bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of Carbon on the Crystallization and Electrochemical Behavior of Portland Cement
Authors: Cho Jeunghyeuon , Shin Byung-Hyun , You Miyoung , Kim Seongjun , Park Jinyong , Ok Jung-Woo , Hong Jonggi , Lee Taekyu , Bae Jong-Seong , Song Pungkeun , Yoon Jang-Hee
Published: February 2025

Cement is one of the most widely used structural materials and serves as the primary component of concrete. Among the various types, Portland cement is the most commonly utilized due to its excellent strength and corrosion resistance. Recently, efforts have been made to incorporate various functional additives into Portland cement to impart new properties; however, studies on the resulting changes in corrosion resistance remain insufficient. While the existing research has largely focused on impurities in cement, systematic studies on the effects of interstitial elements on the crystallization and electrochemical behavior of cement are scarce. This study investigates the influence of carbon (C) addition on the crystallographic structure and electrochemical properties of Portland cement. C concentrations from 0 to 10 wt.% were added. The microstructure and crystallographic structure with different C concentrations were analyzed using FE-SEM and XRD. The bonding characteristics of cement components according to the C composition were measured using XPS, hardness was measured using Vickers hardness, and electroconductivity was calculated using a 4-point probe. The electrochemical behavior was evaluated according to the ASTM G 61 standards through OCP, EIS, and potentiodynamic polarization tests. As the composition of C increased, the number of voids and cracks decreased, while the electrical conductivity increased from 1.7 × 10−4 to 4.3 × 10−2. Additionally, the resistance tended to decrease with the increase in C composition. Therefore, the concentration of C needs to be controlled depending on the required function of the cement.
Kinetics of Reduction of Iron Ore Powder by Industrial Lignin from Pulping and Papermaking Waste Biomass Energy
Authors: Zhou Wendi , Xiang Dongwen , Zhang Qiang , Wu Guoqing , Wang Yajie , Li Dong , Zhang Qinghua , Hu Huaxin
Published: February 2025

To explore the application of industrial lignin, a waste biomass resource, in the field of metallurgy, the kinetic behavior of iron ore powder reduction by Shenmu bituminous coal, Lu’an anthracite, and industrial lignin under different carbon–oxygen molar ratios (nc:no = 0.5, 0.7, 1.0, 1.2, and 1.5) was studied using a thermogravimetric analyzer and reduction furnace. The results show that the reduction process of iron ore powder with three reducing agents conforms to the D1 model, that is, the kinetic equation is G(α)=α2. Under the same carbon–oxygen molar ratio, the activation energy of the iron ore powder reduced by industrial lignin is lower than that of pulverized coal. The activation energy increases first, then decreases and then increases with the increase in the carbon–oxygen molar ratio. When the molar ratio of carbon to oxygen is 1.2, the reaction activation energy is the lowest. At this time, the reaction activation energy of industrial lignin reduction iron ore powder is 14.21 kJ·mol−1, that of Shenmu bituminous coal is 16.81 kJ·mol−1, and that of Lu’an anthracite is 37.13 kJ·mol−1.
DNA Metabarcoding Using Indexed Primers: Workflow to Characterize Bacteria, Fungi, Plants, and Arthropods from Environmental Samples
Authors: Tiedge Teresa M. , Rabasco Jorden T. , Meiklejohn Kelly A.
Published: February 2025

Environmental DNA from bulk materials can be analyzed to gain an understanding of the bacterial, fungal, plant, and/or arthropod communities present. DNA metabarcoding is widely used to characterize these biological communities, by amplifying “barcode” regions and sequencing these amplicons via next-generation sequencing. The Earth Microbiome Project (EMP) adopted the use of indexed primers, PCR primers containing Illumina® adapter sequences and a unique 12-nucleotide Golay barcode to simplify the identification of bacterial taxa via the 16S barcode. We sought to develop a wet laboratory workflow utilizing indexed primers that could cost-effectively reduce bench time while simultaneously targeting multiple DNA barcode regions to characterize bacterial (16S), fungal (ITS1), plant (ITS2, trnL p6 loop), and arthropod (COI) communities. The EMP primer constructs for 16S were modified to accommodate our DNA barcode regions of interest while also permitting successful demultiplexing following sequencing. A single indexed primer pair was designed for ITS1 and trnL p6 loop, and two primer pairs were developed for ITS2 and COI. To test the workflow, a total of 648 soil and 336 dust samples were processed, with key steps including DNA isolation, total DNA quantification, amplification with indexed primers, library purification and quantification, and Illumina MiSeq sequencing. Based on raw read counts and analysis of positive controls, the trnL p6 loop and ITS2 a primer pairs performed comparably to the originally designed 16S primers. Both COI primers pairs, ITS1 and ITS2 b primers, had lower raw reads compared to the other three primer pairs. The combination of the three plant targets successfully recovered all plant taxa in the positive controls except for Nephrolepis exaltata [Nephrolepidaceae] and the COI primers recovered all arthropod taxa except for the beetle. Notably, none of the taxa in the fungal positive control were recovered using ITS1. For environmental samples, sequencing was successful for all primers except COI c, and primer biases were observed for all three plant primers, in which a small number of families were uniquely amplified for each primer pair. This workflow can be applied to many disciplines that utilize DNA metabarcoding given its customizability and flexibility with Illumina sequencing chemistry.
Congenital Heart Disease After Mid-Age: From the “Grown-Up” to the Elderly
Authors: Bonanni Francesca , Servoli Chiara , Spaziani Gaia , Bennati Elena , Di Filippo Chiara , Cirri Giulia Ksenia , Giaccardi Marzia , Olivotto Iacopo , Favilli Silvia
Published: February 2025

