bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Machine Learning and Multi-Agent Simulation on Mining and Visualizing Tourism Tweets as Not Summarized but Instantiated Knowledge
Authors: Hattori Shun , Fujidai Yuto , Sunayama Wataru , Takahara Madoka
Published: August 2024

Various technologies with AI (Artificial Intelligence), DS (Data Science), and/or IoT (Internet of Things) have been starting to be pervasive in e-tourism (i.e., smart tourism). However, most of them for a target (e.g., what to do in such a tourism spot as Hikone Castle) utilize their “typical/major signals” (e.g., taking a photo) as summarized knowledge based on “The Principle of Majority”, and tend to filter out not only their noises but also their valuable “peculiar/minor signals” (e.g., view Sawayama Castle) as instantiated knowledge. Therefore, as a challenge to salvage not only “typical signals” but also “peculiar signals” without noises for e-tourism, this paper compares various methods of ML (Machine Learning) to text-classify a tweet as being a “tourism tweet” or not, to precisely mine tourism tweets as not summarized but instantiated knowledge. In addition, this paper proposes a MAS (Multi-Agent Simulation), powered with artisoc, for visualizing “tourism tweets”, including not only “typical signals” but also “peculiar signals”, whose number can be enormous, as not summarized but instantiated knowledge, i.e., instances of them without any summarization, and validates the effects of the proposed MAS by conducting some experiments with subjects.
A UAV Aerial Image Target Detection Algorithm Based on YOLOv7 Improved Model
Authors: Qin Jie , Yu Weihua , Feng Xiaoxi , Meng Zuqiang , Tan Chaohong
Published: August 2024

To address the challenges of multi-scale objects, dense distributions, occlusions, and numerous small targets in UAV image detection, we present CMS-YOLOv7, a real-time target detection method based on an enhanced YOLOv7 model. Firstly, the detection layer P2 for small targets was added to YOLOv7 to enhance the detection ability of small and medium-sized targets, and the deep detection head P5 was taken out to mitigate the influence of excessive downsampling on small target images. The anchor frame was calculated by the K-means++ method. Using the concept of Inner-IoU, the Inner-MPDIoU loss function was constructed to control the range of the auxiliary border and improve detection performance. Furthermore, the CARAFE module was introduced to replace traditional upsampling methods, offering improved integration of semantic information during the image upsampling process and enhancing feature mapping accuracy. Simultaneously, during the feature extraction stage, a non-strided convolutional SPD-Conv module was constructed using space-to-depth techniques. This module replaced certain convolutional operations to minimize the loss of fine-grained information and improve the model’s ability to extract features from small targets. Experiments on the UAV aerial photo dataset VisDrone2019 demonstrated that compared with the baseline YOLOv7 object detection algorithm, CMS-YOLOv7 achieved an improvement of 3.5% mAP@0.5, 3.0% mAP@0.5:0.95, and the number of parameters decreased by 18.54 M. The ability of small target detection was significantly enhanced.
Explainable Neural Tensor Factorization for Commercial Alley Revenues Prediction
Authors: Kim Minkyu , Lee Suan , Kim Jinho
Published: August 2024

Many individuals aspire to start their own businesses and achieve financial success. Before launching a business, they must decide on a location and the type of service to offer. This decision requires collecting and analyzing various characteristics of potential locations and services, such as average revenues and foot traffic. However, this process is challenging because it demands expert knowledge in data collection and analysis. To address this issue, we propose Neural Tensor Factorization (NeuralTF) and Explainable Neural Tensor Factorization (XNeuralTF). These methods automatically analyze these characteristics and predict revenues. NeuralTF integrates Tensor Factorization (TF) with Multi-Layer Perceptron (MLP). This integration allows it to handle multi-dimensional tensors effectively. It also learns both explicit and implicit higher-order feature interactions, leading to superior predictive performance. XNeuralTF extends NeuralTF by providing explainable recommendations for three-dimensional tensors. Additionally, we introduce two novel metrics to evaluate the explainability of recommendation models. We conducted extensive experiments to assess both predictive performance and explainability. Our results show that XNeuralTF achieves comparable or superior performance to state-of-the-art methods, while also offering the highest level of explainability.
Determination of Site Suitability for a Sanitary Landfill Using GIS and Boolean Logic: The Case of the Regional Unit of Chalkidiki, Northern Greece
Authors: Parastatidou Eleni , Voudouris Konstantinos , Kazakis Nerantzis
Published: August 2024

This study deals with the determination of sites suitable for landfill in the Prefecture of Chalkidiki, North Greece, using Boolean logic and Geographic Information Systems (GIS). Landfill siting is an arduous process as it combines environmental, social, and technical factors. Solid waste management is an urgent requirement in tourist sites worldwide. The Prefecture of Chalkidiki is considered a tourist area where volumes of generated waste increase in the summer. The Boolean logic approach was used in the study area to exclude areas not suitable for the establishment of a landfill site and to select areas that meet all the criteria. Nine criteria were selected to create the final map showing areas with the highest suitability for solid waste disposal. According to the Boolean logic method, suitable areas were given a value of one (1), while unsuitable areas were given a value of zero (0). According to the final thematic map of proposed sites, 12.7% of the study area is suitable for landfill construction. The suitable areas identified include pre-existing landfill sites, thus suggesting that the applied method has a high degree of reliability.
The Effectiveness of Waste Tire Pyrolysis Oils (WTPOs) as Rejuvenating Agents for Asphalt Materials
Authors: El-Ashwah Ahmed S. , Abdelrahman Magdy
Published: August 2024

