bluuebunny/crossref_metadata_2025 huggingface dataset:
Style Transfer of Chinese Wuhu Iron Paintings Using Hierarchical Visual Transformer
Authors: Zhou Yuying , Ren Yao , Wu Chao , Xue Minglong
Published: December 2024

Within the domain of traditional art, Chinese Wuhu Iron Painting distinguishes itself through its distinctive craftsmanship, aesthetic expressiveness, and choice of materials, presenting a formidable challenge in the arena of stylistic transformation. This paper introduces an innovative Hierarchical Visual Transformer (HVT) framework aimed at achieving effectiveness and precision in the style transfer of Wuhu Iron Paintings. The study begins with an in-depth analysis of the artistic style of Wuhu Iron Paintings, extracting key stylistic elements that meet technical requirements for style conversion. Furthermore, in response to the unique artistic characteristics of Wuhu Iron Paintings, this research constructs a multi-layered network structure capable of effectively capturing and parsing style and content features. Building on this, we have designed an Efficient Local Attention Decoder (ELA-Decoder) that adaptively decodes the style and content features through correlation, significantly enhancing the length dependency of local and global information. Additionally, this paper proposes a Content Correction Module (CCM) to eliminate redundant features generated during the style transfer process, further optimizing the migration results. In light of the scarcity of existing datasets for Wuhu Iron Paintings, this study also collects and constructs a dedicated dataset for the style transfer of Wuhu Iron Paintings. Our method achieves optimal performance in terms of loss metrics, with a reduction of at least 4% in style loss and 5% in content loss compared to other advanced methods. Moreover, expert evaluations were conducted to validate the effectiveness of our approach, and the results show that our method received the highest number of votes, further demonstrating its superiority.
A Case Study on EEG Signal Correlation Towards Potential Epileptic Foci Triangulation
Authors: Doll Theodor , Stieglitz Thomas , Heumann Anna Sophie , Wójcik Daniel K.
Published: December 2024

The precise localization of epileptic foci with the help of EEG or iEEG signals is still a clinical challenge with current methodology, especially if the foci are not close to individual electrodes. On the research side, dipole reconstruction for focus localization is a topic of recent and current developments. Relatively low numbers of recording electrodes cause ill-posed and ill-conditioned problems in the inversion of lead-field matrices to calculate the focus location. Estimations instead of tissue conductivity measurements further deteriorate the precision of location tasks. In addition, time-resolved phase shifts are used to describe connectivity. We hypothesize that correlations over runtime approaches might be feasible to predict seizure foci with adequate precision. In a case study on EEG correlation in a healthy subject, we found repetitive periods of alternating high correlation in the short (20 ms) and long (300 ms) range. During these periods, a numerical determination of proportions of predominant latency and, newly established here, directionality is possible, which supports the identification of loops that, according to current opinion, manifest themselves in epileptic seizures. In the future, this latency and directionality analysis could support focus localization via dipole reconstruction using new triangulation calculations.
A Spatial Crowdsourcing Engine for Harmonizing Volunteers’ Needs and Tasks’ Completion Goals
Authors: Puerta-Beldarrain Maite , Gómez-Carmona Oihane , Chen Liming , López-de-Ipiña Diego , Casado-Mansilla Diego , Vergara-Borge Felipe
Published: December 2024

This work addresses the task allocation problem in spatial crowdsensing with altruistic participation, tackling challenges like declining engagement and user fatigue from task overload. Unlike typical models relying on financial incentives, this context requires alternative strategies to sustain participation. This paper presents a new solution, the Volunteer Task Allocation Engine (VTAE), to address these challenges. This solution is not based on economic incentives, and it has two primary goals. The first one is to improve user experience by limiting the workload and creating a user-centric task allocation solution. The second goal is to create an equal distribution of tasks over the spatial locations to make the solution robust against the possible decrease in participation. Two approaches are used to test the performance of this solution against different conditions: computer simulations and a real-world experiment with real users, which include a qualitative evaluation. The simulations tested system performance in controlled environments, while the real-world experiment assessed the effectiveness and usability of the VTAE with real users. This research highlights the importance of user-centered design in citizen science applications with altruistic participation. The findings demonstrate that the VTAE algorithm ensures equitable task distribution across geographical areas while actively involving users in the decision-making process.
Bayesian Architecture for Predictive Monitoring of Unbalance Faults in a Turbine Rotor–Bearing System
Authors: Bera Banalata , Huang Shyh-Chin , Lin Po Ting , Chiu Yu-Jen , Liang Jin-Wei
Published: December 2024