Early surgery and improved medical care have led to the increased survival of neonates with congenital heart disease (CHD), who now commonly reach adulthood. Among adults with CHD, a growing subgroup is represented by middle-aged and even elderly patients. In this elderly population, acquired cardiac and extracardiac comorbidities represent the main cause of morbidity and mortality; the control and correction of cardiovascular risk factors or an appropriate check for extracardiac complications (such as malignancies) is therefore of paramount importance. Complications and frailty syndrome appear to occur earlier in ACHD than in the general population due to a frequent discrepancy between chronological and biological age. Multiple stressors throughout life (hemodynamic abnormalities, cardiac operations and interventional procedures, the placement of foreign materials) that result in a chronic inflammatory response are among the leading causes of premature senescence. This review is aimed at assessing the characteristics and special needs of this elderly ACHD population with a view to proposing novel models for the organization of extended care.
Knowledge and Predictors of Vitamin D Awareness Among Greek Women: A Cross-Sectional Study
Authors: Voulgaridou Gavriela , Athanassiou Fani , Kravvariti Eirini , Doulgeraki Stephania , Papadopoulou Sousana K. , Kokokiris Lambros E.
Published: February 2025

Background: Vitamin D plays a crucial role in bone health, calcium absorption, and immune function, yet significant misconceptions and knowledge gaps persist. This study aimed to assess knowledge regarding vitamin D among Greek women and identify factors associated with vitamin D knowledge. Methods: A cross-sectional study was conducted among 761 Greek women (mean age: 41.2 ± 7.7 years) using an online self-administered questionnaire designed in Google Forms. Participants were recruited via social media platforms to ensure a geographically diverse sample. Results: Overall, 57.4% of participants demonstrated knowledge of vitamin D’s functions, primarily linking it to bone health (34.4%) and immune function (26.8%). The multiple regression model identified significant predictors of knowledge of vitamin D’s functions, including age (OR = 1.041, 95% CI: 1.019–1.062, p < 0.001), weight (OR = 0.964, 95% CI: 0.938–0.992, p = 0.010), and frequent vitamin D testing (>2 times: OR = 2.280, 95% CI: 1.392–3.736, p = 0.001; once–twice: OR = 1.776, 95% CI: 1.111–2.829, p = 0.016). Furthermore, age (OR = 1.054, 95% CI: 1.027–1.081, p < 0.001), weight (OR = 0.987, 95% CI: 0.975–0.999, p = 0.028), higher city population (>50,000 citizens: OR = 1.598, 95% CI: 1.021–2.502, p = 0.040), frequent vitamin D testing (>2 times: OR = 2.616, 95% CI: 1.529–4.447, p < 0.003; one–two times: OR = 1.773, 95% CI: 1.052–2.989, p = 0.032), and children’s supplementation (OR = 1.414, 95% CI: 1.007–1.987, p = 0.046) were significant predictors of knowledge regarding diseases preventable by vitamin D. Conclusions: Greek women demonstrated moderate awareness of vitamin D’s functions, but significant knowledge gaps persist, particularly regarding its role in calcium absorption and dietary sources. Age, frequent vitamin D testing, and urban residence were significant predictors of knowledge. Targeted public health campaigns are essential to address misconceptions and improve vitamin D awareness and practices.
Understanding the Burden and Management of Urinary Tract Infections in Women
Authors: Baimakhanova Baiken , Sadanov Amankeldi , Trenozhnikova Lyudmila , Balgimbaeva Assya , Baimakhanova Gul , Orasymbet Saltanat , Tleubekova Diana , Amangeldi Alma , Turlybaeva Zere , Nurgaliyeva Zhanar , Seisebayeva Roza , Kozhekenova Zhanat , Sairankyzy Saltanat , Shynykul Zhanserik , Yerkenova Sandugash , Turgumbayeva Aknur
Published: February 2025

Urinary tract infections (UTIs) represent a prevalent health concern among the female population, with anatomical and physiological determinants such as a shorter urethra and its proximity to the rectum augmenting vulnerability. The presence of Escherichia coli and various other pathogens plays a significant role in the etiology of these infections, which can be aggravated by sexual intercourse and disturbances to the vaginal microbiome. The physiological alterations associated with pregnancy further elevate the likelihood of UTIs, with untreated cases potentially leading to severe complications such as pyelonephritis, preterm labor, and stillbirth. Furthermore, postmenopausal women encounter an augmented risk of UTIs attributable to estrogen deficiency and vaginal atrophy, as well as conditions including pelvic organ prolapse (POP) and urinary incontinence (UI), which hinder optimal bladder functionality. The aforementioned factors, in conjunction with the rising prevalence of cesarean deliveries and catheterization, complicate the management of UTIs. While precise diagnosis is paramount, it remains a formidable challenge, notwithstanding advancements in molecular diagnostic techniques. Management strategies encompass antibiotic-sparing therapies; however, the increasing incidence of multidrug resistance represents an alarming trend. Diverse guidelines from various medical specialties endeavor to standardize treatment approaches, yet significant inconsistencies continue to exist. This study systematically appraises the extant guidelines, evaluating the quality of evidence while identifying areas of agreement and discord to supply practitioners with effective strategies for UTI management.
Dynamic Plasticity and Fracture of Al 7075 and V95T1 Alloys: High-Velocity Impact Experiments
Authors: Rodionov Egor S. , Cherepanov Andrey Ya. , Fazlitdinova Alfiya G. , Sultanov Timur T. , Lupanov Victor G. , Mayer Polina N. , Mayer Alexander E.
Published: February 2025

