bluuebunny/crossref_metadata_2025 huggingface dataset:
Varietal Differences in the Environmental Behavior of 14C-Caffeine in Tea Plants: Accumulation, Subcellular Distribution, and Metabolism
Authors: Chen Yan , Song Kaitai , Hu Huizhong , Wang Haiyan , Zheng Xinqiang
Published: February 2025

Caffeine contamination in water sources raises concerns about its transfer to agricultural products and potential risks to human health through the food chain. Despite these concerns, limited research has focused on the accumulation and distribution of exogenous caffeine in tea plants. This study explored the uptake, translocation, targeted accumulation, subcellular distribution, and preliminary metabolism of 14C-labeled caffeine in a hydroponic tea seedling system. After 192 h of cultivation, more than 83.8% of the caffeine had been removed from the nutrient solution. Within the plants, 14C-caffeine and its metabolites predominantly accumulated in the roots. Subcellular analysis indicates that in root cells, 14C was mainly distributed in the soluble fraction, cell walls, and plastids, while in shoot cells, it was concentrated in the soluble fraction and cell walls. Metabolic profiling reveals distinct varietal differences: in Longjing 43 tea seedlings, 14C was predominantly present as the caffeine parent compound, whereas in Jiaming No. 1 tea seedlings, 14C was found both as the parent compound and as its metabolite, xanthine. This study revealed differences in the uptake, translocation, and metabolism of exogenous caffeine among different tea plant varieties, providing broader insights into the impact of caffeine pollution on agricultural ecosystems.
The Role of p53 Mutations in Early and Late Response to Mitotic Aberrations
Authors: Hertel Anna , Storchová Zuzana
Published: February 2025

Mutations in the TP53 gene and chromosomal instability (CIN) are two of the most common alterations in cancer. CIN, marked by changes in chromosome numbers and structure, drives tumor development, but is poorly tolerated in healthy cells, where developmental and tissue homeostasis mechanisms typically eliminate cells with chromosomal abnormalities. Mechanisms that allow cancer cells to acquire and adapt to CIN remain largely unknown. Tumor suppressor protein p53, often referred to as the “guardian of the genome”, plays a critical role in maintaining genomic stability. In cancer, CIN strongly correlates with TP53 mutations, and recent studies suggest that p53 prevents the propagation of cells with abnormal karyotypes arising from mitotic errors. Furthermore, p53 dysfunction is frequent in cells that underwent whole-genome doubling (WGD), a process that facilitates CIN onset, promotes aneuploidy tolerance, and is associated with poor patient prognosis across multiple cancer types. This review summarizes current insights into p53’s role in protecting cells from chromosome copy number alterations and discusses the implications of its dysfunction for the adaption and propagation of cancer cells.
Quantitative Characterization and Prediction of the Binding Determinants and Immune Escape Hotspots for Groups of Broadly Neutralizing Antibodies Against Omicron Variants: Atomistic Modeling of the SARS-CoV-2 Spike Complexes with Antibodies
Authors: Alshahrani Mohammed , Parikh Vedant , Foley Brandon , Raisinghani Nishank , Verkhivker Gennady
Published: February 2025

A growing body of experimental and computational studies suggests that the cross-neutralization antibody activity against Omicron variants may be driven by the balance and tradeoff between multiple energetic factors and interaction contributions of the evolving escape hotspots involved in antigenic drift and convergent evolution. However, the dynamic and energetic details quantifying the balance and contribution of these factors, particularly the balancing nature of specific interactions formed by antibodies with epitope residues, remain largely uncharacterized. In this study, we performed molecular dynamics simulations, an ensemble-based deep mutational scanning of SARS-CoV-2 spike residues, and binding free energy computations for two distinct groups of broadly neutralizing antibodies: the E1 group (BD55-3152, BD55-3546, and BD5-5840) and the F3 group (BD55-3372, BD55-4637, and BD55-5514). Using these approaches, we examined the energetic determinants by which broadly potent antibodies can largely evade immune resistance. Our analysis revealed the emergence of a small number of immune escape positions for E1 group antibodies that correspond to the R346 and K444 positions in which the strong van der Waals and interactions act synchronously, leading to the large binding contribution. According to our results, the E1 and F3 groups of Abs effectively exploit binding hotspot clusters of hydrophobic sites that are critical for spike functions along with the selective complementary targeting of positively charged sites that are important for ACE2 binding. Together with targeting conserved epitopes, these groups of antibodies can lead expand the breadth and resilience of neutralization to the antigenic shifts associated with viral evolution. The results of this study and the energetic analysis demonstrate excellent qualitative agreement between the predicted binding hotspots and critical mutations with respect to the latest experiments on average antibody escape scores. We argue that the E1 and F3 groups of antibodies targeting binding epitopes may leverage strong hydrophobic interactions with the binding epitope hotspots that are critical for the spike stability and ACE2 binding, while escape mutations tend to emerge in sites associated with synergistically strong hydrophobic and electrostatic interactions.
Radiographic and Clinical Assessment of Unidirectional Porous Beta-Tricalcium Phosphate to Treat Benign Bone Tumors
Authors: Kunisada Toshiyuki , Nakata Eiji , Fujiwara Tomohiro , Katayama Haruyoshi , Itano Takuto , Kurozumi Takanao , Ando Teruhiko , Ozaki Toshifumi
Published: February 2025

