bluuebunny/crossref_metadata_2025 huggingface dataset:
Bias in Discontinuous Elevational Transects for Tracking Species Range Shifts
Authors: Li Shixuan , Yao Jiannan , Lin Yang , Wu Siyu , Yang Zhongjie , Jin Chao , Zhang Yuhan , Wang Zhen , Liu Jinliang , Shen Guochun , Yu Mingjian
Published: January 2025

Climate change is compelling species to seek refuge at higher elevations and latitudes. While researchers commonly study these migrations using discontinuous elevational transects, this methodology may introduce significant biases into our understanding of species movement. These potential biases could lead to flawed biodiversity conservation policies if left unexamined. To address this concern, we utilized species distribution data from a novel continuous elevational transect to evaluate the accuracy of discontinuous transect methods. Our analysis focused on how quadrat spacing and survey time intervals affect bias in estimating species range shifts. The results were striking: the widely used settings for discontinuous transects failed to detect 7.2% of species, inaccurately estimated shift distances for 78% of species, and produced an overall error rate of 86%. Wider quadrat spacing increased these error rates, while longer survey intervals generally reduced them. Moreover, discontinuous transects consistently underestimated species shift distances, with this underestimation becoming more pronounced over longer survey periods. Our pioneering assessment of bias in discontinuous elevational transects demonstrates that a 50 m quadrat spacing combined with a 60-year survey interval optimizes monitoring species range shifts for conservation planning. This baseline protocol could be further strengthened through supplementary, frequent surveys targeting high-elevation species—a strategic approach that maximizes accuracy while maintaining cost-effectiveness.
Citrus Yellow Vein Clearing Virus Infection in Lemon Influences Host Preference of the Citrus Whitefly by Affecting the Host Metabolite Composition
Authors: Sun Yong-Duo , Wallis Christopher M. , Krugner Rodrigo , Yokomi Raymond
Published: January 2025

Plant viruses have been known to alter host metabolites that influence the attraction of insect vectors. Our study investigated whether Citrus yellow vein clearing virus (CYVCV) infection influences vector attractiveness, focusing on the citrus whitefly, Dialeurodes citri (Ashmead). Free choice assays showed that citrus whiteflies exhibited a preference for settling on CYVCV-infected lemon plants versus healthy control plants. Using chromatography techniques, we found that the levels of sugars were similar in leaves and stems of both plant groups, while the contents of several amino acids in leaf or stem samples and non-volatile phenolic compounds in the leaf samples of CYVCV-infected and healthy plants differ drastically. In addition, volatile terpenes/terpenoids decreased significantly in virus-infected plants compared to healthy controls. Several of the identified volatile compounds such as α-phellandrene, α-terpinolene, p-cymene, linalool, and citral are known for their whitefly repellent properties. Further Y-tube olfactometer bioassays revealed that emissions of volatile organic compounds (VOCs) from infected plants attracted more citrus whiteflies, but not alate spirea aphids, Aphis spiraecola Patch, than those from healthy plants, suggesting that the VOCs released from CYVCV-infected lemon plants may specifically affect citrus whiteflies. Therefore, we suggest that, in addition to the visual cue of yellow vein symptoms, the preference of citrus whiteflies that settled on CYVCV-infected lemon plants was attributed to a reduction in the levels of repellent volatile compounds.
On the Biosynthesis of Bioactive Tryptamines in Black Cohosh (Actaea racemosa L.)
Authors: Spiering Martin J. , Parsons James F. , Eisenstein Edward
Published: January 2025

Botanical dietary supplements are widely used, but issues of authenticity, consistency, safety, and efficacy that complicate their poorly understood mechanism of action have prompted questions and concerns in the popular and scientific literature. Black cohosh (Actaea racemosa L., syn. Cimicifuga racemosa, Nutt., Ranunculaceae) is a multicomponent botanical therapeutic used as a popular remedy for menopause and dysmenorrhea and explored as a treatment in breast and prostate cancer. However, its use and safety are controversial. A. racemosa tissues contain the bioactive serotonin analog N-methylserotonin, which is thought to contribute to the serotonergic activities of black cohosh–containing preparations. A. racemosa has several TDC-like genes hypothesized to encode tryptophan decarboxylases (TDCs) converting L-tryptophan to tryptamine, a direct serotonin precursor in plants. Expression of black cohosh TDC1, TDC2, and TDC3 in Saccharomyces cerevisiae resulted in the production of tryptamine. TDC1 and TDC3 had approximately fourfold higher activity than TDC2, which was attributable to a variable Cys/Ser active site residue identified by site-directed mutagenesis. Co-expression in yeast of the high-activity black cohosh TDCs with the next enzyme in serotonin biosynthesis, tryptamine 5-hydroxylase (T5H), from rice (Oryza sativa) resulted in the production of serotonin, whereas co-expression with low-activity TDCs did not, suggesting that TDC activity is a rate-limiting step in serotonin biosynthesis. Two T5H-like sequences were identified in A. racemose, but their co-expression with the high-activity TDCs in yeast did not result in serotonin production. TDC expression was detected in several black cohosh tissues, and phytochemical analysis using LC-MS revealed several new tryptamines, including tryptamine and serotonin, along with N-methylserotonin and, interestingly, N-N-dimethyl-5-hydroxytryptamine (bufotenine), which may contribute to hepatotoxicity. Incubation of A. racemosa leaves with tryptamine and N-methyltryptamine resulted in increased concentrations of serotonin and N-methylserotonin, respectively, suggesting that methylation of tryptamine precedes hydroxylation in the biosynthesis of N-methylserotonin. This work indicates a significantly greater variety of serotonin derivatives in A. racemosa than previously reported. Moreover, the activities of the TDCs underscore their key role in the production of serotonergic compounds in A. racemosa. Finally, it is proposed that tryptamine is first methylated and then hydroxylated to form the black cohosh signature compound N-methylserotonin.
Microbial Adhesion and Cytotoxicity of Heat-Polymerized and 3D-Printed Denture Base Materials when Modified with Dimethylaminohexadecyl Methacrylate and/or 2-Methacryloyloxyethyl Phosphorylcholine as Antimicrobial and Protein-Repellent Materials
Authors: AlAzzam Njood F. , Bajunaid Salwa O. , Baras Bashayer H. , Mitwalli Heba A. , Weir Michael D. , Xu Hockin H. K.
Published: January 2025