A novel method to measure dynamic flow stress and corresponding strain rates obtained from Taylor tests using profiled samples with a reduced cylindrical head part was applied to study the dynamic characteristics of similar commercial 7075 and V95T1 aluminum alloys. The measured dynamic flow stress is verified using a classical Taylor’s approach with uniform cylinders and compared with the literature data. Our study shows that the dynamic flow stress of 7075 alloy, which is 786 MPa at strain rates of (4–8) × 103 s−1, exceeds the value of 624 MPa for V95T1 alloy at strain rates of (2–6) × 103 s−1 by 25%. The threshold impact velocity resulting in fracture of the 4 mm head part of the profiled samples is 116–130 m/s for 7075 alloy and only 108 m/s for V95T1 alloy. The fracture pattern is also different between the alloys with characteristic shear-induced cracks oriented at 45° to the impact direction in the case of V95T1 alloy and perpendicular to the breaking off head part in the case of 7075 alloy. On the other hand, the compressive fracture strain of V95T1 alloy, which is 0.29–0.36, exceeds that of 7075 alloy, which is 0.27–0.33, by approximately 8%. Thus, V95T1 aluminum alloy exhibits less strength but is more ductile, while 7075 aluminum alloy exhibits more strength but is simultaneously more brittle.
Earthquake Forecasting Based on b Value and Background Seismicity Rate in Yunnan Province, China
Authors: Zhang Yuchen , Wang Rui , Shi Haixia , Miao Miao , Zhuang Jiancang , Chang Ying , Jiang Changsheng , Meng Lingyuan , Li Danning , Liu Lifang , Su Youjin , Zhang Zhenguo , Han Peng
Published: February 2025

Characterized by frequent earthquakes and a dense population, Yunnan Province, China, faces significant seismic hazards and is a hot place for earthquake forecasting research. In a previous study, we evaluated the performance of the b value for 5-year seismic forecasting during 2000–2019 and made a forward prediction of M ≥ 5.0 earthquakes in 2020–2024. In this study, with the forecast period having passed, we first revisit the results and assess the forward prediction performance. Then, the background seismicity rate, which may also offer valuable long-term forecasting information, is incorporated into earthquake prediction for Yunnan Province. To assess the effectiveness of the prediction, the Molchan Error Diagram (MED), Probability Gain (PG), and Probability Difference (PD) are employed. Using a 25-year catalog, the spatial b value and background seismicity rate across five temporal windows are calculated, and 86 M ≥ 5.0 earthquakes as prediction samples are examined. The predictive performance of the background seismicity rate and b value is comprehensively tested and shown to be useful for 5-year forecasting in Yunnan. The performance of the b value exhibits a positive correlation with the predicted earthquake magnitude. The synergistic effect of combining these two predictors is also revealed. Finally, using the threshold corresponding to the maximum PD, we integrate the forecast information of background seismicity rates and the b value. A forward prediction is derived for the period from January 2025 to December 2029. This study can be helpful for disaster preparedness and risk management in Yunnan Province, China.
AMGNet: An Attention-Guided Multi-Graph Collaborative Decision Network for Safe Medication Recommendation
Authors: Li Shiji , Wang Haitao , He Jianfeng , Chen Xing
Published: February 2025

Recommending safe and effective medication (drug) combinations is a key application of artificial intelligence in healthcare. Current methods often focus solely on recommendation accuracy while neglecting drug–drug interactions (DDIs), or overly prioritize reducing DDIs at the cost of model performance. Therefore, we propose the Attention-guided Multi-Graph collaborative decision Network (AMGNet) for safe medication recommendation, which strikes a balance between improving recommendation accuracy and minimizing DDIs. Specifically, AMGNet designs a patient feature encoder that utilizes a transformer encoder–decoder architecture to learn the temporal dependencies of longitudinal medical features from patient visits, effectively capturing the patient’s medication history and health status to enhance recommendation accuracy. AMGNet is also equipped with a medication feature encoder that integrates diverse knowledge graphs of drug molecular structure, electronic health records(EHRs), and drug–drug interactions(DDIs) through multi-graph representation learning and contrastive learning methods, further reducing the DDI rate of the recommended medication combinations and mitigating the risks associated with drug co-administration. We conducted extensive experiments on the widely used MIMIC-III and MIMIC-IV clinical medical datasets. The results demonstrate that AMGNet achieves competitive performance. Additionally, ablation studies and detailed case analyses further confirm that AMGNet offers high precision and safety in medication recommendation.
Aging Analysis and Anti-Aging Circuit Design of Strong-Arm Latch Circuits in 14 nm FinFET Technology
Authors: Xu Xin , Li Meng , Shi Yiqun , Li Yunpeng , Zhu Hao , Sun Qingqing
Published: February 2025