Unbalance faults are among the common causes of interruptions and unexpected failures in rotary systems. Therefore, monitoring unbalance faults is essential for predictive maintenance. While conventional time-invariant mathematical models can assess the impact of these faults, they often rely on proper assumptions of system factors like bearing stiffness and damping characteristics. In reality, continuous high-speed operation and environmental factors like load variations cause these parameters to change. This work presents a novel architecture for unbalance fault monitoring and prognosis, in which the bearing parameters are treated as variables that change with operating conditions. This enables the development of a more reliable mathematical model for continuous monitoring and prognosis of unbalance faults in rotor systems. This Bayesian inference framework uses Markov Chain Monte Carlo (MCMC) sampling to identify dynamic bearing parameters. Specifically, the Metropolis algorithm is employed to systematically evaluate the range of acceptable parameter values within the framework. A novel dual-MCMC loops explore and assess the parameter space, resulting in more accurate and reliable bearing parameter estimations. These updated parameters improve the demonstrated turbine rotor–bearing system’s unbalance assessment up to 74.48% of the residual error compared to models with fixed parameters. This validates the Bayesian framework for predictive monitoring and maintenance-oriented solutions.
Characterisation at Cryogenic Temperatures of an Attenuator for an Application of Astrophysical Instrumentation with MKIDs
Authors: Portero-Rodríguez Diego , García-Vázquez Hugo , Martínez-Rodríguez José Luis , Hernández Alonso Sergio Elías , Joven Álvarez Enrique , Hoyland Roger John , Díaz García José Javier , Rodríguez Ramos Luis Fernando
Published: December 2024

The use of non-cryogenic certified commercial electronics for cryogenic applications may be attractive due to their cost and availability, but it also carries risks related to reliability, performance and thermal compatibility. The decision to use commercial components that are not certified for cryogenics instead of components specifically designed for such applications must be carefully weighed based on specific project needs and risk tolerances. This work presents the characterisation of an attenuator circuit at cryogenic temperatures used in a microwave kinetic inductance detector (MKID) readout system. In order to characterise the operation of the attenuator at cryogenic temperatures and because the circuit works at frequencies up to 40 GHz, a specific microwave PCB has been designed. The cooling system used consists of a cryostat, all the connectors, cables, a vacuum pump, a compressor, pressure and temperature sensors, a temperature control system and a cold head operating in a closed helium gas cycle according to the Gifford–McMahon principle. The circuit was tested and characterised at temperatures ranging from 296.5 K to 83.6 K.
Group Polarization and Echo Chambers in #GaijinTwitter Community
Authors: Yurtcicek Ozaydin Seval , Lubashevskiy Vasily , Ozaydin Fatih
Published: December 2024

This study explores the phenomena of group polarization and echo chambers within the context of online discussions among immigrants in Japan, also known as gaijins, specifically within the #GaijinTwitter community. By analyzing the key topics discussed by divergent groups of Twitter users and examining their interactions through qualitative and quantitative approaches, we provide evidence of group polarization. Additionally, we investigate how blocking and sharing screenshots of tweets instead of reacting to them in the standard ways contribute to the formation and perpetuation of online echo chambers.
Individuality Affects the Efficiency of Basketball Pre-Game Warm-Up on Players’ Performance
Authors: Papagiannis Grigoris , Karatrantou Konstantina , Batatolis Christos , Ioakimidis Panagiotis , Gerodimos Vassilis
Published: December 2024

Pre-game warm-up is integral to athletes’ preparation before a basketball game. The main objectives of this study were to compare specific performance indicators before and immediately after a basketball pre-game warm-up, and examine the individualized players’ responses. The impact of rest intervals after warm-up (9–23 min) was also examined. A total of 20 male basketball players (age: 21.15 ± 2.2 years; body mass: 82.23 ± 10.78 kg; body height: 184.18 ± 7.9 cm) performed a pre-game warm-up and were assessed in selected indicators such as heart rate (HR), flexibility, running speed, and countermovement jump with arm swing (CMJAS) before, immediately after, 9 min and 23 min after warm-up. Immediately after warm-up, HR increased to all players (mean change: 69.78%), while flexibility (mean change: 20.14%) and CMJAS (mean change: 4.95%) increased to the majority of players (except one and two players, respectively). The individualized results regarding speed were conflicting, showing a decrease or increase. However, 9 and 23 min after warm-up, there was a decrease in HR, speed, and CMJAS (p < 0.5), while flexibility remained stable (p > 0.5) in the total sample, with great change variations among players. In conclusion, it seems that each player’s individuality may affect the warm-up’s efficiency. Thus, it is important to carefully design the pre-game warm-up so that all players will be in the most suitable condition to meet the demands of their competition.
Current and Potential Land Use/Land Cover (LULC) Scenarios in Dry Lands Using a CA-Markov Simulation Model and the Classification and Regression Tree (CART) Method: A Cloud-Based Google Earth Engine (GEE) Approach
Authors: Abdelsamie Elsayed A. , Mustafa Abdel-rahman A. , El-Sorogy Abdelbaset S. , Maswada Hanafey F. , Almadani Sattam A. , Shokr Mohamed S. , El-Desoky Ahmed I. , Meroño de Larriva Jose Emilio
Published: December 2024

