bluuebunny/crossref_metadata_2025 huggingface dataset:
A Lightweight Vehicle Detection Method Fusing GSConv and Coordinate Attention Mechanism
Authors: Huang Deqi , Tu Yating , Zhang Zhenhua , Ye Zikuang
Published: April 2024

Aiming at the problems of target detection models in traffic scenarios including a large number of parameters, heavy computational burden, and high application cost, this paper introduces an enhanced lightweight real-time detection algorithm, which exhibits higher detection speed and accuracy for vehicle detection. This paper considers the YOLOv7 algorithm as the benchmark model, designs a lightweight backbone network, and uses the MobileNetV3 lightweight network to extract target features. Inspired by the structure of SPPF, the spatial pyramid pooling module is reconfigured by incorporating GSConv, and a lightweight SPPFCSPC-GS module is designed, aiming to minimize the quantity of model parameters and enhance the training speed even further. Furthermore, the CA mechanism is integrated to enhance the feature extraction capability of the model. Finally, the MPDIoU loss function is utilized to optimize the model’s training process. Experiments showcase that the refined YOLOv7 algorithm can achieve 98.2% mAP on the BIT-Vehicle dataset with 52.8% fewer model parameters than the original model and a 35.2% improvement in FPS. The enhanced model adeptly strikes a finer equilibrium between velocity and precision, providing favorable conditions for embedding the model into mobile devices.
Robust Long-Term Vehicle Trajectory Prediction Using Link Projection and a Situation-Aware Transformer
Authors: Kim Minsung , Kwak Byung Il , Hou Jong-Uk , Kim Taewoon
Published: April 2024

The trajectory prediction of a vehicle emerges as a pivotal component in Intelligent Transportation Systems. On urban roads where external factors such as intersections and traffic control devices significantly affect driving patterns along with the driver’s intrinsic habits, the prediction task becomes much more challenging. Furthermore, long-term forecasting of trajectories accumulates prediction errors, leading to substantially inaccurate predictions that may deviate from the actual road. As a solution to these challenges, we propose a long-term vehicle trajectory prediction method that is robust to error accumulation and prevents off-road predictions. In this study, the Transformer model is utilized to analyze and forecast vehicle trajectories. In addition, we propose an extra encoding network to precisely capture the effect of the external factors on the driving pattern by producing an abstract representation of the situation nearby the driver. To avoid off-road predictions, we propose a post-processing method, called link projection, which projects predictions onto the road geometry. Moreover, to overcome the limitations of Euclidean distance-based evaluation metrics in evaluating the accuracy of the entire trajectory, we propose a new metric called area-between-curves (ABC). It measures the similarity between two trajectories, and thus the accordance between the two can be effectively evaluated. Extensive evaluations are conducted using real-world datasets against widely-used methods to demonstrate the effectiveness of the proposed approach. The results show that the proposed approach outperforms the conventional deep learning models by up to 65.74% (RMSE), 60.13% (MAE) and 91.45% (ABC).
From Scientific Journals to Newspapers in Spain: Interest in Disinformation (2000–2023)
Authors: Catalina García Beatriz , García Galera María , Del Hoyo Hurtado Mercedes
Published: April 2024

As disinformation has become a topic of conversation in the media in recent years, the theory of agenda setting is once again making its presence known. The aim of this research is to verify the degree of interest in disinformation by the media (mainstream press) and in academic writing (scientific communication journals) according to frequency and whether or not such disinformation can be observed in the field of science. The primary research has been carried out through quantitative content analysis of three Spanish newspapers (El País, Abc, El Mundo) and 32 Spanish scientific communication journals included in the SJR-SCImago Journal Rank database from the year 2000 to 2023. The results were 732 units of analysis. From those, it can be concluded that once again, the pandemic represents a before and after. Firstly, a general increase in disinformation has been observed, as well as a corresponding rise in false information in certain fields of science, especially that of health. Secondly, a gradual increase in public interest in disinformation has also been detected, which indicates that the issue is on the agenda of both the media and citizens.
Role of microRNA in Oxidative Stress
Authors: Saha Sarmistha
Published: April 2024

An imbalance between the formation of reactive oxygen species (ROS) and the reaction of antioxidant proteins is referred to as oxidative stress. NFE2L2/Nrf2, also known as nuclear factor erythroid-derived 2-related factor 2, is a critical enabler of cytoprotective responses to oxidative and electrophilic insults. When Nrf2 is activated, it triggers the transcription of numerous cytoprotective genes, whose promoter regions contain antioxidant response elements (AREs). In recent times, the regulation of Nrf2 by miRNAs has garnered significant attention, among the various mechanisms that govern Nrf2 signaling. It has been reported that a number of miRNAs directly suppress the expression of Nrf2s, which in turn negatively regulates the Nrf2-dependent cellular cytoprotective response. Furthermore, it has been shown that Nrf2 itself regulates miRs, which carry out some of Nrf2’s unique metabolic regulation functions. Here, we provide an overview of the functions and mechanisms of action of miRs as downstream effectors of Nrf2, as well as in their regulation of its activity.
RETRACTED: Musharavati, F. A Study on Life Cycle Impact Assessment of Seawater Desalination Systems: Seawater Reverse Osmosis Integrated with Bipolar-Membrane-Enhanced Electro-Dialysis Process. Sustainability 2023, 15, 16673
Authors: Musharavati Farayi
Published: April 2024

