Wimmerová Lenka , Šolcová Olga , Kušta Tomáš , Dvořáková Petra
Published: July 2024

Road transport systems kill millions of animals on every inhabited continent each year, and thousands of human lives are lost. Odour repellents (ORE) are a WVC mitigation measure which have been extensively applied across central Europe to prevent or minimise the number of ungulate–vehicle collisions (UVCs). OREs aim to increase the vigilance of ungulates near roads and therefore change their behaviour in areas where vehicle collisions may occur. Despite many scientific papers on the topic of odour repellent effectiveness, a lack of behavioural studies means there is still little understanding of the mechanism of ORE functionality. OREs are applied as an area repellent, so their effectiveness is influenced by multiple factors, and constantly discussed by both academics and the lay public. This paper summarises the state of knowledge about application and effectiveness of odour repellents in road ecology, and suggests research questions to fill information gaps.
Spatial and Temporal Characteristics of Carbon Emissions from Construction Industry in China from 2010 to 2019
Authors: Song Mengru , Wang Yanjun , Wang Cheng , Musakwa Walter , Ji Yiye
Published: July 2024

The construction industry has become one of the industries that accounts for a relatively large share of China’s total carbon emissions. Aiming at the problems of monitoring difficulties, diversity of segmentation types, and uncertainty of carbon emission factors, this study calculates the carbon emissions and intensity of the construction industry in each province of China from 2010 to 2019, analyzes its spatial and temporal variability using the Moran index and the slope index, analyzes the driving factors by combining the Kaya equation and the LMDI method, and verifies the zero-error characteristics by using the IPAT model. The results show that from 2010 to 2019, carbon emissions from the construction industry in China’s provincial areas increased in general, with a distribution of “high in the east and low in the west”, and the carbon emission intensity declined in general, but some provinces in the north and the center are still higher. Economic development and the increase in housing construction area are the main reasons for the growth of carbon emissions, while the optimization of energy structure and the adjustment of population density reduce carbon emissions. Moreover, the IPAT model verifies the credibility of the results of the LMDI model. This study provides a reference for monitoring and assessing carbon emissions in China’s construction industry from the perspective of spatio-temporal characterization, helps regional energy conservation and emission reduction and dual-carbon strategy, and it analyzes the provincial carbon emission intensity to reveal the low-carbon development issues.
Resilience Approach for Assessing Fish Recovery after Compound Climate Change Effects on Algal Blooms
Authors: Starck Sascha , Wolter Christian
Published: July 2024

In Europe, climate change will increase hydrologic extremes, resulting in shorter flood peaks and longer droughts. Extended low flows will significantly alter physico-chemical water quality, paving the way for compound, novel impacts. We analyze the Oder River catastrophe of August 2022, where the complex interplay of increased salinity, temperature, low flows, reduced water volumes and sunlight enabled Prymnesium parvum blooming. This brackish water alga grew to 100 million cells per liter and killed about 1000 tons of fish. We assess the impact on and the recovery potential of the fish population to guide both preventing future catastrophes and enhancing river resilience. Stock decline rates were assessed while accounting for natural population fluctuations. Significant relative declines in both fish and biomass density reached up to 76% and 62%, respectively. The mid-channel was more severely affected than littoral areas. Littoral shelter, depth variability, and especially lateral and longitudinal connectivity appeared essential for fish survival and recovery. The compound nature of this catastrophic event highlights the urgent need to rethink the present mismanagement of rivers. Resilient rivers are the backbone of climate change-resilient landscapes. Therefore, we argue for holistic approaches to water resource management, aiming to increase the resilience of aquatic ecosystems.
Research on Privacy-by-Design Behavioural Decision-Making of Information Engineers Considering Perceived Work Risk
Authors: Bu Fei , Wang Nengmin , Jiang Qi , Tian Xiang
Published: July 2024

Privacy by design (PbD) has attracted considerable attention from researchers and information security experts due to its enormous potential for protecting private information and improving the privacy and security quality of information technology products. The adoption of PbD among information engineers is currently limited owing to its innovativeness and the distinctive traits of the information technology industry. Utilising the Technology Acceptance Model as a framework, this study innovatively explores the pivotal factors and mechanisms that influence information engineers’ decision-making in the adoption of PbD from the viewpoint of the perceived work risk. In this empirical research, professional information engineers were invited to complete a questionnaire survey. After analysing the data using partial least squares structural equation modelling, the results reveal that information engineers’ perceived work risk in PbD (PWRP) negatively affects their perceptions of the usefulness and ease of use of PbD. This negative perception subsequently reduces their intention to implement PbD (INTP) and adversely impacts their attitudes towards implementing PbD (ATTP). Furthermore, the study findings reveal that a positive ATTP among engineers boosts their INTP and positively influences their behaviours regarding information security. This study provides an in-depth examination of these findings and lays a solid theoretical groundwork for the further promotion and implementation of PbD in information technology enterprises. Moreover, the findings offer invaluable support for management decisions in both information technology companies and information security regulatory authorities, significantly contributing to the expansion and deepening of research in the field of PbD.