bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Fused Filament Fabrication Parameters on Selected Indicators for Assessing Technological Quality of Shaped Models
Authors: Łoś Marek , Zawadka Wojciech , Nadolny Krzysztof
Published: January 2025

Despite many studies, implementation of the additive manufacturing process in industrial and research practice is limited due to the numerous distortions affecting the obtained dependencies to a degree that is difficult to predict. No uniform methodology has been developed for the study of the impact of changes in the FFF parameters on the technological quality indicators. This paper presents a description of the original procedure for assessing technological quality using a reference component. The aim of the research was to analyze the impact of changes in the FFF additive manufacturing parameters on selected indicators of technological quality assessment of products. To compare the technological quality of the various models produced, measurements of surface roughness as well as dimensional and shape accuracy were carried out using stylus profilometry and coordinate measurement. The conducted tests showed that samples with a layer height of 0.12 mm have the most advantageous surface roughness parameters compared to the other layer heights of 0.16 mm and 0.20 mm tested. All the samples obtained were characterized by smaller dimensions than nominal, indicating the material shrinkage occurring during the FFF process. The study showed a negligible effect of material fill rate on surface roughness parameters as well as on the dimensions and shape accuracy. The obtained measurement results allow determining the most advantageous parameters of the FFF process depending on the adopted quality requirements.
Pedestrian Comfort Analysis and Parameterized Optimization Design for Raised Floors
Authors: Guo Juanli , Liang Haonan , Wang Jiehui , Cao Yijie
Published: January 2025

Pedestrian comfort is not only related to the health of the human body, but also directly impacts the efficiency and lifespan of building materials. Raised floors have more complex geometric characteristics and structural dynamic properties compared to traditional flooring, which necessitates an analysis of pedestrian comfort. This study explores four different configurations of raised floors in prefab bathroom units to evaluate their pedestrian comfort. Through theoretical and experimental modal analysis, the natural frequencies and potential deformation areas are identified, enabling the calculation of peak acceleration of the raised floors under walking excitation. The study then quantitatively assesses the pedestrian comfort of raised floors based on natural frequency and peak acceleration measurements, proposing an optimization design method using a multi-island genetic algorithm (MIGA). By adjusting parameters such as the support leg distance, beam shape, and support board surface layer thickness, an optimal balance between pedestrian comfort and heat transfer performance is achieved. Through the integration of simulation and experimental techniques, the study presents an efficient and cost-effective optimization design method for raised floors and explores the impact mechanism between design variables and pedestrian comfort performance.
Machine Learning-Driven Scattering Efficiency Prediction in Passive Daytime Radiative Cooling
Authors: Shi Changmin , Zheng Jiayu , Wang Ying , Gan Chenjie , Zhang Liwen , Sheldon Brian W.
Published: January 2025

Passive daytime radiative cooling (PDRC) has emerged as a promising, electricity-free cooling approach that reflects sunlight while radiating heat through the atmospheric transparent window. However, the design and optimization of PDRC materials remain challenging, requiring significant time and resources for experimental and numerical modeling efforts. In this work, we developed a machine learning (ML)-driven approach to predict scattering efficiency in the wavelength of 0.3–2.5 μm, with the aim of eventually optimizing the microstructural design of PDRC materials. By employing ML models such as linear regression, neural networks, and random forests, we aimed to predict and optimize the scattering efficiency across different pore sizes and mixed-pore-size configurations. As a result, the random forest model demonstrated superior prediction performance with minimal error, effectively capturing complex, non-linear interactions between material features. We also leveraged data transformation techniques such as one-hot encoding for generative predictions in mixed-pore-size configurations. The presented ML-driven platform serves as a valuable open resource for PDRC researchers, facilitating the rapid and cost-effective optimization of PDRC materials and accelerating the development of sustainable cooling technologies.
Excitation of ULF, ELF, and VLF Resonator and Waveguide Oscillations in the Earth–Atmosphere–Ionosphere System by Lightning Current Sources Connected with Hunga Tonga Volcano Eruption
Authors: Rapoport Yuriy G. , Grimalsky Volodymyr V. , Krankowski Andrzej , Grytsai Asen , Petrishchevskii Sergei S. , Błaszkiewicz Leszek , Chen Chieh-Hung
Published: January 2025

The simulations presented here are based on the observational data of lightning electric currents associated with the eruption of the Hunga Tonga volcano in January 2022. The response of the lithosphere (Earth)–atmosphere–ionosphere–magnetosphere system to unprecedented lightning currents is theoretically investigated at low frequencies, including ultra low frequency (ULF), extremely low frequency (ELF), and very low frequency (VLF) ranges. The electric current source due to lightning near the location of the Hunga Tonga volcano eruption has a wide-band frequency spectrum determined in this paper based on a data-driven approach. The spectrum is monotonous in the VLF range but has many significant details at the lower frequencies (ULF, ELF). The decreasing amplitude tendency is maintained at frequencies exceeding 0.1 Hz. The density of effective lightning current in the ULF range reaches the value of the order of 10−7 A/m2. A combined dynamic/quasi-stationary method has been developed to simulate ULF penetration through the lithosphere (Earth)–atmosphere–ionosphere–magnetosphere system. This method is suitable for the ULF range down to 10−4 Hz. The electromagnetic field is determined from the dynamics in the ionosphere and from a quasi-stationary approach in the atmosphere, considering not only the electric component but also the magnetic one. An analytical/numerical method has been developed to investigate the excitation of the global Schumann resonator and the eigenmodes of the coupled Schumann and ionospheric Alfvén resonators in the ELF range and the eigenmodes of the Earth–ionosphere waveguide in the VLF range. A complex dispersion equation for the corresponding disturbances is derived. It is shown that oscillations at the first resonance frequency in the Schumann resonator can simultaneously cause noticeable excitation of the local ionospheric Alfvén resonator, whose parameters depend on the angle between the geomagnetic field and the vertical direction. VLF propagation is possible over distances of 3000–10,000 km in the waveguide Earth–ionosphere. The results of simulations are compared with the published experimental data.
Vector Meson Spectrum from Top-Down Holographic QCD
Authors: Mia Mohammed , Dasgupta Keshav , Gale Charles , Richard Michael , Trottier Olivier
Published: January 2025