Rapid population growth accelerates changes in land use and land cover (LULC), straining natural resource availability. Monitoring LULC changes is essential for managing resources and assessing climate change impacts. This study focused on extracting LULC data from 1993 to 2024 using the classification and regression tree (CART) method on the Google Earth Engine (GEE) platform in Qena Governorate, Egypt. Moreover, the cellular automata (CA) Markov model was used to anticipate the future changes in LULC for the research area in 2040 and 2050. Three multispectral satellite images—Landsat thematic mapper (TM), enhanced thematic mapper (ETM+), and operational land imager (OLI)—were analyzed and verified using the GEE code editor. The CART classifier, integrated into GEE, identified four major LULC categories: urban areas, water bodies, cultivated soils, and bare areas. From 1993 to 2008, urban areas expanded by 57 km2, while bare and cultivated soils decreased by 12.4 km2 and 42.7 km2, respectively. Between 2008 and 2024, water bodies increased by 24.4 km2, urban areas gained 24.2 km2, and cultivated and bare soils declined by 22.2 km2 and 26.4 km2, respectively. The CA-Markov model’s thematic maps highlighted the spatial distribution of forecasted LULC changes for 2040 and 2050. The results indicated that the urban areas, agricultural land, and water bodies will all increase. However, as anticipated, the areas of bare lands shrank during the years under study. These findings provide valuable insights for decision makers, aiding in improved land-use management, strategic planning for land reclamation, and sustainable agricultural production programs.
Reimagining Tradition: A Comparative Study of Artificial Intelligence and Virtual Reality in Sustainable Architecture Education
Authors: Cao Ying , Gao Xuewen , Yin Hanfang , Yu Kexin , Zhou Di
Published: December 2024

Artificial intelligence and virtual reality technologies have significant potential in traditional architectural education. Historically used separately, their educational impacts are not fully understood. To advance sustainable architecture education, this study incorporates language and illustration tools of artificial intelligence, along with immersive painting and simulation capabilities of virtual reality, into the curriculum of Jiangnan traditional architecture. Through a randomized controlled trial, 60 students were divided into AI, VR, and control groups. Based on the establishment of an adaptive course learning assessment system, this study empirically compares the effects of artificial intelligence methods, virtual reality methods, and traditional teaching methods across four dimensions: architectural knowledge, architectural design, architectural computation, and architectural learning. Independent sample t-tests and one-way analysis of variance are used to validate the differences in the effectiveness of these technological applications. Findings reveal that artificial intelligence notably enhances design and learning outcomes, whereas virtual reality shows pronounced effects in bolstering knowledge acquisition and computational tasks. Artificial intelligence proves particularly suited to conceptualization and narrative-based design tasks, while virtual reality aligns closely with model creation and post-design refinement activities. These findings provide new perspectives for hybridizing artificial intelligence and virtual reality in sustainable architecture education, contributing to sustainable outcomes.
The Effect of Soil Tillage Systems on the Soil Microbial and Enzymatic Properties Under Soybean (Glycine max L. Merrill) Cultivation—Implications for Sustainable Soil Management
Authors: Długosz Jacek , Dębska Bożena , Piotrowska-Długosz Anna
Published: December 2024

Reducing soil tillage with the application of catch-crop green mass as a mulch is a conservation practice that is used in agriculture to improve soil ecosystem functioning. Such a cultivation method enhances soil organic matter quantity and quality through the improvement of soil biological activity and nutrient availability, while reducing soil disturbance. Therefore, a three-year field experiment was conducted in the years 2017–2019 to evaluate the effect of three tillage methods (TMs) (conventional, CT; reduced, RT; and strip tillage, ST) on soil microbial and specific enzyme properties (microbial C and N content, the activity of dehydrogenases—DHA, the rate of fluorescein sodium salt hydrolysis—FDAH, CMC-cellulase—Cel and β-glucosidase—Glu) and certain basic soil properties. The study was performed in a field; it was a one-factor experiment that was carried out in a randomized block design. The soil samples were collected from the upper soil layer five times a year: in April (before the sowing of soybean), May, June, August and September (before soybean harvesting). The tillage methods or sampling dates used had no significant effect on the organic carbon and total nitrogen levels. Most of the C-related properties (the content of microbial biomass and the C-cycling enzymatic activity such as Cel and Glu) and microbial activity bioindicators (DHA activity, FDAH rate) revealed significant seasonal changes, whereby each variable was affected in a different order (e.g., the Cel activity was significantly higher in April and September than in other months—22%, while the DHA activity was significantly higher in June and August compared to other months—18%). RT significantly increased the enzymatic activity as compared to CT and ST, and the difference was between 8 and 33% (with a mean of 18%). The exception was the β-glucosidase activity as determined in 2019, which was significantly higher in the case of CT (1.02 mg pNP kg−1 h−1) and ST than in RT (0.705 mg pNP kg−1 h−1). However, the explanation for such phenomenon could not possibly be based on the available data. Our results suggested that the response of the enzyme activities toward the same factor may be due to the inherent variability in enzyme response associated with the spatial variability in soil properties as well as the properties of the enzyme itself and changes in the periodic occurrence of its substrates in the soil. Generally, the reduced tillage combined with plant residues return could be recommended for enhancing soil health and quality by improving its microbial and enzymatic features. The findings above suggest that a reduced tillage system is an important component of soil management in sustainable agriculture.
Air-Assisted Tribo-Electrostatic Separator for Recycling of Shredded Waste Plastics
Authors: Miloua Fethi , Nemmich Said , Zeghloul Thami , Miloudi Mohamed , Medles Karim , Dascalescu Lucian
Published: December 2024

