bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization Configuration of Leasing Capacity of Shared-Energy-Storage Systems in Offshore Wind Power Clusters
Authors: Lou Yuanyuan , Wu Jiekang , Lei Zhen
Published: January 2025

A double-layer robust optimization method for capacity configuration of shared energy storage considering cluster leasing of wind farms in a market environment is proposed based on the autonomy and profitability of shared energy storage. The feasibility of the leasing model of shared energy storage in the current market environment in China is discussed, and a commercial operation model for shared energy storage to provide leasing services and participate in spot market transactions is proposed. A robust optimization model of a master-–slave game for the capacity configuration of shared energy storage is constructed, considering output uncertainties of wind-driven generators and spot prices at multiple time scales. The upper layer of the model aims to minimize the annual cost of shared energy storage and determines the leasing prices and capacity-planning schemes for each period of shared energy storage in the scenario of an interactive game of wind farm clusters. The lower level of the model aims to minimize the assessment cost of the wind farm cluster and updates the leasing capacity for each time period by utilizing the leasing prices and the leasing demand of the wind turbine output power in the worst scenario. By comparing and analyzing multiple scenarios, the master–slave-game-formed lease improves the shared-storage lease benefit by $1.46 million compared to the fixed tariff, and the multi-timescale uncertainty promotes the shared-storage cost-effectiveness to be reduced by 8.7%, while the configuration result is more robust, providing new ideas for optimizing the capacity configuration of shared energy storage in multiple application scenarios.
An Automatic Recognition Approach for Tapping States Based on Object Detection
Authors: Xue Lingfeng , Guo Hongwei , Liang Helan , Yan Bingji , Xu Hao
Published: January 2025

Monitoring tapping states, which reflects the smoothness of blast furnace (BF) production, is important in the blast furnace ironmaking process. Currently, these monitoring data are often recorded manually, which has limitations such as low reliability and high delays. In this study, we propose an automatic recognition approach for tapping states based on object detection, using furnace front monitoring videos combined with learning-based image processing technology. This approach addresses crucial aspects such as automatically recognizing the start and end times of iron tapping and slag discharging, accurately calculating their duration, and logging tapping sequences for multi-taphole operations. The experimental results demonstrate that this approach can meet the requirements of accurate and real-time recognition of tapping states and calculation of key monitoring data in industrial applications. The automatic recognition system developed based on this approach has been successfully applied in engineering projects, which provides real-time guidance for comprehensive monitoring, intelligent analysis, and operational optimization in blast furnace production.
Mitigation of Asphaltene Deposit Formation via Chemical Additives: A Review
Authors: Stratiev Dicho , Nikolova Radoslava , Veli Anife , Shishkova Ivelina , Toteva Vesislava , Georgiev Georgi
Published: January 2025

The deposition of asphaltenes in the petroleum industry has been found to be a significant factor affecting the profitability of petroleum production and refining. For this reason, many efforts have been made to clarify the mechanism of deposition formation and to find measures to reduce its harmful impact on the efficiency of oil production and refining. Recent reports on the mechanism of deposit formation by asphaltenes suggest that it is a phase transition phenomenon. Many studies have shown that this process can be slowed by using chemical inhibitors. Different classes of chemical substances (non-polymeric, organic compounds, polymers, ionic liquids and nanomaterials) have been found to be capable of inhibiting asphaltene precipitation. This paper presents a comprehensive review of asphaltene deposition research and makes an attempt to decipher the convoluted asphaltene deposition phenomena and relate the chemistry of asphaltene inhibitors to the nature of treated petroleum oils. The choice of appropriate additives to mitigate asphaltene deposition in commercial oil and gas facilities requires comprehensive knowledge of chemistry of oils, asphaltenes, and the chemical substances, along with the appropriate laboratory techniques that best mimic the commercial operation conditions.
Synthesis of Combined Heat- and Mass-Exchanger Networks with Multiple Utilities Using the Pinch Technology and Microsoft Excel and GAMS Programs for Comparing Process Flowsheets
Authors: Mena-Pacheco Steven , Tuza Pablo V.
Published: January 2025

In the present work, Combined Heat and Mass Exchanger Networks (CHAMENs) with multiple utilities were synthesized using the pinch technology, the Microsoft Excel and GAMS programs for comparing process flowsheets. Due to the lack of information about streams that can transfer heat and mass, these were generated by combining streams that can only transfer heat and streams that can only transfer mass. On one hand, energy balances and mass balances were made when a common value of an open interval was bounded by source and target values of a stream and, on the other hand, by an open interval bounded by values based on information from the dataset. The CHAMEN formulation was resolved using the Generalized Reduced Gradient method from Microsoft Excel® and the DICOPT solver from GAMS. When there were problems in convergence of a solution, initial values for solving the problem using the Solver Tool were obtained by changing the solving method or resolving the Heat Exchanger Network and the Mass Exchanger Network models separately. Heat and mass transfer per interval bounded by values based on information from the dataset can be used in designing the CHAMEN by hand. Six examples are presented in this work and they include streams exchanging heat and mass jointly and streams exchanging them separately. Two of the six examples presented were designed at the threshold–temperature and threshold–composition difference. For the first time using a mixed-integer linear programming framework, the heating of a stream with its own energy after cooling for the mass transferring process is reported.
Improving the Solving of Optimization Problems: A Comprehensive Review of Quantum Approaches
Authors: Volpe Deborah , Orlandi Giacomo , Turvani Giovanna
Published: January 2025