The continuous increase in solid waste materials, such as waste tires, underscores the critical importance of recycling them to mitigate environmental impact and promote sustainable resource management. This research study evaluated the effectiveness of utilizing waste tire pyrolysis oils (WTPOs) as recycling agents for asphalt materials. The chemical composition and thermal behavior of WTPO were analyzed using Fourier transform infrared (FT-IR) spectroscopy and thermogravimetric analysis (TGA). Mechanically, the prepared WTPO binders were assessed by measuring dynamic viscosity and changes in high- and intermediate-temperature performance grades. Additionally, the cracking susceptibility of the binders was evaluated using the Glover-Rowe (G-R) parameter. The findings indicated that WTPOs might contain water and light aromatics in varying percentages, depending on the pyrolysis process. Incorporating WTPOs enhanced the workability of asphalt mixtures and ensured a high degree of blending between recycled/aged asphalt and raw binder. A 12% WTPO dosage was identified as the most effective for enhancing fatigue and low-temperature cracking resistance, facilitating improved interactions between the virgin binder and recycled asphalt materials. Finally, utilizing WTPOs as rejuvenating agents in pavement construction supports sustainable practices by recycling waste materials and significantly improving the performance and durability of asphalt mixtures.
Alien Species Introduction and Demographic Changes Contributed to the Population Genetic Structure of the Nut-Yielding Conifer Torreya grandis (Taxaceae)
Authors: Tan Yuming , Ou Qian , Huang Xin , Wang Yujin , Kou Yixuan
Published: August 2024

Understanding population genetic structure and its possible causal factors is critical for utilizing genetic resources and genetic breeding of economically important plants. Although Torreya grandis is an important conifer producing nuts in China, little is known about its population structure, let alone the causal factors that shaped its genetic variation pattern and population structure. In this work, we intended to characterize the genetic variation pattern and population structure of the nut-yielding conifer T. grandis throughout its whole geographical distribution and further explore the potentially causal factors for the population structure using multiple approaches. A moderate level of genetic diversity and a novel population structure were revealed in T. grandis based on eleven robust EST-SSR loci and three chloroplast fragments. Alien genetic composition derived from the closely related species T. nucifera endemic to Japan was detected in the Kuaiji Mountain area, where the seed quality of T. grandis is considered the best in China. Demography history and niche modeling were inferred and performed, and the contribution of geographic isolation to its population structure was compared with that of environmental isolation. Significant demographic changes occurred, including a dramatic population contraction during the Quaternary, and population divergence was significantly correlated with geographic distance. These results suggested that early breeding activities and demographic changes significantly contributed to the population structure of T. grandis. In turn, the population structure was potentially associated with the excellent variants and adaptation of cultivars of T. grandis. The findings provide important information for utilizing genetic resources and genetic breeding of T. grandis in the future.
Improving Urban Forest Expansion Detection with LandTrendr and Machine Learning
Authors: Liu Zhe , Zhang Yaru , Zheng Xi
Published: August 2024

Annual urban forest expansion dynamics are crucial for assessing the benefits and potential issues associated with vegetation accumulation over time. LandTrendr (Landsat-Based Detection of Trends in Disturbance and Recovery) can efficiently detect the dynamics of interannual land cover change, but it has difficulty distinguishing urban forest expansion from urban surface rapid conversions, as changes are usually filtered by magnitude-of-change thresholds. To accurately detect annual urban forest expansion dynamics, we developed an improved method using random forest-supervised classification to filter urban forests. We further enhanced the performance of the improved method by incorporating trend features between segments. Additionally, we tested two threshold-based filtering baseline methods. These methods were tested with various spectral and parameter combinations in Beijing’s Central District and the 1st Greenbelt from 1994 to 2022. The improved method with trend features achieved the highest average accuracy of 89.35%, representing a 25% improvement over baseline methods. Post-change trend features aided in accurate identification, while quantitative features rather than extremum features were more important in filtering. The improved method with trend features tested in Beijing’s 2nd Greenbelt also showed an accuracy of 88.27%, confirming its stability. SWIR2 and a higher maximum segment number are efficient for filtering by providing the most detailed dynamics. Accurate annual expansion dynamic mapping offers insights into change rates and precise expansion years, providing a new perspective for urban forest research and management.
Factors Influencing the Change of Phyllosphere Microbial Community of Three Populus spp. in the Same Habitat
Authors: Yin Xin , Zhang Weixi , Li Dan , Wang Ran , Cong Xinyao , Pang Zhongyi , Peng Yanhui , Ge Yang , Zhu Wenxu , Ding Changjun
Published: August 2024