Waste minimization is a major way to achieve sustainable development. Electrostatic separation is already used in the recycling industry for processing certain mixtures of shredded plastics originating from waste electric and electronic equipment. Standard tribo-electrostatic separators use electric forces to deflect the trajectories of triboelectrically charged particles in the electric field generated between two vertical plate electrodes connected to high voltage supplies of opposite polarities. However, the efficiency of this device is often limited by the impacts between the particles and the electrodes, which diminish the recovery and the purity of the end product. An innovative electrostatic separator was specifically designed to mitigate this risk. The innovation lies in using two rotating co-axial vertical cylindrical electrodes and assisting the movement of the particles with downward-oriented air flow to reduce their impact on the electrodes and improve the quality of the recovered products. The aim of this study was to optimize the operation of the patented electrostatic separator by using experimental design methodology to obtain quadratic polynomial models of the recovery and the purity of the products as functions of the high voltage applied to the electrode system and of the air flow through the device. The experiments were conducted with a granular mixture composed of 88% polypropylene (PP) and 12% high-impact polystyrene (HIPS) particles, extracted from the recycling process of waste electrical and electronic equipment, and triboelectrically charged in a fluidized bed device. A voltage of 50 kV combined with an air flow rate of 1700 m3/min maximized the recovery and the purity of PP and HIPS products collected at the outlet of the separator. These results open promising prospects for expanding the use of tribo-electrostatic separation for efficient recycling of granular waste plastics.
Study of Mixtures of 1,3-Propanediol+DBU and DBU+Sulfolane for a New Sustainable Solvent for CO2 Removal
Authors: Schiattarella Valentina , Barbieri Camilla , Moioli Stefania , Pellegrini Laura A. , Filippini Giacomo , de Angelis Alberto Renato , Fiori Gianluca
Published: December 2024

CO2 removal, especially the one applied to reduce the emissions of CO2 to the atmosphere (carbon capture, utilization, and storage), is one of the main research topics nowadays because of its great contribution to the reduction in climate change and to making many industrial processes sustainable. In this regard, alternative solvents to the traditional ones are under study with the aim of employing a more sustainable solvent for the environment, health, and society, in comparison with the traditional amine aqueous solutions that are toxic and corrosive. The CO2-binding organic liquids (CO2-BOLs) are a class of components of interest. In this work, the vapor–liquid equilibrium (VLE) data for two newly selected binary mixtures based on CO2-BOLs, 1,3-Propanediol+DBU and DBU+Sulfolane, have been experimentally determined at the Process Thermodynamics laboratory (PT lab) of Politecnico di Milano to evaluate the suitability of these mixtures for being a solvent for CO2 removal. All the experiments have been carried out by using the Fischer® Labodest® VLLE 602 unit at a constant pressure of 30 kPa. The densities of the mixtures for all the considered compositions have been determined at atmospheric pressure with a density meter (Mettler Toledo Densito Density2Go). No data on the VLE of these mixtures can be found in the literature. This is the first work focusing on mixtures of these components that could be employed as solvents for CO2 removal as alternative solvents to the monoethanolamine (MEA) aqueous solution in the process of chemical absorption. The collected experimental data have then been used for the definition of the thermodynamic model by considering different possible theories (NRTL, Wilson, and UNIQUAC) that could be employed for the representation of the two systems.
Expanding the Horizons of Saccharomyces cerevisiae: Nutrition, Oenology, and Bioethanol Production
Authors: Elhalis Hosam
Published: December 2024

Specialty Saccharomyces cerevisiae strains have emerged as key contributors to innovations across various industries, offering unique functionalities that extend beyond conventional applications. This review explores the diverse roles of specialty S. cerevisiae in nutrition, winemaking, and bioethanol production. In the field of nutrition, yeast biomass serves as a sustainable and nutrient-dense source of proteins, vitamins, and bioactive compounds, presenting potential as a functional food ingredient. S. cerevisiae can bioaccumulate trace elements like selenium, zinc, and chromium, offering health benefits, but challenges in toxicity and biomass recovery must be addressed for safe use in supplements. In winemaking, S. cerevisiae enhances flavor profiles, improves fermentation efficiency, and reduces undesirable compounds, contributing to premium wine quality. The potential of S. cerevisiae in novel applications is vast, including the development of low-alcohol wines, cryotolerant strains for improved fermentation at lower temperatures, and reduced chemical additives, highlighting its versatility in enhancing wine quality and sustainability. Furthermore, specialty S. cerevisiae plays a pivotal role in bioethanol production, with strain selection and further improvement leading to enhanced yield and efficiency, particularly from lignocellulosic biomass. By examining the latest innovations in each of these areas, this review highlights the versatility and potential of specialty S. cerevisiae in advancing sustainable development and enhancing product quality across sectors.
Measuring and Forecasting the Development Concept of the “Green” Macrosystem Using Data Analysis Technologies
Authors: Shinkevich Aleksei I. , Galimulina Farida F. , Barsegyan Naira V.
Published: December 2024

