bluuebunny/crossref_metadata_2025 huggingface dataset:
Digital Hydraulic Transformer Concepts for Energy-Efficient Motion Control
Authors: Kogler Helmut
Published: January 2025

Hydraulic linear drive systems with conventional proportional valves result in poor energy efficiency due to resistance control. In systems with multiple actuators connected to one common pressure supply, a load-sensing strategy is often used to reduce these throttling losses. However, like conventional cylinder actuators, common load-sensing systems are also not able to recuperate the energy, which is actually released when a dead load is lowered. In order to overcome these drawbacks, in this paper, new concepts of a digital hydraulic smart actuator and a load-sensitive pressure supply unit are presented, which are qualified to reduce throttling losses and, furthermore, to harvest energy from the load. According to previous research, the basic concepts used in this contribution promise energy savings in the range of 30% for certain applications, which is one of the main motivations for this study. The operating principles are based on a parallel arrangement of multiple hydraulic switching converters, representing so-called digital hydraulic transformers. Furthermore, the storage module of the presented load-sensitive pressure supply unit is able to boost the hydraulic power in the common pressure rail beyond the maximum power of the primary motor. For exemplary operating cycles of the smart actuator and the pressure supply unit, a significant reduction in the energy consumption could be shown by simulation experiments, which offers a new perspective for energy-efficient motion control.
Time-Variation Damping Dynamic Modeling and Updating for Cantilever Beams with Double Clearance Based on Experimental Identification
Authors: Zhang Yunhe , Meng Fanjun , Li Xueguang , Song Wei , Zhang Dashun , Zhang Faping
Published: January 2025

The accuracy of a space manipulator’s end trajectory and stability is significantly affected by joint clearance. Aiming to improve the prediction accuracy of vibration caused by clearance, a dynamic clearance modeling method is developed based on parameter identification in this study. First, a dynamic model framework for manipulator arms is established based on the Hamilton principle and hypothetical mode method with time-variation damping. Then, a multi-resolution identification is performed for identifying the instantaneous frequency and damping ratio to estimate stiffness and damping by the sensors. The quantum genetic algorithm (QGA) is used to optimize the scale factor, which determines the identification accuracy and calculation efficiency. Finally, a case study is conducted to verify the presented model. In comparison with the initial dynamic model based on constant damping, the modal assurance criterion (MAC) of the proposed improved model based on time-variation damping is improved by 43.97%, the mean relative error (MRE) of the frequency response function (FRF) is reduced by 32.6%, and the root mean square error (RMSE) is reduced by 18.19%. The comparison results indicate the advantages of the proposed model. This modeling method could be used for vibration prediction in control systems for space manipulators to improve control accuracy.
The Identification of a Unique Gene MoUNG Required for Growth, Conidiation, and Pathogenicity in Magnaporthe oryzae Through T-DNA Insertion Mutagenesis
Authors: Chen Jing , He Qingfeng , Xie Xuze , Wu Yuting , Liu Shan , Li Xihong , Yi Xianfeng , Zhang Dan , Olsson Stefan , Lu Guodong , Wang Zonghua , Zhang Youjian , Lin Meizhen , Li Ya
Published: January 2025

Unique genes refer to genes specific to a particular organism and play crucial roles in the biological functions, evolutionary processes, and adaptations to external environments. However, the roles of unique genes in plant pathogenic fungi remain largely unexplored. In this study, we identified a novel unique gene in the rice blast fungus Magnaporthe oryzae, named MoUNG (M. oryzae unique gene), through T-DNA insertion mutagenesis. The disruption of the MoUNG promoter region in the T-DNA insertion mutant (T30-104) led to an almost loss of MoUNG expression. MoUNG has no functional domains and lacks homologues in other organism. It is highly expressed during the early-infection stage between 16 and 32 h post-inoculation (HPI), in contrast to its expression in mycelia and at the later infection stage of 48 HPI. Notably, attempts to knock out MoUNG were unsuccessful, so we examined the T30-104 mutant and found it showed significantly reduced growth, conidiation, and pathogenicity. Introducing the full-length MoUNG with its promoter into T30-104 restored these phenotypic defects. Additionally, subcellular localization assays revealed that MoUNG exhibits a dot-like distribution within the cytoplasm of mycelium, conidium, appressorium, and invasive hypha. Furthermore, knock-down of MoUNG produced results similar to those observed with the insertion mutation. In conclusion, we identified a novel unique gene MoUNG in M. oryzae and demonstrated its involvement in growth, conidiation, and pathogenicity.
Widely Targeted Metabolomics and Transcriptomics Analysis of the Response and Adaptation Mechanisms of Trifolium ambiguum to Low-Temperature Stress
Authors: Cao Kefan , Wang Sijing , Zhang Huimin , Ma Yiming , Wu Qian , Wang Mingjiu
Published: January 2025