The purpose of this study was to evaluate radiographic changes, clinical outcomes, and complications following unidirectional porous beta-tricalcium phosphate (UDPTCP) implantation for the treatment of benign bone tumors. We retrospectively analyzed 46 patients who underwent intralesional resection. The patients were divided into two cohorts: Cohort 1 (n = 32), which included all bones except the phalanges and metacarpal/tarsal bones, and Cohort 2 (n = 14), which included the phalanges and metacarpal/tarsal bones. Radiographic changes were assessed at each reading based on resorption of the implanted UDPTCP and bone trabeculation through the defect. UDPTCP resorption and bone trabeculation were observed on radiographs within 3 months of surgery in all patients. Bone remodeling in the cavity progressed steadily for up to 3 years postoperatively. In Cohort 1, resorption and trabeculation progressed significantly in young patients, and trabeculation developed significantly in small lesions. The rates of resorption and trabeculation at 3 months postoperatively correlated statistically with their increased rates at one year. There was no statistical difference in resorption and trabeculation rates between Cohort 1 and Cohort 2. There were no cases of postoperative deep infections or allergic reactions related to the implant. UDPTCP is a useful bone-filling substitute for the treatment of benign bone tumors and has a low complication rate.
The Application of Entropy in Motor Imagery Paradigms of Brain–Computer Interfaces
Authors: Wu Chengzhen , Yao Bo , Zhang Xin , Li Ting , Wang Jinhai , Pu Jiangbo
Published: February 2025

Background: In motor imagery brain–computer interface (MI-BCI) research, electroencephalogram (EEG) signals are complex and nonlinear. This complexity and nonlinearity render signal processing and classification challenging when employing traditional linear methods. Information entropy, with its intrinsic nonlinear characteristics, effectively captures the dynamic behavior of EEG signals, thereby addressing the limitations of traditional methods in capturing linear features. However, the multitude of entropy types leads to unclear application scenarios, with a lack of systematic descriptions. Methods: This study conducted a review of 63 high-quality research articles focused on the application of entropy in MI-BCI, published between 2019 and 2023. It summarizes the names, functions, and application scopes of 13 commonly used entropy measures. Results: The findings indicate that sample entropy (16.3%), Shannon entropy (13%), fuzzy entropy (12%), permutation entropy (9.8%), and approximate entropy (7.6%) are the most frequently utilized entropy features in MI-BCI. The majority of studies employ a single entropy feature (79.7%), with dual entropy (9.4%) and triple entropy (4.7%) being the most prevalent combinations in multiple entropy applications. The incorporation of entropy features can significantly enhance pattern classification accuracy (by 8–10%). Most studies (67%) utilize public datasets for classification verification, while a minority design and conduct experiments (28%), and only 5% combine both methods. Conclusions: Future research should delve into the effects of various entropy features on specific problems to clarify their application scenarios. As research methodologies continue to evolve and advance, entropy features are poised to play a significant role in a wide array of fields and contexts.
Resting-State EEG Power Spectral Density Analysis Between Healthy and Cognitively Impaired Subjects
Authors: Walters Katherine F. , Shukla Rohit , Kumar Vivek , Schueren Shannon , Yadav Hariom , Schilaty Nathan D. , Jain Shalini
Published: February 2025

Background/Objectives: This study evaluates the potential of electroencephalography (EEG) as a noninvasive tool for distinguishing between healthy individuals (n = 79), those with mild cognitive impairment (MCI; n = 36), and dementia patients (n = 7). Methods: Using a 14-channel Emotiv EPOC-X headset, we analyzed power spectral density during a 2-min eyes-closed resting state. Results: Our results demonstrated that while EEG effectively differentiated dementia patients from healthy controls, it did not show significant differences between MCI and healthy controls. This indicates that EEG holds promise for identifying advanced cognitive decline but faces challenges in early-stage detection. Conclusions: The study contributes to the growing body of literature by highlighting EEG’s potential as a cost-effective alternative to invasive diagnostic methods while also identifying the need for larger sample sizes and task-oriented approaches to improve its diagnostic precision.
Experimental and Kinetic Studies on the Conversion of Glucose to Levulinic Acid Catalyzed by Synergistic Cr/HZSM-5 in GVL/H2O Biphasic System
Authors: Wu Han , Zhang Rui , Li Jiantao , Chang Jing , Liu Zhihua , Chen Jiale , Xiong Jian , Qiao Yina , Yu Zhihao , Lu Xuebin
Published: February 2025