A research framework is formed by the semantics of the “green” macrosystem, supported by a methodological approach, data analysis, and forecasting, with a focus on the dynamics of transition to a qualitatively new state. The purpose of the work is to develop conceptual provisions and methodological tools for assessing the implementation of the concept of a “green” macrosystem. Applying methods of system analysis, content analysis, formalization, statistical analysis (technologies of knowledge discovery in databases and time series analysis), and discriminant analysis contributed to achieving the goal. As a result of the research, the categorical apparatus of a “green” economy was clarified by outlining narrow and broad approaches to defining the “green” macrosystem; the author’s method of assessing the implementation of the concept of the “green” macrosystem was modified by expanding the list of factors of greening the economic system, transforming the condition of the “green” corridor to calculate the developed dynamic coefficient of transition to the concept of the “green” macrosystem (DCGM), and adapting the method to the macrosystem level; the regularities of a transition to the concept of a “green” macrosystem were revealed. The novelty of the study lies in the proposal of an integral DCGM indicator, which avoids the problems of normalization, weighting, and loss of relevant data, incorporates the determinants of the “green” economy (natural resources and pollution), and relies on available data. The formulated provisions develop the theoretical basis on which to transform the macrosystem to the “green” concept and can be taken into account in the implementation’s framework of strategic planning documents for the greening of production and economic systems.
The Impact of Top Management Team Heterogeneity on Environmental, Social, and Governance Performance and Corporate Green Innovation: Evidence from Chinese Manufacturing Companies
Authors: Xi Lei , Guo Ziyi
Published: December 2024

In the context of global climate change and resource scarcity, corporate environmental, social, and governance (ESG) performance, as well as corporate green innovation, have emerged as pivotal drivers for fostering sustainable development. The heterogeneity of the top management team (TMT) significantly influences the direction and effectiveness of both ESG performance and corporate green innovation. Drawing on upper echelon theory, information decision-making theory, and social categorization theory, this paper conducts an empirical study using a sample of 314 manufacturing enterprises and employs multiple linear regression analysis to uncover the impact of TMT heterogeneity on corporate green innovation and the mediating role of ESG performance. The findings from this research suggest that TMT heterogeneity exerts a notable positive influence on green innovation (including green technological innovation and green product innovation), and that ESG performance plays a partial mediating role between TMT heterogeneity and green innovation. This research enriches the theoretical foundation of corporate green innovation from the perspective of TMT heterogeneity and offers pertinent suggestions for enterprises to advance their green innovation development.
Evolution Characteristics of Water Use Efficiency and the Impact of Its Driving Factors on the Yunnan–Guizhou Plateau in China
Authors: Wang Pei , Zhang Xuepeng , Liu Yang , Nie Wei
Published: December 2024

Water use efficiency (WUE) of ecosystems plays a crucial role in balancing carbon storage and water consumption. The Yunnan–Guizhou Plateau, a karst landscape region with relatively fragile ecosystems in China, requires a better understanding of the evolution of WUE and the factors driving it for the region’s ecological sustainability. This study employs Theil–Sen slope estimation and Mann–Kendall significance analysis to investigate the temporal trends and spatial patterns of WUE in the study area. Additionally, a machine learning model, XGBoost, is used to establish driving relationships, and the SHAP model is applied to interpret the importance of the driving factors and their specific relationship with WUE. The results show that (1) WUE exhibits an increasing trend, with a slope of 0.002, indicating improved water absorption and utilization capacity of vegetation in the region. (2) The spatial distribution of WUE follows a “high–low–high” pattern from southwest to northeast, with 6.68% of the area showing a significant increase, 50.80% showing a weak increase, 4.60% showing a significant decrease, and 37.92% showing a weak decrease. (3) The importance of the driving factors is ranked as follows: normalized difference vegetation index (NDVI), maximum temperature (TMAX), shortwave radiation (SRAD), Palmer drought severity index (PDSI), vapor pressure deficit (VPD), and precipitation (PRE). The NDVI has a linear positive relationship with WUE; SRAD has a decreasing effect on WUE, with this effect weakening at higher values; and TMAX, PRE, the PDSI, and VPD show a non-monotonic relationship with WUE, increasing and then decreasing. The findings of this study are significant for ecological civilization construction and sustainable development in the region.
Mapping Acid–Base Sites on Anatase Titania (100) and (101) Surfaces by Density Functional Theory: The Link Between Lewis Acidity and the Surface Ability to Flex
Authors: Ignatchenko Alexey V. , Denman Paige E.
Published: December 2024