Despite the advantages of fin field-effect transistors (FinFETs), there are hidden issues such as electric field enhancement and exacerbated self-heating effects, which will intensify device aging effects. Due to the escalating costs associated with aging protection at the device process level, there is an urgent need to reduce the impact of aging on circuit performance from the circuit design perspective. This study focuses on the specific structure of the strong-arm latch comparator and conducts a detailed aging analysis. Based on the quasi-static approximation (QSA) model, the threshold voltage shift under operational stress is simulated. It is concluded that both the hot carrier injection (HCI) effect and negative bias temperature instability (NBTI) effect play equally non-negligible roles. Furthermore, aging tests were conducted based on 14 nm FinFET devices, validating the substantial HCI effects induced by short-duration pulses. Simultaneously, the test results suggest that the aging effect becomes more remarkable with increasing current. An improved circuit is proposed to reduce the HCI effect by reducing the current pulse by the way of pre-charging, which effectively reduces the threshold voltage shift of the latch comparator input transistors.
Control of Multiple Mobile Robots Based on Data Fusion from Proprioceptive and Actuated Exteroceptive Onboard Sensors
Authors: Joon Arpit , Kowalczyk Wojciech , Herman Przemyslaw
Published: February 2025

This paper introduces a team of Automated Guided Vehicles (AGVs) equipped with open-source, perception-enhancing rotating devices. Each device has a set of ArUco markers, employed to compute the relative pose of other AGVs. These markers also serve as landmarks, delineating a path for the robots to follow. The authors combined various control methodologies to track the ArUco markers on another rotating device mounted on the AGVs. Behavior trees are implemented to facilitate task-switching or to respond to sudden disturbances, such as environmental obstacles. The Robot Operating System (ROS) is installed on the AGVs to manage high-level controls. The efficacy of the proposed solution is confirmed through a real experiment. This research contributes to the advancement of AGV technology and its potential applications in various fields for example in a warehouse with a restricted and known environment where AGVs can transport goods while avoiding other AGVs in the same environment.
Cross-Layer Semantic Guidance Network for Camouflaged Object Detection
Authors: He Shiyu , Yin Chao , Li Xiaoqiang
Published: February 2025

Camouflaged Object Detection (COD) is a challenging task in computer vision due to the high visual similarity between camouflaged objects and their surrounding environments. Traditional methods relying on the late-stage fusion of high-level semantic features and low-level visual features have reached a performance plateau, limiting their ability to accurately segment object boundaries or enhance object localization. This paper proposes the Cross-layer Semantic Guidance Network (CSGNet), a novel framework designed to progressively integrate semantic and visual features across multiple stages, addressing these limitations. CSGNet introduces two innovative modules: the Cross-Layer Interaction Module (CLIM) and the Semantic Refinement Module (SRM). CLIM facilitates continuous cross-layer semantic interaction, refining high-level semantic information to provide consistent and effective guidance for detecting camouflaged objects. Meanwhile, SRM leverages this refined semantic guidance to enhance low-level visual features, employing feature-level attention mechanisms to suppress background noise and highlight critical object details. This progressive integration strategy ensures precise object localization and accurate boundary segmentation across challenging scenarios. Extensive experiments on three widely used COD benchmark datasets—CAMO, COD10K, and NC4K—demonstrate the effectiveness of CSGNet, achieving state-of-the-art performance with a mean error (M) of 0.042 on CAMO, 0.020 on COD10K, and 0.029 on NC4K.
A Transient Control Strategy for Grid-Forming Photovoltaic Systems Based on Dynamic Virtual Impedance and RBF Neural Networks
Authors: Yang Mingshuo , Zhang Lixia , Song Xiaoying , Kang Wei , Kang Zhongjian
Published: February 2025

This paper proposes a grid-forming (GFM) photovoltaic system transient control strategy based on the combination of dynamic virtual impedance and the radial basis function (RBF) algorithm. First, the virtual synchronous generator (VSG) model is analyzed to understand how virtual impedance affects current surges and system stability during faults. By using dynamic virtual impedance throughout the fault, the strategy suppresses current spikes and improves stability. The RBF neural network dynamically adjusts virtual inertia and damping coefficients to optimize transient power-angle characteristics and speed up recovery during fault restoration. Simulation results show that the strategy reduces transient current surges, improves angle recovery, and boosts system stability during voltage sag. This approach offers an effective solution for low-voltage ride-through (LVRT) and transient control in photovoltaic grid-connected systems, ensuring the resilience and stability of renewable energy integration into the grid.
Enhancing the Structural and Electrochemical Properties of Lithium Iron Phosphate via Titanium Doping During Precursor Synthesis
Authors: Li Puliang , Wang Yang , Liu Weifang , Chen Tao , Liu Kaiyu
Published: February 2025

This study investigates the effects of different titanium doping concentrations on the properties of iron phosphate precursors and the final lithium iron phosphate (LiFePO4) materials, aiming to optimize the structural and electrochemical performance of LiFePO4 by introducing titanium during the precursor synthesis stage. Titanium was introduced using titanate as a titanium source to prepare iron phosphate precursors with varying titanium concentrations. The materials were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and other techniques. The results showed that titanium incorporation significantly influenced the Fe and P content in the precursors, with a decrease in both Fe and P levels as the titanium doping concentration increased. Moreover, as the titanium content increased, the particle size of the precursor decreased, and the particle distribution became more uniform. Additionally, titanium doping improved the tap density of the precursors, with a significant increase in tap density observed when the titanium content reached 4000 ppm. Electrochemical measurements revealed that titanium doping had a certain impact on the discharge capacity of LiFePO4, with the discharge capacity gradually decreasing as the titanium content increased. Overall, this study effectively improved the physical properties of LiFePO4 materials by introducing titanium during the precursor synthesis stage, providing a theoretical foundation for further optimization of titanium-doped LiFePO4.
Numerical Simulation of Temperature Field Evolution and Distribution Range During Movement of Underground Coal Gasification Working Face
Authors: Li Wei , Liu Jian , Xin Lin , Li Wei , Fan Jianguo , Wang Xianmin , Ma Yan , Cheng Weimin , Sui Jiancai , Niu Maofei
Published: February 2025