In this paper, modified HZSM-5 catalysts with different ratios of chromium (Cr/HZSM-5) were synthesized and the solvent effect of gamma valerolactone (GVL) on the enhancement of levulinic acid (LA) yield was investigated. Characterization of the Cr/HZSM-5 catalyst revealed that the introduction of Cr did not change the structure of HZSM-5. The LA yield was increased from 42.5% (H2O solvent system) to 51.4% (GVL/H2O solvent system) under optimal conditions. The influence of GVL on the reaction mechanism was investigated through kinetic analysis, revealing that the incorporation of GVL reduces the activation energy barrier for the conversion of glucose to LA, thereby enhancing the glucose dehydration process. The effect of GVL on the product (LA) was studied, based on molecular dynamics. It was found that the addition of GVL squeezes the water in the solvent system into the second solvation shell layer, which causes GVL to distribute around the carbonyl, hydroxyl, and carboxyl groups of LA, and reduces the likelihood of LA side reactions, thus increasing the yield of LA.
Autologous Paracrine Prostasin–Matriptase Serine Protease Interaction in Lymphoid Cancer Cells
Authors: Chen Li-Mei , Chai Karl X.
Published: February 2025

The serine protease prostasin on the surface of the exosomes released from epithelial cells can interact with ectopically over-expressed cell-surface serine protease matriptase in cancerous B cells to initiate the prostasin–matriptase proteolytic activation cascade. Matriptase activation and the ensuing self-activation result in its removal from cancer cells, reducing cell proliferation and migration. In this study, we tested the hypothesis that the matriptase in the lymphoid cells could be removed by the prostasin-initiated activation and self-activation using genetically engineered autologous cells carrying prostasin. In co-cultures with the prostasin-positive cells, the matriptase on the prostasin-negative vector-control cells was removed in a dose-dependent manner, as determined by flow cytometry. This paracrine phenotype requires the active sites of both proteases. In silico analysis of the RNA-seq profiles indicated an imbalanced expression of high matriptase and low prostasin, and their cognate protease inhibitors in B-cell lymphoma patient specimens. The impact of exosomal prostasin on the cluster of differentiation molecules in activated human peripheral blood mononuclear cells was investigated by flow cytometry, revealing candidate mechanisms for prostasin’s role in regulating cellular adaptive immunity. This autologous paracrine prostasin–matriptase interaction could be exploited as a method for targeting over-expressed matriptase in diseases such as B-cell lymphoma.
Too Persistent to Resist: Aromaticity in 16e Osmapentalene Radicals Survives Regardless of Redox
Authors: Pan Shijie , Yan Jun , Li Weitang , Shuai Zhigang , Zhu Jun
Published: February 2025

As one of the most important concepts in organic chemistry, aromaticity has attracted considerable attention from both theoretical and experimental chemists. Limited by the traditional rules (Hückel’s rules and Baird’s rules), species can only achieve aromaticity in a single state (S0 or T1) in most cases. In 2018, our group first reported 16 electron osmapentalene that showed aromaticity in both the S0 and T1 states, which is defined as adaptive aromaticity. In recent years, although adaptive aromatic compounds have been expanded, the adaptive aromatics containing metal-centered radical has not been reported. Here, we carry out density functional theory calculations to explore the aromaticity of the corresponding radicals based on osmapentalyne and osmapentalenes in their S0 states. It is found that the corresponding radicals of adaptive aromatic osmapentalene exhibit aromaticity regardless of the radicals formed by oxidation or reduction, supported by a series of aromaticity indices including ΔBL, NICS, AICD, EDDB, and ELF. In contrast, for the nonaromatic or antiaromatic compound in the T1 state, only its cationic radical shows aromaticity. Furthermore, the spin density localization on the metal center is the key factor for the radicals to achieve aromaticity.
Advancements in the Pathogenesis, Diagnosis, and Therapeutic Implications of Intestinal Bacteria
Authors: Lu Duofei , Ma Xianxiong , Tao Kaixiong , Lei Hongwei
Published: February 2025

Intestinal bacteria form one of the most complex microbial communities in the human body, playing a crucial role in maintaining host health and contributing to the development of various diseases. Here, we provide a comprehensive overview of the composition and function of intestinal bacteria, the factors affecting their homeostasis, and their association and mechanisms with a range of diseases (e.g., inflammatory bowel diseases, colorectal cancer, metabolic diseases). Additionally, their advanced potential in disease diagnosis and treatment is highlighted. Therapies, such as chemotherapy, radiotherapy, and immunotherapy, are significantly impacted by intestinal bacteria, with research indicating that bacteria can enhance chemoimmunotherapy efficiency by affecting T cell recruitment and immune cell infiltration. Fecal microbiota transplantation has emerged as a promising option for treating recurrent Clostridium difficile infections and certain metabolic and neurological disorders. Gut bacteria-related serum metabolites serve as non-invasive indicators for diagnosing CRC, while fecal immunochemical tests offer promising applications in CRC screening. Future research is needed to better understand the causal relationships between intestinal bacteria and diseases, develop more precise diagnostic tools, and evaluate the effectiveness and safety of microbiome-targeted therapies in clinical treatment. This study provides deeper insights into the role of intestinal bacteria in human health and disease, providing a scientific basis for innovative therapeutic strategies that have the potential to transform the landscape of healthcare.
Investigating and Identifying the Surface Damage of Traditional Ancient Town Residence Roofs in Western Zhejiang Based on YOLOv8 Technology
Authors: Yang Shuai , Chen Yile , Zheng Liang , Chen Junming , Huang Yuhao , Huang Yue , Wang Ning , Hu Yuxuan
Published: February 2025