Background: Polymethyl methacrylate (PMMA) is ideal for denture bases but is prone to biofilm accumulation, leading to denture stomatitis (DS), often involving Candida albicans. Dimethylaminohexadecyl methacrylate (DMAHDM) and 2-methacryloyloxyethyl phosphorylcholine (MPC) are introduced into dental materials for their antimicrobial and protein-repellent properties. This study investigates the effects of incorporating dimethylaminohexadecyl methacrylate (DMAHDM) and 2-methacryloyloxyethyl phosphorylcholine (MPC) into heat-polymerized (HP) and 3D-printed (3DP) denture base resins on microbial adhesion and cytotoxicity. Methods: HP and 3DP denture base specimens were prepared using varying concentrations of DMAHDM and MPC. Microbial adhesion was quantified using CFU counts of C. albicans, and cytotoxicity was assessed via an MTT assay using fibroblast cells after 24 h, 3 days, and 7 days. Results: Both DMAHDM and MPC significantly reduced the CFU counts in both HP and 3DP materials; the combination of 1.5% DMAHDM and 3% MPC exhibited the most substantial antimicrobial effects. Cytotoxicity results varied between materials and time points; however, all treated groups maintained cell viability above the 70% threshold, indicating no significant cytotoxic effects. Conclusion: Incorporating DMAHDM and MPC into denture base resins can effectively reduce microbial adhesion while maintaining acceptable cytotoxicity levels.
Damping Optimization and Energy Absorption of Mechanical Metamaterials for Enhanced Vibration Control Applications: A Critical Review
Authors: Fayyaz  , Bashmal Salem , Nazir Aamer , Khan Sikandar , Alofi Abdulrahman
Published: January 2025

Metamaterials are pushing the limits of traditional materials and are fascinating frontiers in scientific innovation. Mechanical metamaterials (MMs) are a category of metamaterials that display properties and performances that cannot be realized in conventional materials. Exploring the mechanical properties and various aspects of vibration and damping control is becoming a crucial research area. Their geometries have intricate features inspired by nature, which make them challenging to model and fabricate. The fabrication of MMs has become possible because of the emergence of additive manufacturing (AM) technology. Mechanical vibrations in engineering applications are common and depend on inertia, stiffness, damping, and external excitation. Vibration and damping control are important aspects of MM in vibrational environments and need to be enhanced and explored. This comprehensive review covers different vibration and damping control aspects of MMs fabricated using polymers and other engineering materials. Different morphological configurations of MMs are critically reviewed, covering crucial vibration aspects, including bandgap formation, energy absorption, and damping control to suppress, attenuate, isolate, and absorb vibrations. Bandgap formation using different MM configurations is presented and reviewed. Furthermore, studies on the energy dissipation and absorption of MMs are briefly discussed. In addition, the vibration damping of various lattice structures is reviewed along with their analytical modeling and experimental measurements. Finally, possible research gaps are highlighted, and a general systematic procedure to address these areas is suggested for future research. This review paper may lay a foundation for young researchers intending to start and pursue research on additive-manufactured MM lattice structures for vibration control applications.
An Extensive Study of an Eco-Friendly Fireproofing Process of Lignocellulosic Miscanthus × giganteus Particles and Their Application in Flame-Retardant Panels
Authors: Khalaf Yasmina , Sonnier Rodolphe , Brosse Nicolas , El Hage Roland
Published: January 2025