We elaborate on the brane configuration that gives rise to a QCD-like gauge theory that confines at low energies and becomes scale invariant at the highest energies. In the limit where the rank of the gauge group is large, a gravitational description emerges. For the confined phase, we obtain a vector meson spectrum and demonstrate how a certain choice of parameters can lead to quantitative agreement with empirical data.
On Analytical Continuation of the Horn’s Hypergeometric Functions H3 and Their Ratios
Authors: Dmytryshyn Roman , Antonova Tamara , Hladun Sofiia
Published: January 2025

This paper considers the Horn’s hypergeometric function H3, which is closely related to other hypergeometric functions and has various mathematical or physical applications. The problem of analytical extension of this function is solved using a special family of functions—branched continued fractions. A new domain of analytical extension of the Horn’s hypergeometric functions H3 and their ratios under certain conditions to real parameters are established. This paper also contains an example of the presentation and continuation of some special function and an analysis of numerical results.
Climate and Soil Properties Drive the Distribution of Minor and Trace Elements in Forest Soils of the Winter Olympic Core Area
Authors: Wu Xiaochang , Zhang Huayong , Wang Zhongyu , Tian Wang , Liu Zhao
Published: January 2025

Minor and trace elements in soil play a crucial role in regulating ecological processes that sustain the functionality of forest ecosystems. In this study, we have selected three conifer forests (Pinus sylvestris, Picea asperata, Larix principis-rupprechtii), one broadleaf forest (Betula Platyfilla) and one mixed forest of Betula Platyfilla and Larix principis-rupprechtii in the Winter Olympic core area and determined the pattern of 12 typical elements (B, Fe, V, Cr, Ni, Co, Mn, As, Cu, Zn, Sn and Se) in soils and their main drivers in the three different soil layers (A, B and C horizon) in each soil profile. Our results showed that the concentrations of B, Fe, Cr, Cu, Ni and Sn were mainly enriched in the broadleaf forest and mixed broadleaf–conifer forest zones, and the average concentrations of Co, Mn, V, Zn, As and Se were mainly enriched in coniferous forest zones in contrast. We have observed that the mean concentrations of Fe, Cr, Ni, Zn, As, Sn and Co increase with soil depth in the BP forest. The concentrations of Se and Cu were higher in the A layer than the C layer. The piecewise structural equation modeling (piecewiseSEM) results visualized a direct and negative effect on B, Fe, V, Cr and Ni concentrations due to soil temperature, while the concentrations of Se is mainly influenced by soil temperature and soil properties.
Molecular Mechanisms Underlying Substance Transport, Signal Transduction, and Anti-Stress Regulation, as Well as Anti-Alkaline Regulation via Bursicon in the Cerebral Ganglion of Chinese Mitten Crab Eriocheir sinensis Under Alkaline Stress
Authors: Wang Meiyao , Zhou Jun , Ge Jiachun , Xu Gangchun , Tang Yongkai
Published: January 2025

(1) Background: Global climate change is intensifying, and the vigorous development and utilization of saline–alkali land is of great significance. As an important economic aquatic species in the context of saline–alkali aquaculture, it is highly significant to explore the regulatory mechanisms of Eriocheir sinensis under alkaline conditions. In particular, the brain (cerebral ganglion for crustaceans) serves as a vital regulatory organ in response to environmental stress; (2) Methods: In this study, a comparative transcriptome approach was employed to investigate the key regulatory genes and molecular regulatory mechanisms in the cerebral ganglion of E. sinensis under alkaline stress. (3) Results: The results demonstrated that the cerebral ganglion of E. sinensis exhibited a positive response to acute alkaline stress. Pathways associated with signal transduction and substance transportation, such as “phagosome” and “regulation of actin cytoskeleton”, along with regulatory genes involved in antioxidation, were upregulated synergistically to maintain homeostasis under alkaline stress. Furthermore, it was discovered for the first time that bursicon plays a positive regulatory role in the adaptation of E. sinensis to alkalinity. (4) Conclusions: The present study elucidates the molecular regulatory pattern of the cerebral ganglion in E. sinensis under acute alkaline stress as well as revealing a novel role of bursicon in facilitating adaptation to alkalinity in E. sinensis, providing valuable theoretical insights into the molecular regulatory mechanisms underlying the responses of cerebral ganglia to saline–alkali environments. These findings also offer a theoretical reference for promoting the sustainable development of the E. sinensis breeding industry under saline–alkali conditions.
Identification and Characterization of a Novel Rat MAVS Variant Modulating NFκB Signaling
Authors: Nalkiran Ihsan , Sevim Nalkiran Hatice
Published: January 2025