Studying temperature evolution and distribution range during underground coal gasification is essential to optimize process efficiency, ensure safe and stable operation and reduce environmental impact. In this paper, based on the Liyan Coal Mine underground gasification project, the moving grid setting is used to simulate the moving heat transfer process of the underground coal gasification (UCG) flame working face (FWF). The results showed that the temperature distribution within the coal wall facing the flame is relatively narrow and remains concentrated within a limited range. Temperature distribution curves for T = 100 °C and T = 600 °C initially exhibit a nonlinear increase, reaching a maximum value, followed by a nonlinear decrease, ultimately trending towards a constant value. The maximum temperature influence ranges at ∆T = 10 °C (T = 30 °C) in the roof, left coal pillar, and floor are approximately 13.0 m, 9.0 m, and 10.1 m, respectively. The temperature values at the +1 m and +2 m positions on the roof exhibit a parabolic pattern, with the height and width of the temperature curve gradually increasing. By the end of the operation at t = 190 d, the length range of temperatures exceeding 600 °C at the +1 m position is 73 m, with a maximum temperature of approximately 825 °C, while at the +2 m position it is 31 m, with a maximum temperature of approximately 686 °C.
The Role of HCl-Catalyzed Sequential Carbonization in Producing Highly Carbonaceous Porous Biochar with Minimized Heavy Metal Content from Swine Manure
Authors: Yoo Seong-Yeun , Kim Seong-Su , Ho Thi. Thu-Trang , Nadeem Ahmad , Choe Kangil , Lee Jai-Young
Published: February 2025

This study investigated the production of high-performance biochar from swine manure using a sequential carbonization process combining hydrothermal carbonization (HTC) and pyrolysis. Biochar produced through HCl-assisted sequential carbonization exhibited superior properties, including the highest fixed carbon (70.0%), higher heating value (28.48 MJ/kg, ~18.8% increase over HTC-Py), and BET surface area (279.66 m2/g, ~17 times higher than other biochars). These improvements were attributed to the catalytic role of HCl in promoting dehydration, hydrolysis, and decarboxylation, leading to a more condensed and stabilized carbon structure. Furthermore, HCl significantly enhanced heavy metal removal, reducing Zn to 343.17 mg/kg (compared to HTC-Py 1324.15 mg/kg) and lowering Cd, As, Cu, Pb, Ni, and Cr by 70–80%, demonstrating effective demineralization. This approach presents a practical strategy for producing high-quality biochar with improved carbonization, energy properties, and pollutant removal, offering potential applications in environmental and agricultural fields.
Review of Conductive Reciprocating Liquid Metal Magnetohydrodynamic Generators
Authors: Zhao Lingzhi , Peng Aiwu
Published: February 2025

Reciprocating liquid metal magnetohydrodynamic (MHD) power generation is a new MHD power generation method in which the working fluid is a single-phase liquid metal with a low melting point and high conductivity. The internal combustion stroke of automobiles, ocean waves, sound waves and other reciprocating external forces drive the liquid metal to flow back and forth in an applied magnetic field, generating single-phase alternating current (AC) energy. Reciprocating liquid metal MHD (LMMHD) power generation has the advantages of a high power density, high efficiency, a fast start and good stability, and it provides a new solution for space static nuclear power conversion, variable-stroke automobile engines, distributed power supply and ocean energy utilization. According to the mode of action of an electromagnetic field, reciprocating LMMHD generators can be divided into the inductive type and conductive type. Compared with the inductive type, the conductive type has a simple structure and is the current research hot spot. Firstly, the classification and characteristics of reciprocating LMMHD power generation are introduced. Then, the working characteristics of conductive reciprocating LMMHD (CRLMMHD) generators are analyzed. On this basis, technical key points and issues in the current research of CRLMMHD generators are elaborated. Finally, conclusions and the future research direction of CRLMMHD generators are pointed out.
Mapping Forest Aboveground Biomass Using Multi-Source Remote Sensing Data Based on the XGBoost Algorithm
Authors: Wang Dejun , Xing Yanqiu , Fu Anmin , Tang Jie , Chang Xiaoqing , Yang Hong , Yang Shuhang , Li Yuanxin
Published: February 2025