Optimization is a crucial challenge across various domains, including finance, resource allocation, and mobility. Quantum computing has the potential to redefine the way we handle complex problems by reducing computational complexity and enhancing solution quality. Optimization, particularly of objective functions, stands to benefit significantly from quantum solvers, which leverage principles of quantum mechanics like superposition, entanglement, and tunneling. The Ising and Quadratic Unconstrained Binary Optimization (QUBO) models are the most suitable formulations for these solvers, involving binary variables and constraints treated as penalties within the overall objective function. To harness quantum approaches for optimization, two primary strategies are employed: exploiting quantum annealers—special-purpose optimization devices—and designing algorithms based on quantum circuits. This review provides a comprehensive overview of quantum optimization methods, examining their advantages, challenges, and limitations. It demonstrates their application to real-world scenarios and outlines the steps to convert generic optimization problems into quantum-compliant models. Lastly, it discusses available tools and frameworks that facilitate the exploration of quantum solutions for optimization tasks.
A Framework for Public Policy Development in BRICS Countries to Support Circular Economy Development in the WEEE Value Chain
Authors: da Silva Christian Luiz , Franz Nádia Mara
Published: January 2025

Waste Electrical and Electronic Equipment (WEEE) has grown three times faster than the world’s population and 13% more than global GDP with increasing urbanization, including in BRICS countries (Brazil, Russia, India, China and South Africa), which were home to around 42% of the world population in 2024. The research question in this study is as follows: how are BRICS countries integrating WEEE actors in moving towards sustainable cities? The integration of actors, based on the principle of sustainable cities, occurs through different forms of interaction: either through the institutional apparatus in which they operate or through the economic, social or environmental issues in which they are involved. The study proposes a framework for public policies of the WEEE value chain under the precepts of sustainable cities in the BRICS countries. The techniques applied were based on bibliographical and documentary research and semi-structured interviews. The Delphi method was applied for the interviews. The framework comprises 39 strategic variables in the urban environmental, economic and social categories. Applying this framework enables the identification of barriers and opportunities in the context of cities in the BRICS countries. Based on the proposed framework, it is possible to evaluate and propose public policies for BRICS countries, reinforcing opportunities and seeking to deal with existing barriers.
Semi-Supervised Change Detection with Data Augmentation and Adaptive Thresholding for High-Resolution Remote Sensing Images
Authors: Zhang Wuxia , Shu Xinlong , Wu Siyuan , Ding Songtao
Published: January 2025

Change detection (CD) is an important research direction in the field of remote sensing, which aims to analyze the changes in the same area over different periods and is widely used in urban planning and environmental protection. While supervised learning methods in change detection have demonstrated substantial efficacy, they are often hindered by the rising costs associated with data annotation. Semi-supervised methods have attracted increasing interest, offering promising results with limited data labeling. These approaches typically employ strategies such as consistency regularization, pseudo-labeling, and generative adversarial networks. However, they usually face the problems of insufficient data augmentation and unbalanced quality and quantity of pseudo-labeling. To address the above problems, we propose a semi-supervised change detection method with data augmentation and adaptive threshold updating (DA-AT) for high-resolution remote sensing images. Firstly, a channel-level data augmentation (CLDA) technique is designed to enhance the strong augmentation effect and improve consistency regularization so as to address the problem of insufficient feature representation. Secondly, an adaptive threshold (AT) is proposed to dynamically adjust the threshold during the training process to balance the quality and quantity of pseudo-labeling so as to optimize the self-training process. Finally, an adaptive class weight (ACW) mechanism is proposed to alleviate the impact of the imbalance between the changed classes and the unchanged classes, which effectively enhances the learning ability of the model for the changed classes. We verify the effectiveness and robustness of the proposed method on two high-resolution remote sensing image datasets, WHU-CD and LEVIR-CD. We compare our method to five state-of-the-art change detection methods and show that it achieves better or comparable results.
The Diurnal Variation of L-Band Polarization Index in the U.S. Corn Belt Is Related to Plant Water Stress
Authors: Cirone Richard , Hornbuckle Brian K.
Published: January 2025