The innate immune response serves as the primary defense against viral infections, with the recognition of viral nucleic acids by pattern recognition receptors (PRRs) initiating antiviral responses. Mitochondrial antiviral-signaling protein (MAVS) acts as a pivotal adaptor protein in the RIG-I pathway. Alternative splicing further diversifies MAVS isoforms. In this study, we identified and characterized a novel rat MAVS variant (MAVS500) with a twenty-one-nucleotide deletion, resulting in a protein seven amino acids shorter than the wild-type (WT) rat MAVS. The MAVS500 was cloned from the rat bladder cancer cell line, NBT-II, using specific primers, and subsequently sequenced. MAVS500 was overexpressed in HEK293T and NBT-II cells and then analyzed using Western Blotting and fluorescence microscopy. MAVS500 overexpression increased downstream signaling proteins, NFκβ and pNFκβ, compared to WT rat MAVS in both human and rat cell lines. Structural analysis revealed a high similarity between MAVS500 and WT rat MAVS. The seven-amino-acid deletion in MAVS500 induces significant conformational rearrangements, reducing helical turns and altering structural dynamics, which may impact its interactions with downstream signaling molecules in the innate immune pathway. The identification of MAVS500 enhances our understanding of MAVS regulation and its role in the innate immune response, providing valuable insights into alternative splicing as a mechanism for diversifying protein function.
Zootechnical and Municipal Solid Waste Digestates: Effects on Soil Nitrogen Mineralization and Kinetics
Authors: Rossi Gabriella , Beni Claudio , Socciarelli Silvia , Neri Ulderico
Published: January 2025

Soil fertilization with fertilizers derived from renewable sources is a topic of great interest in terms of the sustainable management of organic waste. To optimize the management of nitrogen supplied to the soil with digestates, it is necessary to deepen knowledge on the process of mineralization of organic nitrogen over time. In this research, a laboratory incubation system was utilized to study the impact of various digestate sources on nitrogen mineralization processes in soils and nitrogen mineralization kinetics. Six types of digestates of different origins and composition were administered to soil and the soil samples were placed under controlled conditions. The release of N was determined by measuring ammonium-N and nitrate-N concentrations in leachates during a 12-week period of incubation. The nonlinear regression technique was used to fit the cumulative leaching of total N to the Stanford and Smith first-order kinetic model during the incubation period. The results showed that the differences between digestates, nitrogen and organic carbon concentration, and C/N ratio influenced both ammonification and nitrification processes in the soil and the nitrogen mineralization kinetics. The processing of the statistical data highlighted that the potentially mineralizable nitrogen (MPN) followed first-order kinetics.
Design and Aerodynamic Analysis of a Flapping Mechanism for Foldable Biomimetic Aircraft
Authors: Yan Shuai , Zhou Yongjun , Jiang Shuxia , Xue Hao , Guo Pengcheng
Published: January 2025

This study investigates the unsteady aerodynamic mechanisms underlying the efficient flight of birds and proposes a biomimetic flapping-wing aircraft design utilizing a double-crank double-rocker mechanism. Building upon a detailed analysis of avian flight dynamics, a two-stage foldable flapping mechanism was developed, integrating an optimized double-crank double-rocker structure with a secondary linkage system. This design enables synchronized wing flapping and spanwise folding, significantly enhancing aerodynamic efficiency and dynamic performance. The system’s planar symmetric layout and high-ratio reduction gear configuration ensure movement synchronicity and stability while reducing mechanical wear and energy consumption. Through precise modeling, the motion trajectories of the inner and outer wing segments were derived, providing a robust mathematical foundation for motion control and optimization. Computational simulations based on trajectory equations successfully demonstrated the characteristic figure-eight wingtip motion. Using 3D simulations and CFD analysis, key parameters—including initial angle of attack, aspect ratio, flapping frequency, and flapping speed—were optimized. The results indicate that optimal aerodynamic performance is achieved at an initial angle of attack of 9°, an aspect ratio of 5.1, and a flapping frequency and speed of 4–5 Hz and 4–5 m/s, respectively. These findings underscore the potential of biomimetic flapping-wing aircraft in applications such as UAVs and military technology, providing a solid theoretical foundation for future advancements in this field.
Thematic Review of Endocrine Disruptors and Their Role in Shaping Pubertal Timing
Authors: Demir And , Aydin Adem , Büyükgebiz Atilla
Published: January 2025

