bluuebunny/crossref_metadata_2025 huggingface dataset:
Emergency Trajectory Structure for UAVs
Authors: Ongale-Obeyi Maëva , Goubinat Damien , Delahaye Daniel , Garoche Pierre-Loïc
Published: December 2024

The study of the design of emergency trajectories of air vehicles is one of the key elements in improving airspace safety for air vehicles. The aim is to lighten pilots’ workload, offering quick and effective solutions. However, almost all flight optimizers proposed in the literature still need to be completed when it comes to resolving emergency contexts, which presents a significant disadvantage to the advancement of scientific research. This resolution is based on the following problems: (a) finding paths free of obstacles, (b) ensuring their flight capacity, and finally, (c) calculating trajectories optimizing several criteria with a calculation time constraint (a few minutes). This document analyzes the safety landing problem and proposes an architecture that effectively reduces complexity and ensures solvability within a reasonable computational time. This architectural framework is designed to be adaptable, allowing for testing several algorithms to provide a quick overview of their strengths and weaknesses in this context. The primary aim of these tests is to benchmark the computational time of the overall architecture, ensuring that this adaptable framework is fully capable of handling the problem’s complexity. It is important to note that the algorithms chosen address only a simplified version of the problem. The initial results are promising in terms of time response and the potential to enhance the representativeness and complexity of the problem. The next phase of our research will focus on striking the right balance between complexity, representativity, and computational time, aiming to impact emergency response significantly.
Design and Realization of an Orchard Operation-Aid Platform: Based on Planting Patterns and Topography
Authors: Li Zhao , Li Can , Zeng Ye , Mai Chaodong , Jiang Runpeng , Li Jun
Published: December 2024

To address the lack of mechanical orchard operation-aid platforms that assist in the horticultural management tasks such as pruning, spraying, thinning flowers and fruits, and harvesting in litchi and longan orchards, this paper proposes an orchard operation-aid platform specifically tailored for hilly and mountainous orchards. The platform is optimized for orchards with tree and row spacing not exceeding 6 m and slopes not exceeding 15°. By considering the planting patterns and operational topography parameters of litchi and longan, the key components were meticulously designed, including the chassis, lifting device, extension device, and slope operation support device. The driving stability, slope operation stability, and the reachable workspace of the orchard operation-aid platform were analyzed, followed by a prototype experiment. The results demonstrate that the platform achieves an in situ turning radius of 1.2 m with no deviation in the turning path. It satisfies the passability and operational slope requirements of hilly terrains with both driving and operational slopes exceeding 15°. Additionally, the platform features a working height of 4.0 m and an operating radius of 3.7 m, meeting the operational requirements for multiple tasks. This research provides a practical and effective solution for enhancing operational efficiency in multiple stages of fruit cultivation, demonstrating significant practical value and potential for widespread application.
Association of Erythrocyte Hemolysis Products and Kidney Injury During Neonatal Cardiac Surgery
Authors: Patel Rakesh P. , Oh Joo-Yeun , Ricart Karina , Rahman Fazlur , Hock Kristal M. , Smith Royal R. , Crawford Jack H.
Published: December 2024

Background/Objectives: Hemolysis has been associated with acute kidney injury (AKI) in infants and neonates after surgery involving cardiopulmonary bypass (CPB). Erythrocyte hemolysis and subsequent end-organ injury have been shown to be a complex process involving the liberation of multiple molecules that mediate the loss of nitric oxide and oxidative damage. This study assesses the association of multiple products of erythrocyte hemolysis with the evolution of AKI in neonates and infants undergoing CPB surgery. Methods: Blood and urine samples were collected at multiple time points before and after CPB and stored within an institutional biorepository. Twenty-one patients with AKI were matched with twenty-one non-Aki patients based on demographic and case complexity data. Results: Samples were analyzed for cell-free hemoglobin, heme, non-transferrin-bound iron, haptoglobin, hemopexin, and nitrite/nitrate. NGAL and KIM-1 were measured to index AKI. Cell-free hemoglobin was higher, haptoglobin was lower, and haptoglobin:hemoglobin ratio was lower in AKI compared to non-AKI patients. Conclusions: AKI in neonates and infants after CPB is associated with a pre and postoperative decrease in serum haptoglobin. These results confirm the need for future studies to prevent injury from hemolysis during CPB and potentially identify at-risk patients with decreased haptoglobin levels before surgery if delay is an option.
Pharmacological Effects of Antioxidant Mycosporine-Glycine in Alleviating Ultraviolet B-Induced Skin Photodamage: Insights from Metabolomic and Transcriptomic Analyses
Authors: Wang Kai , Qin Ling , Lin Huan , Yao Mengke , Cao Junhan , Zhang Qing , Qu Changfeng , He Yingying , Miao Jinlai , Liu Ming
Published: December 2024

