bluuebunny/crossref_metadata_2025 huggingface dataset:
Curculigoside Attenuates Endoplasmic Reticulum Stress-Induced Epithelial Cell and Fibroblast Senescence by Regulating the SIRT1-P300 Signaling Pathway
Authors: Xie Weixi , Deng Lang , Qian Rui , Huang Xiaoting , Liu Wei , Tang Siyuan
Published: March 2024

The senescence of alveolar epithelial cells (AECs) and fibroblasts plays a pivotal role in the pathogenesis of idiopathic pulmonary fibrosis (IPF), a condition lacking specific therapeutic interventions. Curculigoside (CCG), a prominent bioactive constituent of Curculigo, exhibits anti-osteoporotic and antioxidant activities. Our investigation aimed to elucidate the anti-senescence and anti-fibrotic effects of CCG in experimental pulmonary fibrosis and delineate its underlying molecular mechanisms. Our findings demonstrate that CCG attenuates bleomycin-induced pulmonary fibrosis and lung senescence in murine models, concomitantly ameliorating lung function impairment. Immunofluorescence staining for senescence marker p21, alongside SPC or α-SMA, suggested that CCG’s mitigation of lung senescence correlates closely with the deceleration of senescence in AECs and fibroblasts. In vitro, CCG mitigated H2O2-induced senescence in AECs and the natural senescence of primary mouse fibroblasts. Mechanistically, CCG can upregulate SIRT1 expression, downregulating P300 expression, enhancing Trim72 expression to facilitate P300 ubiquitination and degradation, reducing the acetylation levels of antioxidant enzymes, and upregulating their expression levels. These actions collectively inhibited endoplasmic reticulum stress (ERS) and alleviated senescence. Furthermore, the anti-senescence effects and mechanisms of CCG were validated in a D-galactose (D-gal)-induced progeroid model. This study provides novel insights into the mechanisms underlying the action of CCG in cellular senescence and chronic diseases, offering potential avenues for the development of innovative drugs or therapeutic strategies.
Redox Regulation of Immunometabolism in Microglia Underpinning Diabetic Retinopathy
Authors: Cai Luwei , Xia Mengxue , Zhang Fang
Published: March 2024

Diabetic retinopathy (DR) is the leading cause of visual impairment and blindness among the working-age population. Microglia, resident immune cells in the retina, are recognized as crucial drivers in the DR process. Microglia activation is a tightly regulated immunometabolic process. In the early stages of DR, the M1 phenotype commonly shifts from oxidative phosphorylation to aerobic glycolysis for energy production. Emerging evidence suggests that microglia in DR not only engage specific metabolic pathways but also rearrange their oxidation-reduction (redox) system. This redox adaptation supports metabolic reprogramming and offers potential therapeutic strategies using antioxidants. Here, we provide an overview of recent insights into the involvement of reactive oxygen species and the distinct roles played by key cellular antioxidant pathways, including the NADPH oxidase 2 system, which promotes glycolysis via enhanced glucose transporter 4 translocation to the cell membrane through the AKT/mTOR pathway, as well as the involvement of the thioredoxin and nuclear factor E2-related factor 2 antioxidant systems, which maintain microglia in an anti-inflammatory state. Therefore, we highlight the potential for targeting the modulation of microglial redox metabolism to offer new concepts for DR treatment.
Deferasirox Causes Leukaemia Cell Death through Nrf2-Induced Ferroptosis
Authors: Hsu Wan-Yi , Wang Li-Ting , Lin Pei-Chin , Liao Yu-Mei , Hsu Shih-Hsien , Chiou Shyh-Shin
Published: March 2024