Plant leaves harbor a rich diversity of bacteria and fungi that, through their interactions with host plants, assume an influential role in plant physiological and metabolic processes. The unique phyllosphere environment of different plant species may shape and select distinct phyllosphere microbial communities. While most academic research has focused on the phyllosphere microorganisms within the same plant variety, there is relatively limited research on the phyllosphere microbial communities between different varieties. Populus L. is a typical tree species in temperate monsoon climates, widely distributed in northern China, and it constitutes a crucial component of China’s forestry resources. For the purpose of this study, we investigated the community structure and diversity of phyllosphere fungi and bacteria in different poplar varieties under identical growth conditions to elucidate the main factors contributing to differences in phyllosphere microbial communities among these varieties. Our findings revealed variations in nitrogen, phosphorus, starch, and soluble sugar contents among the three poplar species studied. Additionally, there were considerable disparities in both abundance and α diversity index of phyllosphere fungal and bacterial communities among these species. At the phylum level, Ascomycota and Basidiomycota have been identified as the dominant fungal communities; while Proteobacteria and Actinomycetes were dominant bacterial communities. The correlation analysis pointed out that chemical traits in the leaves, in particular the total phosphorus and the quantity of soluble sugar, had a significant correlation with the structure and diversity of the microbial community residing in the phyllosphere. Overall, our results demonstrate that even under identical site conditions, each poplar species harbors its own unique phyllosphere microbial community composition as well as distinct leaf characteristics—highlighting host plant diversity as a crucial factor driving differences in phyllosphere microbial composition.
Monitoring of Flash Drought on the Loess Plateau and Its Impact on Vegetation Ecosystems
Authors: Jiang Yanmin , Shi Haijing , Wen Zhongming , Yang Xihua , Wu Youfu , Li Li , Ma Yuxin , Dymond John R. , Guo Minghang , Shui Junfeng , Hu Hong
Published: August 2024

Flash drought (FD) has attracted much attention due to its severe stress on vegetation ecosystems. Yet to date, the impacts of FD on vegetation ecosystems in different regions have not been fully evaluated and explored, especially for ecologically fragile areas. In this study, we identified the FD events in the Loess Plateau from 2000 to 2023 based on the attenuation rate in soil moisture percentile over time. The evolution process of FD, the driving roles of meteorological conditions and the responses of different vegetation types to FD were explored by vegetation indicators such as solar-induced chlorophyll fluorescence (SIF), SIFyield, SIF-RCI, etc. The results showed that FD events were predominantly concentrated in wetter areas with dense vegetation, with the highest frequency being 29. Meteorological factors contributed differently to the occurrence and development of FD. The responses of vegetation to FD were not only related to vegetation types (cropland was more sensitive to FD than forest and grassland) but were also significantly influenced by background climate. The SIFyield anomaly of vegetation was more sensitive than SIF anomaly and SIF-RCI. The results advance our understanding of the formation mechanisms of FD and facilitate the exploration of vegetative photosynthetic responses to FD.
Heat Mitigation Benefits of Street Tree Species during Transition Seasons in Hot and Humid Areas: A Case Study in Guangzhou
Authors: Zheng Senlin , He Caiwei , Xu Haodong , Guldmann Jean-Michel , Liu Xiao
Published: August 2024

The potential microclimatic effects of street trees are influenced by their ecological characteristics, planting patterns, and street orientations, especially in subtropical hot and humid areas. To investigate these effects, four typical street tree species in Guangzhou were selected for study during the transition seasons: Khaya senegalensis, Terminalia neotaliala, Ficus microcarpa, and Mangifera indica. Air temperature (AT), relative humidity (RH), solar radiation (SR), surface temperature (ST), wind speed (WS), and the leaf area index (LAI) were monitored. The cooling effects of these four species and the resulting improvements in human thermal comfort (HTC) were assessed. The influences of tree planting patterns and street orientations on cooling benefits were systematically analyzed. The results indicate that, during transition seasons, the four street trees, on average, can block 96.68% of SR, reduce AT by 1.45 °C and ST by 10.25 °C, increase RH by 5.26%, and lower the physiologically equivalent temperature (PET) by 8.34 °C. Terminalia neotaliala, reducing AT and PET by 1.76 °C and 12.4 °C, respectively, offers the greatest potential for microclimate improvement. Among the four tree species, the variations in ST (ΔST) and PET (ΔPET) were minimal, at only 0.76 °C and 0.25 °C, respectively. The average differences in AT and PET between inter-tree and under-tree environments were 0.06 °C and 0.98 °C, respectively. The AT reduction rate was 1.7 times higher in the double-row planting pattern compared to the single-row planting pattern. Street trees planted in the northwest–southeast (NW-SE) orientation exhibited a 16.96% lower WS reduction than those in other orientations. The northeast–southwest (NE-SW) orientation showed the least potential to enhance human thermal comfort. Compared to NE-SW, the northwest–southeast (NW-SE) orientation achieved twice the rate of AT reduction, while the north–south (N-S) orientation improved it by 1.3 times. This data analysis aids in assessing the impact of green infrastructure on urban climates and demonstrates the year-round microclimatic benefits of street trees.
Yogurt Enriched with Chia Seeds: Physicochemical, Microbiological, and Sensory Changes during Storage
Authors: Nakov Gjore , Ninova-Nikolova Nadya , Ivanova Nastia , Raykova Violeta , Trajkovska Biljana , Čolić Mirela Lučan , Lukinac Jasmina , Jukić Marko
Published: August 2024