This review examines the inconsistent effects of endocrine-disrupting chemicals (EDCs) and pollutants on pubertal timing, emphasizing the methodological challenges contributing to variability in findings. Data from nine key studies reveal that chemicals such as BPA, phthalates, and PFAS impact pubertal onset differently based on exposure timing, dosage, and sex. For instance, BPA is linked to earlier puberty in girls but delayed onset in boys, while other EDCs show mixed effects across populations. These discrepancies often arise from challenges in study design, such as the difficulty in establishing reliable control groups, accurately measuring exposures, and accounting for confounding factors like socioeconomic status, diet, and obesity. Sex-specific differences and environmental shifts during the COVID-19 pandemic, including increased indoor exposure and stress, further complicate the picture. These factors highlight the urgent need for more robust research methodologies, including standardized exposure assessments and longitudinal studies, to clarify the mechanisms driving these effects. Despite these challenges, the findings stress the importance of public health interventions, such as stricter EDC regulations, improved pollutant monitoring, and minimizing exposures during sensitive developmental windows. Addressing methodological gaps is crucial for producing reliable, actionable insights to protect adolescent development from the adverse effects of EDCs.
Genetic Tendency Analysis and Comprehensive Antioxidant Activity Evaluation of Leaves and Flowers of Loquat F1 Generation
Authors: Zhu Qixuan , Li Xiaoying , Ge Hang , Wang Zhixuan , Wang Binjun , Chen Junwei , Xu Hongxia
Published: January 2025

Loquat leaves, flowers, and other organs contain abundant antioxidant substances, which have wide applications in medicine, health, and food industries. This study aims to provide theoretical guidance for loquat hybrid parent and combination selection and a basis for high-quality loquat strain screening and development. For comprehensive antioxidant profiling, we used “Ninghaibai” and “Oobusa” loquat and their F1 generation as experimental materials to determine the total phenol, flavonoid, DPPH, ABTS, and FRAP content in the leaves and flowers of 56 strains. Five traits, including total phenols, flavonoids, DPPH, ABTS, and FRAP, were widely separated and normally distributed in the flowers of 56 F1 loquat strains, exhibiting the genetic basis of these quantitative traits. However, these traits displayed widely separated and slightly skewed distribution in the leaves of the F1 generation. The total phenols, flavonoids, DPPH, and FRAP showed a trend of small inheritance in the leaves. However, the ABTS showed a trend of medium and high inheritance in leaves and flowers, respectively. Through cluster and principal component analyses, a comprehensive antioxidant activity evaluation was conducted. Ten strains with comprehensive scores greater than 1 for antioxidant activity in leaves and flowers were selected. Among them, the top three strains with high antioxidant capacity were ND107, “Oobusa”, and ND128. These results suggest that hybrid breeding guided by the genetic characteristics of each trait can improve the possibility of cultivating new varieties with high antioxidant activity.
Estimating Switchgrass Biomass Yield and Lignocellulose Composition from UAV-Based Indices
Authors: Wasonga Daniel , Jang Chunhwa , Lee Jung Woo , Vittore Kayla , Arshad Muhammad Umer , Namoi Nictor , Zumpf Colleen , Lee DoKyoung
Published: January 2025

Innovative methods for estimating commercial-scale switchgrass yields and feedstock quality are essential to optimize harvest logistics and biorefinery efficiency for sustainable aviation fuel production. This study utilized vegetation indices (VIs) derived from multispectral images to predict biomass yield and lignocellulose concentrations of advanced bioenergy-type switchgrass cultivars (“Liberty” and “Independence”) under two N rates (28 and 56 kg N ha−1). Field-scale plots were arranged in a randomized complete block design (RCBD) and replicated three times at Urbana, IL. Multispectral images captured during the 2021–2023 growing seasons were used to extract VIs. The results show that linear and exponential models outperformed partial least square and random forest models, with mid-August imagery providing the best predictions for biomass, cellulose, and hemicellulose. The green normalized difference vegetation index (GNDVI) was the best univariate predictor for biomass yield (R2 = 0.86), while a multivariate combination of the GNDVI and normalized difference red-edge index (NDRE) enhanced prediction accuracy (R2 = 0.88). Cellulose was best predicted using the NDRE (R2 = 0.53), whereas hemicellulose prediction was most effective with a multivariate model combining the GNDVI, NDRE, NDVI, and green ratio vegetation index (GRVI) (R2 = 0.44). These findings demonstrate the potential of UAV-based VIs for the in-season estimation of biomass yield and cellulose concentration.
Combining Cocatalyst and Oxygen Vacancy to Synergistically Improve Fe2O3 Photoelectrochemical Water Oxidation Performance
Authors: Liu Chen , Li Jiajuan , Zhang Wenyao , Zhu Changqing
Published: January 2025

Considering the poor conductivity of Fe2O3 and the weak oxygen evolution reaction associated with it, surface hole accumulation leads to electron hole pair recombination, which inhibits the photoelectrochemical (PEC) performance of the Fe2O3 photoanode. Therefore, the key to improving the PEC water oxidation performance of the Fe2O3 photoanode is to take measures to improve the conductivity of Fe2O3 and accelerate the reaction kinetics of surface oxidation. In this work, the PEC performances of Fe2O3 photoanodes are synergistically improved by combining loaded an FeOOH cocatalyst and oxygen vacancy doping. Firstly, amorphous FeOOH layers are successfully prepared on Fe2O3 nanostructures through simple photoassisted electrodepositon. Then oxygen vacancies are introduced into FeOOH-Fe2O3 through plasma vacuum treatment, which reduces the content of Fe-O (OL) and Fe-OH (-OH), jointly promoting the generation of oxygen vacancies. Oxygen vacancy can increase the concentration of most carriers in Fe2O3 and form photo-induced charge traps, promoting the separation of electron holes and enhancing the conductivity of Fe2O3. The other parts of -OH act as oxygen evolution catalysts to reduce the reaction obstacle of water oxidation and promote the transfer of holes to the electrode/electrolyte interface. The performance of FeOOH-Fe2O3 after plasma vacuum treatment has been greatly improved, and the photocurrent density is about 1.9 times higher than that of the Fe2O3 photoanode. The improvement in the water oxidation performance of PEC is considered to be the synergistic effect of the cocatalyst and oxygen vacancy. All outstanding PEC response characteristics show that the modification of the cocatalyst and oxygen vacancy doping represent a favorable strategy for synergistically improving Fe2O3 photoanode performance.
Psychosocial Distress and the Quality of Life of Cancer Patients in Rural Hospitals in Limpopo Province: A Qualitative Study
Authors: Ramathuba Dorah Ursula , Ramutumbu Neo Jacqueline
Published: January 2025