Increasing the flame retardancy of lignocellulosic materials such as Miscanthus × giganteus can effectively enable their wide use. This study examines the fireproofing process of Miscanthus particles using an eco-friendly process by grafting phytic acid and urea in aqueous solution. Miscanthus particles underwent a steam explosion step before being grafted. Fireproof binderless particle panels were manufactured from miscanthus particles with or without adding olive pomace by hot-pressing. The effect of the steam explosion and/or the flame-retardant treatment on the morphology, chemical composition and thermal stability of the particles, as well as the thermal stability of the panels, was investigated. The results showed that water impregnation followed by a steam explosion at 210 °C for 8 min resulted in particles that were rich in lignin and more homogeneous in size (length and width). Fireproof particles were produced with relatively low P and N contents. The flame retardancy of the binderless particle panels was significantly improved when using miscanthus particles treated with phytic acid and urea, as shown by a reduced heat release (HRR) and an increased time-to-ignition. However, the presence of olive pomace significantly decreased the flame retardancy of the panels. Binderless particle panels prepared from grafted miscanthus particles showed the best fire properties and are considered fireproof.
Mechanisms of the Photomechanical Response in Thin-Film Dye-Doped Glassy Polymers
Authors: Ghorbanishiadeh Zoya , Bhuyan Ankita , Zhou Bojun , Sheibani Karkhaneh Morteza , Kuzyk Mark G.
Published: January 2025

This work aims to determine the mechanism of the photomechanical response of poly(Methyl methacrylate) polymer doped with the photo-isomerizable dye Disperse Red 1 using the non-isomerizable dye Disperse Orange 11 as a control to isolate photoisomerization. Samples are free-standing thin films with thickness that is small compared with the optical skin depth to assure uniform illumination and photomechanical response throughout their volume, which differentiates these studies from most others. Polarization-dependent measurements of the photomechanical stress response are used to deconvolute the contributions of angular hole burning, molecular reorientation and photothermal heating. While photo-isomerization of dopant molecules is commonly observed in dye-doped polymers, the shape changes of a molecule might not couple strongly to the host polymer through steric mechanical interactions, thus not contributing substantially to a macroscopic shape change. To gain insights into the effectiveness of such mechanical coupling, we directly probe the dopant molecules using dichroism measurements simultaneously while measuring the photomechanical response and find mechanical coupling to be small enough to make photothermal heating—mediated by the transfer of optical energy as heat to the polymer—the dominant mechanism. We also predict the fraction of light energy converted to mechanical energy using a model whose parameters are thermodynamic material properties that are measured with independent experiments. We find that in the thin-film geometry, these dye-doped glassy polymers are as efficient as any other material but their large Young’s modulus relative to other organic materials, such as liquid crystal elastomers, makes them suitable in applications that require mechanically strong materials. The mechanical properties and the photomechanical response of thin films are observed to be significantly different than in fibers, suggesting that the geometry of the material and surface effects might play an important role.
Selection of Die Shape for Manufacturing of Energetic Materials by CFD Modeling
Authors: Barua Himel , Povitsky Alex
Published: January 2025

The first principle of numerical modeling of die extrusion of energetic materials is carried out to reduce the needed pressure gradient along the die. The proposed new die design with a converging shape outlet appears to have a smaller pressure drop compared to the current U.S. Army Armament Research, Development and Engineering Center (ARDEC) die shape. The optimal shape was obtained by finite-volume fluid dynamics computations through a range of die designs. The presented computations have been performed for a 3D die equipped with different outflow pipes. The features of the flow field are obtained for the non-Newtonian fluid through the apparatus. The change of fluid model from Newtonian to non-Newtonian complying power law does not make a considerable change in velocity profile at outlets for the same mass flow rate. Nevertheless, there is a substantial increase in the pressure gradient needed to transport the fluid through the die. For the new proposed die design, apparent viscosity steadily drops along the centerline of the outlet. As the viscosity magnitude determines the needed pressure drop, the new die design with a converging shape outlet has a substantially smaller pressure drop compared to the current die.
Characterization of Macromolecular Structure and Molecular Dynamics Optimization of Gas Coal: A Case Study of Hongdunzi Coal
Authors: Hong Lin , Che Xingzhu , Zheng Dan , Gao Dameng
Published: January 2025

To investigate the molecular structure characteristics and chemical reaction mechanisms of gas coal from the Hong II coal mine of the Ningxia Hongdunzi Coal Industry, this study explores its elemental composition, structural features, and methods for constructing and optimizing molecular models. The basic properties of the coal were determined through proximate and elemental analyses. The carbon structure was characterized using 13C-NMR nuclear magnetic resonance, the N and S chemical states were analyzed with XPS, and the distribution of hydroxyl, aliphatic hydrocarbons, aromatic rings, and oxygen-containing functional groups was characterized by FT-IR. Based on the analysis results, a molecular structure model of Hongdunzi gas coal was constructed with the molecular formula C204H117O17NS, and the calculated results of the model showed high consistency with the experimental spectra of 13C-NMR. The macromolecular model of gas coal was constructed using the Materials Studio 2020 software, and its structure was optimized through geometric optimization and dynamic simulations. After optimization, the total energy of the model was significantly reduced from 8525.12 kcal·mol−1 to 3966.16 kcal·mol−1, highlighting the enhanced stability of the coal molecular structure. This optimization indicates that torsional energy plays a dominant role in molecular stability, while van der Waals forces and electrostatic interactions were significantly improved during the optimization process.
A Multi-Model Fusion Network for Enhanced Blind Well Lithology Prediction
Authors: Shao Xiaoqing , Zhang Pengwei , Yan Shunlai , Zhao Qing , Jia Yufeng , Zhang Cheng , Tian Jun
Published: January 2025