Mycosporine-glycine (M-Gly), a member of the mycosporine-like amino acid (MAA) family, is known for its potent antioxidant and anti-inflammatory properties. However, its in vivo efficacy in alleviating acute skin photodamage, primarily caused by oxidative stress, has not been well explored. In this investigation, 30 female ICR mice were divided into four groups: a control group and three Ultraviolet B (UVB)-exposed groups treated with saline or M-Gly via intraperitoneal injection for 30 days. At the end of the experiment, UVB exposure caused erythema, wrinkling, collagen degradation, and mast cell infiltration in mouse dorsal skin. M-Gly treatment improved skin appearance and reduced mast cell numbers, while also elevating antioxidant levels, including superoxide dismutase (SOD), catalase (CAT), and glutathione (GSH). Furthermore, M-Gly reduced inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and IL-1β, typically upregulated after UVB exposure. M-Gly also protected skin collagen by upregulating type I procollagen and decreasing MMP-1 levels. Skin metabolomic profiling identified 34 differentially abundant metabolites, and transcriptomic analysis revealed 752 differentially expressed genes. The combined metabolomic and transcriptomic data indicate that M-Gly’s protective effects may involve the regulation of ion transport, cellular repair, metabolic stability, collagen preservation, and the Nrf2/HO-1 pathway. These findings highlight M-Gly’s potential as an endogenous antioxidant for protecting skin from UVB-induced damage.
Effect of Ginseng Supplementation on Exercise Endurance as a Support for Cardiovascular Disease Management: A Systematic Review and Meta-Analysis
Authors: Szymańska Angelika , Nowak Anna , Lipert Anna , Kochan Ewa
Published: December 2024

Ginseng has multi-directional pharmacological properties. Some data suggest that ginseng can enhance physical endurance, which, in turn, leads to protection of the cardiovascular system. However, not all experiments are conclusive. For this reason, the main aim of this research was to perform a meta-analysis and review of studies published between the years 2013 and 2023 concerning the ginseng effect on physical performance in animal and human models. Medline, Pubmed, and ClinicalKey electronic databases were used to analyze data. The search strategy included the following criteria: ginseng and exercise; ginseng supplementation; and ginseng supplements. The results suggest that ginseng supplementation may have a positive effect on CK levels in animal studies. Similar observations were stated in relation to serum lactate and BUN. Furthermore, a human study showed a significant increase in exercise time to exhaustion and VO2 max after supplementation. The review of the literature and conducted meta-analysis identified that ginseng supplementation may have a positive effect on exercise endurance. Due to the fact that most of the current studies were based on animal models, further research on human models is needed to identify the most effective dosage or form of applied ginseng to be a supportive element in CVD management.
Antioxidant and Laxative Effects of Methanol Extracts of Green Pine Cones (Pinus densiflora) in Sprague-Dawley Rats with Loperamide-Induced Constipation
Authors: Song Hee-Jin , Seol Ayun , Park Jumin , Kim Ji-Eun , Kim Tae-Ryeol , Park Ki-Ho , Park Eun-Seo , Lim Su-Jeong , Wang Su-Ha , Sung Ji-Eun , Choi Youngwoo , Lee Heeseob , Hwang Dae-Youn
Published: December 2024

Oxidative stress is the key cause of the etiopathogenesis of several diseases associated with constipation. This study examined whether the green pine cone can improve the symptoms of constipation based on the antioxidant activities. The changes in the key parameters for the antioxidant activity and laxative effects were examined in the loperamide (Lop)-induced constipation of Sprague-Dawley (SD) rats after being treated with the methanol extracts of green pine cone (MPC, unripe fruits of Pinus densiflora). MPC contained several bioactive compounds, including diterpenoid compounds such as dehydroabietic acid, taxodone, and ferruginol. In addition, it exhibited high scavenging activity against 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radicals. These effects of MPC successfully reflected the improvement in nicotinamide adenine dinucleotide phosphate oxidase (NADP) H oxidase transcription, superoxide dismutase (SOD) levels, and nuclear factor erythroid 2-related factor 2 (Nrf2) phosphorylation levels in the mid colon of Lop+MPC-treated SD rats. Furthermore, significant improvements in the stool parameters, gastrointestinal (GI) transit, intestine length, and histopathological structure of the mid colon were detected in the Lop-induced constipation rats after MPC treatment. The other parameters, including the regulators for the adherens junction (AJ) and tight junction (TJ), and GI hormone secretion for laxative effects, were improved significantly in Lop+MPC-treated SD rats. These effects were also verified in Lop+MPC-treated primary rat intestine smooth muscle cells (pRISMCs) through analyses for antioxidant defense mechanisms. Overall, the finding of this study offers novel scientific evidence that MPC could be considered as a significant laxative for chronic constipation based on its antioxidant activity.
Nicotinamide Mononucleotide Restores NAD+ Levels to Alleviate LPS-Induced Inflammation via the TLR4/NF-κB/MAPK Signaling Pathway in Mice Granulosa Cells
Authors: Ahmed Mehboob , Riaz Umair , Lv Haimiao , Amjad Muhammad , Ahmed Sohail , Ali Shaokat , Ghani Muhammad Usman , Hua Guohua , Yang Liguo
Published: December 2024