Caucasian clover (Trifolium ambiguum M.Bieb.) is a perennial legume known for its exceptional cold tolerance, commonly used in agriculture and ecosystems in cold climates. Given the impact of climate change, enhancing the cold adaptation of Caucasian clover is crucial for sustaining agricultural productivity. This study employs metabolomics, transcriptomics, and Weighted Gene Co-expression Network Analysis (WGCNA) to investigate the molecular mechanisms of Caucasian clover’s response to low-temperature stress. Metabolomic analysis showed that low-temperature stress triggered the accumulation of fatty acids, amino acids, and antioxidants, which are critical for maintaining membrane stability and antioxidant capacity, thus protecting the plant from oxidative damage. Transcriptomic analysis revealed significant upregulation of genes involved in cold adaptation, particularly those related to antioxidant defense, membrane lipid repair, and signal transduction, including genes in the ABA signaling pathway and antioxidant enzymes, thereby improving cold tolerance. WGCNA identified gene modules closely linked to cold adaptation, especially those involved in antioxidant defense, fatty acid metabolism, signal transduction, and membrane repair. These modules function synergistically, with coordinated gene expression enhancing cold resistance. This study also investigated the isoflavonoid biosynthesis pathway under low-temperature stress, highlighting its role in enhancing antioxidant capacity and cold tolerance. Low-temperature stress induced upregulation of key enzyme genes, such as Isoflavone Synthase (IFS) and Isoflavone-7-O-Glucosyltransferase (IF7GT), promoting antioxidant metabolite accumulation and further enhancing the plant’s cold adaptation. Overall, this study offers novel molecular insights into the cold tolerance mechanisms of Caucasian clover and provides valuable theoretical support for breeding cold-resistant crops in cold climates.
Antimicrobial and Antioxidant Properties of Sambucus nigra L. (Elderflower) Oil: A Molecular Docking and Biochemical Study
Authors: Floares (Oarga) Doris , Obistioiu Diana , Hulea Anca , Suleiman Mukhtar Adeiza , Popescu Iuliana , Berbecea Adina , Samfira Ionel , Radulov Isidora
Published: January 2025

The present study investigates the antimicrobial and antioxidant potential of an essential oil extracted from Sambucus nigra L. flowers. Using hydrodistillation, the volatile compounds were profiled through GC–MS analysis for the fatty acid profile and volatile compounds. The fatty acid profile demonstrated a balanced composition of saturated fatty acids, monounsaturated fatty acids, and polyunsaturated fatty acids, with oleic, palmitic, and linolenic acids as key contributors. The volatile profile revealed the dominance of nonanal, cis-rose oxide, trans-rose oxide, and 2-Pentadecanone, 6,10,14-trimethyl-. Antioxidant activity was assessed using the 1,1-Diphenyl-2-Picrylhydrazyl radical scavenging assay, showing significant inhibition, with an IC50 value of 2.52 mg/mL. Antimicrobial efficacy was determined against Gram-positive, Gram-negative, and fungal strains, highlighting moderate inhibitory activity for Streptococcus pyogenes, Staphylococcus aureus, and Candida albicans. The S. nigra essential oil exhibited more activity against fungal strains, especially C. albicans, compared to the bacterial strains, which might be attributed to differences in the composition and permeability of the cell wall between fungi and bacteria. Among the bacteria, E. coli was the most susceptible, while P. aeruginosa showed moderate resistance, in agreement with its known stronger membrane structure and efflux mechanisms. Molecular docking analysis was conducted to evaluate the potential inhibitory effects of the oil on microbial proteins to corroborate the observed in vitro outcome. The results indicated that nonanal, cis-rose oxide, trans-rose oxide, and 2-pentadecanone, 6,10,14-trimethyl- displayed interesting hydrophilic and hydrophobic binding interactions with the putative microbial proteins. These findings elucidate the bioactive role of Sambucus nigra essential oils, suggesting their potential as therapeutic agents in managing oxidative stress and microbial infections.
Acanthoscelides atrocephalus (Pic, 1938) and Its Potential for Biological Control of Two Weed Species
Authors: Greco Mayara Guelamann da Cunha Espinelli , Correia Enrique Soratto , Morse Geoffrey , Caron Edilson , Agostinetto Dirceu , Garcia Flávio Roberto Mello
Published: January 2025

In order to replace chemical herbicides, which harm the environment and health, we seek sustainable methods to control weeds. We remove a seed-beetle species, Acanthoscelides atrocephalus, from synonymy with Acanthoscelides modestus and recognize it as a potential bioagent for Aeschynomene denticulata and A. indica. Belonging the megacornis group of the genus Acanthoscelides, its fine morphology was analyzed using high-resolution photography and scanning electron microscopy. The species differs from others of the A. megacornis group based on integument coloration, distinctive patterns of vestiture on the pronotum and pygidium, large and sexually dimorphic eyes, a strong frontal carina extending from the vertex of the head to the clypeus, and distinctive armature in the internal sac of the male genitalia. It stands out as a biological control agent due to the larvae’s habit of feeding on seeds, which hinders the development of the embryo. Through tetrazolium and germination tests, it was discovered that 100% of the infested seeds had no viable seed integument and did not germinate. A. atrocephalus is no longer a synonym of Acanthoscelides modestus. This species is a predator of A. denticulata and A. indica and prevents seed germination, becoming promising as a bioagent for the control of these weeds.
Synergistic Ability and Effect of Leaf Color and Leaf Thickness to Improve the Photosynthetic Performance of Wheat
Authors: Ding Weihua , Chang Sujing , Feng Suwei , Sun Haili , Yue Junlong , Qiao Jian , Zheng Weihua , Ru Zhengang
Published: January 2025