Background: The diagnosis and treatment of cancer are associated with substantial physical, psychological, and social morbidity for most patients. Distress can be seen as an unpleasant experience of an emotional, psychological, social, or spiritual nature that interferes with the ability to cope with cancer treatment. Purpose: The aim was to understand patients’ experiences of distress in their context and to analyze and interpret the findings. Method: An explorative, descriptive qualitative study was conducted among cancer patients receiving treatment and care at rural hospitals in Limpopo. A face-to-face individual interview was conducted to determine the participants’ cancer-related experiences and quality of life. Thematic analysis was conducted following Tesch’s method, and the themes developed were subjected to a triangulation process to ensure the validity and rigor of the findings. Findings: The participants revealed experiences of symptomatic distress resulting in biopsychosocial distress such as pain, fatigue, emotional distress related to prognosis and uncertainty about the future, psychosocial distress related to a lack or absence of support, financial instability, and poor self-esteem. Conclusions: Cancer patients face many challenges during their treatment journey. Participants were drained by anxiety and uncertainty of the cancer trajectory and required psychosocial support. The oncology team must provide supportive preventive measures for side effects management and culture-sensitive psychotherapy at an early stage to improve their quality of life.
Greening up the City with Native Species: Challenges and Solutions
Authors: Hardberger Amy , Craig Danielle , Simpson Catherine , Cox Robert D. , Perry Gad
Published: January 2025

Urban green spaces provide many benefits, including to human wellbeing, ecosystem services, and urban wildlife. Thus, there are many reasons to green up urban spaces, especially by using native species. Furthermore, urban green spaces are suited to enhancing biodiversity without negatively impacting food or fiber production. Municipalities and private landowners invest substantially in landscaping and its maintenance. However, much of that outlay supports non-native plants that may be less adapted to local conditions such as rainfall patterns and temperature ranges, thus having greater resource requirements, as well as being less supportive of native wildlife and possessing a greater potential of becoming invasive. Here, we explore ways to increase the use of native plant species in urban settings to reduce the need for watering or chemical application, enhance the support of native species, and reduce the risk of invasion to urban and ex-urban habitats. We identify three main impediments: the perception of native species as less aesthetically pleasing, the availability of native plants in the nursery industry, and the willingness of policymakers to take supportive measures. We propose methods to address all three, providing successful examples from a number of US localities and a case study that demonstrates what drivers might exist and what actions remain to be taken.
Advanced Path Planning for UAV Swarms in Smart City Disaster Scenarios Using Hybrid Metaheuristic Algorithms
Authors: Adam Mohammed Sani , Abdullah Nor Fadzilah , Abu-Samah Asma , Amodu Oluwatosin Ahmed , Nordin Rosdiadee
Published: January 2025

In disaster-stricken areas, rapid restoration of communication infrastructure is critical to ensuring effective emergency response and recovery. Swarm UAVs, operating as mobile aerial base stations (MABS), offer a transformative solution for bridging connectivity gaps in environments where the traditional infrastructure has been compromised. This paper presents a novel hybrid path planning approach combining affinity propagation clustering (APC) with genetic algorithms (GA), aimed at maximizing coverage, and ensuring quality of service (QoS) compliance across diverse environmental conditions. Comprehensive simulations conducted in suburban, urban, dense urban, and high-rise urban environments demonstrated the efficacy of the APC-GA approach. The proposed method achieved up to 100% coverage in suburban settings with only eight unmanned aerial vehicle (UAV) swarms, and maintained superior performance in dense and high-rise urban environments, achieving 97% and 93% coverage, respectively, with 10 UAV swarms. The QoS compliance reached 98%, outperforming benchmarks such as GA (94%), PSO (90%), and ACO (88%). The solution exhibited significant stability, maintaining consistently high performance, highlighting its robustness under dynamic disaster scenarios. Mobility model analysis further underscores the adaptability of the proposed approach. The reference point group mobility (RPGM) model consistently achieved higher coverage rates (95%) than the random waypoint model (RWPM) (90%), thereby demonstrating the importance of group-based mobility patterns in enhancing UAV deployment efficiency. The findings reveal that the APC-GA adaptive clustering and path planning mechanisms effectively navigate propagation challenges, interference, and non-line-of-sight (NLOS) conditions, ensuring reliable connectivity in the most demanding environments. This research establishes the APC-GA hybrid as a scalable and QoS-compliant solution for UAV deployment in disaster response scenarios. By dynamically adapting to environmental complexities and user mobility patterns, it advances state-of-the-art emergency communication systems, offering a robust framework for real-world applications in disaster resilience and recovery.
Safety-Critical Trajectory Tracking Control with Safety-Enhanced Reinforcement Learning for Autonomous Underwater Vehicle
Authors: Li Tianli , Tao Jiaming , Hu Yu , Chen Shiyu , Wei Yue , Zhang Bo
Published: January 2025