Inflammation disrupts the normal function of granulosa cells (GCs), which leads to ovarian dysfunction and fertility decline. Inflammatory conditions such as polycystic ovary syndrome (PCOS), primary ovarian insufficiency (POI), endometriosis, and age-related ovarian decline are often associated with chronic low-grade inflammation. Nicotinamide mononucleotide (NMN) is an important precursor of NAD+ and has gained attention for its potential to modulate cellular metabolism, redox homeostasis, and mitigate inflammation. This study investigated the protective roles of NMN against lipopolysaccharide LPS-mediated inflammation in GCs. The results of this experiment demonstrated that LPS had negative effects on GCs in term of reduced viability and proliferation rates and upregulated the production of pro-inflammatory cytokines, including interleukin-1 beta (IL-1β), interleukin-6 (IL-6), cyclooxygenase-2 (Cox-2), and tumor necrosis factor-alpha (TNF-α). Notably, the levels of NAD+ and NAD+/NADH ratio in GCs were reduced in response to inflammation. On the other hand, NMN supplementation restored the NAD+ levels and the NAD+/NADH ratio in GCs and significantly reduced the expression of pro-inflammatory markers at both mRNA and protein levels. It also enhanced cell viability and proliferation rates of GCs. Furthermore, NMN also reduced apoptosis rates in GCs by downregulating pro-apoptotic markers, including Caspase-3, Caspase-9, and Bax while upregulating anti-apoptotic marker Bcl-2. NMN supplementation significantly reduced reactive oxygen species ROS and improved steroidogenesis activity by restoring the estradiol (E2) and progesterone (P4) levels in LPS-treated GCs. Mechanistically, this study found that NMN suppressed the activation of the TLR4/NF-κB/MAPK signaling pathways in GCs, which regulates inflammatory processes. In conclusion, the findings of this study revealed that NMN has the potential to reduce LPS-mediated inflammatory changes in GCs by modulating NAD+ metabolism and inflammatory signaling pathways. NMN supplementation can be used as a potential therapeutic agent for ovarian inflammation and related fertility disorders.
Estimating VS30 at South Korean Seismic Observatory Stations Through Horizontal and Vertical Ground Motions
Authors: Yee Eric , Lee Chang-kyu
Published: December 2024

This investigation attempts to estimate time-averaged shear wave velocity in the upper 30 m of surficial material, VS30, from the horizontal-to-vertical spectral ratios, HVSRs, of seismic observatory stations in the South Korean region. From 2016 to 2023, a collection of 783 three-component ground motions were obtained from 19 stations operated by the Korea Institute of Geoscience and Mineral Resources. HVSRs were extracted from 5% damped acceleration and velocity RotD50 response spectra at each site. Peak HVSR frequencies and amplitudes were extracted and regressed to field-measured VS30s at available sites. An evaluation of different frequency and amplitude conditions was made to ascertain any effects on the regression. Findings included confirmation on minimum frequency and having amplitude conditions were unnecessary. Additionally, another peak frequency to VS30 relationship derived from Central and Eastern North America captured most of the behavior found in the Korean dataset.
Technical Diagnostics of Industrial Robots Using Vibration Signals: Case Study on Detecting Base Unfastening
Authors: Fedorova Daria , Tlach Vladimír , Kuric Ivan , Dodok Tomáš , Zajačko Ivan , Tucki Karol
Published: December 2024

In the domain of modern manufacturing digitalization, artificial intelligence tools are increasingly employed for condition monitoring and technical diagnostics. However, the majority of existing methodologies primarily concentrate on the technical diagnosis of rotating machines, with a noticeable lack of research addressing these issues in sequential machines. In this paper, we deal with the selection of suitable vibration signal characteristics for the detection of an industrial robot’s release from its base during a handling operation. Statistical methods, including one-way ANOVA and t-tests, were used to identify the most significant features, which allowed us to isolate vibration metrics with significant predictive potential. These selected features were then used as inputs to various machine learning models to evaluate the hypothesis that these parameters can reliably indicate fastening releasing events. The results show that the optimized parameters significantly improve the detection accuracy, thus providing a reliable basis for future applications in predictive maintenance and monitoring. The findings represent an advance in robotic condition monitoring, providing a structured approach to feature selection that improves the reliability of disconnection detection in automated systems with potential applicability in various industrial environments.
Detecting Methotrexate in Pediatric Patients Using Artificial Neural Networks
Authors: Santiago Alejandro , Rodríguez Jorge , Torres Jorge , Rabasa Julio , Izaguirre José , Alejandro Gladys
Published: December 2024

Methotrexate is an antimetabolic agent with proliferative and immunosuppressive activity. It has been demonstrated to be an effective treatment for acute lymphoblastic leukemia (ALL) in children. However, there is evidence of an association between methotrexate and toxicity risks, which influences the personalization of treatment, particularly in the case of childhood ALL. This article presents the development and implementation of an algorithm based on artificial neural networks to detect methotrexate toxicity in pediatric patients with acute lymphoblastic leukemia. The algorithm utilizes historical clinical and laboratory data, with an effectiveness of 99% in the tests performed with the patient dataset. The use of neural networks in medicine is often linked to disease diagnosis systems. However, neural networks are not only capable of recognizing examples but also hold very important information. For this reason, one of the main areas of application of neural networks is the interpretation of medical data. In this article, we diagnose, with the application of neural networks in medicine, a concrete example: detecting methotrexate in its early stages in pediatric patients.
On the Uniform Projection Problem in Descriptive Set Theory
Authors: Kanovei Vladimir , Lyubetsky Vassily
Published: December 2024

For every n≥1, generic models of ZFC will be presented for either of the following two sentences: 1. There exists a linear Σn+21 set not equal to the projection of any uniform planar Πn+21 set. 2. There exists a linear Δn+21 set not equal to the projection of any uniform planar Πn+11 set. Ensuing consistency and independence corollaries are discussed.
Factor Rings with Algebraic Identities via Generalized Derivations
Authors: Hummdi Ali Yahya , Al-Amery Zakia Z. , Al-omary Radwan M.
Published: December 2024