Leaf traits are important factors affecting the photosynthetic capacity of crops. In Bainong 4199 (BN4199) and Aikang 58 (AK58) wheat, the role of leaf color and leaf thickness in improving wheat photosynthetic performance and its influence on material accumulation and yield were studied in the field environment. Compared with AK58, BN4199 has a deeper leaf color and thicker leaves. Further study on photosynthetic physiological characteristics showed that the photosynthetic capacity of BN4199 with deep color and thick leaves was higher than that of AK58 at flowering stage, 7 days after flowering, 15 days after flowering, and 20 days after flowering regardless of low light in the morning and evening or light at noon. During the flowering stage, the light saturation point and compensation point were 1% higher and 15.23% lower, respectively, in BN4199 than AK58. According to the diurnal variation in chlorophyll content in different growth stages, BN4199 was generally higher than AK58, and the chlorophyll content was the highest at each time point 7 days after flowering. The chlorophyll content was highest at each time point 7 days after flowering. Chlorophyll fluorescence parameters and light reflectance analyses indicated that BN4199 has significantly higher photosynthetic electron transport and population light energy absorption and utilization capacity than AK58. The 2-year field yields indicated significantly higher material accumulation in BN4199 than AK58. In summary, thick leaves with deep color were resistant to both strong light and weak light, thus, markedly increasing photosynthetic efficiency. Improvement in leaf color and leaf thickness might serve as an important index to enhance the photosynthetic performance of wheat, and achieve improvement and breeding of wheat with high light efficiency.
Rapamycin Increases the Development Competence of Yak (Bos grunniens) Oocytes by Promoting Autophagy via Upregulating 17β-Estradiol and HIF-1α During In Vitro Maturation
Authors: Wang Meng , Ma Xin , Zhang Qian , Zhang Hui , Qiu Shantong , Xu Ruihua , Pan Yangyang
Published: January 2025

High-quality oocyte production strategies play an important role in animal-assisted reproductive biotechnologies, and rapamycin (Rap) has been commonly used to increase the development potential of mammalian oocytes. The purpose of this study is to evaluate the effects and possible molecular mechanisms of rap on the maturation of yak oocytes. Different concentrations of Rap were supplemented during in vitro maturation (IVM) of yak oocytes. The maturation rates of oocytes and development rates of parthenogenetically activated embryos were assessed. The levels of 17β-estradiol (E2) were detected via ELISA, and the expression of autophagy-related factors, steroidogenic enzymes, and HIF-1α was detected via qRT-PCR, western blotting, and fluorescence microscopy, respectively. In addition, the impacts of E2 and HIF-1α on Rap-mediated oocyte autophagy were investigated by investigating the activities of E2 and HIF-1α. Our results showed that 0.1 nM Rap substantially enhanced the developmental ability of yak oocytes. In this group, the levels of E2, CYP19A1, CYP17A1, and autophagy-related factors were also significantly increased, and the expression of ATG5 and BECN1 in subsequent embryos was also increased. Further analysis revealed that Rap tends to enhance the development competence of yak oocytes and that the levels of autophagy-related factors are reduced when the activity of E2 or HIF-1α is inhibited. Furthermore, the levels of E2, CYP19A1, and CYP17A1 were downregulated when the activity of HIF-1α was inhibited, and the levels of HIF-1α were also significantly reduced by the estrogen receptor antagonist G15. Nevertheless, the levels of CYP11A1 mRNA in mature yak COCs were not significantly different among these groups, a phenomenon which implies that the levels of E2 were not correlated with the CYP11A1 content in yak COCs. There was an increasing tendency for the development competence of yak oocytes at the optimum concentration of Rap during IVM. The potential underlying mechanism is that Rap can activate autophagy and upregulate the levels of E2 and HIF-1α in mature oocytes. Additionally, the levels of both E2 and HIF-1α are regulated by each other and involve Rap-regulated autophagy in oocytes.
The Role of Amphibian AMPs Against Oxidative Stress and Related Diseases
Authors: Silva Ortíz Yudy Lorena , de Sousa Thaís Campos , Kruklis Natália Elisabeth , Galeano García Paula , Brango-Vanegas José , Soller Ramada Marcelo Henrique , Franco Octávio Luiz
Published: January 2025

Amphibians use their skin as an effective defense mechanism against predators and microorganisms. Specialized glands produce antimicrobial peptides (AMPs) that possess antioxidant properties, effectively reducing reactive oxygen species (ROS) levels. These peptides are promising candidates for treating diseases associated with oxidative stress (OS) and redox imbalance, including neurodegenerative disorders such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and amyotrophic lateral sclerosis (ALS), as well as age-related conditions, like cardiovascular diseases and cancer. This review highlights the multifaceted roles of AMPs and antioxidant peptides (AOPs) in amphibians, emphasizing their protective capabilities against oxidative damage. They scavenge ROS, activate antioxidant enzyme systems, and inhibit cellular damage. AOPs often share structural characteristics with AMPs, suggesting a potential evolutionary connection and similar biosynthetic pathways. Peptides such as brevinin-1FL and Cath-KP demonstrate neuroprotective effects, indicating their therapeutic potential in managing oxidative stress-related diseases. The antioxidant properties of amphibian-derived peptides pave the way for novel therapeutic developments. However, a deeper understanding of the molecular mechanisms underlying these peptides and their interactions with oxidative stress is essential to addressing ROS-related diseases and advancing therapeutic strategies in clinical practice.
Development of a Spectrophotometric Assay for the Cysteine Desulfurase from Staphylococcus aureus
Authors: Sabo Emily , Nelson Connor , Tyagi Nupur , Stark Veronica , Aasman Katelyn , Morrison Christine N. , Boyd Jeffrey M. , Holz Richard C.
Published: January 2025