This paper investigates a novel reinforcement learning (RL)-based quadratic programming (QP) method for the safety-critical trajectory tracking control of autonomous underwater vehicles (AUVs). The proposed approach addresses the substantial challenge posed by model uncertainty, which may hinder the safety and performance of AUVs operating in complex underwater environments. The RL framework can learn the inherent model uncertainties that affect the constraints in Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs). These learned uncertainties are subsequently integrated for formulating a novel RL-CBF-CLF Quadratic Programming (RL-CBF-CLF-QP) controller. Corresponding simulations are demonstrated under diverse trajectory tracking scenarios with high levels of model uncertainties. The simulation results show that the proposed RL-CBF-CLF-QP controller can significantly improve the safety and accuracy of the AUV’s tracking performance.
Statistical Complexity Analysis of Sleep Stages
Authors: Duarte Cristina D. , Pacheco Marianela , Iaconis Francisco R. , Rosso Osvaldo A. , Gasaneo Gustavo , Delrieux Claudio A.
Published: January 2025

Studying sleep stages is crucial for understanding sleep architecture, which can help identify various health conditions, including insomnia, sleep apnea, and neurodegenerative diseases, allowing for better diagnosis and treatment interventions. In this paper, we explore the effectiveness of generalized weighted permutation entropy (GWPE) in distinguishing between different sleep stages from EEG signals. Using classification algorithms, we evaluate feature sets derived from both standard permutation entropy (PE) and GWPE to determine which set performs better in classifying sleep stages, demonstrating that GWPE significantly enhances sleep stage differentiation, particularly in identifying the transition between N1 and REM sleep. The results highlight the potential of GWPE as a valuable tool for understanding sleep neurophysiology and improving the diagnosis of sleep disorders.
Risk Modeling for the Emergence of the Primary Outbreak Area of the Siberian Moth Dendrolimus sibiricus Tschetv. in Coniferous Forests of Central Siberia
Authors: Goroshko Andrey A. , Sultson Svetlana M. , Ponomarev Evgenii I. , Demidko Denis A. , Slinkina Olga A. , Mikhaylov Pavel V. , Tatarintsev Andrey I. , Kulakova Nadezhda N. , Khizhniak Natalia P.
Published: January 2025

In the southern taiga of Siberia, periodic outbreaks of the Siberian moth Dendrolimus sibrircus Tschetv. have been observed. The outbreaks result in the defoliation of Siberian fir Abies sibirica Ledeb. and Siberian pine Pinus sibirica Du Tour. stands across approximately one million hectares, leading to dieback of the affected forests. This is largely attributable to the inability to promptly identify the onset of the pest population growth in a timely manner, particularly in the context of expansive forest areas with limited accessibility. It is feasible to enhance the efficacy of monitoring Siberian moth populations by discerning stands with the highest propensity for damage and concentrating efforts on these areas. To achieve this, we employed machine learning techniques, specifically gradient boosting, support vector machines, and decision trees, training models on two sets of predictors. One of the datasets was obtained through a field study conducted in forest stands during the previous outbreak of the Siberian moth (2015–2018), while the other was derived from the analysis of remote sensing data during the same period. In both 2015 and 2016, the defoliation was most accurately predicted using gradient boosting (XGB algorithm), with ROC-AUC values reaching 0.89–0.94. The most significant predictors derived from the ground data were the proportions of Siberian fir, Siberian spruce Picea obovata Ledeb., and Scots pine Pinus sylvestris L., phytosociological data, tree age, and site quality. Among the predictors obtained from the analysis of remote sensing data, the distance to disturbed forest stands was identified as the most significant, while the proportion of dark coniferous species (A. sibirica, P. sibirica, or Picea obovata Ledeb.), the influx of solar radiation (estimated through the CHILI index), and the position in the relief (mTPI index) were also determined to be important.
Biopolymers Derived from Forest Biomass for the Sustainable Textile Industry
Authors: Dias Juliana C. , Marques Susana , Branco Pedro C. , Rodrigues Thomas , Torres Cristiana A. V. , Freitas Filomena , Evtyugin Dmitry V. , Silva Carla J.
Published: January 2025

In line with environmental awareness movements and social concerns, the textile industry is prioritizing sustainability in its strategic planning, product decisions, and brand initiatives. The use of non-biodegradable materials, obtained from non-renewable sources, contributes heavily to environmental pollution throughout the textile production chain. As sustainable alternatives, considerable efforts are being made to incorporate biodegradable biopolymers derived from residual biomass, with reasonable production costs, to replace or reduce the use of synthetic petrochemical-based polymers. However, the commercial deployment of these biopolymers is dependent on high biomass availability and a cost-effective supply. Residual forest biomass, with lignocellulosic composition and seasonably available at low cost, constitutes an attractive renewable resource that might be used as raw material. Thus, this review aims at carrying out a comprehensive analysis of the existing literature on the use of residual forest biomass as a source of new biomaterials for the textile industry, identifying current gaps or problems. Three specific biopolymers are considered: lignin that is recovered from forest biomass, and the bacterial biopolymers poly(hydroxyalkanoates) (PHAs) and bacterial cellulose (BC), which can be produced from sugar-rich hydrolysates derived from the polysaccharide fractions of forest biomass. Lignin, PHA, and BC can find use in textile applications, for example, to develop fibers or technical textiles, thus replacing the currently used synthetic materials. This approach will considerably contribute to improving the sustainability of the textile industry by reducing the amount of non-biodegradable materials upon disposal of textiles, reducing their environmental impact. Moreover, the integration of residual forest biomass as renewable raw material to produce advanced biomaterials for the textile industry is consistent with the principles of the circular economy and the bioeconomy and offers potential for the development of innovative materials for this industry.
Impact of Solid Particle Concentration and Liquid Circulation on Gas Holdup in Counter-Current Slurry Bubble Columns
Authors: Mahmoudi Sadra , Hlawitschka Mark W.
Published: January 2025