The current article focuses on studying the behavior of a ring ℜ/Π when ℜ admits generalized derivations Ψ and Ω with associated derivations ϕ and δ, respectively. These derivations satisfy specific differential identities involving Π, where Π is a prime ideal of an arbitrary ring ℜ, not necessarily prime or semiprime. Furthermore, we explore some consequences of our findings. To emphasize the necessity of the primeness of Π in the hypotheses of our various theorems, we provide a list of examples.
Intuitionistic Hesitant Fuzzy Rough Aggregation Operator-Based EDAS Method and Its Application to Multi-Criteria Decision-Making Problems
Authors: Khan Muhammad Kamraz , Khan Muhammad Sajjad Ali , Kamran  , Popa Ioan-Lucian
Published: December 2024

The fundamental notions of the intuitionistic hesitant fuzzy set (IHFS) and rough set (RS) are general mathematical tools that may easily manage imprecise and uncertain information. The EDAS (Evaluation based on Distance from Average Solution) approach has an important role in decision-making (DM) problems, particularly in multi-attribute group decision-making (MAGDM) scenarios, where there are many conflicting criteria. This paper aims to introduce the IHFR-EDAS approach, which utilizes the IHF rough averaging aggregation operator. The aggregation operator is crucial for aggregating intuitionistic hesitant fuzzy numbers into a cohesive component. Additionally, we introduce the concepts of the IHF rough weighted averaging (IHFRWA) operator. For the proposed operator, a new accuracy function (AF) and score function (SF) are established. Subsequently, the suggested approach is used to show the IHFR-EDAS model for MAGDM and its stepwise procedure. In conclusion, a numerical example of the constructed model is demonstrated, and a general comparison between the investigated models and the current methods demonstrates that the investigated models are more feasible and efficient than the present methods.
The Characteristic Relation in Two-Dimensional Type I Intermittency
Authors: Colman Juan , Elaskar Sergio
Published: December 2024

To explore intermittency in discrete systems with two or more degrees of freedom, we analyze the general characteristics of type I intermittency within a two-dimensional map. This investigation is carried out numerically, concentrating on the system’s attractors, bifurcation diagrams, and the characteristic relation associated with type I intermittency. We present two methods for determining the laminar interval and the channel structure. Our computations yield numerical results for the average laminar length as a function of the control parameter, which we then compare with findings from intermittency in one-dimensional maps. We observe a strong agreement between the numerical data and the theoretical predictions.
Analyzing Uniqueness of Solutions in Nonlinear Fractional Differential Equations with Discontinuities Using Lebesgue Spaces
Authors: Hafeez Farva , Jeelani Mdi Begum , Alqahtani Nouf Abdulrahman
Published: December 2024

We explore the existence and uniqueness of solutions to nonlinear fractional differential equations (FDEs), defined in the sense of RL-fractional derivatives of order η∈(1,2). The nonlinear term is assumed to have a discontinuity at zero. By employing techniques from Lebesgue spaces, including Holder’s inequality, we establish uniqueness theorems for this problem, analogous to Nagumo, Krasnoselskii–Krein, and Osgood-type results. These findings provide a fundamental framework for understanding the properties of solutions to nonlinear FDEs with discontinuous nonlinearities.
Synthesis and Investigation of Tricyclic Isoquinoline Derivatives as Antibacterial Agents
Authors: Phillips Matthew J. A. , Ung Alison T. , Harry Elizabeth J. , Ashmore Jason , McDonagh Andrew M.
Published: December 2024

Isoquinoline derivatives exhibit a range of biological properties, including antibacterial activity, and are thus attractive as a scaffold for developing broad-spectrum antibacterial compounds. A series of six isoquinoline-based compounds were synthesized using the reaction of 6,7-dimethoxy-1-methyl-3,4-dihydroisoquinoline with dimethyl acetylenedicarboxylate (DMAD) to provide the tricyclic (2Z)-[2-oxo-5,6-dihydropyrrolo[2,1,a]isoquinolin-3-ylidene]-2-ethanoate. The [2 + 3] cycloaddition of DMAD with C-6 and C-7 substituted 1-methyl-3,4-dihydroisoquinolines proceeded using aryl ethers or unsubstituted compounds, but not with amine, amide or nitro moieties at the C-7 position. Compounds 8d and 8f were found to have antibacterial properties against some Gram-positive pathogens (Staphylococcus aureus—8d = 16 µg/mL, 8f = 32 µg/mL; Streptococcus pneumoniae—8f = 32 µg/mL; and Enterococcus faecium—8d = 128 µg/mL, 8f = 64 µg/mL). Evaluation of their cytotoxic properties against mammalian cell lines revealed some cytotoxic effects (8b and 8d, 125 µM, 24 h, HEp-2 cells) and (8a, 8b, 8d = 125 µM, 8f = 62.5 µM, 24 h, McCoy B cells), suggesting limitations in their antibacterial applications without further development.
Identification and Characterization of the LecRLKs Gene Family in Maize, and Its Role Under Biotic and Abiotic Stress
Authors: Yang Xiangbo , Chen Ziqi , Lu Jianyu , Wei Xuancheng , Yao Yanying , Lv Wendi , Han Jiarui , Fei Jianbo
Published: December 2024