The environment continues to erode the roofs of ancient buildings in Longmen Ancient Town, posing a threat to the safety of villagers. Scientific detection and diagnosis are important steps in the repair and protection of historical buildings. In order to effectively protect cultural heritage, this study uses the YOLOv8 deep learning model to automatically detect damage on images of traditional residential roofs. The researchers constructed image data sets for the four categories of green vegetation, dry vegetation, missing tiles, and repaired tiles and then perform model training. The results show that the model is generally accurate for missing tiles (0.94 for missing tiles and 0.93 for repaired tiles), and it has a low false detection rate and a low missed detection rate. It does make some mistakes when it comes to green and dry vegetation in complex backgrounds, but the overall detection coverage and F1 score are better. This practical application shows that the model can accurately mark most target areas, especially for the recognition of high-contrast damage types. This study provides efficient and accurate technical support for the diagnosis of traditional roof structures and protection of cultural heritage.
Thickness Prediction of Negative Electrodes for Lithium Batteries in the Slot-Die Coating Process
Authors: Li Yuan , Ma Li’e , Yan Yanpeng , Wang Qiang , Zhang Peng , Liu Shanhui , Zhang Yifan , Yang Saiqiang
Published: February 2025

Slot-die coating is widely used in the preparation of negative electrodes for lithium batteries. The thickness of the negative electrode has a significant influence on the battery performance and lifespan, and different manufacturers have different requirements for its thickness. In order to reduce the waste caused by trial and error in the electrode preparation process, a prediction model for the negative electrode thickness was established and verified through simulation and experiments. Based on the Landau–Levich film equation and the Ruschak model, a high-precision prediction model was constructed by taking into account the influence of factors’, such as temperature and slurry, spreading characteristics on the coating thickness. The minimum coating thickness and its influencing factors were explored. Meanwhile, the simulation analysis of the coating thickness was performed, and the theoretical values of three common process parameters were compared with the simulation results, showing a deviation of only 2.9%. An experiment on predicting the thickness of the negative electrode of lithium batteries was conducted. Thickness measurements were performed on the samples prepared through the experiment and compared with theoretical values. The accuracy rate of this thickness prediction model can reach 98.75%.
Achieving Transparency and Minimizing Losses of Rough Additively Manufactured Optical Components by a Dip-Coating Surface Finish
Authors: Shrotri Abhijeet , Preu Sascha , Stübbe Oliver
Published: February 2025

Additive manufacturing of optical, electrical, and mechanical components is a beneficial approach for the rapid prototyping of components and error elimination, with short turnaround times. However, additively manufactured components usually have rough surfaces that need post-processing, particularly for optical components, where the surface roughness must be a small fraction of the wavelength. We demonstrate an innovative and economical approach by dip-coating with the same resin used for printing in a simple post-processing step, providing high transparency to the 3D-printed optical components and reducing surface roughness while achieving perfect index matching of the coating layer. The surface roughness of the 3D-printed optical components drops to 5 nm (arithmetic average) after the dip-coating process. We observed significant performance enhancements after comparing the unprocessed optical components and the dip-coated optical components, including optical transparency and a shiny surface finish for previously rough surfaces.
Inhomogeneous Evolution of a Dense Ensemble of Optically Pumped Excitons to a Charge Transfer State
Authors: Kirova Natasha , Brazovskii Serguei
Published: February 2025

Phase transformations induced by short optical pulses are mainstream in studies on the dynamics of cooperative electronic states. We present a semiphenomenological modeling of spatiotemporal effects expected when optical excitons are intricate with the order parameter such as in, e.g., organic compounds with neutral-ionic ferroelectric phase transitions. A conceptual complication appears here, where both the excitation and the ground state ordering are built from the intermolecular electronic transfer. To describe both thermodynamic and dynamic effects on the same root, we adopt, for the phase transition, a view of the excitonic insulator—a hypothetical phase of a semiconductor that appears if the exciton energy becomes negative. After the initial pumping pulse, a quasi-condensate of excitons can appear as a macroscopic quantum state that then evolves, while interacting with other degrees of freedom which are prone to an instability. The self-trapping of excitons enhances their density, which can locally surpass a critical value to trigger the phase transformation. The system is stratified in domains that evolve through dynamical phase transitions and may persist even after the initiating excitons have recombined.
NPA Hierarchy and Extremal Criterion in the Simplest Bell Scenario
Authors: Ishizaka Satoshi
Published: February 2025

It is difficult to establish an analytical criterion to identify the boundaries of quantum correlations, even for the simplest Bell scenario. Here, we briefly reviewed the plausible analytical criterion, and we found a way to confirm the extremal conditions from another direction. For that purpose, we analyzed the Navascués-Pironio-Acín (NPA) hierarchy to study the algebraic structure and found that the problem could not be simplified using the 1+AB level. However, considering the plausible criterion, the 1+AB and second levels for correlations were equal, and the extremal condition in the simplest Bell scenario was replaced by that in the 1+AB level. Thus, the correctness of the plausible criterion was verified, and the results demonstrated that the plausible criterion held, thereby explaining its simplicity. It seemed plausible, but now it becomes more certain.
Developing Creativity in Psychological Science and Beyond
Authors: Sternberg Robert J.
Published: February 2025