The Sustainability Editorial Office retracts the article, “A Study on Life Cycle Impact Assessment of Seawater Desalination Systems: Seawater Reverse Osmosis Integrated with Bipolar-Membrane-Enhanced Electro-Dialysis Process” [...]
Identification of Aggregates Quarries via Computer Vision Analysis as a Tool for Sustainable Aggregates Management and Land Planning
Authors: López-Acevedo Francisco J. , Herrero María J. , Escavy José I. , Peláez Fernández Miguel A.
Published: April 2024

The mineral raw materials industry is crucial for European industry, with the European Economic and Social Committee estimating that 70% of the industry relies directly or indirectly on its supply. In the context of a decarbonized and digitalized economy, the new European industrial model requires carbon-neutral raw materials and production processes. The crucial role of aggregates mining, as the primary construction material, emerges as a key supplier in this paradigm. Aggregates are the main component of the built environment and are a social and economic engine in most countries. Quarries of this type include a wide range of sizes and exploitation methods and use characteristic mining and processing equipment. Quarries are commonly close to their processing plants, which transform natural rock into crushed and ground materials with different grain sizes depending on the future uses. The quarry itself and the presence of certain equipment and facilities help distinguish it from mining sites that exploit other materials. Effective management of aggregates quarries is important in promoting circular economy practices, ensuring efficient management, reuse, and recycling of diverse wastes, including the recovery of high-value components and the production of recycled aggregates, and addressing construction and demolition waste (DCW) management. As aggregates become a progressively scarcer resource due to the increasing demand from developing countries, it is essential to provide reliable and comprehensive information on their potential to the public, policymakers, and other stakeholders to promote their use. This study focuses on employing artificial intelligence and computer vision analysis to automatically identify aggregates quarries from satellite images within continental Spain. A model has been trained to detect aggregates quarries from satellite images by computer vision. The model permits the detection of mining exploitation and the objects located at the interior, which permits determination of the type of mine and the activity status of it. The findings highlight the ability of artificial vision to discern quarries and distinguish whether the observed feature is an aggregates quarry. Additionally, the technology allows for the determination of the quarry’s operational status, distinguishing between active and abandoned quarries. The ability to detect the locations of quarries and assess their activity statuses is of significant value for resource exploration initiatives and location-allocation assessments. It can be a valuable tool for authorities involved in land planning, activities monitoring, and early detection of potential illegal mining activities. This analytical approach demonstrates substantial potential for various stakeholders, including mining companies, mining authorities, policymakers, and land use planners in both the private and public sectors.
A Sustainable W-RLG Model for Attack Detection in Healthcare IoT Systems
Authors: Gupta Brij B. , Gaurav Akshat , Attar Razaz Waheeb , Arya Varsha , Alhomoud Ahmed , Chui Kwok Tai
Published: April 2024

The increasingly widespread use of IoT devices in healthcare systems has heightened the need for sustainable and efficient cybersecurity measures. In this paper, we introduce the W-RLG Model, a novel deep learning approach that combines Whale Optimization with Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU) for attack detection in healthcare IoT systems. Leveraging the strengths of these algorithms, the W-RLG Model identifies potential cyber threats with remarkable accuracy, protecting the integrity and privacy of sensitive health data. This model’s precision, recall, and F1-score are unparalleled, being significantly better than those achieved using traditional machine learning methods, and its sustainable design addresses the growing concerns regarding computational resource efficiency, making it a pioneering solution for shielding digital health ecosystems from evolving cyber threats.
Simulation Study on Performance of Solar-Powered Desiccant Wheel and Ground Source Heat Pump Air Conditioning in Qingdao
Authors: Wu Yicheng , Hou Litong , Su Tianxi , Ma Yongzhi
Published: April 2024

In China, a large amount of the total energy consumption is made up of building energy, particularly in humid regions. The conventional vapor compression refrigeration systems cannot effectively control the indoor humid and thermal environment. Therefore, this article proposes a solar-powered desiccant wheel and ground-source heat pump (SDW-GSHP) air conditioning system. The energy consumption of the system is mainly from sustainable sources of solar and geothermal energy, showcasing excellent energy efficiency and environmental friendliness. The desiccant wheel (DW) processes latent heat loads, and the GSHP processes the sensible heat load. The regeneration air of the DW is heated by a solar collector. The operational performance of the system was simulated by using TRNSYS during the typical summer week (15 July to 22 July) in Qingdao. The simulation results indicated that indoor temperature was maintained within 25.8–26.2 °C and the relative humidity was maintained in the range of 57–61%. The COP of the SDW-GSHP air conditioning system was 42.1% higher than that of the DW air conditioning system with electric heating regeneration, and electricity saved 43.7%.
Sustainable Financing for Transport Infrastructure: An Integral Approach for the Russian Federation
Authors: Chupin Alexander , Sorokin Alexey , Veselko Alena , Morkovkin Dmitry , Pishchik Victor Ya. , Alekseev Petr V.
Published: April 2024