Plant lectin receptor-like kinases (LecRLKs) are plant membrane protein receptor kinases. Lectin-like receptor kinases play a crucial role in regulating plant growth, development, and responses to environmental stimuli. It can rapidly respond to both biotic and abiotic stresses while mediating mechanisms of plant immune responses. This study represents the first identification of the LecRLK family genes in maize. It analyzes the gene structure, chromosomal locations, phylogenetic classification, promoter homoeotropic elements, and expression patterns under both biotic and abiotic stresses. The results indicate that these genes possess kinase and transmembrane domains, along with specific L-type or G-type extracellular domains. Most ZmLecRLK gene promoters contain cis-acting elements that are responsive to known hormones and stressors. Furthermore, these genes have been identified as being sensitive to both biotic and abiotic stresses. This discovery establishes a significant theoretical foundation for the selection of corn varieties in adverse environments. Additionally, it provides a basis for further in-depth exploration of the molecular regulatory mechanisms of LecRLK family genes.
Optimizing Vegetation Restoration: A Comprehensive Index System for Reclaiming Abandoned Mining Areas in Arid Regions of China
Authors: Aili Aishajiang , Zhang Yuguang , Lin Tao , Xu Hailiang , Waheed Abdul , Zhao Wanyu , Kuerban Amannisha , Liu Kun , Dou Haitao
Published: December 2024

Mining activities in arid regions of China have led to severe environmental degradation, including soil erosion, vegetation loss, and contamination of soil and water resources. These impacts are particularly pronounced in abandoned mining areas, where the cessation of mining operations has left vast landscapes unrehabilitated. In response, the Chinese government has implemented a series of legal and regulatory frameworks, such as the “Mine Environmental Protection and Restoration Program”, aimed at promoting ecological restoration in these areas. However, the unique environmental conditions of arid regions, including water scarcity, extreme temperatures, and poor soil quality, present significant challenges to restoration efforts. This review provides a comprehensive analysis of the ecological restoration of abandoned mining areas in China’s arid regions, focusing on the legal framework, restoration techniques, and evaluation systems. The restoration methods, their initiation timelines, monitoring systems, and the cost–benefit aspects of various strategies are critically reviewed alongside case studies from regions such as the Mu Us Desert and Qaidam Basin. Key strategies like phytoremediation, soil rehabilitation, and water resource management are assessed for their effectiveness, while challenges in enforcement, socioeconomic integration, and community engagement are discussed. This review concludes that while significant progress has been made, further improvements in restoration practices and evaluation systems are essential for long-term sustainability. Integration of socioeconomic indicators, community involvement, and advanced monitoring technologies are necessary for successful outcomes.
miR-134-3p Regulates Cell Proliferation and Apoptosis by Targeting INHBA via Inhibiting the TGF-β/PI3K/AKT Pathway in Sheep Granulosa Cells
Authors: Huang Xinai , Bao Yongjin , Yang Fan , Li Xiaodan , Wang Feng , Zhang Chunxiang
Published: December 2024

Inhibin β-A (INHBA), a TGF-β superfamily member, is crucial for developing follicles. Although miRNAs are essential for post-transcriptional gene regulation, it is not yet known how they affect the expression of INHBA during follicle development. Using bioinformatics analyses, miR-134-3p was found, in this investigation, to be a crucial microRNA that targets INHBA in sheep GCs. Furthermore, when the follicular diameter expanded, there was a discernible decline in miR-134-3p expression. The miR-134-3p overexpression markedly reduced the proliferation of GCs, whereas its knockdown augmented it. Moreover, cell cycle progression was enhanced by miR-134-3p overexpression. Furthermore, miR-134-3p overexpression heightened GC apoptosis, while its knockdown reduced it. Importantly, miR-134-3p overexpression blocked the PI3K/AKT/mTOR axis, whereas its knockdown stimulated it. Overall, the outcomes of transfections with INHBA and miR-134-3p showed that, in sheep GCs, miR-134-3p targets INHBA to control cell proliferation and apoptosis. In summary, these results add to our understanding of the molecular mechanisms involving important miRNAs in ewe fecundity by indicating that miR-134-3p influences cell proliferation, cell apoptosis, and the TGF-β/PI3K/AKT/mTOR axis, which, in turn, influences the follicular development of sheep GCs.
Senegalin-2: A Novel Hexadecapeptide from Kassina senegalensis with Antibacterial and Muscle Relaxant Activities, and Its Derivative Senegalin-2BK as a Bradykinin Antagonist
Authors: Lu Yueyang , Zhu Yanguo , Ma Chengbang , Wang Lei , Zhou Mei , Chen Tianbao , Ma Xiaonan , Zhang Xu , Fan Zhimin
Published: December 2024