The acidity of anatase titania before and after KOH doping was probed by pyridine adsorption in a pulse microreactor and modeled by DFT optimization of the geometry of CO and pyridine adsorption on a periodic slab of (101) and (100) surfaces using a GGA/PBE functional and verified by an example of a single-point calculation of the optimized geometry using an HSE-06 hybrid functional. The anatase (101) surface was slightly more acidic compared to the (100) surface. Both experimental and computational methods show that the acidity of anatase surfaces decreased after KOH doping and increased after the dissociative adsorption of water. Higher acidity of Ti metal centers was indicated by the shortening of the Ti-N, Ti-C, and C-O bond lengths, increasing the IR frequency of CO and pyridine ring vibrations and energy of adsorption. The DFT calculated energy of pyridine adsorption was analyzed in terms of binding energy and the energy of lattice distortion. The latter was used to construct Hammett plots for the adsorption of 4-substituted pyridines with electron-donating and -withdrawing substituents. The Hammett rho constant was obtained and used to characterize the acidity of various metal centers of −1.51 vs. −1.46 on pristine (101) and (100) surfaces, which were lowered to −1.07 and −1.19 values on KOH-doped (101) and (100) surfaces, respectively. The mechanism of lowering surface acidity via KOH doping proceeds through the stabilization of the atomic structure of Lewis acid centers. When an alkaline metal cation binds to several lattice oxygen atoms, the surface structure becomes more rigid. The ability of Ti atoms to move toward the adsorbate is restricted. Consequently, the lattice distortion energy and binding energy are decreased. In contrast, higher flexibility of the outermost layer of Ti atoms as a result of electron density redistribution, for example, in the presence of water on the surface, allows them to move farther outward, make shorter contacts with the adsorbate, and attain higher energies of binding and lattice distortion.
Conditional Skipping Mamba Network for Pan-Sharpening
Authors: Tang Yunxuan , Li Huaguang , Liu Peng , Li Tong
Published: December 2024

Pan-sharpening aims to generate high-resolution multispectral (HRMS) images by combining high-resolution panchromatic (PAN) images with low-resolution multispectral (LRMS) data, while maintaining the symmetry of spatial and spectral characteristics. Traditional convolutional neural networks (CNNs) struggle with global dependency modeling due to local receptive fields, and Transformer-based models are computationally expensive. Recent Mamba models offer linear complexity and effective global modeling. However, existing Mamba-based methods lack sensitivity to local feature variations, leading to suboptimal fine-detail preservation. To address this, we propose a Conditional Skipping Mamba Network (CSMN), which enhances global-local feature fusion symmetrically through two modules: (1) the Adaptive Mamba Module (AMM), which improves global perception using adaptive spatial-frequency integration; and (2) the Cross-domain Mamba Module (CDMM), optimizing cross-domain spectral-spatial representation. Experimental results on the IKONOS and WorldView-2 datasets demonstrate that CSMN surpasses existing state-of-the-art methods in achieving superior spectral consistency and preserving spatial details, with performance that is more symmetric in fine-detail preservation.
Condition for the Construction of a Hilbert-Type Integral Inequality Involving Upper Limit Functions
Authors: Hong Yong , Zhang Lijuan , Xiao Huasong
Published: December 2024

Hilbert-type integral inequalities, which feature a symmetric structure, are a significant class of inequalities with broad applications in the study of operator theory. Hilbert-type integral inequalities involving variable upper limit integral functions are a generalized form of the classical Hilbert-type integral inequalities. In this paper, we employ the construction theorem of homogeneous kernel Hilbert-type integral inequalities and the properties of the Gamma function to discuss the conditions for constructing a Hilbert-type integral inequality involving an upper limit integral function and the best constant factor. We derive the necessary and sufficient conditions for constructing this inequality and a formula for calculating the best constant factor, thereby improving the existing results. Finally, as an application, we consider some special cases of parameters.
A Review of Fused Filament Fabrication of Metal Parts (Metal FFF): Current Developments and Future Challenges
Authors: Jacob Johnson , Pejak Simunec Dejana , Kandjani Ahmad E. Z. , Trinchi Adrian , Sola Antonella
Published: December 2024

Fused filament fabrication (FFF) is the most widespread and versatile material extrusion (MEX) technique. Although powder-based systems have dominated the metal 3D printing landscape in the past, FFF’s popularity for producing metal parts (“metal FFF”) is growing. Metal FFF starts from a polymer–metal composite feedstock and proceeds through three primary stages, namely shaping (i.e., printing), debinding, and sintering. As critically discussed in the present review, the final quality of metal FFF parts is influenced by the characteristics of the composite feedstock, such as the metal loading, polymer backbone, and presence of additives, as well as by the processing conditions. The literature shows that a diverse array of metals, including steel, copper, titanium, aluminium, nickel, and their alloys, can be successfully used in metal FFF. However, the formulation of appropriate polymer binders represents a hurdle to the adoption of new material systems. Meanwhile, intricate geometries are difficult to fabricate due to FFF-related surface roughness and sintering-induced shrinkage. Nonetheless, the comparison of metal FFF with other common metal AM techniques conducted herein suggests that metal FFF represents a convenient option, especially for prototyping and small-scale production. Whilst providing insights into the functioning mechanisms of metal FFF, the present review offers valuable recommendations, facilitating the broader uptake of metal FFF across various industries.
Metagenomic Analysis Reveals the Effects of Microplastics on Antibiotic Resistance Genes in Sludge Anaerobic Digestion
Authors: Li Zhonghong , Yuan Donghai
Published: December 2024