The development of global transport infrastructure is a crucial aspect of economic growth and prosperity. In this study, the main trends in the development of global transport infrastructure are analyzed, with a focus on the state and trends in the functioning of the national transport infrastructure of the Russian Federation. By identifying key problems and determinants of financial growth, a preliminary decomposition is made to guide future development. Proceeding from the fact that the innovative development of Russia’s transport infrastructure should occur through state stimulation of the development of intellectual and partnership relationships and the formation of a digital environment for managing projects for its innovative transformation at the state level, this study identifies the goals, methods, and levels of ensuring the implementation of innovative transformations in transport infrastructure. Consideration of the historical aspects of the formation of the modern economy and comprehension of the mechanisms of state management and tools to ensure innovative transformations in the sphere of transport allowed us to identify three stages (dogmatic, strategic regulation, and innovative integration) of transformation regarding the theory of the state management for the innovative development of transport infrastructure in Russia. Taking into account the content of these periods of transformation allowed us to detail the specifics of the modern stage; highlight the shortcomings; and propose theoretical and methodological foundations for revising the provisions of the state regulation of innovative development in transport infrastructure. To determine the effectiveness of the processes of the state regulation of innovation activity in the transport industry, we propose a model for assessing the effectiveness of innovation activity in the transport complex, which is presented in the form of a three-level parametric system, where the first group of indicators allows us to assess the innovation activity of economic entities in the transport industry; the second allows us to assess innovation potential; and the third allows us to assess the effectiveness of innovation. The novelty of the proposed model is the consideration of the principles of dynamism, perspective, and expediency, and its application allows us to establish the level of innovative development in transport infrastructure. An important factor in ensuring the sustainable development of a country’s economy and forming its positive image in the world is its financial attractiveness. Therefore, the assessment of financial attractiveness is a priority task for the development of modern sustainable transport infrastructure in Russia.
A Transformer Heavy Overload Spatiotemporal Distribution Prediction Ensemble under Imbalanced and Nonlinear Data Scenarios
Authors: Liu Yanzheng , Sun Chenhao , Yang Xin , Jia Zhiwei , Su Jianhong , Guo Zhijie
Published: April 2024

As a crucial component of power systems, distribution transformers are indispensable to ensure the sustainability of power supply. In addition, unhealthy transformers can lead to wasted energy and environmental pollution. Thus, accurate assessments and predictions of their health statuses have become a top priority. Unlike assumed ideal environments, however, some complex data distributions in practical scenarios lead to more difficulties in diagnosis. One challenge here is the potential imbalanced distribution of data factors since sparsely occurring factors along with some Unusual High-Risk (UHR) components, whose appearance may also damage transformer operations, can easily be neglected. Another is that the importance weight of data components is simply calculated according to their frequency or proportion, which may not always be reasonable in real nonlinear data scenes. With such motivations, this paper proposes a novel integrated method combining the Two-fold Conditional Connection Pattern Recognition (TCCPR) and Component Significance Diagnostic (CSD) models. Initially, the likely environmental factors that could result in distribution transformer heavy overloads were incorporated into an established comprehensive evaluation database. The TCCPR model included the UHR time series and factors that are associated with heavy overload in both spatial and temporal dimensions. The CSD model was constructed to calculate the risk impact weights of each risky component straightforwardly, in line with the total risk variation levels of the whole system caused by them. Finally, the results of one empirical case study demonstrated their adaptation capability and enhanced performance when applied in complex and imbalanced multi-source data scenes.
Community Battery for Collective Self-Consumption and Energy Arbitrage: Independence Growth vs. Investment Cost-Effectiveness
Authors: Pasqui Mattia , Becchi Lorenzo , Bindi Marco , Intravaia Matteo , Grasso Francesco , Fioriti Gianluigi , Carcasci Carlo
Published: April 2024

Integrating a grid-connected battery into a renewable energy community amplifies the collective self-consumption of photovoltaic energy and facilitates energy arbitrage in the electricity markets. However, how much can energy independence really increase? Is it a cost-effective investment? The answer to these questions represents a novelty in the literature due to the innovative nature of the asset under consideration and the market and regulatory framework in which it is evaluated. Employing a net present value assessment, our analysis incorporated aging effects and conducts sensitivity analyses across various parameters: the number of community customers, electricity market prices, battery cost and size, and the decision to engage in energy arbitrage. Each scenario underwent a 20-year hourly simulation using an aging-aware rolling-horizon 24 h-looking-ahead scheduling, optimized with mixed-integer linear programming. Simulations conducted on the Italian market indicate that dedicating a battery solely to collective self-consumption is the most efficient solution for promoting a community’s energy independence, but it lacks economic appeal. However, integrating energy arbitrage, despite slight compromises in self-sufficiency and battery longevity, halves the payback period and enhances the attractiveness of larger battery investments. The net present value is contingent upon the battery size, customer number, and market prices. Nevertheless, if the battery cost does not exceed 200 EUR/kWh, the investment becomes cost-effective across all scenarios.
Unveiling the Patterns and Drivers of Ecological Efficiency in Chinese Cities: A Comprehensive Study Using Super-Efficiency Slacks-Based Measure and Geographically Weighted Regression Approaches
Authors: Peng Jiantao , Liu Yihua , Xu Chong , Chen Debao
Published: April 2024