Background/Objectives: Antibiotic-resistant Staphylococcus aureus represents a growing threat in the modern world, and new antibiotic targets are needed for its successful treatment. One such potential target is the pyridoxal-5′-phosphate (PLP)-dependent cysteine desulfurase (SaSufS) of the SUF-like iron–sulfur (Fe-S) cluster biogenesis pathway upon which S. aureus relies exclusively for Fe-S synthesis. The current methods for measuring the activity of this protein have allowed for its recent characterization, but they are hampered by their use of chemical reagents which require long incubation times and may cause undesired side reactions. This problem highlights a need for the development of a rapid quantitative assay for the characterization of SaSufS in the presence of potential inhibitors. Methods: A spectrophotometric assay based on the well-documented absorbance of PLP intermediates at 340 nm was both compared to an established alanine detection assay and used to effectively measure the activity of SaSufS incubated in the absence and presence of the PLP-binding inhibitors, D-cycloserine (DCS) and L-cycloserine (LCS) as proof of concept. Methicillin-resistant S. aureus strain LAC was also grown in the presence of these inhibitors. Results: The Michaelis–Menten parameters kcat and Km of SaSufS were determined using the alanine detection assay and compared to corresponding intermediate-based values obtained spectrophotometrically in the absence and presence of the reducing agent tris(2-carboxyethyl)phosphine (TCEP). These data revealed the formation of both an intermediate that achieves steady-state during continued enzyme turnover and an intermediate that likely accumulates upon the stoppage of the catalytic cycle during the second turnover. The spectrophotometric method was then utilized to determine the half maximal inhibitory concentration (IC50) values for DCS and LCS binding to SaSufS, which are 2170 ± 920 and 62 ± 23 μM, respectively. Both inhibitors of SaSufS were also found to inhibit the growth of S. aureus. Conclusions: Together, this work offers a spectrophotometric method for the analysis of new inhibitors of SufS and lays the groundwork for the future development of novel antibiotics targeting cysteine desulfurases.
MCC950 Reduces the Anxiodepressive-like Behaviors and Memory Deficits Related to Paclitaxel-Induced Peripheral Neuropathy in Mice
Authors: Martínez-Martel Ignacio , Negrini-Ferrari Sylmara Esther , Pol Olga
Published: January 2025

Chemotherapy-induced peripheral neuropathy and the accompanying affective disorders are serious side effects, and their resolution is not guaranteed. Oxidative stress and elevated levels of Nod-like receptor protein 3 (NLRP3) have been detected in the peripheral and central nervous systems of animals with neuropathic pain provoked by several antineoplastic drugs, such as paclitaxel (PTX). Several studies have further indicated that NLRP3 inflammasome inhibition could be an approach for treating chronic pain, but its impact on the anxiodepressive-like behaviors and memory deficits related to PTX-provoked neuropathy has not yet been investigated. MCC950 is a potent and specific inhibitor of the NLRP3 pathway that acts through inhibiting NLRP3 activation and inflammasome formation. We hypothesized that the administration of MCC950 could alleviate the affective and cognitive disorders accompanying PTX-provoked neuropathy. Using male C57BL/6 mice, we assessed the effects of MCC950 on the mechanical and thermal allodynia, anxiodepressive-like behavior, and memory deficits incited by this taxane. The results indicated that the intraperitoneal administration of 10 mg/kg of MCC950 twice daily for three consecutive days fully reversed the PTX-induced mechanical and thermal allodynia. This treatment also completely attenuated the anxiolytic (p < 0.004) and depressive-like behaviors (p < 0.022) and memory deficits (novel object recognition test; p < 0.0018) incited by PTX. These actions were mainly achieved through blocking NLRP3 inflammasome activation in the sciatic nerve, amygdala, and hippocampus, and oxidative stress in the amygdala and hippocampus. MCC950 also normalized the p-ERK 1/2 overexpression in the sciatic nerve and apoptotic responses in the sciatic nerve and the amygdala. This study suggests that MCC950 might be a promising treatment for PTX-induced mental illnesses and neuropathy.
Effects of Silibinin on Delaying Aging in Drosophila melanogaster
Authors: Zhu Kai , Ni Hang , Hafeez Eqra , Hu Yaxuan , Hu Fan , Du Dongsheng , Chen Dongsheng
Published: January 2025

Aging is an inevitable physiological process, but delaying aging has always been an enduring human pursuit. Silibinin (SIL), derived from the seeds of the milk thistle plant, exhibits a broad spectrum of pharmacological properties, including anti-tumor effects, liver protection, inhibition of apoptosis, and alleviation of inflammation. However, whether it has anti-aging effects remains unclear. The SIL dietary supplement to Drosophila melanogaster prolonged lifespan, improved climbing ability, ameliorated age-associated intestinal barrier disruption, enhanced the resistance to oxidative stress, and increased the enzyme activities of superoxide dismutase (SOD) and catalase (CAT). Furthermore, RNA-seq results showed that SIL addition significantly upregulated 74 genes and downregulated 50 genes compared with the control. KEGG (Kyoto Encyclopedia of genes and genomes) analysis demonstrated that these differentially expressed genes were primarily involved in the Toll signaling pathway and endoplasmic reticulum proteins processing, six among which, including IM2, IM3, Drsl3, CG7556, GCS1, and TRAM, were particularly involved in the regulation by SIL supplementation. The results indicate that SIL exhibits anti-aging effects by enhancing antioxidant capacity and regulating aging-related signaling pathways. Therefore, SIL shows a potential application in anti-aging dietary regimens.
Isolation, In Vitro Antioxidant Capacity, Hypoglycemic Activity and Immunoactivity Evaluation of Polysaccharides from Coriandrum sativum L.
Authors: Jin Weiwei , Zhou Huan , Zhao Haijun , Pei Yue , Su Fengxian , Li Yan , Luo Tao
Published: January 2025