Lithology identification is essential for formation evaluation and reservoir characterization, serving as a fundamental basis for assessing the potential value of oil and gas resources. However, traditional models often struggle with identification accuracy due to the complexities of nonlinear relationships and class imbalances in well-logging data. This paper presents an effective multi-model ensemble approach for lithology identification, integrating one-dimensional multi-scale convolutional neural networks (MCNN1D), Graph Attention Networks (GAT), and Transformer networks. MCNN1D extracts local features of lithological changes with varying convolutional kernels, enhancing robustness to complex geological data. The GAT assigns adaptive weights to adjacent nodes, capturing spatial relationships among lithological samples and enhancing local interactions. Meanwhile, the Transformer uses self-attention to capture contextual relationships in lithological sequences, improving global feature processing and identification. The multi-model fusion effectively combines the strengths of individual models, enabling comprehensive and efficient modeling of geological features. Experimental results show that the proposed Multi-Model Fusion Network outperforms other models in accuracy, precision, recall, and F1-score on the Hugoton–Panoma oilfield dataset, achieving a lithology identification accuracy of 95.06% for adjacent lithologies. This approach mitigates the effects of data imbalance and enhances identification accuracy, making it a powerful tool for lithology identification in complex reservoirs.
A Fuzzy Inertia-Based Virtual Synchronous Generator Model for Managing Grid Frequency Under Large-Scale Electric Vehicle Integration
Authors: Jia Yajun , Jin Zhijian
Published: January 2025

The rapid proliferation of EVs has ushered in a transformative era for the power industry, characterized by increased demand volatility and grid frequency instability. In response to these challenges, this paper introduces a novel approach that combines fuzzy logic with adaptive inertia control to improve the frequency stability of grids amidst large-scale electric vehicle (EV) integration. The proposed methodology not only adapts to varying charging scenarios but also strikes a balance between steady-state and dynamic performance considerations. This research establishes a solid theoretical foundation for the inertia-adaptive virtual synchronous generator (VSG) concept and introduces a pioneering fuzzy inertia-based VSG methodology. Additionally, it incorporates adaptive output scaling factors to enhance the robustness and adaptability of the control strategy. These contributions offer valuable insights into the evolving landscape of adaptive VSG strategies and provide a pragmatic solution to the pressing challenges arising from the integration of large-scale EVs, ultimately fostering the resilience and sustainability of contemporary power systems. Finally, simulation results illustrate that the new proposed fuzzy adaptive inertia-based VSG method is effective and has superior advantages over the traditional VSG and droop control strategies. Specifically, the proposed method reduces the maximum frequency change by 25% during load transitions, with a peak variation of 0.15 Hz compared to 0.2 Hz for the traditional VSG.
Research and Application of Deep Profile Control Technology in Narrow Fluvial Sand Bodies
Authors: Zheng Xu , Wang Yu , Lei Yuan , Zhang Dong , Bao Wenbo , Huang Shijun
Published: January 2025

Narrow Fluvial Sand Bodies are primarily developed along the river center, with horizontal wells for injection and production in some Bohai waterflooded oilfields. This results in a rapid increase in water cut due to a single injection–production direction. Over time, dominant water breakthrough channels form between wells, and the remaining oil moves to deeper regions, which makes conventional profile control measures less effective. We developed a quantitative method based on integrated dynamic and static big data to identify these breakthrough channels and measure the flow intensity between injection and production wells. To address deep remaining oil mobilization, we performed micro-analysis and physical simulations with heterogeneous core models, which led to the development of a deep profile control system using emulsion polymer gel and self-assembling particle flooding. Experiments show that the combined technology can reduce oil saturation in low-permeability layers to 45.3% and improve recovery by 30.2% compared to water flooding. Field trials proved to be completely effective, with a cumulative oil increase of over 23,200 cubic meters and a 12% reduction in water cut per well. This deep profile control technology offers significant water cut reduction and enhanced oil recovery. It can provide technical support for efficient water control and profile management in similar reservoirs.
DNA Damage-Induced Ferroptosis: A Boolean Model Regulating p53 and Non-Coding RNAs in Drug Resistance
Authors: Gupta Shantanu , Silveira Daner A. , Mombach José Carlos M. , Hashimoto Ronaldo F.
Published: January 2025