The microwave polarization index (PI), defined as the difference between vertically polarized (V-pol) and horizontally polarized (H-pol) brightness temperature divided by their average, is independent of land surface temperature. Since soil emission is stronger at V-pol than H-pol and vegetation attenuates this polarized soil signal primarily because of liquid water stored in vegetation tissue, a lower PI will be indicative of more water in vegetation if vegetation emits a mostly unpolarized signal and changes in soil moisture within the emitting depth are small (like during periods of drought) or accommodated by averaging over long periods. We hypothesize that the L-band PI will reveal diurnal changes in vegetation water related to whether plants have adequate soil water. We compare 6 a.m. and 6 p.m. L-band PI from NASA’s Soil Moisture Active Passive (SMAP) satellite to the evaporative stress index (ESI) in the U.S. Corn Belt during the growing season. When ESI<0 (there is not adequate plant-available water, also called plant water stress), the L-band PI is not significantly different at 6 a.m. vs. 6 p.m. On the other hand, when ESI≥0 (no plant water stress), the L-band PI is greater in the evening than in the morning. This diurnal behavior can be explained by transpiration outpacing root water uptake during daylight hours (resulting in a decrease in vegetation water from 6 a.m. to 6 p.m.) and continued root water uptake overnight (that recharges vegetation water) only when plants have adequate soil water. Consequently, it may be possible to use L-band PI to identify plant water stress in the Corn Belt.
Study of Shale Gas Source Rock S-Wave Structure Characteristics via Dense Array Ambient Noise Tomography in Zhangjiakou, China
Authors: Chen Si , Lu Zhanwu , Wang Haiyan , Wu Qingyu , Cai Wei , Wu Guowei , Wang Guangwen
Published: January 2025

Utilizing short-period dense seismic arrays, ambient noise tomography has proven effective in delineating continuous geological structures, a task critical for characterizing shale gas reservoir configurations. This study deployed 153 short-period seismic stations across the Xiahuayuan District in Zhangjiakou, a region with prospective shale gas deposits, to perform an ambient noise tomography survey. Through a meticulous process involving cross-correlation analysis, dispersion curve extraction, and subsequent inversion, a three-dimensional velocity structure model of the area was constructed. The model discerns subtle velocity changes within the 0–3 km depth interval, achieving a horizontal resolution of approximately 1.5 km in the 0–3 km stratum, thereby effectively delineating the shale reservoir structure. Integration of the velocity model with regional geological data facilitated a comprehensive interpretation and structural analysis of the prospective shale gas zone. Low-velocity anomalies observed within the velocity structure correspond to the spatial distribution of the Xiahuayuan Formation, likely attributable to the prevalent stratum of mudstone shale deposits within this formation. Employing a binary stratigraphic model, the study predicted shale content based on the velocity structure, with predictions exhibiting a moderate correlation (correlation coefficient of 0.58) with empirical data. This suggests the presented method as a viable rapid estimation technique for assessing the shale content of target strata.
Understanding the Influence of Image Enhancement on Underwater Object Detection: A Quantitative and Qualitative Study
Authors: Saleem Ashraf , Awad Ali , Paheding Sidike , Lucas Evan , Havens Timothy C. , Esselman Peter C.
Published: January 2025

Underwater image enhancement is often perceived as a disadvantageous process to object detection. We propose a novel analysis of the interactions between enhancement and detection, elaborating on the potential of enhancement to improve detection. In particular, we evaluate object detection performance for each individual image rather than across the entire set to allow a direct performance comparison of each image before and after enhancement. This approach enables the generation of unique queries to identify the outperforming and underperforming enhanced images compared to the original images. To accomplish this, we first produce enhanced image sets of the original images using recent image enhancement models. Each enhanced set is then divided into two groups: (1) images that outperform or match the performance of the original images and (2) images that underperform. Subsequently, we create mixed original-enhanced sets by replacing underperforming enhanced images with their corresponding original images. Next, we conduct a detailed analysis by evaluating all generated groups for quality and detection performance attributes. Finally, we perform an overlap analysis between the generated enhanced sets to identify cases where the enhanced images of different enhancement algorithms unanimously outperform, equally perform, or underperform the original images. Our analysis reveals that, when evaluated individually, most enhanced images achieve equal or superior performance compared to their original counterparts. The proposed method uncovers variations in detection performance that are not apparent in a whole set as opposed to a per-image evaluation because the latter reveals that only a small percentage of enhanced images cause an overall negative impact on detection. We also find that over-enhancement may lead to deteriorated object detection performance. Lastly, we note that enhanced images reveal hidden objects that were not annotated due to the low visibility of the original images.
National Exposed Sediment Search and Inventory (NESSI): Utilizing Satellite Imagery and Machine Learning to Identify Dredged Sediment Placement Site Recovery
Authors: Huff Thomas P. , Russ Emily R. , Swannack Todd M.
Published: January 2025