This study investigates the physicochemical, microbiological, and sensory properties of yogurt fortified with honey and chia seeds at concentrations of 5% and 10% (w/w) over a 21-day storage period at 4 ± 1 °C. The addition of chia seeds resulted in initial pH increases, with 5% and 10% chia seeds having pH values of 4.22 ± 0.02 and 4.31 ± 0.01, respectively, compared to 4.20 ± 0.01 for the control yogurt. During storage, the pH decreased by 0.17 units for the control yogurt and by 0.08 and 0.13 units for 5% and 10% chia seeds, respectively. The titratable acidity (TA) increased significantly, by 9.1% for the control yogurt and by 22.9% and 29.6% for the 5% and 10% yogurt, respectively. The protein content increased from 3.22 ± 0.03 g/100 g in the control sample to 3.92 ± 0.08 g/100 g and 4.59 ± 0.00 g/100 g for 5% and 10% chia seeds, respectively, without any significant changes during storage. The number of lactic acid bacteria (LAB) was highest in the control sample (9.005 ± 0.007 log CFU/g) and lowest in the 10% yogurt with chia seeds (8.495 ± 0.007 log CFU/g), with all samples remaining free of harmful microorganisms. The sensory evaluation showed that yogurt with 5% chia seeds received the highest overall acceptability scores, while yogurt with 10% chia seeds had poorer scores for taste and texture. Overall, fortification of yogurt with 5% chia seeds improves its nutritional value and sensory properties without compromising product safety or microbiological quality.
Fire Resistance in Screwed and Hollow Core Wooden Elements Filled with Insulating Material
Authors: Osório Miguel , Fonseca Elza M. M. , Pereira Domingos
Published: August 2024

This study looks at wall partition panels with hollow core wood elements and gypsum board as protection in fire conditions. In addition to our previous research, this study on wall partitions considers the effect of steel screws in the assembly of the elements, as well as the filling of the cavity with insulating material. The goal of this work is to calculate the fire resistance time and compare the results using different numerical models. The discussion of the results analyzes the effect of steel screws and the introduction of insulating material inside the cavities. The steel screws are verified with and without threads. The numerical models are based on the finite element method, using thermal and transient analysis with nonlinear materials. The thermal insulation criterion for measuring fire resistance is referenced by the EN 1363-1:2020 standard. The steel screws allow more heat to be concentrated and, therefore, distribute it throughout the wooden wall partition members. Based on the results obtained, the use of steel screws reduces fire resistance by 71.75 min, regardless of whether the wall partition is filled with or without insulating material.
Numerical Investigation of the Combustion Characteristics of a Hydrogen-Fueled Engine with Water Injection
Authors: Yao Qinghe , Lu Hongbo , Chen Junyi , Kwan Trevor Hocksun
Published: August 2024

The quest for clean, efficient engine technologies is imperative in reducing transportation’s environmental impact. Hydrogen, as a zero-emission fuel, offers significant potential for internal combustion engines but faces challenges such as optimizing engine performance and longevity. Water injection is proposed as a solution, yet its effects on engine performance require thorough investigation. This study bridges the knowledge gap by examining various water injection ratios (WIRs) and their impact on engine performance, focusing on the balance between power output and engine longevity. We identified the existence of an optimum WIR (e.g., 10% in this study), which provides peak performance with minimal adverse effects on engine performance and health. Computational simulations of a single-cylinder engine revealed how WIRs influence in-cylinder temperature, pressure, and IMEP, emphasizing the nuanced benefits of water injection. Additionally, our analysis of turbulence, through TKE and dissipation rate, deepens the understanding of combustion and fuel efficiency in hydrogen engines. This research provides valuable guidance for optimizing engine operations and paves the way for advanced water injection systems in hydrogen engines, marking a significant step towards cleaner engine technology.
Effect of Initial Temperature and Pressure on the Explosion Characteristics and Intermediate Reaction Products of Formic Acid Mixtures: A Theoretical Study
Authors: Mitu Maria
Published: August 2024

Formic acid is a promising candidate fuel that can be produced by reacting renewable hydrogen with carbon dioxide. However, the burning safety characteristics of formic acid–air mixtures have not been fully studied. This paper presents an extensive theoretical study of the adiabatic explosion pressure of formic acid–air premixed laminar flames at various initial conditions (composition of formic acid: 17–38% volume; initial pressure: 0.1–1.5 bar; initial temperature: 333–500 K), using the GASEQ software package. GASEQ software calculates chemical equilibria based on ideal gas behavior and is based on the hypothesis of adiabatic expansion inside a closed containment that allows ideal expansion. The influence of the initial conditions (pressure, temperature, and concentration) of formic acid–air mixtures on the adiabatic explosion pressures, maximum flame temperature, and peak concentrations of the main reaction intermediates is investigated and discussed. It is found that the adiabatic peak explosion pressure (calculated equilibrium pressure) of the studied concentrations decreases with increasing initial temperature and increases linearly with increasing initial pressure.
Consumer Perception of the Performance of Online Catering Food Safety Regulations: The Case of Shanghai, China
Authors: Liu Weijun , Wu Yige , Sun Yue , Florkowski Wojciech J.
Published: August 2024