Acute lymphoblastic leukaemia (ALL) is the most prevalent cancer in children, and excessive iron buildup resulting from blood transfusions and chemotherapy potentially has a negative impact on treatment outcomes and prognosis in patients with ALL. Therefore, initiating early iron chelation therapy during ALL treatment is a logical approach. Ideally, the selected iron chelator should also possess anti-leukaemia properties. The aim of the present study was to explore the potential impact and underlying mechanism of deferasirox (DFX) in ALL therapy. This study proved that DFX, an iron chelator, is capable of inducing leukaemia cell death through ferroptosis, which is achievable by increasing the expression of acetylated nuclear factor erythroid 2-related factor 2 (NRF2). More specifically, NRF2 acetylation on Lys599 was facilitated by acetyltransferase-p300/CBP. These findings indicate that DFX could serve as a potent adjunctive medication for patients with ALL. Moreover, DFX may offer dual benefits in ALL treatment, functioning as both an iron chelator and NRF2-modulating agent. Further research and clinical trials are necessary to fully elucidate the therapeutic potential of DFX in patients with ALL and incorporate it into treatment protocols.
Mechanistic Insights into the Multiple Functions of Niacinamide: Therapeutic Implications and Cosmeceutical Applications in Functional Skincare Products
Authors: Marques Cíntia , Hadjab Farid , Porcello Alexandre , Lourenço Kelly , Scaletta Corinne , Abdel-Sayed Philippe , Hirt-Burri Nathalie , Applegate Lee Ann , Laurent Alexis
Published: March 2024

Niacinamide (or nicotinamide) is a small-molecule hydrosoluble vitamin with essential metabolic functions in mammalian cells. Niacinamide has become a key functional ingredient in diverse skincare products and cosmetics. This vitamin plays a pivotal role in NAD+ synthesis, notably contributing to redox reactions and energy production in cutaneous cells. Via diversified biochemical mechanisms, niacinamide is also known to influence human DNA repair and cellular stress responses. Based on decades of safe use in cosmetics, niacinamide recently gained widespread popularity as an active ingredient which aligns with the “Kligman standards” in skincare. From a therapeutic standpoint, the intrinsic properties of niacinamide may be applied to managing acne vulgaris, melasma, and psoriasis. From a cosmeceutical standpoint, niacinamide has been widely leveraged as a multipurpose antiaging ingredient. Therein, it was shown to significantly reduce cutaneous oxidative stress, inflammation, and pigmentation. Overall, through multimodal mechanisms, niacinamide may be considered to partially prevent and/or reverse several biophysical changes associated with skin aging. The present narrative review provides multifactorial insights into the mechanisms of niacinamide’s therapeutic and cosmeceutical functions. The ingredient’s evolving role in skincare was critically appraised, with a strong focus on the biochemical mechanisms at play. Finally, novel indications and potential applications of niacinamide in dermal fillers and alternative injectable formulations were prospectively explored.
Dietary Polyphenols: Review on Chemistry/Sources, Bioavailability/Metabolism, Antioxidant Effects, and Their Role in Disease Management
Authors: Rudrapal Mithun , Rakshit Gourav , Singh Ravi Pratap , Garse Samiksha , Khan Johra , Chakraborty Soumi
Published: March 2024

Polyphenols, as secondary metabolites ubiquitous in plant sources, have emerged as pivotal bioactive compounds with far-reaching implications for human health. Plant polyphenols exhibit direct or indirect associations with biomolecules capable of modulating diverse physiological pathways. Due to their inherent abundance and structural diversity, polyphenols have garnered substantial attention from both the scientific and clinical communities. The review begins by providing an in-depth analysis of the chemical intricacies of polyphenols, shedding light on their structural diversity and the implications of such diversity on their biological activities. Subsequently, an exploration of the dietary origins of polyphenols elucidates the natural plant-based sources that contribute to their global availability. The discussion extends to the bioavailability and metabolism of polyphenols within the human body, unraveling the complex journey from ingestion to systemic effects. A central focus of the review is dedicated to unravelling the antioxidant effects of polyphenols, highlighting their role in combating oxidative stress and associated health conditions. The comprehensive analysis encompasses their impact on diverse health concerns such as hypertension, allergies, aging, and chronic diseases like heart stroke and diabetes. Insights into the global beneficial effects of polyphenols further underscore their potential as preventive and therapeutic agents. This review article critically examines the multifaceted aspects of dietary polyphenols, encompassing their chemistry, dietary origins, bioavailability/metabolism dynamics, and profound antioxidant effects. The synthesis of information presented herein aims to provide a valuable resource for researchers, clinicians, and health enthusiasts, fostering a deeper understanding of the intricate relationship between polyphenols and human health.
A Mechanistic Study of the Osteogenic Effect of Arecoline in an Osteoporosis Model: Inhibition of Iron Overload-Induced Osteogenesis by Promoting Heme Oxygenase-1 Expression
Authors: Jiang Zhongjing , Deng Linhua , Xiang Gang , Xu Xia , Wang Yunjia
Published: March 2024