Anthropogenic activity leads to changes in sediment dynamics, creating imbalances in sediment distributions across the landscape. These imbalances can be variable within a littoral system, with adjacent areas experiencing sediment starvation and excess sediment. Historically, sediments were viewed as an inconvenient biproduct destined for disposal; however, beneficial use of dredge material (BUDM) is a practice that has grown as a preferred methodology for utilizing sediment as a resource to help alleviate the sediment imbalances within a system. BUDM enables organizations to adopt a more innovative and sustainable sediment management approach that also provides ecological, economic, and social co-benefits. Although location data are available on BUDM sites, especially in the US, there is limited understanding on how these sites evolve within the larger landscape, which is necessary for quantifying the co-benefits. To move towards BUDM more broadly, new tools need to be developed to allow researchers and managers to understand the effects and benefits of this practice. The National Exposed Sediment Search and Inventory (NESSI) was built to show the capability of using machine learning techniques to identify dredged sediments. A combination of satellite imagery data obtained and processed using Google Earth Engine and machine learning algorithms were applied at known dredged material placement sites to develop a time series of dredged material placement events and subsequent site recovery. These disturbance-to-recovery time series are then used in a landscape analysis application to better understand site evolution within the context of the surrounding areas.
An Energy-Domain IR NUC Method Based on Unsupervised Learning
Authors: Li Ting , Lai Xuefeng , Liao Sheng , Xia Yucheng
Published: January 2025

To obtain accurate blackbody temperature, emissivity, and waveband measurements, an energy-domain infrared nonuniformity method based on unsupervised learning is proposed. This method exploits the inherent physical correlation within the calibration dataset and sets the average predicted energy-domain value of the same blackbody temperature as the learning goal. Then, the coefficients of the model are learned without theoretical radiance labels by leveraging clustering-based unsupervised learning methodologies. Finally, several experiments are performed on a mid-wave infrared system. The results show that the trained correction network is uniform and produces stable outputs when the integration time and attenuator change within the optimal dynamic range. The maximum change in the image corrected using the proposed algorithm was 1.29%.
Applying MLP-Mixer and gMLP to Human Activity Recognition
Authors: Miyoshi Takeru , Koshino Makoto , Nambo Hidetaka
Published: January 2025

The development of deep learning has led to the proposal of various models for human activity recognition (HAR). Convolutional neural networks (CNNs), initially proposed for computer vision tasks, are examples of models applied to sensor data. Recently, high-performing models based on Transformers and multi-layer perceptrons (MLPs) have also been proposed. When applying these methods to sensor data, we often initialize hyperparameters with values optimized for image processing tasks as a starting point. We suggest that comparable accuracy could be achieved with fewer parameters for sensor data, which typically have lower dimensionality than image data. Reducing the number of parameters would decrease memory requirements and computational complexity by reducing the model size. We evaluated the performance of two MLP-based models, MLP-Mixer and gMLP, by reducing the values of hyperparameters in their MLP layers from those proposed in the respective original papers. The results of this study suggest that the performance of MLP-based models is positively correlated with the number of parameters. Furthermore, these MLP-based models demonstrate improved computational efficiency for specific HAR tasks compared to representative CNNs.
Inclusion and Well-Being Among National and Immigrant University Students in Portugal: Avenues for Participatory Research
Authors: Teixeira Maria Odília , Laranjeira Márcia
Published: January 2025

In the context of European migratory flows, the inclusion paradigm gives education the responsibility of welcoming, integrating, and training students in an environment that defends humanistic values of equity, respect and dignity. In higher education, this requires institutions to implement inclusive educational policies, promote supportive cultures, and adopt practices that promote change, development, and individual and social well-being. This study examines inclusion variables and their relationship with well-being in a sample of 256 higher education students, including immigrant (n = 107) and non-immigrant (n = 149) students. Immigrant students reported lower perceptions of inclusion across policies (p < 0.001), practices (p < 0.05), and cultures (p < 0.001) compared to their non-immigrant peers. Furthermore, structural equation modeling analysis revealed that inclusive practices of teachers and institutions are significantly associated with the well-being of all students (β = 0.33, p = 0.032). These results highlight the need to implement inclusive educational strategies in both intervention and research. In this context, innovative approaches to participatory research stand out. These approaches must consider the diversity of students, create conditions that promote the well-being of the entire school community, and promote an academic environment that is agentive, relational, and empathetic, and which supports the integration of immigrant students.
Relationship Between Attachment and Social Skills in Adulthood Education in the Digital Society
Authors: Muñoz-Pradas Raquel , de la Fuente Benítez María , Palacios-Rodríguez Antonio , Fernández Scagliusi Mª Victoria
Published: January 2025

In the midst of the Knowledge Society, where social interactions, contact, and the establishment of relationships—whether face to face or through the use of new technologies—prevail, isolation is detected as a consequence of the global COVID-19 pandemic, due to which both interpersonal relationships and attachment bonds are negatively affected. It is for all this that the need arises in this study to analyze the possible existence of a correlation between both variables. The objective of this work is to analyze the relationship between social skills and the type of attachment in a sample of subjects over 18 years of age. After carrying out the analyses, the existence of a statistically significant relationship was detected between the social skills variable and Attachment Scale 3, corresponding to subjects with good abilities to express feelings and comfort with relationships (secure attachment). It is concluded by stating that subjects who have developed a secure attachment will have more satisfactory social relationships.
Critical Soft Skills for Sustainability in Higher Education: A Multi-Phase Qualitative Study
Authors: Costa Marcelle Feitoza Bassi , Cipolla Carla Martins
Published: January 2025