Urban ecological efficiency stands as a pivotal indicator that mirrors the level of sustainable development within cities. To unravel the sustainable development status of Chinese cities and illuminate the factors impacting the diverse developments among them, this study leveraged the super-efficiency SBM (slacks-based measure) model to assess the ecological efficiency of 284 prefectural-level and above cities across China in 2019, divulging their spatial distribution. Furthermore, a GWR (geographically weighted regression) model was also employed to scrutinize the factors influencing the ecological efficiency of these cities. Key findings include: (1) The mean ecological efficiency of Chinese cities in 2019 stood at 0.555, signaling moderate urban sustainability, with southern cities outperforming their northern counterparts. (2) A pronounced spatial clustering of ecological efficiency was evident, featuring positive spillover effects around high-efficiency cities and conversely, negative spillover effects around low-efficiency cities. (3) Economic development and population density positively influenced urban ecological efficiency, while urbanization levels exhibited a negative impact. The influences of industrial structure, technological level, and opening-up level varied, showcasing both positive and negative impacts contingent upon the spatial disposition of the cities. Hence, policymakers are advised to recognize the spatial nuances in the impacts of distinct factors on urban ecological efficiency and tailor measures accordingly to fortify urban sustainability.
Potential Bioactivities of Tamarind Seed Jellose at the Cellular Level for Cosmetic Product Development
Authors: Khongkow Pasarat , Khakhong Suphatsa , Thammarat Chayanee , Amnuaikit Thanaporn
Published: April 2024

In recent years, the utilization of tamarind seeds as a potential and sustainable ingredient in green cosmetics has gained significant interest. These seeds, previously considered by-products in various food industries, are now being recognized for their interesting value and wide range of bioactive compounds. This study aimed to deeply examine the potential biological activities and underlying molecular mechanisms of tamarind seed jellose (TJ), a natural polysaccharide derived from Tamarindus indica seeds, for various cosmetic applications. Tyrosinase, a key regulator of melanin synthesis and skin color, was the main focus of this study. Through a series of in vitro experiments on skin fibroblasts and B16 melanoma cells, the cytotoxicity, antioxidant activity, and melanogenesis inhibitory potential of tamarind seed jellose were evaluated. Notably, the results revealed that TJ had no obvious cytotoxic effects on skin fibroblast cells at any tested concentrations, ranging from 0 to 10 mg/mL. Interestingly, tamarind seed jellose effectively reduced melanin synthesis by inhibiting tyrosinase expression in a dose-dependent manner. In addition, TJ exhibited a promising antioxidant activity. Collectively, these findings highlight that TJ has the potential to serve as a safe and multi-functional ingredient for green cosmetic applications, offering the potential opportunity to repurpose waste for the beauty industry.
Numerical Analysis of Air Supply Alternatives for Forced-Air Precooling of Agricultural Produce
Authors: Chen Long , Wang Wenzhi , Li Jiazheng , Zhang Zhijun
Published: April 2024

Precooling agricultural produce is an intensive, energy-consuming process. To improve the efficiency of forced-air precooling and ultimately contribute to energy sustainability for postharvest storage of fresh produce, we designed three alternative air supply systems, simulated their cooling performances over a 96 h precooling process in a cold storage facility storing Chinese cabbages, and then compared their performances with a conventional design. All models were developed on a large scale on the basis of validated computational fluid dynamics models. The horizontal air supply scheme shortened the seven-eighths cooling time by 18.8%, and its maximum cooling rate increased by 19.7% compared to the conventional air supply scheme. The seven-eighths cooling time under another alternative design, the vertical air supply scheme, was 9.4% lower than the conventional, with the maximum cooling rate increasing by 10.5%. However, the maximum cooling rate of the last alternative design, the perforated ceiling air supply system, was 6.6% less than the conventional scheme, resulting in a 6.3% longer seven-eighths cooling time. The heterogeneity index of temperature implied that the horizontal air supply offered better overall cooling uniformity than the other designs, which can be attributed to its evenly distributed airflows and well-organized air movement paths, based on the combined analysis of temperature contours and air velocity contours at selected planes. Our findings are expected to provide practical guidelines for the refinement of the air supply system to improve its energy sustainability in forced-air precooling.
Addressing Epistemic Injustice: Engaging Children as Environmental Communicators to Support the Long-Term Sustainability of Forest Ecosystems
Authors: McEntee Marie , Thomas Kat , Mullen Molly , Houghton Christina , Harvey Mark , Craig-Smith Ariane
Published: April 2024