Coriander (Coriandrum sativum) is a classical medicinal and edible herb as well as a spice, but the physicochemical and biological properties of its polysaccharides have not been fully studied. In this study, the polysaccharides were extracted using an ultrasonic-assisted method and purified from fresh coriander, and then the coriander polysaccharide (CSP) fraction was separated using an agarose gel Q-Sepharose Fast Flow column. The total sugar content, protein content and monosaccharides composition of CSPs were determined using a phenol–sulfuric acid method, Coomassie Brilliant Blue method and HPLC. The structural characterization was detected using ultraviolet spectrophotometry and FT-IR spectroscopy. DPPH and ABTS free radicals were used to explore their antioxidant activities, while the inhibitory abilities of α-amylase and α-glucosidase were used to evaluate their hypoglycemic activity. After that, the immunomodulatory and antitumor activities were investigated using macrophage RAW264.7 and HepG2 cells as the targets. The results showed that the total sugar and protein contents of CSPs were 66.90 ± 1.44% and 1.06 ± 0.32%, respectively. CSPs were mainly composed of fucose, rhamnose, arabinose, galactose, glucose, galacturonic acid and glucuronic acid, with a molar ratio of 1.13:15.11:9.60:25.98:1.55:44.33:2.29, and may be an acidic heteropolysaccharide containing pyran rings, α- and β-glycosidic bonds and glucuronic acid. Results from in vitro experiments of biological activities showed that the IC50 of CSPs for scavenging DPPH and ABTS free radicals were 0.759 mg/mL and 1.758 mg/mL, respectively; the IC50 values for inhibiting the activities of α-amylase and α-glucosidase were 0.634 mg/mL and 2.178 mg/mL, respectively; the CSPs with a concentration of 25~200 μg/mL showed no obvious toxicity to macrophage RAW264.7, and when treated with 100 μg/mL of CSPs, the relative cell phagocytosis capacity and secreted nitric oxide amount of RAW264.7 were 153.75 ± 12.01% and 133.56 ± 5.37%, respectively; CSPs showed a concentration-dependent ability to inhibit the growth of HepG2 cells within the test concentration of 0.25–2.0 mg/mL. Summarizing the results, due to their excellent antioxidant, immunomodulatory and anti-tumor activities, the coriander acid polysaccharides were expected to show good potential in comprehensive development of food and medicine.
User Profile Construction Based on High-Dimensional Features Extracted by Stacking Ensemble Learning
Authors: Wang Zhaoyang , Li Li , He Ketai , Zhu Zhenyang
Published: January 2025

Online social networks, as platforms for personal expression, have evolved into complex networks integrating political and social dimensions. This evolution has shifted the focus of network governance from addressing hacking activities to mitigating unpredictable social behaviors, such as the malicious manipulation of public opinion, the doxing of ordinary users, and cyberbullying. However, the sparsity of data and the concealed nature of user behavior pose significant challenges to existing network reconnaissance technologies. In this study, we focus on constructing user profiles on online social network platforms by extracting features to build deep user profiles based on behavioral patterns. Drawing inspiration from the 5Cs principle of credit evaluation, we refine it into a 3Cs principle tailored for user profiling on social network platforms and associate it with user behavioral patterns. To further analyze user behavior, a high-dimensional feature extraction method is proposed using an improved stacking ensemble learning model. Based on experimental data analysis, the most suitable base algorithms for high-dimensional feature extraction are identified. Experimental results demonstrate that the integration of high-dimensional features improved the behavior prediction accuracy of the profiling model by 9.26% on balanced datasets and enhanced the AUC (area under the curve) metric by 3.69% on imbalanced datasets. The proposed method effectively increases the depth and generalization performance of user profiling.
Enhancing Student Academic Success Prediction Through Ensemble Learning and Image-Based Behavioral Data Transformation
Authors: Zhao Shuai , Zhou Dongbo , Wang Huan , Chen Di , Yu Lin
Published: January 2025

Predicting student academic success is a significant task in the field of educational data analysis, offering insights for personalized learning interventions. However, the existing research faces challenges such as imbalanced datasets, inefficient feature transformation methods, and limited exploration data integration. This research introduces an innovative method for predicting student performance by transforming one-dimensional student online learning behavior data into two-dimensional images using four distinct text-to-image encoding methods: Pixel Representation (PR), Sine Wave Transformation (SWT), Recurrence Plot (RP), and Gramian Angular Field (GAF). We evaluated the transformed images using CNN and FCN individually as well as an ensemble network, EnCF. Additionally, traditional machine learning methods, such as Random Forest, Naive Bayes, AdaBoost, Decision Tree, SVM, Logistic Regression, Extra Trees, K-Nearest Neighbors, Gradient Boosting, and Stochastic Gradient Descent, were employed on the raw, untransformed data with the SMOTE method for comparison. The experimental results demonstrated that the Recurrence Plot (RP) method outperformed other transformation techniques when using CNN and achieved the highest classification accuracy of 0.9528 under the EnCF ensemble framework. Furthermore, the deep learning approaches consistently achieved better results than traditional machine learning, underscoring the advantages of image-based data transformation combined with advanced ensemble learning approaches.
Peri-Implant Bone Stability Around Tapered Implant Prosthetic Connection: A Systematic Review and Meta-Analysis Comparing Different Cone Morse and Conometric Implants Angle Contact and Coupling Interface Designs
Authors: Alla Iris , Scarano Antonio , Sinjari Bruna , Xhajanka Edit , Lorusso Felice
Published: January 2025