Aboveground biomass (AGB) serves as an important indicator for assessing the productivity of forest ecosystems and exploring the global carbon cycle. However, accurate estimation of forest AGB remains a significant challenge, especially when integrating multi-source remote sensing data, and the effects of different feature combinations for AGB estimation results are unclear. In this study, we proposed a method for estimating forest AGB by combining Gao Fen 7 (GF-7) stereo imagery with data from Sentinel-1 (S1), Sentinel-2 (S2), and the Advanced Land Observing Satellite digital elevation model (ALOS DEM), and field survey data. The continuous tree height (TH) feature was derived using GF-7 stereo imagery and the ALOS DEM. Spectral features were extracted from S1 and S2, and topographic features were extracted from the ALOS DEM. Using these features, 15 feature combinations were constructed. The recursive feature elimination (RFE) method was used to optimize each feature combination, which was then input into the extreme gradient boosting (XGBoost) model for AGB estimation. Different combinations of features used to estimate forest AGB were compared. The best model was selected for mapping AGB distribution at 30 m resolution. The outcomes showed that the forest AGB model was composed of 13 features, including TH, topographic, and spectral features extracted from S1 and S2 data. This model achieved the best prediction performance, with a determination coefficient (R2) of 0.71 and a root mean square error (RMSE) of 18.11 Mg/ha. TH was found to be the most important predictive feature, followed by S2 optical features, topographic features, and S1 radar features.
Seed Quality and Seedling Production of Sequoia sempervirens, Sequoiadendron giganteum, and Pseudotsuga menziesii
Authors: Moraes Carolina , Navroski Marcio Carlos , de Oliveira Pereira Mariane , de Oliveira Luciana Magda , Miranda Ivan Adelke , Nascimento Bruno , Angelo Alessandro Camargo , Nicoletti Marcos Felipe , Mantovani Adelar , Pereira da Silva Filho Daniel
Published: February 2025

Given the ecological significance and potential for afforestation and carbon sequestration of these species, this study contributes to optimizing nursery practices for successful regeneration and conservation efforts. Thus, this research assessed the physical and physiological seed quality and seedling production of Sequoia sempervirens, Sequoiadendron giganteum, and Pseudotsuga menziesii. For seed characteristics the following were tested: (I) Tetrazolium at concentrations: 0.0%, 0.1%, 0.5%, 1.0%; (II) moisture content and thousand-seed weight; (III) in-lab germination; and (IV) the classification of seeds’ viability through the use of a seed blower. Meanwhile, seedling production was tested: (I) five compositions of substrates and (II) doses of a controlled-release fertilizer (14-14-14): 0.0, 2.0, 4.0, 6.0, 8.0 g L−1, for S. giganteum. The seed evaluations revealed no significant effect of tetrazolium concentrations on determining their viability. The water content results classify all species as orthodox. All species’ seeds were classified as small according to the weight of a thousand seeds. A maximum of 41% germination was observed for both S. sempervirens and S. giganteum, this value was 56% for P. menziesii, attributed to non-viability and emptiness. The seed blower increased germination by more than 20% for S. giganteum and almost 40% for P. menziesii. Seedling production was affected by the substrates, and a dosage of 4.0 g L−1 of the controlled-release fertilizer is recommended for S. giganteum.
Spatiotemporal Patterns and Interconnections of Forest Biomass and Economic Density in the Yellow River Basin, China
Authors: Hu Yaopeng , Zhai Jiahui , Wu Qingjun , Yang Xuanqin , Dou Yaquan , Zhao Xiaodi
Published: February 2025

Forests are among the most diverse ecosystems on the planet, and their biomass serves as a key measure for assessing the biological productivity and carbon cycle of terrestrial forest ecosystems. Recognizing the factors that impact forest ecosystems is essential for assessing their health and developing effective conservation strategies to preserve species diversity and ecological equilibrium. This study considered forest biomass as the explained variable, economic density as the explanatory variable, and human activities, land use, and forestland protection as the control variables. Panel data encompassing 448 counties within the Yellow River Basin (YRB) for the years 2008, 2013, and 2018 were utilized as inputs for ArcGIS spatial analysis and two-way fixed-effects modeling. This approach aimed to evaluate the impact of socio-economic factors on forest biomass. The findings indicate that, (1) from both temporal and spatial viewpoints, the distribution of forest biomass in the upper reaches of the Yellow River demonstrated an improvement over the period from 2008 to 2018. Notably, in 2013, there was a significant reduction in the forest biomass distribution in the middle and lower sections, although the levels remained substantially above the average for those regions. Throughout the period from 2008 to 2018, the overall forest biomass within the YRB displayed a spatial distribution pattern, with elevated levels observed in the western areas and diminished levels in the eastern regions. (2) A one-unit increase in economic density led to a 1.002% increase in forest biomass. In the YRB, a positive correlation was observed between the economic density and forest biomass, especially in the middle and lower reaches of the river. (3) In the upstream region, forest biomass was strongly negatively correlated with cultivated land but significantly positively correlated with forest land protection. In the middle reaches, although population growth and arable land expansion led to a decrease in forest biomass, primary industry development and urbanization promoted forest biomass growth. The development of primary industries other than planting, such as the forestry industry, can contribute to the forest biomass. Moreover, in the downstream area, a strong negative correlation was observed between the number of permanent residents and forest biomass. We recommend modifications to human activities to enhance the forest biomass and the preserve forest ecosystem stability.
Expanding Horizons: The Untapped Potential of Kluyveromyces marxianus in Biotechnological Applications
Authors: Reina-Posso Diana , Gonzales-Zubiate Fernando A.
Published: February 2025