Closure of a forest for biosecurity purposes led to the marginalisation and disconnection of Year 6 children from a local forest of significance to them in Aotearoa, New Zealand. The marginalisation of children’s voices and concomitantly of their knowledge, ideas, and values from environmental issues can be viewed as an example of epistemic injustice, which manifests widely in the environmental area, particularly in relation to marginalised groups. To counter this marginalisation and promote epistemic justice, we explored how the creative arts involving a child-driven environmental communication project could foster children’s sense of agency by supporting the protection of a local forest affected by a tree disease. We show that the creative arts could facilitate the children’s meaningful engagement in environmental issues in a learning environment that fostered child-centric approaches that enabled children to express their visions for sustainable futures in distinctly unique ways that were relevant to them. Furthermore, enabling the children to participate as environmental communicators re-established their relationship with their local forest and re-balanced the power structures that had led to the children’s sense of marginalisation. The insights on how this child-centred relational approach can promote epistemic justice and provide a meaningful contribution to the long-term sustainable management of forest ecosystems has implications for other marginalised groups.
Waste-Based Vertical Planting System Proposal to Increase Productivity in Sustainable Horticulture; “PETREE”
Authors: Gürsu Hakan
Published: April 2024

The problems experienced with the decrease in agricultural areas per capita against the uncontrolled population growth in the World and in Turkey are becoming increasingly evident. Especially the manpower engaged in horticulture is increasingly experiencing the problems of migration, economic reasons, and inefficient production methods. For healthy and efficient production, agricultural lands need a sequential cycle that includes cultivation and fallow periods. Agricultural lands, the salt they contain, etc. When left fallow, the soil area needs to rest to re-establish the mineral balance. It is now vital for small producers, whose production areas are gradually shrinking due to global conditions, to continue production while their lands are resting to produce more continuously and efficiently. In the face of increasing demands, decreasing production amounts and areas, the constantly increasing prices of economically simple agricultural products “fresh vegetables” and affecting the easy accessibility of local products, it has become inevitable to seek new and alternative solutions. This study includes an innovative solution proposal to increase the production efficiency of low-scale producers and individual gardeners, especially those producing in small agricultural areas. Critical problems of large-scale greenhouse systems, interactions of agricultural practices within the framework of urban life, water and energy efficiency in agriculture, and sustainability and waste management of the proposed system are examined. To meet changing conditions and maintain productivity in small areas, it is envisaged that mobile and vertical production stations, which can produce by increasing productivity even in fallow areas while the soil is resting, can be an alternative solution to the problems of small producers. The vertical planting system “PETREE” develops mobile units for sustainable agriculture by collecting 5th LT-PET packages, which have a natural lifespan of about 90 years, and reusing them as plant pots and some recycled plastic pieces as structures. With efficient and environmentally friendly design suggestions, the system also examined the possibilities of more efficient gardening with mobile production stations in small agricultural areas, and efficient and enjoyable gardening that suits the needs of urban consumers “production with local seeds and seedlings” with the increase in environmental awareness and food safety concerns.
The Impact of Eco-Friendly Practices on Generation Z’s Green Image, Brand Attachment, Brand Advocacy, and Brand Loyalty in Coffee Shop
Authors: Ko Ju-Hee , Jeon Hyeon-Mo
Published: April 2024

This study examined eco-friendly practices (EFPs), green image, and brand attachment to identify antecedents that affect coffee shop consumers’ brand advocacy and brand loyalty, targeting Generation Z, who are emerging as the primary agents of eco-friendly consumption. In particular, we applied only the tangible EFPs that consumers can observe to identify a clear relationship between perceptions of EFPs and consumer behavior. This is the most significant difference from previous studies. In this study, 287 people who responded that they had visited Starbucks, which was selected as the coffee shop brand to be investigated through a pilot test, were used as a sample. As a result of the verification, EFPs demonstrated a positive influence on green image and brand attachment, and green image appeared to have a positive effect on brand attachment. Brand attachment was confirmed to be an antecedent that strengthens brand advocacy and brand loyalty. This study contributes to the literature on environmental friendliness in the hospitality industry and can be used to establish sustainable, eco-friendly marketing strategies in the food service business.
Bridging the Gap: Determinants of Consumers’ Willingness to Pay for Environmentally Friendly Packages of Leafy Greens
Authors: Dieli Carissa , Priyadarshini Anushree , Ludgate Robert , Foley Lorraine
Published: April 2024

Government and corporate policies have mandated a reduction in plastic packaging to combat issues of waste and climate change. This move towards sustainable packaging alternatives in the fresh food sector will increase costs for consumers. Much of the present research finds consumers are willing to pay more for sustainability, but their willingness to pay (WTP) does not align with real-world purchases, representing an attitude–behaviour gap. To combat this gap, it is posited that consumers’ current purchasing- and sustainability-related behaviours will meaningfully correlate with their WTP and bridge the attitude–behaviour gap. This research used an online survey (n = 476) to gauge consumers’ attitudes and behaviours regarding sustainability as it relates to packaging, biofortification, and WTP in the fresh leafy greens sector. Using binary logistic regression, this research finds that price- and sustainability-related purchasing habits and attitudes towards sustainable packaging meaningfully narrow the attitude–behaviour gap, but organic purchasing habits, waste segregation habits, and sustainability literacy do not. This research contributes the knowledge that, for environmentally friendly leafy greens, past price- and sustainability-related purchasing behaviour should be used instead of merely attitudes as an indication of WTP.
Construction of Product Appearance Kansei Evaluation Model Based on Online Reviews and FAHP: A Case Study of Household Portable Air Conditioners
Authors: Du Yuanjian , Zhang Meng , Cai Mobing , Park Kyungjin
Published: April 2024