Background/Objectives: Internal implant–abutment connection has been proposed to increase interface stability and reduce biological and prosthetic issues. The aim of the present investigation was to evaluate the influence of the implant abutment conical angle on marginal bone loss and mechanical complications. Methods: The literature screening was performed by considering Pubmed/MEDLINE, EMBASE, and Google Scholar sources. The eligibility process was conducted in order to perform a descriptive synthesis, determine the risk of bias, and carry out network meta-analyses. The following categories were considered for pairwise comparisons: external hexagon (EI), internal hexagon (HI), cone morse (CM) (<8° contact angle), and conometric joint (>8° contact angle). For the descriptive data synthesis, the following parameters were considered: sample size, implant manufacturer, prosthetic joint type, prosthetic complications, marginal bone loss, and study outcomes. Results: A total of 4457 articles were screened, reducing the output to the 133 studies included in the descriptive synthesis, while 12 articles were included in the statistical analysis. No significant differences in marginal bone loss were reported when comparing a cone angle of <8° and a cone angle of >8; Conclusions: Within the limits of the present investigation, the cone interface seems to produce lower marginal bone loss compared to external and internal hexagon connection. No differences were found when comparing a cone angle of <8° and a cone angle of >8°.
Force-Velocity Profile in Middle- and Long-Distance Athletes: Sex Effect and Impact on Endurance Performance Determinants
Authors: Muñoz de la Cruz Violeta , González-Mohíno Fernando , Rodríguez-Barbero Sergio , Valero Fernando , González-Ravé José María
Published: January 2025

Background: Muscle strength plays a critical role in the performance of middle- and long-distance athletes. However, the vertical force–velocity (F–V) profile has not been studied in this population. The objectives of this study were twofold: (i) to characterize the F–V profile in middle- and long-distance athletes and (ii) to explore its relationship with physiological and biomechanical performance variables. Methods: Thirty-nine highly trained athletes (13 middle-distance and 26 long-distance athletes), comprising men (18) and women (21), participated in this study. Each athlete performed a squat-jump to determine their F–V profile, followed by two 5 min bouts of low-intensity running and a graded exercise test to assess physiological and kinematic parameters. Results: Significant differences (p ≤ 0.05) were observed in maximal estimated power (Pmax) and jump height between middle- and long-distance female athletes (21.20 ± 4.78 W·kg−1 vs. 15.80 ± 2.83 W·kg−1; 26.00 ± 0.05 cm vs. 19.50 ± 0.03 cm), and between male and female long-distance athletes (19.70 ± 2.87 W·kg−1; 24.10 ± 0.02 cm). Stride length during low intensity running showed significant correlations with Pmax (r = 0.340) and jump height (r = 0.374). Pmax was positively associated with running economy (RE) (r = 0.396) and VO2max (r = 0.346), and negatively correlated with F–V imbalance (FVimb) (r = −0.531). Conclusions: Middle- and long-distance athletes demonstrate similar F–V profiles; however, middle-distance athletes exhibit a rightward shift, resulting in higher Pmax and jump height, particularly among women. Nevertheless, F–V profile characteristics display only weak associations with physiological and kinematic variables which directly influence performance.
Pedestrian Re-Identification Algorithm Based on Unmanned Aerial Vehicle Imagery
Authors: Song Lili , Jin Xin , Han Jianfeng , Yao Jie
Published: January 2025

Pedestrian re-identification in complex scenarios is often hindered by challenges such as viewpoint diversity, background interference, and behavioral complexity, which traditional methods struggle to address effectively in wide-area surveillance. Unmanned Aerial Vehicles (UAVs) offer a promising solution to this problem due to their flexibility and extensive coverage capabilities. However, UAV aerial images introduce additional challenges, including significant viewpoint variations and the complexity of pedestrian behaviors. To address these issues, this paper proposes a Transformer-based model that integrates a multi-scale graph convolution network (MU-GCN) with a non-local attention mechanism to address these challenges. A MU-GCN enhances feature extraction by employing graph convolutional networks to improve feature representation after extracting detailed features at various scales through multi-scale convolution kernels. This strengthens the model’s focus on local information. Meanwhile, the non-local attention mechanism enhances the model’s capacity to capture global contextual information by modeling dependencies between distant regions in the image. This approach is better suited for the unique characteristics of UAV aerial imagery. Experimental results demonstrate that, compared to the baseline model, the proposed method achieves improvements of 9.5% in mean average precision (mAP) and 4.9% in Rank-1 accuracy, validating the effectiveness of the model.
Non-Invasive and Accurate Blood Glucose Detection Based on an Equivalent Bioimpedance Spectrum
Authors: Gong Qiong , Xu Chuanpei , Yuan Hongyu , Shi Xiuli , Li Wenhan , Li Xinjun , Fang Cheng
Published: January 2025