This article considers the problem of developing creativity, with a focus on psychological science. What makes a psychological or other scientist creative, and what are the attitudes as well as skills that one must develop to become creative? What can educators do to enhance their creativity for the benefit of science and the world? The essay focuses on transformational creativity—creativity that makes the world a better place. Transformational creativity requires individuals to defy popular beliefs (the crowd) and assumptions (the Zeitgeist) and often, their own past beliefs (the self). The essay also provides tips for improving creativity that draw on the experience of 100 highly eminent psychologists who were identified in a survey by Edward Diener and his associates. These creators were transformational in their own field of psychology. Mentors and teachers, in general, should put more focus on developing transformationally creative attitudes in their work with young people, because those are the attitudes that will make the field better and make the world a better place.
School Climate and Sense of Coherence Among Vocational and General Education Teachers in a Nursing School Context
Authors: Matić Nikolina , Matić Ivica , Stanešić Đurđica
Published: February 2025

This study explores the relationship between teachers’ Sense of Coherence (SOC) and their perceptions of school climate, with a particular focus on potential differences between vocational education teachers (VETs) and teachers of general education subjects (GETs). Utilizing a cross-sectional design, the research involved 103 teachers who completed validated measures to assess their SOC and perceptions of school climate. The results reveal a significant positive correlation between SOC and school climate, with a correlation coefficient of r = 0.395 (p < 0.001). Notably, SOC explains 15.6% of the variance in teachers’ perceptions of school climate, as indicated by R2 = 0.156 (p < 0.001). The study did not identify any significant differences in SOC (p = 0.612) or school climate ratings (p = 0.372) between VETs and GETs. These findings suggest that teachers who possess a stronger SOC are more inclined to perceive their work environments as supportive and well organized. The implications of this study underscore the importance of psychological resilience in enhancing educators’ professional experiences. In summary, this investigation highlights the critical interplay between teachers’ psychological attributes and their perceptions of the educational environment, emphasizing the need for supportive measures that bolster SOC among educators.
Science Learning Environments in Higher Education: Researching Classroom, Laboratory, and Field Settings
Authors: Borch Katrine Bergkvist , Svabo Connie
Published: February 2025

This study investigates how science learning environments in higher education have been researched and proposes methodological approaches for future studies. Through a state-of-the-art review, this study identifies a predominant reliance on inventory-based methods which provide valuable insights but often overlook the interplay between psychosocial and physical dimensions and the dynamic nature of learning environments. Science education extends beyond classrooms to laboratory and field settings, yet these are under-researched. This article argues for integrated, pragmatic, and holistic approaches that combine qualitative and quantitative methods to enhance understanding and improve science education. With a holistic approach we can expand the knowledge of pedagogical practices as well as designing study and learning environments that foster students’ deep engagement and learning.
Generative AI Tools in Salvadoran Higher Education: Balancing Equity, Ethics, and Knowledge Management in the Global South
Authors: Valdivieso Tizziana , González Oscar
Published: February 2025

The integration of generative artificial intelligence (GAI) tools in higher education offers new opportunities for personalized learning, critical thinking, and digital literacy. However, socio-economic disparities and ethical concerns present significant challenges to equitable and responsible GAI use, particularly in under-resourced educational settings. This mixed-methods study explored how undergraduate students at Universidad Centroamericana José Simeón Cañas (UCA) in El Salvador engage with GAI tools, focusing on patterns of access, usage, and the socio-economic and ethical factors shaping these interactions. A quantitative survey of 365 students and qualitative focus groups with 25 participants were conducted to examine device preferences, tool usage, and concerns related to academic integrity, data privacy, and responsible AI use. Results revealed significant socio-economic disparities in access to GAI tools, with students from lower-income backgrounds primarily using smartphones and free AI tools, while higher-income students reported greater access to laptops and premium features. Ethical concerns were more prominent among students with limited institutional support, highlighting the need for structured guidance on the responsible use of GAI tools. These findings underscore the importance of institutional policies that promote equitable access to educational technologies and provide ethical frameworks for their use. By integrating socio-constructivist and connectivist learning theories, this study emphasizes that equitable access and guided support are critical for maximizing the educational potential of GAI tools. The study contributes to ongoing discussions about how higher education institutions, particularly in the Global South, can responsibly and effectively integrate AI technologies to support diverse student populations.
Dendroclimatology of Cedrela fissilis Vell. and Copaifera langsdorffii Desf. in an Urban Forest Under Cerrado Domain
Authors: Santos Larissa da Silva Bueno dos , Carvalho Letícia Seles de , Roquette José Guilherme , Souza Matheus Marcos Xavier de , Agostini Gabriel Bazanela de , Drescher Ronaldo , Milani Jaçanan Eloisa de Freitas , Favalessa Cyro Matheus Cometti
Published: February 2025