The tumor suppressor p53, in its wild-type form, plays a central role in cellular homeostasis by regulating senescence, apoptosis, and autophagy within the DNA damage response (DDR). Recent findings suggest that wild-type p53 also governs ferroptosis, an iron-dependent cell death process driven by lipid peroxidation. Post-translational modifications of p53 generate proteoforms that significantly enhance its functional diversity in regulating these mechanisms. A key target in this process is the cystine/glutamate transporter (xCT), which is essential for redox balance and ferroptosis resistance. Additionally, p53-induced miR-34c-5p suppresses cancer cell proliferation and drug resistance by modulating Myc, an oncogene further influenced by non-coding RNAs like circular RNA NOTCH1 (CricNOTCH1) and long non-coding RNA MALAT1. However, the exact role of these molecules in ferroptosis remains unclear. To address this, we introduce the first dynamic Boolean model that delineates the influence of these ncRNAs and p53 on ferroptosis, apoptosis, and senescence within the DDR context. Validated through gain- and loss-of-function perturbations, our model closely aligns with experimental observations in cancers such as oral squamous cell carcinoma, nasopharyngeal carcinoma, and osteosarcoma. The model identifies crucial positive feedback loops (CricNOTCH1/miR-34c/Myc, MALAT1/miR-34c/Myc, and Myc/xCT) and highlights the therapeutic potential of using p53 proteoforms and ncRNAs to combat drug resistance and induce cancer cell death.
Case Report of Concomitant Presentation of Ovarian Torsion and Acute Appendicitis in a Patient Post-Hysterectomy
Authors: Schmitt Eric , Glasford Krystal , Carson Samantha , Rosemeyer Christopher
Published: January 2025

Background: Diagnoses for right lower quadrant pain in women must include both gynecologic and non-gynecologic causes. In this differential, ovarian torsion and appendicitis are both serious etiologies that can require swift surgical intervention. Ovarian torsion is the least common of the two, accounting for 2.7% of emergency surgery cases according to a 10-year review, while the lifetime risk of appendectomy for females is 23.1%. As many as 2–3% of patients undergoing surgery for acute appendicitis are instead found to have ovarian torsion. However, there are currently only rare case reports of these two conditions co-presenting in the same patient simultaneously, with little discussion on how to be better prepared before entering the operating room. Objective: The purpose of this study is to describe this rare co-presentation to better inform providers of this potential complication and to improve future patient care outcomes. Method: A case report of a patient seen at Tripler Army Medical Center, Honolulu, Hawaii, was assessed. Conclusions: This case shows the rare possibility of dual acute etiologies of abdominal pain warranting urgent surgical management. This case also highlights the need for a multidisciplinary approach in the pre-procedural evaluation of possible competing etiologies of acute abdominal pain that warrant surgical management. Additionally, this case brings up interesting ethical questions regarding informed consent, autonomy, and the obligation of intraoperatively consulted surgeons to provide definitive and indicated surgical care in the absence of prior discussion of possible pathology.
A Dynamic Evaluation of the Use of Natural Resources in Crop Rotation in Family Farming Production Units
Authors: Vargas Dayhanna Stephania , Osorio Juan Carlos , Bravo Juan José
Published: January 2025

A total of 35.4% of the earth’s surface is used for agriculture, and 32.7% of it for crops. Agricultural activity uses 70% of the world’s freshwater, and due to the intensive use of agrochemical inputs and energy, a high percentage of greenhouse gas emissions, pollution, and waste are generated. With the increase in population and fluctuating consumption trends, it is necessary to increase crop production and productivity to meet present and future demands. A relevant factor for the analysis of the production of agricultural goods is the size of the productive unit since about 84% is less than 2 ha in size and distributed over 12% of arable land; however, it is important to highlight other factors, such as the availability of family labour, crop diversification and the development of other agricultural activities that have a lower use of insecticides, pesticides, and chemical fertilisers compared to industrial crops. Therefore, food is produced, providing social and ecological benefits. Thus, a dynamic simulation is presented to evaluate the use of natural resources in developing different rotations of transient and permanent crops in a municipality in Colombia. This study assesses the impact on land use, soil degradation due to crop development, and the total water footprint associated with each rotation.
Integrating Drone Truthing and Functional Classification of Remote Sensing Time Series for Supervised Vegetation Mapping
Authors: Quattrini Giacomo , Pesaresi Simone , Hofmann Nicole , Mancini Adriano , Casavecchia Simona
Published: January 2025

Accurate vegetation mapping is essential for monitoring biodiversity and managing habitats, particularly in the context of increasing environmental pressures and conservation needs. Ground truthing plays a crucial role in ensuring the accuracy of supervised remote sensing maps, as it provides the high-quality reference data needed for model training and validation. However, traditional ground truthing methods are labor-intensive, time-consuming and restricted in spatial coverage, posing challenges for large-scale or complex landscapes. The advent of drone technology offers an efficient and cost-effective solution to these limitations, enabling the rapid collection of high-resolution imagery even in remote or inaccessible areas. This study proposes an approach to enhance the efficiency of supervised vegetation mapping in complex landscapes, integrating Multivariate Functional Principal Component Analysis (MFPCA) applied to the Sentinel-2 time series with drone-based ground truthing. Unlike traditional ground truthing activities, drone truthing enabled the generation of large, spatially balanced reference datasets, which are critical for machine learning classification systems. These datasets improved classification accuracy by ensuring a comprehensive representation of vegetation spectral variability, enabling the classifier to identify the key phenological patterns that best characterize and distinguish different vegetation types across the landscape. The proposed methodology achieves a classification accuracy of 92.59%, significantly exceeding the commonly reported thresholds for habitat mapping. This approach, characterized by its efficiency, repeatability and adaptability, aligns seamlessly with key environmental monitoring and conservation policies, such as the Habitats Directive. By integrating advanced remote sensing with drone-based technologies, it offers a scalable and cost-effective solution to the challenges of biodiversity monitoring, enabling timely updates and supporting effective habitat management in diverse and complex environments.
DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection
Authors: Lin Shaofu , Yang Yang , Liu Xiliang , Tian Li
Published: January 2025