To protect the safety of food bought from the online catering sector, the former State Food and Drug Administration of China issued two separate regulations in 2016 and 2017. Independently, the Shanghai government formulated local regulations, including the Shanghai Online Catering Service Supervision and Management Measures, to strengthen food safety supervision in this megacity with the largest catering sector in China. This study explored factors that influence consumer perceptions of the performance of online catering food safety regulations using survey data from 1050 respondents collected in 2019. The results indicate that consumers believe that Shanghai’s online catering industry has improved by varying degrees in terms of food freshness, ingredient traceability, foreign matter control, food temperature control, internal packaging hygiene and environmental protection, and satisfaction with food safety. The factors that influenced the listed features include the number and effectiveness of government-issued regulations regarding the online catering sector, effectiveness of ordering platform food safety regulations, employee training frequency, employee food safety awareness, delivery box cleanliness and courier personal hygiene, consumer trust in ordering platform services, and consumer confidence in government supervision. These factors significantly and positively affected the consumers’ perceptions of the performance of food safety regulations in the online catering sector.
Technological Evaluation of Fiber Effects in Wheat-Based Dough and Bread
Authors: Verbeke Celeste , Debonne Els , Versele Stien , Van Bockstaele Filip , Eeckhout Mia
Published: August 2024

Dietary fiber incorporation in bread offers potential health benefits but poses challenges due to its impact on dough rheology and bread quality. This study evaluated the effects of pea, cocoa, and apple fiber on wheat-based dough and bread properties using rheological methods (farinograph, alveograph, pasting, and proofing) and baking trials. Substituting flour with fiber at 1%, 5%, or 10% increased water absorption and affected dough development, stability, and extensibility, particularly at high fiber concentrations. Pasting properties showed varying gelatinization behaviors influenced by fiber type and concentration. Principal component analysis (PCA) highlighted the clustering of dough and bread characteristics based on fiber concentration and type. At low fiber concentrations (up to 5% of flour replacement), negative effects were minimal, suggesting no need for comprehensive compositional analysis. However, high fiber concentrations (10%) introduced significant variability and complexity in dough properties. New farinographic parameters (FU4, FU6, FU8, FU10, and FU12) improved the explanatory power of PCA, enhancing the understanding of fiber-rich dough dynamics. The significant alterations in moisture content and texture underscore the intricate relationship between type of fiber, concentration, and dough functionality. Optimizing rheological parameters for fiber-enriched flour is crucial for adapting the bread-making process to produce high-quality bread with desired characteristics and enhanced nutritional benefits.
Performance of Different Saccharomyces Strains on Secondary Fermentation during the Production of Beer
Authors: Dilmetz Brooke A. , Brar Gurpreet , Desire Christopher T. , Meneses Jon , Klingler-Hoffmann Manuela , Young Clifford , Hoffmann Peter
Published: August 2024

Bottle conditioning of beer is an additional fermentation step where yeast and fermentable extract are added to the beer for carbonation. During this process, yeast must overcome environmental stresses to ensure sufficient fermentation in the bottle. Additionally, the yeast must be able to survive for a prolonged time, as a decline in viability will lead to alterations in the product. Here, we investigated the effects of bottle conditioning on beer using six different yeast strains from the brewing, wine making, and distilling industries over 120 days. The ale and lager strains resulted in a beer possessing typical characteristics of a pale ale-style beer, whereas sparkling wine and distilling yeast strains resulted in aromas that were uncharacteristic, which was expected. In addition, we observed that the various strains had different propensities to survive during bottle conditioning. Proteomic analysis was performed to ascertain protein abundance changes and reveal biological processes that potentially enabled specific yeast strains to survive longer during secondary fermentation. Our results showed that proteins associated with oxidoreductase activity and mitochondrial ribosomes were increased in the yeast strain with superior survival and were able to respond to cellular stress more effectively, whereas proteins associated with cell wall modulation were increased in the strain with poor survival characteristics. Overall, we demonstrated the impact of yeast selection on bottle conditioning and the biological processes involved in yeast physiology under these conditions.
Caletodraco cottardi: A New Furileusaurian Abelisaurid (Dinosauria: Theropoda) from the Cenomanian Chalk of Normandy (North-Western France)
Authors: Buffetaut Eric , Tong Haiyan , Girard Jérôme , Hoyez Bernard , Párraga Javier
Published: August 2024

An articulated group of skeletal elements comprising a sacrum, both ilia and a first caudal vertebra, plus an isolated tooth found in immediate proximity to the bones, from the lower Cenomanian Chalk at Saint-Jouin-Bruneval (Seine-Maritime, Normandy, France) is described and attributed to a new genus and species of abelisaurid theropod, Caletodraco cottardi, on the basis of several characters of the sacrum and pelvis. The peculiar shape of the transverse process of the first caudal vertebra shows that Caletodraco cottardi differs from majungasaurine abelisaurids previously described from Europe, such as Arcovenator escotae, and belongs to the Furileusauria, a group of derived abelisaurids hitherto recognized only from South America. The presence of a furileusaurian abelisaurid in the Cenomanian of Normandy suggests that the biogeographical history of the Abelisauridae in Europe was more complex than hitherto admitted. Several previously described European abelisaurids, such as the Albian Genusaurus sisteronis, may in fact belong to the Furileusauria.
Numerical Analysis and Computation of the Finite Volume Element Method for the Nonlinear Coupled Time-Fractional Schrödinger Equations
Authors: Zhao Xinyue , Yang Yining , Li Hong , Fang Zhichao , Liu Yang
Published: August 2024