The amphibian skin secretions are excellent sources of bioactive peptides, some of which and their derivatives exhibit multiple properties, including antibacterial and antagonism against bradykinin. A novel peptide Senegalin-2 was isolated from the skin secretions of Kassina senegalensis frog. Senegalin-2 relaxed rat bladder smooth muscle (EC50 17.94 nM) and ileum smooth muscle (EC50 135 nM), inhibited S. aureus and MRSA at 2 μM, and exhibited low hemolytic activity with no cytotoxicity. To design effective bradykinin antagonists, Senegalin-2 was conjugated with bradykinin to synthesize Senegalin-2BK. This modification retained potent activity against Gram-positive bacteria. Compared to Senegalin-2, Senegalin-2BK significantly reduced hemolysis and exhibited a more than threefold increase in the selectivity index. Furthermore, Senegalin-2BK contracted the bladder (EC50 2.83 μM) and ileum (EC50 56.64 nM)’s smooth muscle. The pretreatment with 10−7 M Senegalin-2BK reduced the 10−6 M bradykinin contraction on the bladder by over 70%. In conclusion, Senegalin-2 has dual functionalities as an antibacterial agent and muscle relaxant, positioning it as a potential therapeutic candidate for managing overactive bladder. As a synthetically derived bradykinin antagonist and myotropic peptide with antibacterial properties, Senegalin-2BK shows promise in effective therapies for relieving pain, inflammation, and addressing muscular disorders such as urinary retention, constipation, and infections.
An Overview on the Manufacture and Properties of Clay-Based Porous Ceramics for Water Filtration
Authors: Maury Njoya Iffat Qoudsiyyah , Lecomte-Nana Gisèle Laure , Barry Kassoum , Njoya Dayirou , El Hafiane Youssef , Peyratout Claire
Published: December 2024

This study explores the different techniques used to manufacture porous clay-based ceramics, examining their properties such as porosity, strength, permeability and filtration efficiency. Different techniques are discussed in this review, with additive manufacturing being one of the most innovative techniques for manufacturing porous ceramics. Porous ceramics have their applications in numerous domains. Such ceramic filters have the advantages of retaining heavy materials, suspended particles, bacteria, viruses and, water turbidity. Thus, the choice of the technique and propriety is a crucial step in obtaining a porous ceramic with the best performance. Barry et al. prepared porous phyllosilicate-based ceramics by freeze-tape casting on four samples and obtained porosity values in the range of 67–79% and diametrical compressive strength in the range of 3–7 MPa. Manni et al. prepared porous red ceramics from Moroccan clay and coffee waste (10, 20 and 30 wt.%) via uniaxial pressing and sintering at 1150 °C. They obtained porosities ranging from 30.2 to 63.8% and flexural strength values from 1.8 to 19.5 MPa. Medri et al. prepared ZrB2-based porous bodies with the use of sponges and polyurethane foams as templates via the replica method and obtained high porosity over 80% and compressive strength up to 4.8 MPa. The use of clay and peanut shell mixtures was used in preparing porous silicate ceramics after unidirectional pressing and sintering at 1100 °C. These samples included 25 mass% of peanut shells, and exhibited porosity in the range of 40 to 60% and diametrical compressive strength in the range of 1–6 MPa. Such properties are suitable for domestic use of these types of clay-based ceramic filters. Moreover, the permeability values and removal of some pollutants, like arsenic, have been satisfactory for the first set of samples.
Measurement and Correlation of Vapor–Liquid Equilibrium of Mixtures of 1,2-Propanediol or 1,4-Butanediol + 1,8-Diazabicyclo(5.4.0)undec-7-ene at 30 kPa
Authors: Barbieri Camilla , Schiattarella Valentina , Moioli Stefania , Pellegrini Laura A. , Filippini Giacomo , de Angelis Alberto R. , Fiori Gianluca
Published: December 2024

In this study, vapor–liquid equilibrium (VLE) experimental data were measured for two binary solvents based on 1,8-diazabicyclo(5.4.0)undec-7-ene (DBU), which can be used as a new CO2-binding organic liquids (CO2-BOLs) solvent. No experimental data are available in the literature and are fundamental to determine whether the considered mixtures are suitable to be possible alternatives to traditional amine solutions for CO2 removal. The bubble point data of 1,2-propanediol+1,8-diazabicyclo(5.4.0)undec-7-ene (DBU) and 1,4-butanediol+DBU mixtures were measured at 30 kPa. The experimental determination was carried out in an all-glass dynamic recirculation still at the Process Thermodynamics laboratory (PT lab) of Politecnico di Milano. The thermodynamic modeling of the VLE behavior of two DBU-based mixtures was performed considering the NRTL, the UNIQUAC, and the Wilson models, and binary interaction parameters of the NRTL activity coefficients model were regressed on the basis of the measured experimental data.
Effect of Various Foaming Agents on Ceramic Foam from Solid Waste
Authors: Zhao Chenglin , Wang Chunmin , Xia Zichen , Jiang Congcong , Dong Yiran , Lan Zihao
Published: December 2024

Due to the significant amount of solid waste generated annually in China, the rational use of these wastes has become increasingly important. The production of foam ceramics is considered an effective method for the large-scale utilization of such solid waste. In this study, granite sawing mud was selected as the raw material, with SiC and MnO2 serving as foaming agent to prepare foam ceramics. The foaming behavior of sintered samples using different foaming agent was investigated to determine the most suitable type and amount of foaming agent for obtaining foam ceramics with excellent pore structures. Additionally, the effects of the foaming agent on the pore structure and physical mechanical properties of the foam ceramics were studied in detail. The results showed that SiC and MnO2 both resulted in the pronounced expansion to different extent, and increasing the content of foaming agent enhances foam expansion. The best dosage of SiC was 1%, the optimum additive amount of MnO2 is 2–3%. For SiC, the oxidation reduction reaction occurred between SiC and O2 to generate CO2/CO. For MnO2, firstly, the reduction of MnO2 to Mn2O3 occurred, and then the Mn2O3 dissolved in the glass melt and, subsequently, Mn3+ was reduced to Mn2+, leading to gas formation and foaming. Under the same dosage of foaming agent and preparation conditions, the sample prepared with SiC as the blowing agent has higher compressive strength, lower water absorption, and a more uniform pore structure.
Aerodynamic Investigation for a Propeller-Induced Lift-Enhancing Vertical Take-Off and Landing (VTOL) Configuration
Authors: Wang Hongbo , Li Guangjia , Li Jie , Zhuang Junjie
Published: December 2024