Precise statistics on the spatial distribution of photovoltaics (PV) are essential for advancing the PV industry, and integrating remote sensing with artificial intelligence technologies offers a robust solution for accurate identification. Currently, numerous studies focus on the detection of single-type PV installations through aerial or satellite imagery. However, due to the variability in scale and shape of PV installations in complex environments, the detection results often fail to capture detailed information and struggle to scale for multi-scale PV systems. To tackle these challenges, a detection method known as Dynamic Spatial-Frequency Attention SwinNet (DSFA-SwinNet) for multi-scale PV areas is proposed. First, this study proposes the Dynamic Spatial-Frequency Attention (DSFA) mechanism, the Pyramid Attention Refinement (PAR) bottleneck structure, and optimizes the feature propagation method to achieve dynamic decoupling of the spatial and frequency domains in multi-scale representation learning. Secondly, a hybrid loss function has been developed with weights optimized employing the Bayesian Optimization algorithm to provide a strategic method for parameter tuning in similar research. Lastly, the fixed window size of Swin-Transformer is dynamically adjusted to enhance computational efficiency and maintain accuracy. The results on two PV datasets demonstrate that DSFA-SwinNet significantly enhances detection accuracy and scalability for multi-scale PV areas.
Evaluating Sentinel-2 for Monitoring Drought-Induced Crop Failure in Winter Cereals
Authors: Descals Adrià , Torres Karen , Verger Aleixandre , Peñuelas Josep
Published: January 2025

Extreme climate events can threaten food production and disrupt supply chains. For instance, the 2023 drought in Catalonia caused large areas of winter cereals to wilt and die early, yielding no grain. This study examined whether Sentinel-2 can detect total crop losses of winter cereals using ground truth data on crop failure. The methodology explored which Sentinel-2 phenological and greenness variables could best predict three drought impact classes: normal growth, moderate impact, and high impact, where the crop failed to produce grain. The results demonstrate that winter cereals affected by drought exhibit a premature decline in several vegetation indices. As a result, the best predictors for detecting total crop losses were metrics associated with the later stages of crop development. Specifically, the mean Normalized Difference Vegetation Index (NDVI) for the first half of May showed the highest correlation with drought impact classes (R2 = 0.66). This study is the first to detect total crop losses at the plantation level using field data combined with Sentinel-2 imagery. It also offers insights into rapid monitoring methods for crop failure, an event likely to become more frequent as the climate warms.
Optimal Design and Operation of an Ultrasonic Driving System for Algae Removal Considering Underwater Environment Load
Authors: Joo Changdae , Kim Taekue
Published: January 2025

This study investigates the optimal design and operation of an underwater ultrasonic system for algae removal, focusing on the electromechanical load of Langevin-type piezoelectric transducers. These piezoelectric transducers, which operate in underwater environments, exhibit variations in electrical–mechanical impedance due to practical environmental factors, such as waterproof molding structures or variations in pressure and flow rates depending on the water depth. To address these challenges, we modeled the underwater load conditions using the finite element method and analyzed the impedance characteristics of the piezoelectric transducer under realistic environmental conditions. Based on this analysis, we developed an ultrasound-driven system capable of efficient output control by incorporating the impedance characteristics of the transducer under load variations and subaquatic conditions. This study proposes analytical and experimental methods for modeling and analyzing practical ultrasound-driven systems for algae removal.
The Application of Supervised Machine Learning Algorithms for Image Alignment in Multi-Channel Imaging Systems
Authors: Romanenko Kyrylo , Oberemok Yevgen , Syniavskyi Ivan , Bezugla Natalia , Komada Pawel , Bezuglyi Mykhailo
Published: January 2025

This study presents a method for aligning the geometric parameters of images in multi-channel imaging systems based on the application of pre-processing methods, machine learning algorithms, and a calibration setup using an array of orderly markers at the nodes of an imaginary grid. According to the proposed method, one channel of the system is used as a reference. The images from the calibration setup in each channel determine the coordinates of the markers, and the displacements of the marker centers in the system’s channels relative to the coordinates of the centers in the reference channel are then determined. Correction models are obtained as multiple polynomial regression models based on these displacements. These correction models align the geometric parameters of the images in the system channels before they are used in the calculations. The models are derived once, allowing for geometric calibration of the imaging system. The developed method is applied to align the images in the channels of a module of a multispectral imaging polarimeter. As a result, the standard image alignment error in the polarimeter channels is reduced from 4.8 to 0.5 pixels.
Mixed-Effects Model to Assess the Effect of Disengagements on Speed of an Automated Shuttle with Sensors for Localization, Navigation, and Obstacle Detection
Authors: Grandhi Abhinav , Gore Ninad , Pulugurtha Srinivas S.
Published: January 2025