Meeting the personalized needs of users is the key to achieving the sustainable success of a product. It depends not only on the product’s functionality but also on satisfying users’ emotional needs for the product’s appearance. Therefore, researchers have been conducting research focusing on Kansei engineering theory to determine users’ emotional needs effectively. The initial process involves accurately extracting and filtering emotional data and Kansei words from consumers. Thus, we propose an evaluation model to efficiently obtain, screen, and sort these Kansei words based on Kansei engineering, using household portable air conditioners as research subjects. By integrating techniques for online user comment mining methods, users’ Kansei terms related to the product’s appearance can be gathered efficiently. These terms are then combined with image samples and filtered to determine a final set of 16 Kansei word pairs. Subsequently, the fuzzy analytic hierarchy process (FAHP) is utilized to prioritize these terms, and the fuzzy comprehensive evaluation (FCE) method is used to validate the results and determine the applicability of the evaluation model. The results showed that Kansei words could be quickly and objectively acquired using existing text mining techniques on online reviews. Moreover, the weights of different Kansei terms of the product’s appearance in the consumer’s perception are accurately produced through the FAHP. This evaluation model marks a significant advancement in accurately obtaining users’ emotional data in Kansei engineering. It offers valuable guidance for designing products that meet users’ personalized needs, enhancing design efficiency and reducing resource wastage at the early stages of designing, and improving the sustainability development of Kansei engineering.
Crafting Genetic Diversity: Unlocking the Potential of Protein Evolution
Authors: Gali Vamsi Krishna , Tee Kang Lan , Wong Tuck Seng
Published: April 2024

Genetic diversity is the foundation of evolutionary resilience, adaptive potential, and the flourishing vitality of living organisms, serving as the cornerstone for robust ecosystems and the continuous evolution of life on Earth. The landscape of directed evolution, a powerful biotechnological tool inspired by natural evolutionary processes, has undergone a transformative shift propelled by innovative strategies for generating genetic diversity. This shift is fuelled by several factors, encompassing the utilization of advanced toolkits like CRISPR-Cas and base editors, the enhanced comprehension of biological mechanisms, cost-effective custom oligo pool synthesis, and the seamless integration of artificial intelligence and automation. This comprehensive review looks into the myriad of methodologies employed for constructing gene libraries, both in vitro and in vivo, categorized into three major classes: random mutagenesis, focused mutagenesis, and DNA recombination. The objectives of this review are threefold: firstly, to present a panoramic overview of recent advances in genetic diversity creation; secondly, to inspire novel ideas for further innovation in genetic diversity generation; and thirdly, to provide a valuable resource for individuals entering the field of directed evolution.
A New Diving Pliocene Ardenna Shearwater (Aves: Procellariidae) from New Zealand
Authors: Tennyson Alan J. D. , Salvador Rodrigo B. , Tomotani Barbara M. , Marx Felix G.
Published: April 2024

We report a new species of shearwater, Ardenna buchananbrowni sp. nov., from the Pliocene of New Zealand. It is both the smallest and oldest known diving member of the genus, demonstrating that this now abundant form of shearwater has had a long presence in southern oceans. Ardenna buchananbrowni sp. nov. is among the few extinct shearwaters described from the Southern Hemisphere and adds to an increasingly diverse seabird assemblage in the Pliocene of the region.
The Role of Botulinum Toxin Type-A in Spasticity: Research Trends from a Bibliometric Analysis
Authors: Facciorusso Salvatore , Spina Stefania , Picelli Alessandro , Baricich Alessio , Francisco Gerard E. , Molteni Franco , Wissel Jörg , Santamato Andrea
Published: April 2024

Botulinum toxin type-A (BoNT-A) has emerged as a key therapeutic agent for the management of spasticity. This paper presents a comprehensive bibliometric and visual analysis of research concerning BoNT-A treatment of spasticity to elucidate current trends and future directions in this research area. A search was conducted in the Web of Science database for articles focused on the use of BoNT-A in spasticity published between 2000 and 2022. We extracted various metrics, including counts of publications and contributions from different countries, institutions, authors, and journals. Analytical methods in CiteSpace were employed for the examination of co-citations, collaborations, and the co-occurrence of keywords. Our search yielded 1489 publications. Analysis revealed a consistent annual increase in research output. The United States, United Kingdom, and Italy were the leading contributors. The top institution in this research was Assistance Publique Hopitaux, Paris. The journal containing the highest number of relevant publications was Toxins. Key frequently occurring keywords were ‘stroke’, ‘cerebral palsy’, ‘adult spasticity’, and ‘upper extremity’. This study identified 12 clusters of keywords and 15 clusters of co-cited references, indicating the main focus areas and emerging themes in this field. This study comprehensively analyzed and summarized trends in BoNT-A research in the field of spasticity over the past 22 years.
STINGing Defenses: Unmasking the Mechanisms of DNA Oncovirus-Mediated Immune Escape
Authors: Martínez-López Mayra , Muslin Claire , Kyriakidis Nikolaos
Published: April 2024