Difficulty in thrust-matching between the cruise and vertical take-off and landing (VTOL) phases is one of the prominent issues faced by conventional VTOL fixed-wing drones. To address this issue, a propeller-induced lift-enhancing (PILE) biplane wing VTOL configuration is proposed with the goal of lift enhancement on the wing during the no-forward-speed VTOL phase. Numerical simulation methods are used to study and analyze the aerodynamic characteristics of this configuration in the cruise and VTOL phases. The results show that the favorable inducing effect of the propeller makes the PILE configuration have a good effect of increasing lift and reducing drag compared with a single wing of the same area during the cruise phase, improving the lift-to-drag ratio by 7.27%. During the VTOL phase, the optimal tilt angle of the propeller for the PALE configuration is 70°, matched with an installation angle of 5° for the aided wing. This parameter combination balances the total drag while also achieving a lift-to-thrust ratio of 1.12. As a result, the required thrust of the propeller is reduced under the same take-off weight, which helps to alleviate the thrust-matching problem and enables VTOL with a smaller power cost.
A Framework of Recommendation System for Unmanned Aerial Vehicle Autonomous Maneuver Decision
Authors: Hao Qinzhi , Jing Tengyu , Sun Yao , Yang Zhuolin , Zhang Jiali , Wang Jiapeng , Wang Wei
Published: December 2024

Autonomous maneuvering decision-making in unmanned serial vehicles (UAVs) is crucial for executing complex missions involving both individual and swarm UAV operations. Leveraging the successful deployment of recommendation systems in commerce and online applications, this paper pioneers a framework tailored for UAV maneuvering decisions. This novel approach harnesses recommendation systems to enhance decision-making in UAV maneuvers. Our framework incorporates a comprehensive six-degree-of-freedom dynamics model that integrates gravitational effects and defines mission success criteria. We developed an integrated learning recommendation system capable of simulating varied mission scenarios, facilitating the acquisition of optimal strategies from a blend of expert human input and algorithmic outputs. The system supports extensive simulation capabilities, including various control modes (manual, autonomous, and hybrid) and both continuous and discrete maneuver actions. Through rigorous computer-based testing, we validated the effectiveness of established recommendation algorithms within our framework. Notably, the prioritized experience replay deep deterministic policy gradient (PER-DDPG) algorithm, employing dense rewards and continuous actions, demonstrated superior performance, achieving a 69% success rate in confrontational scenarios against a versatile expert algorithm after 1000 training iterations, marking an 80% reduction in training time compared to conventional reinforcement learning methods. This framework not only streamlines the comparison of different maneuvering algorithms but also promotes the integration of multi-source expert knowledge and sophisticated algorithms, paving the way for advanced UAV applications in complex operational environments.
External Constraints on the Development of Quality Assessment of Students’ Learning in Higher Education
Authors: Manrique-Arribas Juan C. , López-Pastor Víctor M. , Palacios-Picos Andrés
Published: December 2024

Learning-oriented assessment models, which tend to generate better learning processes, better academic performance and greater student involvement in teaching–learning processes, are increasingly being used in European universities; they are also more suitable for competence-based learning. However, there are a number of constraints that hinder their implementation, either due to internal (lack of teacher training and attitude/motivation to make changes in teaching and assessment methodology) or external (teaching load of lecturers and group size (number of students per group)) factors. Taking the latter into account, the aim of this study was to determine to what extent the teaching load and the number of students per group condition the use or not of quality assessment systems in the university world. A questionnaire of assessment systems and instruments with a high level of reliability and validity was administered to a large and representative sample of the teaching staff from numerous Spanish universities. Multivariate analyses were carried out to try to achieve the research objective. The results, based on a post facto model, show that quality assessment systems are advancing. Furthermore, the conclusion was reached that the teaching load and the number of students to be assessed are factors that correlate significantly with a greater use of assessment systems involving exams with closed questions. They correlate negatively with the use of continuous and formative assessment (FA) systems, although there is much variability in the latter case and the results do not seem clearly conclusive, suggesting more research on this topic and its sustainability.
Sequence Analysis-Enhanced AI: Transforming Interactive E-Book Data into Educational Insights for Teachers
Authors: Opanasenko Yaroslav , Bardone Emanuele , Pedaste Margus , Siiman Leo Aleksander
Published: December 2024