Sustainability requires a holistic perspective beyond technological advancements, integrating relational and socio-emotional dimensions critical for addressing the complexity of contemporary challenges. In this context, interpersonal and intrapersonal skills, often referred to as soft skills, emerge as central elements, particularly within the educational domain. This article aims to identify critical soft skills for sustainability and systematize educational practices supporting their development and integration into higher education. Employing a methodological framework grounded in Design-Based Research (DBR) and Design Thinking (DT), this research was conducted in three phases: (i) immersion, (ii) content analysis, and (iii) synthesis. The results identify 19 soft skills, grouped into four main categories: (i) Communication, Collaboration, and Diversity Management; (ii) Self-Awareness and Emotional Management; (iii) Environmental, Cultural, and Social Awareness; and (iv) Ethical Values and Spirituality. For each category, specific educational practices are presented, offering a strategic pathway to integrate these skills into higher education and advance competencies aligned with sustainability. This study highlights the urgent need for a transformative shift in higher education, proposing a structured and adaptable model for integrating critical soft skills into the educational field. This approach aims to equip individuals with the interpersonal and intrapersonal competencies to navigate complex socio-environmental challenges and contribute to a more sustainable future.
The Effects of Blended Learning on Learning Engagement in Physical Education Among University Students in China: The Mediating Role of Attitudes
Authors: Yu Yanan , Che Tak Khairudin Bin , Bailey Richard Peter , Samsudin Nadia , Ren Ce
Published: January 2025

Under the pedagogical concept of sustainable development, an increasing number of interdisciplinary pedagogies are being applied in physical education, moving away from traditional face-to-face teaching methods. This study investigated the influence of blended learning on students’ engagement in physical education and the role of attitudes in this process. A questionnaire was used to validate the model based on a comprehensive literature review. PLS-SEM was used to assess the direct relationship between blended learning and learning engagement in physical education and the mediating influence of attitudes toward blended learning on these factors. The findings revealed that face-to-face sessions and students’ attitude toward blended learning positively affect their engagement in physical education. The results also indicated that students’ attitudes significantly mediate course design, learning experience, and face-to-face sessions with learning engagement. Based on the variable relationship, this study proposes a blended learning strategy rooted in the Five-star Teaching Model. By stimulating students’ initiative in learning, their attitude improved, enhancing their engagement in physical education classes. This research holds both theoretical and practical significance by improving the quality of physical education teaching and learning methods, offering novel insights into instruction in this field.
Perceptions and Behaviors Concerning Tourism Degrowth and Sustainable Tourism: Latent Dimensions and Types of Tourists
Authors: Pinto Hugo , Barboza Miriam , Nogueira Carla
Published: January 2025

The current economic model centered on perpetual growth is unsustainable. Without a shift away from this growth-centric approach and rampant consumerism, the environmental and social crises will persist. This article explores tourists’ relationship with degrowth and sustainability. Through an empirical investigation, the study explores the relatively uncharted territory of how tourists engage with degrowth. Employing an online survey with a sample of 261 respondents obtained through convenience sampling via online distribution, the research seeks to unearth key facets of tourist behavior and categorize tourists based on their attitudes toward sustainability and degrowth. The findings indicate that degrowth remains a largely unfamiliar concept among tourists. Interestingly, those exhibiting more sustainable travel practices also display a greater alignment with degrowth principles. Conversely, younger tourists appear less inclined towards sustainable behaviors and more resistant to embracing degrowth ideologies. These findings underscore the potential of degrowth in addressing sustainability challenges within the tourism industry while emphasizing the need of including tourists and local communities in fostering a shift toward more sustainable tourism practices.
A Comparison of Tourists’ Spatial–Temporal Behaviors Between Location-Based Service Data and Onsite GPS Tracks
Authors: Parkinson Colby , Pan Bing , Morris Sophie A. , Rice William L. , Taff B. Derrick , Chi Guangqing , Newman Peter
Published: January 2025

Tourism and recreation managers rely on spatial-temporal data to measure visitors’ behavior for gauging carrying capacity and sustainable management. Location-based service (LBS) data, which passively record location data based on mobile devices, may enable managers to measure behaviors while overcoming constraints in labor, logistics, and cost associated with in-person data collection. However, further validation of LBS data at more refined spatial and temporal scales within tourism attractions is needed. We compared observations of salient spatial–temporal measures from a stratified sample of onsite visitors’ GPS traces in a popular U.S. National Park during peak season over two years with a sample of visitors’ traces collected during the same period by a third-party LBS data provider. We described trip characteristics and behaviors within 34 points of interest (POIs) and then pre-processed both datasets into weighted, directed networks that treated POIs as nodes and flow between POIs as edges. Both datasets reported similar proportions of day-use visitors (~79%) and had moderate-to-strong correlations across networks depicting visitor flow (r = 0.72–0.85, p < 0.001). However, relative to the onsite data, LBS data underestimated the number of POIs the visitors stopped by and differed in its rank of popular POIs, underestimating the length of time visitors spent in POIs (z = 1, p ≤ 0.001) and overestimating visitation to the most popular POIs (z = 180, p = 0.044). Our findings suggest that LBS data may be helpful for identifying trends or tracking tourist movement in aggregate and at crude spatial and temporal scales, but they are too sparse and noisy to reliably measure exact movement patterns, visitation rates, and stay time within attractions.
Evaluating Fast-Growing Fibers for Building Decarbonization with Dynamic LCA
Authors: Chilton Kate , Arehart Jay , Hinkle Hal
Published: January 2025