DNA oncoviruses represent an intriguing subject due to their involvement in oncogenesis. These viruses have evolved mechanisms to manipulate the host immune response, facilitating their persistence and actively contributing to carcinogenic processes. This paper describes the complex interactions between DNA oncoviruses and the innate immune system, with a particular emphasis on the cGAS-STING pathway. Exploring these interactions highlights that DNA oncoviruses strategically target and subvert this pathway, exploiting its vulnerabilities for their own survival and proliferation within the host. Understanding these interactions lays the foundation for identifying potential therapeutic interventions. Herein, we sought to contribute to the ongoing efforts in advancing our understanding of the innate immune system in oncoviral pathogenesis.
The High Capacity of Brazilian Aedes aegypti Populations to Transmit a Locally Circulating Lineage of Chikungunya Virus
Authors: de Freitas Amanda , Rezende Fernanda , de Mendonça Silvana , Baldon Lívia , Silva Emanuel , Ferreira Flávia , Almeida João , Amadou Siad , Marçal Bruno , Comini Sara , Rocha Marcele , Fritsch Hegger , Santos Ellen , Leite Thiago , Giovanetti Marta , Alcantara Luiz Carlos Junior , Moreira Luciano , Ferreira Alvaro
Published: April 2024

The incidence of chikungunya has dramatically surged worldwide in recent decades, imposing an expanding burden on public health. In recent years, South America, particularly Brazil, has experienced outbreaks that have ravaged populations following the rapid dissemination of the chikungunya virus (CHIKV), which was first detected in 2014. The primary vector for CHIKV transmission is the urban mosquito species Aedes aegypti, which is highly prevalent throughout Brazil. However, the impact of the locally circulating CHIKV genotypes and specific combinations of local mosquito populations on vector competence remains unexplored. Here, we experimentally analyzed and compared the infectivity and transmissibility of the CHIKV-ECSA lineage recently isolated in Brazil among four Ae. aegypti populations collected from different regions of the country. When exposed to CHIKV-infected AG129 mice for blood feeding, all the mosquito populations displayed high infection rates and dissemination efficiency. Furthermore, we observed that all the populations were highly efficient in transmitting CHIKV to a vertebrate host (naïve AG129 mice) as early as eight days post-infection. These results demonstrate the high capacity of Brazilian Ae. aegypti populations to transmit the locally circulating CHIKV-ECSA lineage. This observation could help to explain the high prevalence of the CHIKV-ECSA lineage over the Asian lineage, which was also detected in Brazil in 2014. However, further studies comparing both lineages are necessary to gain a better understanding of the vector’s importance in the epidemiology of CHIKV in the Americas.
Story Starter: A Tool for Controlling Multiple Virtual Reality Headsets with No Active Internet Connection
Authors: Woods Andy T. , Whittaker Laryssa , Smith Neil , Ispas Robert , Moore Jackson , Morgan Roderick D. , Bennett James
Published: April 2024

Immersive events are becoming increasingly popular, allowing multiple people to experience a range of VR content simultaneously. Onboarders help people do VR experiences in these situations. Controlling VR headsets for others without physically having to put them on first is an important requirement here, as it streamlines the onboarding process and maximizes the number of viewers. Current off-the-shelf solutions require headsets to be connected to a cloud-based app via an active internet connection, which can be problematic in some locations. To address this challenge, we present Story Starter, a solution that enables the control of VR headsets without an active internet connection. Story Starter can start, stop, and install VR experiences, adjust device volume, and display information such as remaining battery life. We developed Story Starter in response to the UK-wide StoryTrails tour in the summer of 2022, which was held across 15 locations and attracted thousands of attendees who experienced a range of immersive content, including six VR experiences. Story Starter helped streamline the onboarding process by allowing onboarders to avoid putting the headset on themselves to complete routine tasks such as selecting and starting experiences, thereby minimizing COVID risks. Another benefit of not needing an active internet connection was that our headsets did not automatically update at inconvenient times, which we have found sometimes to break experiences. Converging evidence suggests that Story Starter was well-received and reliable. However, we also acknowledge some limitations of the solution and discuss several next steps we are considering.
Method to Quickly Map Multifocal Pupillary Response Fields (mPRF) Using Frequency Tagging
Authors: Lorenceau Jean , Ajasse Suzon , Barbet Raphael , Boucart Muriel , Chavane Frédéric , Lamirel Cédric , Legras Richard , Matonti Frédéric , Rateaux Maxence , Rouland Jean-François , Sahel José-Alain , Trinquet Laure , Wexler Mark , Vignal-Clermont Catherine
Published: April 2024