The focus of this study is to investigate the underexplored operational effects of disengagements on the speed of an automated shuttle, providing novel insights into their disruptive impact on performance metrics. For this purpose, global positioning system data, disengagement records, weather reports, and roadway geometry data from an automated shuttle pilot program, from July to December 2023, at the University of North Carolina in Charlotte, were collected. The automated shuttle uses sensors for localization, navigation, and obstacle detection. A multi-level mixed-effects Gaussian regression model with a log-link function was employed to analyze the effect of disengagement events on the automated shuttle speed, while accounting for control variables such as roadway geometry, weather conditions, time-of-the-day, day-of-the-week, and number of intermediate stops. When these variables are controlled, disengagements significantly reduce the automated shuttle speed, with the expected log of speed decreasing by 0.803 units during such events. This reduction underscores the disruptive impact of disengagements on the automated shuttle’s performance. The analysis revealed substantial variability in the effect of disengagements across different route segments, suggesting that certain segments, likely due to varying traffic conditions, road geometries, and traffic control characteristics, pose greater challenges for autonomous navigation. By employing a multi-level mixed-effects model, this study provides a robust framework for quantifying the operational impact of disengagements. The findings serve as vital insights for advancing the reliability and safety of autonomous systems through targeted improvements in technology and infrastructure.
Safety of Oral Administration of 5-Aminolevulinic Acid Phosphate Combined with Ferrous Iron in Healthy Subjects: An Open-Label Trial
Authors: Higashikawa Fumiko , Ito Hidenori , Tanaka Tohru
Published: January 2025

The combination of 5-aminolevulinic acid (5-ALA) phosphate and sodium ferrous citrate (SFC) has been approved as an ingredient in dietary supplements in several countries, owing to its broad applicability in healthcare. This study aimed to assess the safety of oral administration of 5-ALA and SFC in healthy adults at doses several times higher than those commercially available. This study included 22 healthy subjects (11 males and 11 females) aged 21–59. Doses of 250 mg 5-ALA phosphate and 143.4 mg SFC (15 mg Fe) per day were administered orally for 28 days. Blood tests, urinalysis, and medical interviews were performed to assess safety. No test compound-related adverse events or abnormal changes were observed, except for elevated serum Fe levels, which were mild-to-moderate and transient. In conclusion, the combined oral administration of 5-ALA phosphate and SFC in healthy adults was safe and well-tolerated at the dose and duration investigated in this study.
“They Are Our Children”: An Examination of Faith-Based, Tuition-Free, Private Schools as Potential Sites of Educational Opportunity for Refugee Children in Egypt and Lebanon
Authors: Bonet Sally Wesley , Chatila Samira Nabil
Published: January 2025

(1) Background: Turning the lens away from national schooling, which has long been proven problematic for refugee populations, this comparative case study explores the educational opportunities that faith-based, tuition-free schools provide refugee youth living in protracted exile in low and middle-income neighboring countries. (2) Methods: Leveraging Shirazi and Jaffe-Walter’s concept of countertopography and Bartlett and Vavrus’s comparative case study, this article draws on ethnographic engagement (2017–2019) at “Cairo Christian Academy”, a Sudanese refugee school in Egypt, and qualitative interviews with teachers, administrators, and staff at “Beirut Covenant School” (2020–2021) in Lebanon to answer the following question: What is possible within private, faith-based, tuition-free schools—particularly schools that teach secular curricula and are open to children from all faith backgrounds, as these mirror some of the more egalitarian aspects of public education—which have absorbed refugee students as a part of their mission to care for others? (3) Results and conclusions: Our findings suggest that the funding structures, hiring practices, and moral underpinnings of these schools facilitate caring, loving environments for refugee youth while also providing educational opportunities unavailable to them otherwise in these host countries. Furthermore, our methodological approach explores ways to conduct research in contexts mired in multiple, overlapping crises.
Optimizing Muscle Performance in Young Soccer Players: Exploring the Impact of Resisted Sprint Training and Its Relationship with Distance Covered
Authors: Hermosilla-Palma Felipe , Loro-Ferrer Juan Francisco , Merino-Muñoz Pablo , Gómez-Álvarez Nicolás , Zacca Rodrigo , Cerda-Kohler Hugo , Brito Ciro , Pérez-Contreras Jorge , Portes-Junior Moacyr , Aedo-Muñoz Esteban
Published: January 2025