Standard carbon accounting methods and metrics undermine the potential of fast-growing biogenic materials to decarbonize buildings because they ignore the timing of carbon uptake. The consequence is that analyses can indicate that a building material is carbon-neutral when it is not climate-neutral. Here, we investigated the time-dependent effect of using fast-growing fibers in durable construction materials. This study estimated the material stock and flow and associated cradle-to-gate emissions for four residential framing systems in the US: concrete masonry units, light-frame dimensional timber, and two framing systems that incorporate fast-growing fibers (bamboo and Eucalyptus). The carbon flows for these four framing systems were scaled across four adoption scenarios, Business as Usual, Early-Fast, Late-Slow, and Highly Optimistic, ranging from no adoption to the full adoption of fast-growing materials in new construction within 10 years. Dynamic life cycle assessment modeling was used to project the radiative forcing and global temperature change potential. The results show that the adoption of fast-growing biogenic construction materials can significantly reduce the climate impact of new US residential buildings. However, this study also reveals that highly aggressive, immediate adoption is the only way to achieve net climate cooling from residential framing within this century, highlighting the urgent need to change the methods and metrics decision makers use to evaluate building materials.
Adaptive Thermal Comfort in the Different Buildings of Temperate Climates—Comparison Between High-Latitude Europe and Mountainous Himalayas in India
Authors: Thapa Samar , Pernigotto Giovanni
Published: January 2025

Thermal comfort in buildings is essential for occupant well-being and energy efficiency, particularly in naturally ventilated environments where indoor conditions are closely influenced by outdoor climates. Current studies have not fully explored how thermal comfort varies across regions with similar climatic classifications but distinct geographic and cultural contexts. Addressing this gap, we analyzed and compared the adaptive thermal comfort responses in different naturally ventilated buildings located in temperate oceanic regions arising due to the high latitude in Europe and the elevated Himalayan region of Darjeeling, India. A mixed-methods approach was used with data from classrooms, offices, and residential buildings with adaptive thermal comfort modeling. The results show that European buildings exhibit narrower thermal comfort ranges compared to Darjeeling, for example, 21.2~24.8 °C versus 16.0~21.6 °C for 80% comfortability in classroom settings, respectively. Statistical analysis revealed significant differences in clothing insulation levels, with occupants in Darjeeling buildings demonstrating higher variability (mean rank 2103.31) compared to their European counterparts (mean rank 1207.30, p < 0.001). Additionally, a stronger correlation between indoor and outdoor air temperature was observed in Darjeeling (R: 0.785, p < 0.001), reflecting limited thermal buffering compared to European buildings (R: 0.372, p < 0.001). The paper advances adaptive thermal comfort models that account for regional differences and links these finding to sustainable building practices. The findings provide actionable insights for energy-efficient, climate-responsive building practices while supporting global sustainable development goals.
Derivation of Tensor Algebra as a Fundamental Operation—The Fermi Derivative in a General Metric Affine Space
Authors: Tsamparlis Michael
Published: January 2025

The aim of this work is to demonstrate that all linear derivatives of the tensor algebra over a smooth manifold M can be viewed as specific cases of a broader concept—the operation of derivation. This approach reveals the universal role of differentiation, which simplifies and generalizes the study of tensor derivatives, making it a powerful tool in Differential Geometry and related fields. To perform this, the generic derivative is introduced, which is defined in terms of the quantities Qk(i)(X). Subsequently, the transformation law of these quantities is determined by the requirement that the generic derivative of a tensor is a tensor. The quantities Qk(i)(X) and their transformation law define a specific geometric object on M, and consequently, a geometric structure on M. Using the generic derivative, one defines the tensor fields of torsion and curvature and computes them for all linear derivatives in terms of the quantities Qk(i)(X). The general model is applied to the cases of Lie derivative, covariant derivative, and Fermi derivative. It is shown that the Lie derivative has non-zero torsion and zero curvature due to the Jacobi identity. For the covariant derivative, the standard results follow without any further calculations. Concerning the Fermi derivative, this is defined in a new way, i.e., as a higher-order derivative defined in terms of two derivatives: a given derivative and the Lie derivative. Being linear derivative, it has torsion and curvature tensor. These fields are computed in a general affine space from the corresponding general expressions of the generic derivative. Applications of the above considerations are discussed in a number of cases. Concerning the Lie derivative, it is been shown that the Poisson bracket is in fact a Lie derivative. Concerning the Fermi derivative, two applications are considered: (a) the explicit computation of the Fermi derivative in a general affine space and (b) the consideration of Freedman–Robertson–Walker spacetime endowed with a scalar torsion field, which satisfies the Cosmological Principle and the computation of Fermi derivative of the spatial directions defining a spatial frame along the cosmological fluid of comoving observers. It is found that torsion, even in this highly symmetric case, induces a kinematic rotation of the space axes, questioning the interpretation of torsion as a spin. Finally it is shown that the Lie derivative of the dynamical equations of an autonomous conservative dynamical system is equivalent to the standard Lie symmetry method.
Isolation and Structural Identification of New Diol Esters of Okadaic Acid and Dinophysistoxin-1 from the Cultured Prorocentrum lima
Authors: Ji Yeong Kwang , Moon Semin , Lee Sangbum , Kim Yun Na , Jeong Eun Ju , Rho Jung-Rae
Published: January 2025