In this article, our aim is to consider an efficient finite volume element method combined with the L2−1σ formula for solving the coupled Schrödinger equations with nonlinear terms and time-fractional derivative terms. We design the fully discrete scheme, where the space direction is approximated using the finite volume element method and the time direction is discretized making use of the L2−1σ formula. We then prove the stability for the fully discrete scheme, and derive the optimal convergence result, from which one can see that our scheme has second-order accuracy in both the temporal and spatial directions. We carry out numerical experiments with different examples to verify the optimal convergence result.
Analysis of Fractal Properties of Atmospheric Turbulence and the Practical Applications
Authors: Liu Zihan , Zhang Hongsheng , Fu Zuntao , Cai Xuhui , Song Yu
Published: August 2024

Atmospheric turbulence, recognized as a quintessential space–time chaotic system, can be characterized by its fractal properties. The characteristics of the time series of multiple orders of fractal dimensions, together with their relationships with stability parameters, are examined using the data from an observational station in Horqin Sandy Land to explore how the diurnal variation, synoptic process, and stratification conditions can affect the fractal characteristics. The findings reveal that different stratification conditions can disrupt the quasi-three-dimensional state of atmospheric turbulence in different manners within different scales of motion. Two aspects of practical applications of fractal dimensions are explored. Firstly, fractal properties can be employed to refine similarity relationships, thereby offering prospects for revealing more information and expanding the scope of application of similarity theories. Secondly, utilizing different orders of fractal dimensions, a systematic algorithm is developed. This algorithm distinguishes and eliminates non-turbulent motions from observational data, which are shown to exhibit slow-changing features and result in a universal overestimation of turbulent fluxes. This overestimation correlates positively with the boundary frequency between turbulent and non-turbulent motions. The evaluation of these two aspects of applications confirms that fractal properties hold promise for practical studies on atmospheric turbulence.
Wind Turbine Blade Fault Diagnosis: Approximate Entropy as a Tool to Detect Erosion and Mass Imbalance
Authors: Lahmiri Salim
Published: August 2024

Wind energy is a clean, sustainable, and renewable source. It is receiving a large amount of attention from governments and energy companies worldwide as it plays a significant role as an alternative source of energy in reducing carbon emissions. However, due to long-term operation in reduced and difficult weather conditions, wind turbine blades are always seriously damaged. Hence, damage detection in blade structure is essential to evaluate its operational condition and ensure its structural integrity and safety. We aim to use fractal, entropy, and chaos concepts as descriptors for the diagnosis of wind turbine blade condition. They are, respectively, estimated by the correlation dimension, approximate entropy, and the Lyapunov exponent. Formal statistical tests are performed to check how they are different across wind turbine blade conditions. The experimental results follow. First, the correlation dimension is not able to distinguish between all conditions of wind turbine blades. Second, approximate entropy is suitable to distinguish between healthy and erosion conditions and between healthy and mass imbalance conditions. Third, chaos is not a discriminative feature to distinguish between wind turbine blade conditions. Fourth, wind turbine blades with either erosion or mass imbalance exhibit less irregularity in their respective signals than healthy wind turbine blades.
Remaining Useful Life Prediction for Power Storage Electronic Components Based on Fractional Weibull Process and Shock Poisson Model
Authors: Song Wanqing , Yang Xianhua , Deng Wujin , Cattani Piercarlo , Villecco Francesco
Published: August 2024

For lithium-ion batteries and supercapacitors in hybrid power storage facilities, both steady degradation and random shock contribute to their failure. To this end, in this paper, we propose to introduce the degradation-threshold-shock (DTS) model for their remaining useful life (RUL) prediction. Non-homogeneous compound Poisson process (NHCP) is proposed to simulate the shock effect in the DTS model. Considering the long-range dependence and heavy-tailed characteristics of the degradation process, fractional Weibull process (fWp) is employed in the diffusion term of the stochastic degradation model. Furthermore, the drift and diffusion coefficients are constantly updated to describe the environmental interference. Prior to the model training, steady degradation and shock data must be separated, based on the three-sigma principle. Degradation data for the lithium-ion batteries (LIBs) and ultracapacitors are employed for model verification under different operation protocols in the power system. Recent deep learning models and stochastic process-based methods are utilized for model comparison, and the proposed model shows higher prediction accuracy.
Insights for Future Pharmacology: Exploring Phytochemicals as Potential Inhibitors Targeting SARS-CoV-2 Papain-like Protease
Authors: Jabeen Jawaria , Ahmed Nabeel , Shahzad Zunaira , Shahid Maida , Ahmad Taseer
Published: August 2024