Accurate blood glucose monitoring is a key issue for the diagnosis and treatment of diabetes. For this purpose, a non-invasive blood glucose detection method is proposed, which makes use of the equivalent bioelectric impedance spectrum. An impedance detection platform is designed using an automatic balance bridge technique, which can acquire an impedance spectrum within the range of dispersion. Then, the K-nearest neighbor algorithm is used to extract the characteristics of the impedance spectrum. Furthermore, higher-order multiple regression methods are used to establish a blood glucose–electrical impedance spectrum model. Experimental results show that the proposed blood glucose–electrical impedance spectrum model can estimate the change in blood glucose and reliably identify the high blood glucose samples. The correlation between the proposed method and the biochemical blood glucose values can reach 0.89 and 0.87 in personal and multi-person blood glucose tests, respectively. Thus, the proposed method provides a feasible solution for non-invasive blood glucose detection and can help us identify diabetes mellitus.
Short-Medium-Term Solar Irradiance Forecasting with a CEEMDAN-CNN-ATT-LSTM Hybrid Model Using Meteorological Data
Authors: Camacho Max , Maldonado-Correa Jorge , Torres-Cabrera Joel , Martín-Martínez Sergio , Gómez-Lázaro Emilio
Published: January 2025

In recent years, the adverse effects of climate change have increased rapidly worldwide, driving countries to transition to clean energy sources such as solar and wind. However, these energies face challenges such as cloud cover, precipitation, wind speed, and temperature, which introduce variability and intermittency in power generation, making integration into the interconnected grid difficult. To achieve this, we present a novel hybrid deep learning model, CEEMDAN-CNN-ATT-LSTM, for short- and medium-term solar irradiance prediction. The model utilizes complete empirical ensemble modal decomposition with adaptive noise (CEEMDAN) to extract intrinsic seasonal patterns in solar irradiance. In addition, it employs a hybrid encoder-decoder framework that combines convolutional neural networks (CNN) to capture spatial relationships between variables, an attention mechanism (ATT) to identify long-term patterns, and a long short-term memory (LSTM) network to capture short-term dependencies in time series data. This model has been validated using meteorological data in a more than 2400 masl region characterized by complex climatic conditions south of Ecuador. It was able to predict irradiance at 1, 6, and 12 h horizons, with a mean absolute error (MAE) of 99.89 W/m2 in winter and 110.13 W/m2 in summer, outperforming the reference methods of this study. These results demonstrate that our model represents progress in contributing to the scientific community in the field of solar energy in environments with high climatic variability and its applicability in real scenarios.
Mapping Noise from Motorised Transport in the Context of Infrastructure Management
Authors: Jaskowski Piotr , Koniak Marcin , Matijošius Jonas , Kilikevičius Artūras
Published: January 2025

Noise pollution presents significant challenges for urban infrastructure management, highlighting the need for practical assessment tools such as noise maps. These maps enable the visualization and geo-referencing of noise levels, identifying areas requiring immediate intervention and long-term strategic responses. Road sections with traffic exceeding 3 million vehicles per year were selected for measurement. The findings are presented in detail, revealing that the Long-term Day-Night Average Noise Level (Lden) exceeds acceptable limits, affecting approximately 1.899 km2 and impacting around 1200 residents within the exceedance zone. Similarly, the equivalent noise level (LAeq) surpasses acceptable thresholds over an area of 1.220 km2, affecting an additional 700 residents. Notably, there were no exceedances of the key noise impact indicators, including high annoyance (HA), high sleep disturbance (HSD), and ischemic heart disease (IHD). Changes in traffic organisation were implemented to address areas that exceed the applicable noise standards, including a ban on trucks and the introduction of local speed limits. The measures have successfully mitigated the noise problem in Grodzisk County (Poland). Further anti-noise initiatives are planned, including planting vegetation along the roadways.
SIMECK-T: An Ultra-Lightweight Encryption Scheme for Resource-Constrained Devices
Authors: Anton Alin-Adrian , Csereoka Petra , Capota Eugenia-Ana , Cioargă Răzvan-Dorel
Published: January 2025

The Internet of Things produces vast amounts of data that require specialized algorithms in order to secure them. Lightweight cryptography requires ciphers designed to work on resource-constrained devices like sensors and smart things. A new encryption scheme is introduced based on a blend of the best-performing algorithms, SIMECK and TEA. A selection of software-oriented Addition–Rotation–XOR (ARX) block ciphers are augmented with a dynamic substitution security layer. The performance is compared against other lightweight approaches. The US National Institute of Standards and Technology (NIST) SP800-22 Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications and the German AIS.31 of the Federal Office for Information Security (BSI) are used to validate the output of the proposed encryption scheme. The law of iterated logarithm (LIL) for randomness is verified in all three forms. The total variance (TV), the Hellinger Distance (HD), and the root-mean-square deviation (RMSD) show values smaller than the required limit for 10.000 sequences of ciphertext. The performance evaluation is analyzed on a Raspberry PICO 2040. Several security metrics are compared against other ciphers, like χ2 and encryption quality (EQ). The results show that SIMECK-T is a powerful and fast, software-oriented, lightweight cryptography solution.
Transformer-Based Explainable Model for Breast Cancer Lesion Segmentation
Authors: Wang Huina , Wei Lan , Liu Bo , Li Jianqiang , Li Jinshu , Fang Juan , Mooney Catherine
Published: January 2025