Sewage sludge is recognized as both a source and a reservoir for antibiotic resistance genes (ARGs). Within an anaerobic digestion (AD) system, the presence of microplastics (MPs) has been observed to potentially facilitate the proliferation of these ARGs. Understanding the influence of MPs on microbial behavior and horizontal gene transfer (HGT) within the AD system is crucial for effectively managing the dissemination of ARGs in the environment. This study utilized metagenomic approaches to analyze the dynamics of various types of ARGs and potential microbial mechanisms under exposure to MPs during the AD process. The findings indicated that MPs in the AD process can enhance the proliferation of ARGs, with the extent of this enhancement increasing with the dosage of MPs: polyethylene (PE), polyethylene terephthalate (PET), and polylactic acid (PLA) MPs increased the abundance of ARGs in the anaerobic digestion system by up to 29.90%, 18.64%, and 14.15%, respectively. Additionally, the presence of MPs increased the relative abundance of mobile genetic elements (MGEs) during the AD process. Network correlation analysis further revealed that plasmids represent the predominant category of MGEs involved in the HGT of ARGs. Propionibacterium and Alicycliphilus were identified as the primary potential hosts for these ARGs. The results of gene function annotation indicated that exposure to MPs led to an increased the relative abundance of genes related to the production of reactive oxygen species (ROS), alterations in membrane permeability, ATP synthesis, and the secretion of extracellular polymeric substances (EPS). These genes play crucial roles in influencing the HGT of ARGs.
Spatial Distribution of Ultracold Neutron Probability Density in the Gravitational Field of the Earth Above a Mirror
Authors: Altarawneh Derar , Höllwieser Roman , Wellenzohn Markus
Published: December 2024

We present a theoretical analysis of the experimental data reported by Ichikawa et al. on the spatial distribution of ultracold neutrons in the Earth’s gravitational field above a mirror. The data involve a projection onto a pixelated detector via scattering by a cylindrical mirror. Our study includes a calculation of the theoretical spatial distribution of the probability density associated with the quantum gravitational states of ultracold neutrons. Furthermore, we analyze this spatial distribution using the Wigner function framework. Based on our analysis, we cannot confirm that the experimental data reported by Ichikawa et al. correspond to the spatial distribution of quantum gravitational states of ultracold neutrons.
Immune Response to SARS-CoV-2 XBB.1.5 and JN.1 Variants Following XBB.1.5 Booster Vaccination in Liver Transplant Recipients
Authors: von der Schulenburg Philippa , Behrens Georg M. N. , Hoffmann Markus , Linke Alexandra , Nehlmeier Inga , Kempf Amy Madeleine , Stankov Metodi , Lütgehetmann Marc , Jahnke-Triankowski Jacqueline , Addo Marylyn M. , Fischer Lutz , Lohse Ansgar W. , Pöhlmann Stefan , Schulze zur Wiesch Julian , Sterneck Martina
Published: December 2024

Background/Objectives: The efficacy of monovalent BNT162b2 Omicron XBB.1.5 booster vaccination in liver transplant recipients (LTRs) has yet to be described, particularly regarding the immune response to emerging variants like JN.1. Methods: This study evaluated humoral and cellular immune responses in 34 liver transplant recipients (LTRs) with varying SARS-CoV-2 immune histories before and after receiving a BNT162b2 Omicron XBB.1.5 booster vaccination. The assessment involved variant-specific serology, pseudovirus neutralization tests, and Interferon-γ release assays. Results: Participants had a median of four prior vaccinations, with 91.2% having a history of infection. Post-vaccination, significant increases in both Wuhan anti-S and Omicron-specific IgG antibodies and improved neutralization of B.1, XBB.1.5, and JN.1 pseudovirus particles were observed. Also, T-cell responses significantly increased post-vaccination. However, 17.6% of LTRs had no neutralizing antibodies against XBB.1.5 and JN.1, while 100% of healthy controls did. Shortly after vaccination, 18% of patients developed mild COVID-19. These LTRs had particularly low immune responses at baseline. Conclusions: The monovalent XBB.1.5 booster improved overall SARS-CoV-2-specific immunity. However, some LTRs still showed low or undetectable immune responses, indicating that ongoing monitoring and further booster doses are necessary in this high-risk group.
Respiratory Virus-Specific and Time-Dependent Interference of Adenovirus Type 2, SARS-CoV-2 and Influenza Virus H1N1pdm09 During Viral Dual Co-Infection and Superinfection In Vitro
Authors: Stincarelli Maria Alfreda , Arvia Rosaria , Guidotti Bernardo , Giannecchini Simone
Published: December 2024