The study is about the influence of climate change on tree growth in urban forests in Cuiabá, Mato Grosso, Brazil, using dendrochronology. The study focuses on two species, Cedrela fissilis Vell. and Copaifera langsdorffii Desf., both with dendrochronological potential. Samples were collected from an urban forest fragment, and local (temperature and precipitation) and global (ocean surface temperature—SST and Niño 3.4 index) meteorological data were analyzed to correlate with ring width. The methodology involved collecting, preparing, polishing, and marking the rings. The data series were analyzed using the COFECHA, Arstan, and CooRecorder programs to verify the accuracy of ring dating and SAS program for correlations with climatic variables. Both species exhibited good correlations between growth rings and climatic conditions. Cedrela fissilis and Copaifera langsdorffii were positively correlated with precipitation during the dry season and generally negatively correlated with temperatures. Negative correlations were identified with SST and Niño 3.4 for both species. These results are important for understanding how urban forests respond to climate change and how the study of growth rings can be used to predict the future impacts of these changes on plant species.
Safeguarding the Aspromonte Forests: Random Forests and Markov Chains as Forecasting Models for Predicting Land Transformations
Authors: Bilotta Giuliana , Meduri Giuseppe M. , Genovese Emanuela , Bibbò Luigi , Barrile Vincenzo
Published: February 2025

Forests are crucial for human well-being and the health of our planet, particularly due to their role in carbon storage and climate mitigation. Mediterranean forests, in particular, are a vital natural resource for the region. They help absorb anthropogenic carbon emissions, reduce erosion, and provide essential habitats for various species, which in turn increases genetic diversity and species richness. This study combines Random Forest and Markov chain models to propose a highly accurate method for predicting land use. This approach offers substantial scientific support for sustainable land management policies. The methods used demonstrated excellent classification performance over time, allowing for an examination of the evolution of Mediterranean forests in the Aspromonte region. This study also provides a foundation for estimating carbon stored above and below ground using remote sensing images. The model achieved an impressive accuracy of 98.88%, making it a reliable tool for predicting the dynamics of Mediterranean forests. The results of this study have significant implications for urban planning and climate change mitigation efforts.
Prediction of Heat-Treated Wood Adhesive Strength Using BP Neural Networks Optimized by Four Novel Metaheuristic Algorithms
Authors: Cao Ying , Wang Wei , He Yan
Published: February 2025

This study integrates the Backpropagation (BP) Neural Network with several optimization algorithms, namely Hippopotamus Optimization (HO), Parrot Optimization (PO), Osprey Optimization Algorithm (OOA), and Goose Optimization (GO), to develop four predictive models for the adhesive strength of heat-treated wood: HO-BP, PO-BP, OOA-BP, and GO-BP. These models were used to predict the adhesive strength of the wood that was heat-treated under multiple variables such as treatment temperature, time, feed rate, cutting speed, and abrasive particle size. The efficacy of the BP neural network models was assessed utilizing the coefficient of determination (R2), error rate, and CEC test dataset. The outcomes demonstrate that, relative to the other algorithms, the Hippopotamus Optimization (HO) method shows better search efficacy and convergence velocity. Furthermore, XGBoost was used to statistically evaluate and rank input variables, revealing that cutting speed (m/s) and treatment time (hours) had the most significant impact on model predictions. Taken together, these four predictive models demonstrated effective applicability in assessing adhesive strength under various processing conditions in practical experiments. The MAE, RMSE, MAPE, and R2 values of the HO-BP model reached 0.0822, 0.1024, 1.1317, and 0.9358, respectively, demonstrating superior predictive accuracy compared to other models. These findings support industrial process optimization for enhanced wood utilization.
Drought Mitigation of Populus euphratica by Microenvironmental Changes Within Forest Gaps in Flooded and Non-Flooded Areas
Authors: Tian Aolei , Halik Ümüt , Zhang Haijun , Liang Jiye , Lv Ruiheng
Published: February 2025

Populus euphratica is the only dominant tree species of desert riparian forest in the Tarim River Basin and faces a great threat of drought. Policy-based artificial water delivery projects are an effective engineering method to mitigate drought and reduce the degradation of desert riparian forests. Forest gaps have been shown to be the primary mode of forest regeneration. However, little is known about growth status of P. euphratica in various arid zone habitats, particularly in light of the complex and diverse microenvironmental alterations in the understory. This study quantified the effects of forest gaps and flooded areas on microenvironmental changes in the understory. The relationships between the microenvironmental changes, soil physicochemical properties, and physiological characteristics of P. euphratica were investigated through a cross-experiment that compared whether the water delivery process was flooded and whether forest gaps existed. The results revealed that the forest gap increased the diversity of light conditions on the ground; floods decreased the temperature of the forest gap by 1.94 °C while they increased the air humidity by 8.19%. Flooding improved the vertical distribution of soil physicochemical properties within the forest gap while also altering the content of soil indicators in different directions. In the research area, only the peroxidase activity (POD) exhibited significant differences (p < 0.05) in drought indicators between the forest gaps and understory of P. euphratica, while all of the drought indicators improved after flooding. Changes in the microenvironments and soil physicochemical features together play an important ecological role in mitigating the drought of P. euphratica. These results provide an actionable theoretical basis for the efficient management of riparian forests and a research basis for sustainable forest development in arid zones.
Ophiostomatalean Fungi (Ascomycota, Ophiostomatales) Associated with Dendroctonus valens in Liaoning, China
Authors: Wang Zheng , Liang Lingyu , Yan Shuo , Wang Huimin , Lu Quan
Published: February 2025