We present a method for mapping multifocal Pupillary Response Fields in a short amount of time using a visual stimulus covering 40° of the visual angle divided into nine contiguous sectors simultaneously modulated in luminance at specific, incommensurate, temporal frequencies. We test this multifocal Pupillary Frequency Tagging (mPFT) approach with young healthy participants (N = 36) and show that the spectral power of the sustained pupillary response elicited by 45 s of fixation of this multipartite stimulus reflects the relative contribution of each sector/frequency to the overall pupillary response. We further analyze the phase lag for each temporal frequency as well as several global features related to pupil state. Test/retest performed on a subset of participants indicates good repeatability. We also investigate the existence of structural (RNFL)/functional (mPFT) relationships. We then summarize the results of clinical studies conducted with mPFT on patients with neuropathies and retinopathies and show that the features derived from pupillary signal analyses, the distribution of spectral power in particular, are homologous to disease characteristics and allow for sorting patients from healthy participants with excellent sensitivity and specificity. This method thus appears as a convenient, objective, and fast tool for assessing the integrity of retino-pupillary circuits as well as idiosyncrasies and permits to objectively assess and follow-up retinopathies or neuropathies in a short amount of time.
A Modeling Analysis of Wastewater Heat Recovery Effects on Wastewater Treatment Plant Nitrification
Authors: Mattioli Davide , Sabia Gianpaolo , Petta Luigi , Altobelli Margherita , Evangelisti Margherita , Maglionico Marco
Published: April 2024

A global shift towards renewable energy production, driven primarily by the challenges posed by climate change, is currently underway. In this context, the utilization of heat recovery from municipal wastewater emerges as a promising green technology. Notably, the advantage of implementing energy recovery in sewers, as opposed to wastewater treatment plants (WWTPs), lies in the higher temperature of the wastewater and its proximity to potential heat users. Despite these benefits, concerns arise regarding the potential adverse effects on biological wastewater treatment processes downstream of the heat recovery section, particularly during colder seasons. This paper seeks to assess the impact of a heat recovery system along the sewer network on the efficiency of biological wastewater treatment processes. The methodology involves a modeling analysis of a real sewage network in Italy. Under typical northern Italy climate conditions, the results demonstrate the feasibility of heat recovery in sewers for WWTPs designed with a sludge residence time under aerobic conditions (SRTaer) greater than 13 days. In such cases, the nitrification process remains relatively unaffected. However, for lower SRTaer values, a case-specific feasibility assessment is recommended to evaluate the overall process efficiency comprehensively.
Endogenous Hormones and Cognitive Decline in Women: Unveiling the Complex Interplay
Authors: Targonskaya Anna , Wieczorek Karolina , Maslowski Katherine
Published: April 2024

This narrative review delves into the area of endogenous hormones and their impact on cognitive function, with a focus on women transitioning through perimenopause. While artificial intelligence technologies have revolutionized cognitive research, the inclusion of hormonal biomarkers remains sparse. The review synthesizes findings from diverse studies exploring the relationships between estrogen, progesterone, testosterone, other sex hormones, and cognitive performance. The research question explores the potential for monitoring endogenous hormonal levels during perimenopause to predict cognitive decline and inform preventive strategies. An analysis of relevant studies reveals a complex relationship, with varying impacts on cognitive domains. Thus, high E2 levels correlate positively with verbal memory and retrieval efficiency, contrasting with lower levels associated with enhanced visual memory, and testosterone shows positive links to verbal fluency. The limitations of existing research, including heterogeneous methodologies and a dearth of premenopausal representation, emphasize the necessity for future studies. To achieve this objective, it is important to leverage data from studies implementing standardized methodologies for tracking endogenous hormonal levels while accounting for cycle phases and menopausal transition stages. Additionally, employing standardized assessments for cognitive decline and analyzing extensive datasets derived from real-world sources, such as hospital or outpatient clinic chains, and digital apps, is crucial.
Apoyo social a estudiantes por organizaciones latinoamericanos: Revisión sistemática
Authors: Cancino Cotrina Doris Magdalena , Justiniano Flores Rosmery Juliana
Published: April 2024

El apoyo social desempeña un papel crucial en el rendimiento académico y el bienestar general de los estudiantes. Este estudio tuvo como objetivo describir el apoyo social proporcionado a los estudiantes por organizaciones en Latinoamérica. Se llevó a cabo una revisión sistemática utilizando la declaración PRISMA, utilizando bases de datos como Scielo, SCOPUS, Redalyc y DOAJ. Los resultados de la búsqueda arrojaron un total de 822 estudios, de los cuales se seleccionaron 18 siguiendo criterios de inclusión y exclusión. Los hallazgos mostraron que el apoyo social en las escuelas y las familias mejora no solo los resultados académicos, sino también otras áreas relacionadas, como la disminución de la tasa de abandono escolar y la promoción de la salud mental en general. Esta revisión subraya la importancia del apoyo social para los estudiantes en América Latina y destaca la necesidad de intervenciones para fortalecerlo.