Background. Understanding the interference patterns of respiratory viruses could be important for shedding light on potential strategies to combat these human infectious agents. Objective. To investigate the possible interactions between adenovirus type 2 (AdV2), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A/H1N1 pandemic (H1N1pdm09) using the A549 cell line. Methods. Single infections, co-infections, and superinfections (at 3 and 24 h after the first virus infection) were performed by varying the multiplicity of infection (MOI). Virus replication kinetics and the mRNA expression of IFN-α, IL-1α and IL-6 were assessed by real-time qPCR. Results. Co-infection experiments showed different growth dynamics, depending on the presence of the specific virus and time. AdV2 replication remained stable or possibly enhanced in the presence of co-infection with each of the two H1N1pdm09 and SARS-CoV-2 viruses used. In contrast, SARS-CoV-2 replication was facilitated by H1N1pdm09 but hindered by AdV2, indicating possible different interactions. Finally, H1N1pdm09 replication exhibited variably effectiveness in the presence of AdV2 and SARS-CoV-2. Superinfection experiments showed that the replication of all viruses was affected by time and MOI. The mRNA expression of IFN-α, IL-1α and IL-6 showed divergent results depending on the virus used and the time of infection. Conclusions. Further investigation of co-infection or superinfection may be helpful in understanding the potential relationship involved in the outcome of viral respiratory infection in the human population.
Induced Pluripotent Stem Cells in Birds: Opportunities and Challenges for Science and Agriculture
Authors: Zahoor Nousheen , Arif Areej , Shuaib Muhammad , Jin Kai , Li Bichun , Li Zeyu , Pei Xiaomeng , Zhu Xilin , Zuo Qisheng , Niu Yingjie , Song Jiuzhou , Chen Guohong
Published: December 2024

The only cells in an organism that could do any other sort of cell until 2006 (except sperm or egg) were known as embryonic stem cells, ESC [...]
Enhancing Efficiency and Selectivity of Nitrate Reduction Toward Nitrogen Gas in an Open-Air UV/Fe(III)–Oxalate System
Authors: Chen Jialin , Xie Yi , Xia Jun , Zhang Xiaolin , Chen Dong
Published: December 2024

An advanced photochemical reduction system involving the UV/Fe(III)–oxalate system was developed for the reduction of nitrate (NO3−) to harmless N-gaseous species, primarily nitrogen (N2), by carbon dioxide radical (·CO2−) generated in the presence of dissolved oxygen (DO). Electron paramagnetic resonance (EPR) analyses confirmed the presence of both ·CO2− and ·OH radicals. Systematic investigations were conducted on various operational parameters, such as the initial Fe(III) concentration, oxalate concentration, and pH levels, to assess their impacts on the efficiency and products of NO3− reduction. Notably, solution pH played a significant role in influencing the NO3− reduction efficiency and the final products. At pH 2, approximately 75% of NO3− was converted into N2 with an 80% selectivity. In the pH range of 3 to 5, a remarkable NO3− removal rate of about 90% was achieved. Furthermore, higher concentrations of Fe(III) (2 mM) and oxalate (10 mM) were found to enhance NO3− removal to 91.95% and 88.71%, respectively. The presence of DO increased the oxidative potential in the reaction system, subsequently enhancing the selectivity conversion of NO3− to N2. In summary, the UV/Fe(III)–oxalate system exhibits significant potential for effective removal of NO3− while achieving high selectivity for the production of N2 in water remediation applications.
A CiteSpace-Based Analysis of the Impact of Sea-Level Rise and Tropical Cyclones on Mangroves in the Context of Climate Change
Authors: Liu Siyu , Zhu Yan , Xiao He , Ye Jingliang , Yang Tingzhi , Ma Jin , Liu Dazhao
Published: December 2024

This study aims to analyze the impact of sea-level rise and tropical cyclones on mangroves in the context of global climate change from 1993 to 2023, and to explore the development status, co-operative relationships and future trends in this research field. In order to analyze future research directions for mangroves in the context of climate, this study also provides an important basis and reference for the development of research related to the mitigation of natural disasters. Using CNKI and the Web of Science as data sources, this study employs the bibliometric tool CiteSpace 6.3 R1 to conduct a quantitative and visual analysis of the research field. The research findings indicate the following: (1) The volume of publications in this field has been increasing year by year; especially since 2010, the rate of increase has accelerated, indicating an increased academic interest in this area. (2) From the authorship maps of the two data sources, it can be observed that the collaboration network is dense, indicating the existence of co-operative relationships among researchers. (3) From the analysis of the keywords, it is evident that, with the rise of artificial intelligence, the focus of keywords has gradually shifted from traditional mangrove mechanism research and ecosystem studies to research on mangroves that integrates big data, artificial intelligence, and high-resolution remote sensing data. (4) As time has progressed, areas of research interest have been shifting from the study of disturbances and damage to mangrove vegetation to the study of mangrove resilience and vulnerability in the context of natural disasters, their carbon sequestration capabilities, and their protective functions against wind and waves. The use of remote sensing technology for the monitoring and conservation of mangroves has emerged as a key area of focus for future research. In future research, there will be a focus on the adaptive capacity of mangroves to varying degrees of sea-level rise and the increasing frequency of tropical cyclones, as well as on what measures can be taken to enhance the resilience of mangrove ecosystems. Quantitative and visual analysis of the development trends in this field can provide a reference for the construction of a disaster monitoring platform for mangroves affected by sea-level rise and tropical cyclones, and can aid the development of research aimed at mitigating the impacts of natural disasters. Furthermore, the integration of remote sensing technology and ecological models can facilitate more detailed research, offering more effective tools and strategies for the conservation and management of mangroves. This approach also provides a reference point for developing a monitoring platform for mangrove disasters associated with sea-level rise and the impact of tropical cyclones.