(1) Background: The SARS-CoV-2 papain-like protease (PLpro) remains an underexplored antiviral target so far. The reduced efficacy of approved treatments against novel variants highlights the importance of developing new agents. This review aims to provide a comprehensive understanding of phytochemicals as inhibitors of PLpro, identify gaps, and propose novel insights for future reference. (2) Methods: A thorough literature search was conducted using Google Scholar, ScienceDirect, and PubMed. Out of 150 articles reviewed, 57 met inclusion criteria, focusing on SARS-CoV-2 PLpro inhibitors, excluding studies on other coronaviruses or solely herbal extracts. Data were presented class-wise, and phytochemicals were grouped into virtual, weak, modest, and potential inhibitors. (3) Results: Approximately 100 phytochemicals are reported in the literature as PLpro inhibitors. We classified them as virtual inhibitors (70), weak inhibitors (13), modest inhibitors (11), and potential inhibitors (6). Flavonoids, terpenoids, and their glycosides predominated. Notably, six phytochemicals, including schaftoside, tanshinones, hypericin, and methyl 3,4-dihydroxybenzoate, emerged as potent PLpro inhibitors with favorable selectivity indices and disease-mitigation potential; (4) Conclusions: PLpro stands as a promising therapeutic target against SARS-CoV-2. The phytochemicals reported in the literature possess valuable drug potential; however, certain experimental and clinical gaps need to be filled to meet the therapeutic needs.
Carboxypeptidase Inhibitor LXN Expression in Endometrial Tissue Is Menstrual Cycle Phase-Dependent and Is Upregulated in Endometriotic Lesions
Authors: Sarsenova Meruert , Stepanjuk Artjom , Saare Merli , Kasvandik Sergo , Soplepmann Pille , Mikeltadze Iveta , Götte Martin , Salumets Andres , Peters Maire
Published: August 2024

Endometriosis is a chronic hormone-dependent disease characterized by the spread of endometrial cells outside the uterus, which form endometriotic lesions and disrupt the functions of the affected organs. The etiopathogenesis of endometriosis is still unclear, and thus it is important to examine the genes that may contribute to the establishment of endometriotic lesions. The aim of this study was to investigate the expression of new potential candidate gene latexin (LXN), an inhibitor of carboxypeptidases, in endometrium and endometriotic lesions to elucidate its possible role in endometriosis development. LXN expression in tissues was assessed using quantitative reverse transcription PCR (qRT–PCR) analysis and immunohistochemical staining (IHC). The functions of LXN were examined using Transwell and MTT assays. qRT–PCR analysis revealed that LXN expression in endometrium was menstrual cycle-dependent, being lowest in the early-secretory phase and highest in the late-secretory phase and was significantly upregulated in endometriotic lesions. IHC confirmed LXN expression in endometrial stromal cells, and in vitro assays demonstrated that knockdown of LXN effectively reduced the migratory capacity of endometrial stromal cells while promoting cell viability. In conclusion, our results showed that LXN can be involved in the pathogenesis of endometriosis by regulating the proliferation and migration activity of endometriotic stromal cells.
Advances in the Application of Protein Language Modeling for Nucleic Acid Protein Binding Site Prediction
Authors: Wang Bo , Li Wenjin
Published: August 2024

Protein and nucleic acid binding site prediction is a critical computational task that benefits a wide range of biological processes. Previous studies have shown that feature selection holds particular significance for this prediction task, making the generation of more discriminative features a key area of interest for many researchers. Recent progress has shown the power of protein language models in handling protein sequences, in leveraging the strengths of attention networks, and in successful applications to tasks such as protein structure prediction. This naturally raises the question of the applicability of protein language models in predicting protein and nucleic acid binding sites. Various approaches have explored this potential. This paper first describes the development of protein language models. Then, a systematic review of the latest methods for predicting protein and nucleic acid binding sites is conducted by covering benchmark sets, feature generation methods, performance comparisons, and feature ablation studies. These comparisons demonstrate the importance of protein language models for the prediction task. Finally, the paper discusses the challenges of protein and nucleic acid binding site prediction and proposes possible research directions and future trends. The purpose of this survey is to furnish researchers with actionable suggestions for comprehending the methodologies used in predicting protein–nucleic acid binding sites, fostering the creation of protein-centric language models, and tackling real-world obstacles encountered in this field.
Exploring the Association between Health-Related Physical Fitness and Quality of Life in Patients with Cancer: A Cross-Sectional Study
Authors: Borsati Anita , Giannarelli Diana , Belluomini Lorenzo , Ciurnelli Christian , Colonna Alessio , D’Amico Irene , Daniele Arianna , Del Bianco Nicole , Toniolo Linda , Trestini Ilaria , Tregnago Daniela , Insolda Jessica , Sposito Marco , Lanza Massimo , Milella Michele , Schena Federico , Pilotto Sara , Avancini Alice
Published: August 2024