In this study, in a three-phase reactor with a rectangular cross-section, the effects of liquid circulation rates and solid particle concentration on gas holdup and bubble size distribution (BSD) were investigated. Air, water, and glass beads were used as the gas, liquid, and solid phases, respectively. Different liquid circulation velocities and different solid loads were applied. The results demonstrate that increasing solid content from 0% to 6% can decrease gas holdup by 50% (due to increased slurry phase viscosity and promotion of bubble coalescence). Also, increasing the liquid circulation rate showed a weak effect on gas holdup, although a slight incremental effect was observed due to the promotion of bubble breakup and the extension of bubble residence time. The gas holdup in counter-current slurry bubble columns (CCSBCs) was predicted using a novel correlation that took into account the combined effects of solid concentration and liquid circulation rate. These findings are crucial for the design and optimization of the three-phase reactors used in industries such as mining and wastewater treatment.
Characteristics and Functional Properties of Bioactive Oleogels: A Current Review
Authors: Ferdaus Md. Jannatul , Mahmud Niaz , Talukder Sudipta , Silva Roberta Claro da
Published: January 2025

Oleogels have been a revolutionary innovation in food science in terms of their health benefits and unique structural properties. They provide a healthier alternative to traditional solid or animal fats. They have improved oxidative stability and nutritional value to maintain the desirable sensory qualities of lipid-based foods. Moreover, oleogels offer an ideal carrier for poorly water-soluble bioactive compounds. The three-dimensional structure of oleogels can protect and deliver bioactive compounds in functional food products. Bioactive compounds also affect the crystalline behavior of oleogelators, the physical properties of oleogels, and storage stability. Generally, different incorporation techniques are applied to entrap bioactive compounds in the oleogel matrix depending on their characteristics. These approaches enhance the bioavailability, controlled release, stability of bioactive compounds, and the shelf life of oleogels. The multifunctionality of oleogels extends their applications beyond fat replacements, e.g., food preservation, nutraceutical delivery, and even novel innovations like 3D food printing. Despite their potential, challenges such as large-scale production, cost efficiency, and consumer acceptance remain areas for further exploration. This review emphasizes the understanding of the relationship between the structure of oleogels and their functional properties to optimize their design in different food applications. It also highlights the latest advancements in bioactive oleogels, focusing on how they incorporate bioactive compounds such as polyphenols, essential oils, and flavonoids into oleogels. The impact of these compounds on the gelation process, storage stability, and overall functionality of oleogels is also critically examined.
Genome Sequencing Reveals the Potential of Enterobacter sp. Strain UNJFSC003 for Hydrocarbon Bioremediation
Authors: Castillo Gianmarco , Contreras-Liza Sergio Eduardo , Arbizu Carlos I. , Rodriguez-Grados Pedro Manuel
Published: January 2025

Bioremediation induced by bacteria offers a promising alternative for the contamination of aromatic hydrocarbons due to their metabolic processes suitable for the removal of these pollutants, as many of them are carcinogenic molecules and dangerous to human health. Our research focused on isolating a bacterium from the rhizosphere of the tara tree with the ability to degrade polycyclic aromatic hydrocarbons, using draft genomic sequencing and computational analysis. Enterobacter sp. strain UNJFSC 003 possesses 4460 protein-coding genes, two rRNA genes, 77 tRNA genes, and a GC content of 54.38%. A taxonomic analysis of our strain revealed that it has an average nucleotide identity (ANI) of 87.8%, indicating that it is a new native Enterobacteria. Additionally, a pangenomic analysis with 15 strains demonstrated that our strain has a phylogenetic relationship with strain FDAARGOS 1428 (Enterobacter cancerogenus), with a total of 381 core genes and 4778 accessory genes. Orthologous methods predicted that strain UNJFSC 003 possesses genes with potential for use in hydrocarbon bioremediation. Genes were predicted in the sub-pathways for the degradation of homoprotocatechuate and phenylacetate, primarily located in the cytoplasm. Studies conducted through molecular modeling and docking revealed the affinity of the predicted proteins in the degradation of benzo[a]pyrene in the homoprotocatechuate sub-pathway, specifically hpcB, which has enzymatic activity as a dioxygenase, and hpcC, which functions as an aldehyde dehydrogenase. This study provides information on native strains from Lomas de Lachay with capabilities for the bioremediation of aromatic hydrocarbons and other compounds.
Root Penetration Is Associated with Root Diameter and Root Growth Rate in Tropical Forage Grasses
Authors: Huot Chanthy , Philp Joshua N. M. , Zhou Yi , Denton Matthew D.
Published: January 2025