The red turpentine beetle Dendroctonus valens is an invasive forest pest that has been rapidly spreading northward since its introduction in China. Some ophiostomatalean associates of D. valens are essential contributing factors for this beetle to become an aggressive pine killer in China. In this study, a survey was conducted in a new invasive area of this beetle’s habitat in Liaoning Province. A total of 126 ophiostomatalean fungal associates of D. valens were isolated. Based on the combination of morphological characteristics and phylogeny, these isolates were identified as Ceratocystiopsis jianpingensis sp. nov., along with two new records, Leptographium terebrantis and Ophiostoma gilletteae. Ophiostoma gilletteae was the dominant species, with an isolation rate of 85.7%. The results of this study show that more shared ophiostomatalean fungi are associated with D. valens in China and North America, and accumulate resources for the development of fungal associate-mediated bark beetle management strategies.
Construction and Comparison of Single-Tree Biomass Model for Dendrocalamus brandisii
Authors: Wang Zuming , Zeng Weisheng , Guo Lei , Xu Zhihong , Fan Shaohui , Cai Chunjun , Hui Chaomao , Liu Weiyi
Published: February 2025

Dendrocalamus brandisii (Munro) Kurz is a high-quality bamboo species for shoots, known for its sweet, tender, and crisp bamboo shoots, making it highly valuable for development. The biomass of bamboo forests is closely related to bamboo shoot yield, and studying biomass accumulation helps maintain the stability of artificial forest ecosystems. Biomass estimation facilitates the monitoring of stand dynamics and promotes the scientific management and sustainable development of D. brandisii plantations. This study collected biological data from 181 D. brandisii individuals in Changning County, Yunnan Province, to construct mathematical models for estimating single-plant biomass using the least squares method. The models were iteratively optimized using the quasi-Newton method. Based on performance indicators and residual analysis, six models were identified as suitable for estimating the biomass of D. brandisii, including multiple linear regression (MLR), linear, allometric growth, and cubic models. These models provide valuable references for biomass estimation and the management of D. brandisii plantations.
Intra-Annual Growth Dynamics and Environmental Response of Leaves, Shoots and Stems in Quercus serrata on Lushan Mountain, Subtropical China
Authors: Fu Dina , Zhang Wenpeng , Liu Xinsheng , Zhao Yesi , Sun Lian , Zhang Sirui , Chen Zilong
Published: February 2025

Primary and secondary growth of trees are key components of carbon sequestration in forest ecosystems. However, the temporal relationships between primary and secondary growth as well as their responses to environmental variations are still poorly understood. Herein, we continuously measured the intra-annual leaf, shoot and stem growth of Quercus serrata for two years on Lushan Mountain, southeastern China. Our results showed that shoots were ranked as the first organ to initiate, peak and cease growth, rather than leaves and stems. Moreover, the phenological stages of shoot growth were negatively associated with those of leaves and stems, whereas there was a weak positive correlation in phenological events between leaves and stems. These temporal connections in phenological events between primary and secondary growth suggest a prioritized carbon allocation to shoot growth and a high dependence of stem growth on carbon from newly developing leaves. Although stem growth started earlier in response to the warmer spring in 2018 compared to the colder spring in 2017, no significant difference in annual increment was observed between years, which was related to the more severe drought condition during the dry season in 2018. At the intra-annual scale, different organs generally had a consistent growth response to temperature variables but showed a divergent response to vapor pressure deficit. Despite a relatively short observational period and potential bias in spatial representativeness, our data provide nuanced knowledge on seasonal growth dynamics in primary and secondary of broadleaved species, underlining the importance of jointly considering intra-seasonal variabilities of environmental conditions in order to correctly predict tree growth response to climate change in subtropical regions.
Response of Soil Microbial Communities in Extreme Arid Deserts to Different Long-Term Management Methods
Authors: Zhang Yulin , Du Yi , Mu Zhaobin , Islam Waqar , Zeng Fanjiang , Zhang Zhihao , Gonzalez Norela C. T.
Published: February 2025