Breast cancer is one of the most prevalent cancers among women, with early detection playing a critical role in improving survival rates. This study introduces a novel transformer-based explainable model for breast cancer lesion segmentation (TEBLS), aimed at enhancing the accuracy and interpretability of breast cancer lesion segmentation in medical imaging. TEBLS integrates a multi-scale information fusion approach with a hierarchical vision transformer, capturing both local and global features by leveraging the self-attention mechanism. This model addresses the limitations of existing segmentation methods, such as the inability to effectively capture long-range dependencies and fine-grained semantic information. Additionally, TEBLS incorporates visualization techniques to provide insights into the segmentation process, enhancing the model’s interpretability for clinical use. Experiments demonstrate that TEBLS outperforms traditional and existing deep learning-based methods in segmenting complex breast cancer lesions with variations in size, shape, and texture, achieving a mean DSC of 81.86% and a mean AUC of 97.72% on the CBIS-DDSM test set. Our model not only improves segmentation accuracy but also offers a more explainable framework, which has the potential to be used in clinical settings.
Can Foot Orthoses Prevent Falls? A Proposal for a New Evaluation Protocol
Authors: Montesissa Matteo , Raimondi Ilaria , Baldini Nicola , Mazzotti Antonio , Brognara Lorenzo
Published: January 2025

Foot pain represents one of the most common symptoms in lower limb issues, especially in elderly individuals. This condition, often associated with other pathologies, increases the risk of falling. To better understand the risk of falls, it is essential to assess patients’ postural stability. In this pilot study, we aimed to set a protocol to prevent the falling risk. We propose the use of inertial sensors (IMUs) to detect even minimal body oscillations in a non-invasive, rapid, and cost-effective way. We have analyzed a sample of 35 patients (age = 58 ± 14 years, female = 20/male = 15) to investigate the total range of body sway in the anteroposterior (AP) and mediolateral (ML) directions during static balance in relation to their age and BMI. The analysis of the collected parameters (sway area, sway pathAP, and sway pathML) has showed a lower stability at t1, at the time of orthosis application, with respect to the previous condition, implied by the necessary period of adaptation to the new plantar device. In fact, the postural parameters have visibly improved at 30 days (t2). Comparing the results obtained in the different postural exercises, we have obtained significant differences between the natural standing position with eyes open and the others. According to these results, we can suppose that using inertial sensors associated to postural exercise is the best way to assess a patient’s postural stability and that the progressive improvements may be more marked over a longer period, such as six months (t3).
Prediction Model for Cutterhead Rotation Speed Based on Dimensional Analysis and Elastic Net Regression
Authors: Liu Junsheng , Liang Feng , Wei Kai , Zuo Changqun
Published: January 2025

The development and maturation of TBM (tunnel boring machine) technology have significantly improved the accuracy and richness of excavation data, driving advancements in intelligent tunneling research. However, challenges remain in managing data noise and parameter coupling, limiting the interpretability of traditional machine learning models regarding TBM parameter relationships. This study proposes a cutterhead rotation speed prediction model based on dimensional analysis. By utilizing boxplot methods and low-pass filtering techniques, excavation data were preprocessed to select appropriate operational and mechanical parameters. A dimensionless model was established and integrated with elastic net regression to quantify parameters. Using TBM cluster data from a water diversion tunnel project in Xinjiang, the accuracy and generalizability of the model were validated. Results indicate that the proposed model achieves high prediction accuracy, effectively capturing trends in cutterhead rotation speed while demonstrating strong generalizability.
Proton Exchange Membrane Fuel Cell Stack Durability Prediction Using Arrhenius-Based Accelerated Degradation Model
Authors: Choi Youngjin , Kim MyongHwan , Park JiYoung , Goo Youngmo
Published: January 2025

To expand the applications of proton exchange membrane fuel cell (PEMFC) stacks, it is essential to address the issue of their short lifetime. Various studies are being conducted to improve this limitation, and efficient methods for verifying durability in a short period of time are required. This study presents a novel dynamic load cycling protocol designed to emulate the real-world driving conditions of commercial vehicles. This protocol was employed as an accelerated degradation test for PEMFC stacks under two elevated temperatures (65 and 80 °C), each conducted for 1000 h. A bi-exponential model, incorporating Arrhenius principles, was fitted to the degradation data. During this process, a mixed effects modeling approach was employed to distinguish between fixed and random effects within the model parameters. The activation energy was consistent across all cells and was thus designated as a fixed effect. Activation energy, which predominantly affects the long-term durability of PEMFC stacks, was estimated as 0.808 eV. By applying this estimated value to the Arrhenius equation, we calculated the acceleration factors for the degradation of fuel cell performance. Specifically, the rate of voltage degradation was found to be approximately 1.516 times faster at 65 °C and 4.923 times faster at 80 °C, compared to the standard operating temperature of 60 °C. Additionally, Monte Carlo simulations were conducted to predict the failure-time distribution under normal use conditions, estimating a median lifetime of 3884 h, which corresponds to 155,360 km of driving. This methodology offers a reliable and time-efficient framework for assessing PEMFC durability, with significant implications for reducing testing costs and accelerating the development of hydrogen fuel cell technology.