Soil compaction impedes root exploration by plants, which limits access to nutrients and water, ultimately compromising survival. The capability of roots to penetrate hard soils is therefore advantageous. While root penetration has been studied in various annual crops, the relationships between root growth and root penetration are poorly understood in tropical perennial grasses. This study aimed to compare root penetration capability in 10 tropical perennial forage grasses and identify relationships between root penetration, root diameter and vertical root growth. Root penetration of each species, namely Urochloa (syn. Brachiaria) brizantha cv. Mekong Briz, U. decumbens cv. Basilisk, U. humidicola cv. Tully, U. hybrid cv. Mulato II, U. mosambicensis cv. Nixon, U. ruziziensis cv Kennedy, Panicum coloratum cv. Makarikariense, Megathyrsus maximus (syn. Panicum maximum) cv. Tanzânia, Paspalum scrobiculatum (syn. Paspalum coloratum) cv. BA96 10 and Setaria sphacelata cv Solendar, was evaluated using wax layers of varying resistances, created from a mixture of 40% (1.39 MPa) and 60% (2.12 MPa) paraffin wax, combined with petroleum jelly. Reference root sizes were determined for the grass species by measuring root diameter and root lengths of seedlings grown in growth pouches. Vertical root growth rate for each species was measured in grasses grown in 120 cm deep rhizotrons. Species with greater root penetration at both resistances had significantly higher shoot growth rates (r = 0.65 at 40% wax and 0.66 at 60% wax) and greater root diameters (r = 0.67 at 40% wax and 0.68 at 60% wax). Root penetration was significantly higher in species with greater vertical root growth rate only in the 60% wax treatment (r = 0.82). Root penetration at higher resistance was correlated with the root diameter and rapid vertical root growth of the species. This may indicate a contribution of these traits to root penetration ability. The combination of greater root diameter and root vertical growth rate, as observed in M. maximus, may assist in the identification of perennial forage grasses suitable for agroecosystems challenged by soil compaction and rapidly drying soil surface.
The Effect of Long-Term Cryopreservation on the Properties and Functionality of Platelet-Rich Plasma
Authors: Beitia Maider , Guadilla Jorge , Mercader Ruiz Jon , Marijuan Pinel Daniel , Sánchez Pello , Iriondo Ane , Andrade Renato , Espregueira-Mendes João , Delgado Diego , Sánchez Mikel
Published: January 2025

Platelet-Rich Plasma (PRP) is a biological treatment widely used in regenerative medicine for its restorative capacity. Although PRP is typically applied at the time of obtention, long-term storage and preservation could enhance its versatility and clinical applications. The objective of this study was to evaluate the effect of long-term freezing on PRP. For that, PRP and Platelet Lysates (PL) were collected and preserved at −20 °C and −80 °C for 6 and 12 months. The parameters analyzed included platelet count and size, fibrinogen levels, platelet activation percentage, growth factor (GF) levels, and bioactivity on cultured dermal fibroblasts. No significant changes in platelet count were found; however, variations in platelet size were observed. Platelets stored at −20 °C and −80 °C showed structural changes and increased activation over time, including membrane roughness and possible aggregation. GF analysis revealed a reduction in platelet-derived growth factors (PDGF-AB and VEGF), while extraplatelet factors like IGF-1 remained stable. Fibroblast cultures showed comparable cell viability when exposed to fresh and cryopreserved PRP and PL samples. These findings suggest that cryopreserving PRP at −20 °C or −80 °C for up to 12 months is a feasible approach for retaining its therapeutic potential, supporting its use in biobanking, and expanding clinical accessibility.
Comparative Analysis of Viral Load Quantification Using Reverse Transcription Polymerase Chain Reaction and Digital Droplet Polymerase Chain Reaction
Authors: Gebe Abreu Cabral Paula , Bastos de Souza Sávio , Ferraz Arruda Raul , Passos de Figueiredo Cabral Sheila , Leone Evangelista Monteiro de Assis Arícia , Porto Muniz Martins Yolanda , Brazil Viana Junior Antônio , Chang Junbiao , Lei Pingsheng , Martins da Silva Renato
Published: January 2025

In the year 2019, a highly virulent coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged, precipitating the outbreak of the illness known as coronavirus disease 2019 (COVID-19). The commonly employed reverse transcription polymerase chain reaction (RT-qPCR) methodology serves to estimate the viral load in each patient’s sample by employing a standard curve. However, it is imperative to recognize that this technique exhibits limitations with respect to clinical diagnosis and therapeutic applications, since an advancement of the conventional polymerase chain reaction methods, digital polymerase chain reaction (digital PCR or DDPCR), enables the direct quantification and clonal amplification of nucleic acid strands. The primary divergence between dPCR and traditional PCR resides in their approaches to measuring nucleic acid quantities. In this study, we investigated the viral loads of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) within 461 participants. By employing both RT-qPCR and DDPCR techniques, we established a comparison between the quantification methodologies of the two approaches. Our findings illustrate that the quantification through DDPCR affords a superior means of monitoring viral load within lower respiratory tract samples, thus enhancing the assessment of disease progression, particularly in scenarios characterized by low viral loads.