(1) Background: As population growth accelerates, unsustainable practices such as excessive cutting and burning of desert plants in the transition zones between deserts and oases have led to widespread vegetation loss. (2) Methods: The experiment was conducted in the oasis transition zone on the southern edge of the Taklamakan Desert from 2010 to 2023 year. Among the treatments included a control group (CK), cutting in spring (CS), cutting in fall (CF), burning in spring (BS), and flood water irrigation (FI). We used high-throughput sequencing to determine soil microbial composition and diversity and routine laboratory methods to determine soil physical and chemical properties and enzyme activities. (3) Results: No significant differences in bacterial alpha diversity (Chao1, Dominance, Observed_features, Pielou_e, Shannon, and Simpson) across the different long-term disturbance patterns. In fungi, the CK treatment showed significantly higher Chao1, Shannon, and Observed_features indices compared to BS and FI. Principal component analysis revealed a substantial reduction in bacterial community diversity in BS compared to FI, while fungal communities were lower in CK and CS compared to BS, CF, and FI; (4) Conclusions: Soil moisture content, electrical conductivity, organic carbon, and the activity of the enzyme cellobiohydrolase as key factors shaping the bacterial community. For fungi, organic carbon and the β-1,4-glucosidase enzyme were the main drivers.
Mechanical Properties of Asymmetric Woven Bamboo Structure from Bamboo Strips
Authors: Phongphinittana Ekkarin , Klangtup Navapon , Jearanaisilawong Petch
Published: February 2025

The study evaluates the mechanical properties of a woven bamboo structure made from bamboo strips using an analytical relation and finite element simulation. The bamboo studied is a recently discovered species, Bambusa Nghiana, characterized by long internodes. Bamboo strips have lower strength at the node junctions, a feature that can be advantageous for this species due to its extended internode length. Plain weave bamboo structures were handwoven from thin, rectangular bamboo strips cut from the bamboo culm along the radial direction. The high bending rigidity of the bamboo strips resulted in an asymmetric woven structure with curved warp strips and straight weft strips. The stiffness of the woven structure was correlated with the stiffness of the bamboo strips and the weave geometry. The in-plane shear resistance of the woven structure was significantly lower than its axial stiffness due to the asymmetric weaving. These in-plane properties were validated using finite element simulation through a user subroutine incorporating the woven structure and the Hashin damage criteria. The prediction of the puncture simulation showed good agreement with the corresponding experiment. These results confirm the proposed analytical relation between the mechanical properties of individual bamboo strips and those of the woven structure.
A Class of Finite Difference Schemes with Adaptive Controllable Dispersion and Low Dissipation for Compressible Turbulence
Authors: Hao Jianxin , Wang Qiang
Published: February 2025

The dispersion and dissipation properties of a numerical scheme are critical in simulating flow fields involving a wide range of length scales. In this study, we highlight the common oversight of focusing merely on controlling dispersion error without considering the importance of appropriate dispersion and scalability in computational efficiency. This study demonstrates that adjusting dispersion to match the local flow field near discontinuities is more effective in suppressing oscillations than simply minimizing dispersion. This proposed high-order finite difference scheme with adaptive dispersion minimized dissipation (ADMD) achieves adaptive controllable dispersion near flow field discontinuities, known as the ADMD scheme. This scheme, derived as a fourth-order finite difference scheme with seven points based on Taylor expansion, comprises a basic central component, additional dissipation component, and dispersion component. By exploring the effect of dispersion on numerical oscillations and the importance of adjusting dispersion according to the local flow field, a discontinuity detection function was established to enable the dispersion properties to adapt to the local flow field. Drawing inspiration from flow field smoothing in the weighted essentially non-oscillatory (WENO) scheme, efforts were made to minimize scheme dissipation. The main benefits of the ADMD scheme over several WENO-type schemes are robustness and efficiency, as the ADMD scheme saves at least 40–90% CPU time compared to the same-order WENO-type schemes for some numerical examples. Additionally, the numerical scheme proves advantageous in terms of simulating the decaying isotropic turbulence problem of three-dimensional compressible turbulence.
Vibration Suppression of the Vehicle Mechatronic ISD Suspension Using the Fractional-Order Biquadratic Electrical Network
Authors: Shen Yujie , Li Zhaowei , Tian Xiang , Ji Kai , Yang Xiaofeng
Published: February 2025

In order to break the bottleneck of the integer-order transfer function in vehicle ISD (inerter-spring-damper) suspension design, a positive real synthesis design method of vehicle mechatronic ISD suspension based on the fractional-order biquadratic transfer function is proposed. The emergence of the fractional-order components disrupts the equivalence relationship between the passivity of components and the positive realness of integer-order transfer functions in traditional networks. In this paper, the positive real condition of the fractional-order biquadratic transfer function is given. Then, a quarter dynamic model of the vehicle mechatronic ISD suspension is established, and the parameters of the fractional-order biquadratic transfer function and vehicle suspension are obtained by an NSGA-II multi-objective genetic algorithm. Moreover, the structure of the external circuit and the parameters of the electrical components are obtained by the fractional-order passive network synthesis theory. The simulation results show that under the condition of random road input and vehicle speed of 20 m/s, the root-mean-square (RMS) value of the vehicle body acceleration and the dynamic tire load of the fractional-order ISD suspension are reduced by 7.98% and 18.75% compared with the traditional passive suspension, while under the same condition, the integer-order ISD suspension can only reduce by 5.34% and 16.07%, respectively. The results show that employing a fractional-order biquadratic electrical network in the vehicle mechatronic ISD suspension enhances vibration isolation performance compared with the suspension using an integer-order biquadratic electrical network.