Prorocentrum, a dinoflagellate responsible for producing diarrhetic shellfish poisoning (DSP) toxins, poses significant threats to marine ecosystems, aquaculture industries, and human health. DSP toxins, including okadaic acid (OA), dinophysis toxin (DTX), and their diverse derivatives, continue to be identified and characterized. In this study, we report the isolation of four new diol esters of OA/DTX-1 from large-scale cultures of Prorocentrum lima. Their chemical structures were elucidated through comprehensive NMR and MS analyses, along with structural comparisons with the well-known OA. Notably, compound 1 featured an additional ester group within the diol unit, while compound 2 was revealed to be a C11 diol ester. The cytotoxicity of these newly isolated derivatives was evaluated against three cell lines: Neuro2a (mouse), HCT116 (human), and HepG2 (human). All diol esters exhibited cytotoxic effects, with compound 3 displaying toxicity comparable to OA. These results expand our understanding of DSP toxin diversity and provide valuable insight into the structural variations and biological activity of diol esters of OA/DTX-1.
Personal Satisfaction with Accessibility and Service Quality: Spatial Justice in Guangzhou’s Social Housing Communities
Authors: Chao Ruixia , Hong Haolin , Wei Wei
Published: January 2025

Individuals in social housing heavily depend on the surrounding infrastructure and services. There is a gap in understanding the needs of vulnerable groups regarding access to these resources. From the lens of spatial justice, we explored the specific needs of financially limited residents, considering affordability, service levels, and service quality. Surveying 660 individuals across 13 communities in Guangzhou, we firstly assessed the accessibility to facilities by using travel data. Subsequently, a principal component analysis revealed key factors influencing individuals’ satisfaction, including proximity to essential amenities, efficient service, high-quality education, affordability of commercial establishments, and access to healthcare services. While proximity to basic facilities achieves satisfaction, it falls short of ensuring fulfilment in healthcare, commerce, and education service quality. Satisfaction varies by community location and age, with newer communities, especially those established post-2010 in outlying areas, struggling to uphold spatial justice.
Emerging Roles of TRIM56 in Antiviral Innate Immunity
Authors: Wang Dang , Li Kui
Published: January 2025

The tripartite-motif protein 56 (TRIM56) is a RING-type E3 ubiquitin ligase whose functions were recently beginning to be unveiled. While the physiological role(s) of TRIM56 remains unclear, emerging evidence suggests this protein participates in host innate defense mechanisms that guard against viral infections. Interestingly, TRIM56 has been shown to pose a barrier to viruses of distinct families by utilizing its different domains. Apart from exerting direct, restrictive effects on viral propagation, TRIM56 is implicated in regulating innate immune signaling pathways that orchestrate type I interferon response or autophagy, through which it indirectly impacts viral fitness. Remarkably, depending on viral infection settings, TRIM56 either operates in a canonical, E3 ligase-dependent fashion or adopts an enzymatically independent, non-canonical mechanism to bolster innate immune signaling. Moreover, the recent revelation that TRIM56 is an RNA-binding protein sheds new light on its antiviral mechanisms against RNA viruses. This review summarizes recent advances in the emerging roles of TRIM56 in innate antiviral immunity. We focus on its direct virus-restricting effects and its influence on innate immune signaling through two critical pathways: the endolysosome-initiated, double-stranded RNA-sensing TLR3-TRIF pathway and the cytosolic DNA-sensing, cGAS-STING pathway. We discuss the underpinning mechanisms of action and the questions that remain. Further studies understanding the complexity of TRIM56 involvement in innate immunity will add to critical knowledge that could be leveraged for developing antiviral therapeutics.
Decomposition Processes and Characteristics of Wetland Plant Residues: Impacts of Biomass, Sediment, Living V. spinulosa Yan
Authors: Wang Dongsheng , Liu Enqi , Huang Yunhua , Zhang Mengyang , Wu Haiming , Wu Suqing , Gu Jianya
Published: January 2025