Background: Speed training with resisted sprints has been shown to positively affect neuromuscular performance in soccer players. Various loads, ranging from 10% to 120% of body mass, have demonstrated performance improvements across the spectrum. However, the impact of sprint distance with optimal load on these adaptive responses has yet to be thoroughly described. Objective. To analyze the influence of sprint distance in resisted sprints on muscle performance in young soccer players. Methods. This quantitative study utilized a pre-post experimental design. The sample consisted of 24 young soccer players (15.3 ± 0.68 years; 61.4 ± 7.08 kg; 1.60 ± 0.06 m) randomized into three groups (10, 20, and 30 m) and subjected to 12 sessions of resisted sprint training over six weeks. The volume was homogenized across groups, with a total distance of 120 m for each. The intervention’s effect was analyzed through performance in the isometric mid-thigh pull (IMTP), countermovement jump (CMJ), modified 505 agility test (505 m), and linear sprint tests. Differences were analyzed using a mixed ANOVA, incorporating a between-subjects factor (training group) and a within-subjects factor (pre- and post-intervention). Results. Time-dependent differences were observed in all groups for peak force (PF) (p < 0.001; η2p = 0.62), time to PF (TPF) (p < 0.001; η2p = 0.53), impulse at 50 (p < 0.001; η2p = 0.57), 100 (p < 0.001; η2p = 0.60), and 200 ms (p < 0.001; η2p = 0.67) in IMTP; jump height by impulse-momentum (p < 0.001; η2p = 0.64), rate of force development (p = 0.04; η2p = 0.14), yielding impulse (p < 0.001; η2p = 0.49), and concentric impulse (p = 0.01; η2p = 0.19) in CMJ; time (p < 0.001; η2p = 0.46) in 505 m; and average speed in linear sprint (p = 0.003; η2p = 0.36), with moderate to large effect sizes, regardless of the distance covered. No differences were observed for the interaction between the time* and group or between groups. Conclusion. Performance improvements were independent of the sprint distance, with no differences between training groups. Distances between 10 and 30 m may enhance muscle performance in young soccer players.
Reducing Product Loss Through Ventilation in Bourbon Maturation Warehouses
Authors: Schafrik Steven J. , Long Michael W. , Wedding Zachary E. , Diddle Benjamin M. , Agioutantis Zach
Published: January 2025

The aging process of bourbon within rickhouses is influenced by various environmental factors, including temperature, humidity, air flow, and air quality. Most rickhouses are not climate-controlled, and natural ventilation is a major contributor to airflow. The corrosion of the steel hoops on bourbon barrels occurs due to the presence of ethyl alcohol vapors and has become an issue for the distilling industry. The loss of a barrel or product is the loss of all of the energy and materials that went into the distillation, as well as the removal of the barrel from the secondary market. Despite the large economic and sustainability impact of barrel losses, there is limited published research with respect to corrective actions. This paper investigates airflow patterns within a bourbon rickhouse using a combination of differential pressure surveys and smoke tracing techniques to understand how natural ventilation impacts the aging process and potential for corrosion. A newly constructed rickhouse was surveyed using a micro-manometer to measure differential pressure and a sheet laser with smoke to visualize airflow. This study revealed significant zones of stagnant air and minimal recirculation within the ricks, which are the structures that hold the bourbon barrels. Airflow was found to primarily enter through windows and ground vents, moving along the walkways before exiting through other openings, with minimal penetration into the ricks. Differential pressure measurements generally indicated a lack of significant airflow, while smoke tracing showed that air entering the side of the building does not circulate into the ricks. This lack of airflow promotes the separation of ethyl alcohol vapor due to density, leading to its accumulation on the floor of the ricks. The findings of this study highlight the need to consider how rickhouse design impacts airflow and the potential for the corrosion of metal hoops on barrels due to the presence of ethyl alcohol vapor, and provide insight into optimizing the ventilation of rickhouses for more efficient and sustainable bourbon maturation.
An Approach to CO2 Emission Reduction in the Iron and Steel Industry: Research Status and Development Trends of Integrated Absorption-Mineralization Technologies
Authors: Zhang Chuanbo , Cheng Sihong , Tong Yali , Li Guoliang , Yue Tao
Published: January 2025

With the acceleration of global industrialization, the issue of carbon dioxide (CO2) emissions has become increasingly severe, highlighting the urgent need to develop effective CO2 capture and utilization technologies. CO2 absorption-mineralization technology, as an emerging method, can convert CO2 into solid minerals, achieving both long-term storage and emission reduction goals. This paper systematically reviews the latest research progress in CO2 absorption-mineralization technology, with a particular focus on its application potential and sustainability in the steel industry. Additionally, it summarizes the research status and optimization strategies of various monoamine and mixed amine absorbents and explores the main process technologies, reaction mechanisms, and key parameters of industrial CO2 mineralization. Through multiscale modeling analysis, the study delves into the reaction mechanisms and influencing factors of the mineralization process, providing theoretical support for the industrial application of the technology. The research indicates that CO2 absorption-mineralization technology not only effectively reduces greenhouse gas emissions but also offers raw materials for industries such as construction, thus promoting sustainable resource development. Although this technology shows good application prospects, it still faces key challenges in economic viability and technical feasibility during practical implementation. This paper aims to clarify the current research hotspots and challenges, providing theoretical and practical support for future large-scale application.