One of the most unique non-conventional yeasts, Kluyveromyces marxianus, is rapidly gaining ground in biotechnology applications. K. marxianus possesses fast growth, thermotolerance, and a Crabtree-negative metabolism, features with a clear advantage over conventional yeasts like Saccharomyces cerevisiae. Additionally, it is diverse in carbon sources, utilizing lactate and xylose as well as lignocellulosic materials, which becomes critical in waste-utilizing and sustainable production industries. Besides the fact that K. marxianus has been useful in the production of valuable metabolites like β-galactosidase, ethanol, aroma compounds, and organic acids, its GRAS (Generally Recognized as Safe) designation makes K. marxianus a prime candidate for pharmaceutical and nutraceutical applications. This review summarizes a detailed description of K. marxianus’s biochemical and genetic features, its present applications, and future unexplored potentials such as probiotic development, vaccine production, bioremediation, and anticancer therapies. We also describe genetic tools that have been developed with improved metabolic pathways useful for new industry applications, making K. marxianus a resource in modern biotechnology. In sum, due to its unique features, K. marxianus appears to be a perfect alternative for areas such as biofuel production, biochemical synthesis, enzyme manufacturing, the dairy industry, and pharmaceuticals.
Diluted Acid Hydrolysate of Olive Stones: Overliming and Biomass Fermentation
Authors: Andary Jeanne , Ouaini Naïm , Abou-Khalil Rony
Published: February 2025

To valorize olive stones, this study focuses on the composition of their dilute-acid hydrolysate DAH and aims to highlight the effect of the overliming process to achieve an effective treatment that maximizes sugar concentrations while minimizing the number of toxic materials. The study examined the impact of pH (10 and 12), temperature (25 and 60 °C), and detoxification time (15, 30, and 60 min) on the viability and vitality of M. pulcherrima and S. cerevisiae, using an experimental design of 2231. Detoxification was significantly influenced by pH and temperature, with xylose and furans probably following the same kinetic degradation. Viability improved to 52% for M. pulcherrima and 67% for S. cerevisiae in detoxified hydrolysate due to reduced toxic compounds. Optimal conditions were found to be a pH of 10 at 25 °C for 30 min, achieving 71% and 62% degradation of hydroxymethylfurfural and furfural, respectively, with a minimum polyphenol concentration of 580 mg·L−1. M. pulcherima exhibited greater vitality than S. cerevisiae because of the medium’s high xylose content and low glucose concentration. Conversely, pH 12 not only promoted sugar (xylose) loss but also generated new toxic compounds that negatively affected yeast development. To improve fermentation, further attention needs to be paid to these conditions.
Design and Operation of a Multifunctional Pilot-Scale Bioreactor for Enhanced Aerobic Fermentation
Authors: Moresi Mauro
Published: February 2025

The primary aim of this work was to share the results from a Research Project supported by the Italian National Research Council, which led to the development of a versatile jacketed tower bioreactor. Designed to optimize oxygen transfer efficiency and process control, the reactor incorporated a reciprocating air compressor, centrifugal pumps, a draft tube with or without perforated plates, and a series of gas–liquid ejectors. Its flexible design enabled operation in both airlift and ejector-loop modes, making it suitable for a wide range of aerobic fermentation processes. By sharing the detailed engineering design, operational procedures of this pilot-scale bioreactor, as well as its performance data when cultivating yeasts on whey and potato wastewater, a detailed blueprint was given to researchers seeking to advance bioreactor technology, particularly in the context of emerging fields like cultured meat production, pharmaceutical manufacturing, and environmental bioremediation.
From Bottom of Sea to Space: Quo Vadis IoT? So What About Security?
Authors: Zolfaghari Behrouz , Krzciok Jacob , Bibak Khodakhast
Published: February 2025

In recent years, we have witnessed the era of IoT. Extensions of the IoT are found almost everywhere in the modern world: under the ground, on the ground, under the sea, in the sky, and in space. Such a rapid proliferation has given rise to a variety of requirements and challenges. As suggested by the recent literature, security is the most critical challenge in this area. A comprehensive survey in this area can pave the way for further research by highlighting current trends and shedding light on less-studied aspects of the area. This paper provides a comprehensive review of the current state of research on IoT extensions, with a focus on security. We start with reviewing existing relevant surveys, noting their shortcomings. We highlight the lack of inclusiveness in existing surveys. Moreover, we show that these surveys do not look closely at security challenges and fail to develop a taxonomy or a solid future roadmap. Then, we provide an overview of the security challenges and mechanisms of IoT extensions. We proceed to develop a taxonomy of these extensions with a focus on security. Lastly, we discuss what the future may hold for IoT extensions, given the role of artificial intelligence in IoT and the advancements of artificial intelligence on the horizon.
Application of Hyperspectral Imaging and Deep Convolutional Neural Network for Freezing Damage Identification on Embryo and Endosperm Side of Single Corn Seed
Authors: Zhang Jun , Dai Limin
Published: February 2025

In this paper, the feasibility of identifying freezing damage on the endosperm side and embryo side of single corn seeds was studied by combining hyperspectral imaging technology and the deep convolutional neural network (DCNN) method. Firstly, hyperspectral image data of the endosperm and embryo side of three freezing-damage categories of corn seeds were collected, and the average spectra of the endosperm part and embryo part were obtained with the range of 450–979 nm. After the spectral data were pre-processed by non-pretreatment or standard normal variation (SNV) pretreatment, a support vector machine (SVM) and a DCNN model were established for freezing-damage identification. Finally, multiple evaluation indexes (including accuracy, sensitivity, specificity, and precision) were used to comprehensively evaluate the performance of the SVM and DCNN models in the whole waveband. The results showed that the DCNN model obtained better performance in accuracy, sensitivity, specificity, and accuracy. The values of each category, especially for the category-2 and category-3 testing sets of the SVM model, were lower than those of the DCNN model. The classification results of the embryo-side corn seeds were better than those of the endosperm side. The accuracy value of the testing set of the DCNN model on the embryo side was higher than 96.7%, while the accuracy value of the DCNN model on the endosperm side was lower than 93.8%. The specificity values of the SVM and DCNN models were both higher than 94%. In addition, the sensitivity and precision values of the category-2 testing set of the embryo-side DCNN model increased by at least 2.8% and 4.8%. The sensitivity value of the category-3 testing set of the DCNN model was improved by at least 8.2% and 4.4%. These results of the embryo side of the corn seed showed significant improvement in the training and testing set. This study proved that the DCNN model can accurately and quickly identify single freezing-damage corn seeds, which provided a theoretical basis for constructing an end-to-end recognition and classification model of frozen corn seeds.
Assessment of the Anti-Listeria Effect of Citrus limon Peel Extract In Silico, In Vitro, and in Fermented Cow Milk During Cold Storage
Authors: Mkadem Wafa , Belguith Khaoula , Indio Valentina , Oussaief Olfa , Guluzade Gulnara , ElHatmi Halima , Serraino Andrea , De Cesare Alessandra , Boudhrioua Nourhene
Published: February 2025