The decomposition of submerged plants is an important factor affecting water quality and microbial community structure of aquatic ecosystems. This study aims to investigate the effects of the decomposition process of V. spinulosa Yan residues on the water quality and microbial community of the receiving water under different conditions, including biomass weight, sediment component, and living V. spinulosa Yan. The results showed that the optimal biomass for the decomposition of residues was 0.3 g/L. The sand–soil mixture (3:7) showed the lowest decomposition rate (90.4%) due to the poor moisture retention of sand and lack of organic matter and minerals, which slowed down the decomposition process. N and P could be released into the water rapidly through decomposing the residues, and the concentrations of TP, TN, and PO43−-P were positively correlated with the biomass of the residues. The decrease in TN and TP concentrations observed with bioceramic and Fe-C ceramic was partly due to their porous structures promoting microbial attachment and the adsorption of N and P, possibly also through an increase in Firmicutes. After planting living V. spinulosa Yan, TP and PO43−-P concentrations, as well as dissolved oxygen levels, were lower in the sediment groups compared to those in the control group without living V. spinulosa Yan. This suggests that living V. spinulosa Yan effectively purifies water by absorbing nutrients and promoting nitrification–denitrification processes. These differences underscore the active role of living plants in nutrient removal. This study provides a scientific basis for the management of submerged plants.
Identifying the Primary Producer of High Concentrations of 2-Methylisoborneol and Assessing the Impact of Weather Conditions at the Haizuka Reservoir, Japan
Authors: Hayashi Shohei , Kim Sangyeob , Ayukawa Kazuhiro , Sugahara Shogo , Seike Yasushi , Nakamura Yasuhide
Published: January 2025

2-methylisoborneol (2-MIB), produced by cyanobacteria in water systems, has a musty odor and causes discomfort in humans. Extra costs are incurred when removing 2-MIB from water. The growth of 2-MIB-producing cyanobacteria, as well as the occurrence of 2-MIB, are affected by many environmental factors, including water temperature and nutrient concentrations. These factors are influenced by weather conditions. 2-MIB-producing cyanobacteria and 2-MIB production in various water systems have been investigated using several methods. However, the combined spatiotemporal monitoring of various indicators, especially weather conditions, is limited. In May 2023, a high concentration of 2-MIB was detected in the Haizuka Reservoir, Japan. This study aims to clarify the transition of 2-MIB-producing cyanobacteria and the effects of environmental factors, including weather meteorological conditions, on 2-MIB production. To achieve this, combined spatiotemporal monitoring of various indicators was conducted, including 2-MIB concentration, the cell count of the producers, the 2-MIB biosynthesis gene, water quality, and weather conditions. Our analysis revealed that a high concentration of 2-MIB was produced by the proliferated Pseudanabaena sp. in the surface water in May 2023. The proliferation of 2-MIB-producing Pseudanabaena sp. might be related to the higher-than-average rainfall in April and May and consistently higher-than-average temperature from January to May. Although this study was unable to clarify how these weather conditions led to the proliferation of 2-MIB-producing Pseudanabaena sp., these weather conditions can be used to warn of the occurrence of high concentrations of 2-MIB in the Haizuka Reservoir. In conclusion, it is effective to incorporate weather conditions into the monitoring of 2-MIB production in water sources.
Cultural Influence of Local Food Heritage on Sustainable Development
Authors: Chukwurah Gladys Ogochukwu , Okeke Francis Ogochukwu , Isimah Matthew Ogorchukwu , Enoguanbhor Evidence Chinedu , Awe Foluso Charles , Nnaemeka-Okeke Rosemary Chidimma , Guo Shuang , Nwafor Ifeanyichukwu Valentine , Okeke Chioma Angela
Published: January 2025

This article explores relations between cultural heritage and cultural values for sustainable development in the Enugu region. It discusses the potential to advance a cultural approach to sustainable development of regions by examining the cultural food heritage and relating it to cultural values. Based on empirical research, the article employed a mixed-methods approach to examine the relationship between the identified major local food heritage and cultural values for sustainable regional planning and development. The study examined primary data from 380 community elders, traders, and relevant institutions—including the Ministry of Arts and Culture and the Ministry of Agriculture—through interviews, participant observation, and questionnaires. Data were analyzed using SPSS and Pearson product–moment correlation. Findings identified eight local food heritages and six cultural values. The findings suggest that promoting and preserving local food heritage can be crucial in fostering sustainable cultural values and contributing to sustainable regional development. The local food had a statistically significant influence on cultural values. The Pearson correlation result (p-value = 0.000) shows a strong correlation between the local food heritage and cultural values for sustainable regional planning and development. However, the study also identified several challenges threatening the sustainability of local food heritage in the region, including high costs, small-scale farming, insecurity, climate change, and poor transportation. The study recommends the development and implementation of comprehensive policies and programs that prioritize the preservation and promotion of local food heritage while addressing the identified challenges.