This study explores the potential of large language models as interfaces for conducting sequence analysis on log data from interactive E-Books. As studies show, qualitative methods are not sufficient to comprehensively study the process of interaction with interactive E-Books. The quantitative method of educational data mining (EDM) has been considered as one of the most promising approaches for studying learner interactions with E-Books. Recently, sequence analysis showed potential in identifying typical patterns of interaction from log data collected from the Estonian Interactive E-Book Platform Opiq, allowing one to see the types of sessions from students in different grades, clusters of students based on the amount of the content they studied, and the interaction type they preferred. The main goal of the present study is to understand how teachers can utilize insights from CustomGPT to enhance their understanding of students’ interaction strategies with digital learning environments (DLEs) such as Opiq, and what the potential areas for further development of such tools are. We specified the process for developing a chatbot for transferring teachers’ queries into sequence analysis results and gathered feedback from teachers, allowing us both to estimate current design solutions to make sequence analysis results available and to find potential vectors of its development. Participants provided explicit feedback on CustomGPT, appreciating its potential for group and individual analysis, while suggesting improvements in visualization clarity, legend design, descriptive explanations, and personalized tips to better meet their needs. Potential areas of development, such as integrating personalized learning statistics, enhancing visualizations and reports for individual progress and mitigating AI hallucinations by expanding training data, are described.
Heterogeneous Edge Computing for Molecular Property Prediction with Graph Convolutional Networks
Authors: Grailoo Mahdieh , Nunez-Yanez Jose
Published: December 2024

Graph-based neural networks have proven to be useful in molecular property prediction, a critical component of computer-aided drug discovery. In this application, in response to the growing demand for improved computational efficiency and localized edge processing, this paper introduces a novel approach that leverages specialized accelerators on a heterogeneous edge computing platform. Our focus is on graph convolutional networks, a leading graph-based neural network variant that integrates graph convolution layers with multi-layer perceptrons. Molecular graphs are typically characterized by a low number of nodes, leading to low-dimensional dense matrix multiplications within multi-layer perceptrons—conditions that are particularly well-suited for Edge TPUs. These TPUs feature a systolic array of multiply–accumulate units optimized for dense matrix operations. Furthermore, the inherent sparsity in molecular graph adjacency matrices offers additional opportunities for computational optimization. To capitalize on this, we developed an FPGA GFADES accelerator, using high-level synthesis, specifically tailored to efficiently manage the sparsity in both the graph structure and node features. Our hardware/software co-designed GCN+MLP architecture delivers performance improvements, achieving up to 58× increased speed compared to conventional software implementations. This architecture is implemented using the Pynq framework and TensorFlow Lite Runtime, running on a multi-core ARM CPU within an AMD/Xilinx Zynq Ultrascale+ device, in combination with the Edge TPU and programmable logic.
Gait Phase Recognition of Hip Exoskeleton System Based on CNN and HHO-SVM Model
Authors: Wang Hongmin , Wang Meng , Li Dagang , Deng Fuqin , Pan Zengxi , Song Yingying
Published: December 2024

Gait phase recognition is crucial for developing wearable lower-limb exoskeleton robots and is a prerequisite for the compliance control of lower-limb exoskeleton robots. Accurately estimating the gait phase is still a key challenge in exoskeleton control. To address these challenges, this study proposes a hybrid model that combines Convolutional Neural Networks (CNN) and Harris Hawks Optimization (HHO)—based Support Vector Machine (SVM). First, the collected sensor signals are preprocessed by normalization to reduce the differences in the data of the subjects. Then, a simplified CNN is used to automatically extract more discriminative features from the dataset. These features are classified using SVM instead of the softmax layer in CNN. In addition, an improved Harris hawk optimization (HHO) algorithm is used to optimize the SVM classification process. This model can accurately identify the heel strike (HS), flat foot (FF), heel off (HO), and swing (SW) phases of the gait cycle. The experimental results show that the CNN-HHO-SVM algorithm can achieve an average phase recognition accuracy of 96.03% for seven subjects in the self-built dataset, which is superior to the traditional method that relies on manually extracting time-frequency features. In addition, the F1-score and macro-recall of the CNN-HHO-SVM algorithm are better than those of other algorithms, which verifies the superiority of the algorithm.
Semi-Automated Building Dataset Creation for 3D Semantic Segmentation of Point Clouds
Authors: Yoo Hyeongjun , Kim Yeonggwang , Ryu Je-Ho , Lee Seungjoo , Lee Jong Hun
Published: December 2024

When 2D drawings are unavailable or significantly differ from the actual site, scan-to-BIM (Building Information Modeling) technology is employed to generate 3D models from point cloud data. This process is predominantly manual, but ongoing research aims to automate it. However, compared to 2D image data, 3D point clouds face a persistent shortage of data, limiting the ability of deep learning models to learn diverse data characteristics and reducing their generalization performance. To address data scarcity, this paper proposes a semi-automated framework for generating datasets for semantic segmentation using 3D point clouds and Building Information Modeling (BIM) models. The framework includes a preprocessing method to spatially segment entire building datasets and applies boundary representations of BIM objects to detect intersections with point cloud data, enabling automated labeling. Using this framework, data from five buildings were processed to create 10 areas. Additionally, six datasets were constructed by combining Stanford 3D Indoor Scene Dataset (S3DIS) data with the newly generated data, and both quantitative and qualitative evaluations were conducted on various areas. Models trained on datasets incorporating diverse domains consistently achieved the highest performance across most areas, demonstrating that diverse domain data significantly enhance model generalization. The proposed framework facilitates the generation of high-quality 3D point cloud datasets from various domains, supporting the improvement of deep learning model generalization.