In this study, the antimicrobial effect of Citrus limon peel extract against Listeria monocytogenes was analyzed in silico, tested in vitro, and validated in fermented cow milk during cold storage. The in silico analysis revealed that 4,5-di-O-caffeoyquinic acid interacts with L. monocytogenes proteins involved in colonization and intracellular survival. The in vitro experiments demonstrated that the anti-Listeria activity of Citrus limon peel extract is primarily attributed to limonene and phenolic compounds. In fermented milk stored at 4 °C for 7 days, the addition of Citrus limon peel extract resulted in a 2 Log reduction of L. monocytogenes compared to the control. Using the Baranyi and Roberts model, a significant decrease in the maximum growth rate (−0.021 h−1) and the concentration of L. monocytogenes from 5.95 to 3.67 log CFU/mL was observed in fermented milk supplemented with a 2×MIC level of Citrus limon peel extract during storage at 4 °C. The findings from all three approaches highlighted that the inhibitory effect of Citrus limon peel extract against L. monocytogenes is primarily due to chlorogenic acid derivatives, especially 4,5-di-O-caffeoyquinic acid, and limonene. Beyond its antimicrobial properties, the supplementation of fermented milk with Citrus limon peel extract also enhances the milk antioxidant capacity and total organic acids content.
Enhanced Thermal and Storage Stability of Glucose Oxidase via Encapsulation in Chitosan-Coated Alginate and Carboxymethyl Cellulose Gel Particles
Authors: Guo Zhihao , Ren Jian , Song Chunli
Published: February 2025

Glucose oxidase (GOD) is widely used as an important oxidoreductase in various fields. However, maintaining the vitality and stability of GOD under environmental stress is a challenge. To improve the thermal and storage stability of GOD, this study constructed sodium alginate–carboxymethyl cellulose sodium gel particles (SA/CMC) and chitosan-coated SA/CMC gel particles (CS/SA/CMC) of GOD. The encapsulation efficiency (EE), gel particle structure, stability, and release behavior of GOD were evaluated. The results showed that the thermal stability of GOD encapsulated in SA/CMC and CS/SA/CMC gel particles was improved by approximately 2.8-fold and 4.3-fold compared with the free enzyme at 85 °C, respectively. In addition, CS/SA/CMC gel particles enhanced the enzyme activity retention rate of GOD to over 80% during storage at 4 °C for four weeks. Both SA/CMC and CS/SA/CMC gel particles loaded with GOD had more than 70% of the enzymes released during the simulated gastrointestinal experiment. The results demonstrated that encapsulating GOD in SA/CMC and CS/SA/CMC gel particles could improve its thermal stability and storage stability, which is conducive to further expanding the application of GOD in food, pharmaceutical and feed industries.
FODMAP Profile of Wholegrain Pasta
Authors: Torbica Aleksandra M. , Miljić Milorad , Radosavljević Miloš
Published: February 2025

Pasta is a staple food consumed worldwide and is made from wholegrain semolina, which is a food rich in dietary fibre, proteins, minerals, vitamins, and bioactive compounds. However, fermentable oligo-, di-, and monosaccharides and polyols (FODMAP), part of soluble dietary fibre in pasta, can trigger/worsen irritable bowel syndrome (IBS) symptoms and increase the prevalence of gastrointestinal disorders. These dietary fibres include lactose, excess fructose relative to glucose, polyols, fructans (mostly fructooligosaccharides), and galactooligosaccharides. Due to a lack of information on the FODMAP profile for pasta, this research conducted a detailed analysis using high-performance anion-exchange chromatography with pulsed amperometric detection to determine the FODMAP compound content in commercially available pasta, with a focus on wholegrain products. The results showed that fructooligosaccharides (FOSs) are the dominant group of FODMAPs, and kestose is the predominant oligosaccharide in all pasta samples both dry (67.1–95.0%) and cooked (27.1–93.9%). Almost all pasta samples are classified as high-FODMAP foods. The degree of reduction in FODMAP compound content during cooking varies between pasta types and is influenced by the wheat type, cooking time, amount of water used for cooking, pasta shapes, and pasta supplementation. In samples of dry pasta, there are statistically significant differences in the results between all samples, while after cooking, there is evident grouping of the results in four clusters. The reduction in FOS content of pasta after cooking was in the range from 30.9% to 84%. Further research should be focused on higher activity of FODMAP degrading enzymes during pasta production process.