Whereas an exercise intervention effectively improves patients’ quality of life, little information is available about the contribution of each physical fitness component. This study aims to explore the association between physical fitness components and the quality-of-life domain in patients with cancer. Between September 2021 and August 2023, 160 patients with mixed cancer types visiting the Oncology Unit were selected on a consecutive basis according to selection criteria. They underwent a comprehensive baseline assessment including the six-minute walking test, the handgrip strength test, the isometric leg press test, the back scratch, sit and reach tests, their waist–hip ratio, and their body mass index. The European Organization for Research and Treatment of Cancer Quality of Life and Core Questionnaire was used to measure the quality of life. The sample size was based on the use of regression models to study associations between clinical characteristics and fitness outcomes. All of the analyses were performed using the SPSS v.25 statistical package. Patients had a mean age of 58 years, 68% were female, 42% were affected by breast cancer, and all were receiving anticancer treatments. Higher functional capacity was associated with better global health status (p < 0.0001) and physical (p < 0.0001), role (p < 0.0001), emotional (p = 0.026), and social function (p = 0.016) and inversely linked with fatigue (p = 0.001). Lower-limb flexibility was significantly associated with all of the domains except for role and social functions. The waist–hip ratio was inversely associated with physical function (p < 0.0001) and positively related to fatigue (p = 0.037). Exercise programs aiming to improve the quality of life in cancer should be addressed to optimize these fitness components.
The Influence of Climatic Conditions Associated with Altitude on the Volatile Composition of Cabernet Sauvignon Wines from Argentina, Spain and Portugal
Authors: Deis Leonor , Martínez Liliana , da Costa Bianca S. , Vilanova Mar
Published: August 2024

In addition to winemaking techniques, wine’s quality and typicity are linked to the place where the grapes are grown. Climate, soil and the cultivar are major drivers of the terroir’s expression. Moreover, climate change is affecting the distribution of grapevine varieties in different wine-growing regions because changes in climatic conditions over the past years is affecting grape production. This study investigated the influence of some terroir parameters on the volatile composition of Cabernet Sauvignon wines. Eight wines from vineyards sited in Argentina, Spain and Portugal with altitudes between 2400 and 77 m above sea level (a.s.l.) with different soils and climatic conditions were selected. The results suggested that the vineyard’s place significantly modified the volatile composition of Cabernet Sauvignon wines because all chemical groups of volatiles quantified were affected. Volatile acids, C6 compounds, aldehydes, esters and terpenes showed the highest concentrations at 2400 m a.s.l., where the highest thermal amplitude was observed. In Portugal, where the vineyard studies were sited at lower altitudes (77 m a.s.l.) and under warm climatic conditions, high concentrations of alcohols and lactones were observed. Alcohols also showed high concentrations in wines from vineyards sited at 413 and 155 m a.s.l. (Spain). Principal component analysis showed the positive correlation of Cabernet Sauvignon wines located at higher altitudes with terpenes. On the contrary, wines from grapes grown at lower altitude conditions exhibited a correlation with alcohols and lactones.
Hydrogen Production from Wave Power Farms to Refuel Hydrogen-Powered Ships in the Mediterranean Sea
Authors: Pompodakis Evangelos E. , Orfanoudakis Georgios I. , Katsigiannis Yiannis A. , Karapidakis Emmanuel S.
Published: August 2024

The maritime industry is a major source of greenhouse gas (GHG) emissions, largely due to ships running on fossil fuels. Transitioning to hydrogen-powered marine transportation in the Mediterranean Sea requires the development of a network of hydrogen refueling stations across the region to ensure a steady supply of green hydrogen. This paper explores the technoeconomic viability of harnessing wave energy from the Mediterranean Sea to produce green hydrogen for hydrogen-powered ships. Four promising island locations—near Sardegna, Galite, Western Crete, and Eastern Crete—were selected based on their favorable wave potential for green hydrogen production. A thorough analysis of the costs associated with wave power facilities and hydrogen production was conducted to accurately model economic viability. The techno-economic results suggest that, with anticipated cost reductions in wave energy converters, the levelized cost of hydrogen could decrease to as low as 3.6 €/kg, 4.3 €/kg, 5.5 €/kg, and 3.9 €/kg for Sardegna, Galite, Western Crete, and Eastern Crete, respectively. Furthermore, the study estimates that, in order for the hydrogen-fueled ships to compete effectively with their oil-fueled counterparts, the levelized cost of hydrogen must drop below 3.5 €/kg. Thus, despite the competitive costs, further measures are necessary to make hydrogen-fueled ships a viable alternative to conventional diesel-fueled ships.
Assessing and Predicting Nearshore Seawater Quality with Spatio-Temporal Semivariograms: The Case of Coastal Waters in Fujian Province, China
Authors: Wang Wei , Cheng Wenfang , Chen Jing
Published: August 2024

The scientific assessment and prediction of nearshore water quality are crucial for marine environment protection efforts. This study is based on a comprehensive analysis of existing assessment and prediction methods and considers the regular and random characteristics of nearshore seawater quality due to both natural and anthropogenic influences. It proposes a new method that applies the kriging interpolation algorithm to empirically generated spatio-temporal semivariograms to assess and predict seawater quality. The application of this method in Fujian coastal areas shows that it is able to flexibly and scientifically estimate the variations in various indicators in the region. Combined with GIS spatial data overlay analysis operations, it can be used to quantitatively evaluate different qualities of seawater and provide scientific guidance for marine environmental protection.