Iron overload-associated osteoporosis presents a significant challenge to bone health. This study examines the effects of arecoline (ACL), an alkaloid found in areca nut, on bone metabolism under iron overload conditions induced by ferric ammonium citrate (FAC) treatment. The results indicate that ACL mitigates the FAC-induced inhibition of osteogenesis in zebrafish larvae, as demonstrated by increased skeletal mineralization and upregulation of osteogenic genes. ACL attenuates FAC-mediated suppression of osteoblast differentiation and mineralization in MC3T3-E1 cells. RNA sequencing analysis suggests that the protective effects of ACL are related to the regulation of ferroptosis. We demonstrate that ACL inhibits ferroptosis, including oxidative stress, lipid peroxidation, mitochondrial damage, and cell death under FAC exposure. In this study, we have identified heme oxygenase-1 (HO-1) as a critical mediator of ACL inhibiting ferroptosis and promoting osteogenesis, which was validated by HO-1 knockdown and knockout experiments. The study links ACL to HO-1 activation and ferroptosis regulation in the context of bone metabolism. These findings provide new insights into the mechanisms underlying the modulation of osteogenesis by ACL. Targeting the HO-1/ferroptosis axis is a promising therapeutic approach for treating iron overload-induced bone diseases.
Experimental and Theoretical Investigations of the Mechanical Behavior of Column-Free Quasi-Rectangular Segmental Tunnel Linings
Authors: Liu Zhen , Chen Yizheng , Wu Yuebin , Liu Xian
Published: March 2024

To investigate the mechanical behavior and design methodology of column-free QRST (quasi-rectangular segmental tunnel) structures, a theoretical analysis based on prototype experiments and simulation models is conducted. Initially, a prototype experimental investigation is conducted to reveal the structural behavior at the service stage. Subsequently, the ESHR model (Equivalent Stiffness Homogeneous Ring), the BS model (Beam Spring), and the MBS model (Modified Beam Spring) are used to simulate structural behavior. For design purposes, the design methodology is explored based on the ESHR model, followed by a sensitivity analysis of several key load parameters. Based on the experimental results, weak parts of the column-free QRST structure are found to include several joints (Joint 1, Joint 5, Joint 3, and Joint 8), and corresponding optimization measures are proposed. By comparing the test results, the above-mentioned three models demonstrate their applicability in structural simulation, with the ESHR model having sufficient design accuracy. A model-based deformation mechanism analysis found that joints contribute approximately 2/3 of the structural deformation. For the structural design of the column-free QRST using the ESHR model, amplifying the calculated results of structures directly subjected to the service stage by 10% suffices to meet engineering requirements. Based on the test and study, special attention should be paid to the negative bending moment regions at the waists of the structure during both the design and service stages.
Research on the Calculation Method for the Load Distribution of the Dual-Input Counter-Rotating Transmission System
Authors: Yu He , Shi Wankai , Su Zhenhao
Published: March 2024

In order to solve the problem of an uneven load distribution in a double-input and double-output gearbox, based on the small-displacement Jacobi spin theory and considering the manufacturing and assembly errors of the gearbox, a Jacobi spin analysis model of the gearbox was established. In order to improve the accuracy of the three-dimensional tolerance analysis of the gearbox, on the basis of the processing method of parallel chain of gears and shafts and box and shafts, the serialization method of parallel chain of meshing gear pairs is proposed, and the gearbox was established. For the three-dimensional tolerance analysis model, three-dimensional tolerance analysis was carried out on the side-clearance dimensions of double-input and double-output gearboxes, and the side clearance values under the extreme value method and Monte Carlo method were deduced and combined with the theoretical side clearance to obtain the range of the side clearance of the gearboxes. Elastic deflection analysis was carried out on the gearbox shaft system, and the compensation relationship between the elastic deflection and the side clearance was investigated, so as to calculate the range of the value of the gearbox uniform load coefficient from 1 to 1.259. The error between the theoretically calculated uniform load coefficient and the experimentally tested uniform load coefficient was 6.61%, which verifies the reasonableness of the load distribution method of double-input and double-output gearboxes calculated using three-dimensional tolerance analysis combined with the elastic deflection angle, and provides a theoretical basis for the optimal design of the uniform load of multi-branch input gearboxes.
Improved Bootstrap Method Based on RBF Neural Network for Reliability Assessment
Authors: Wang Houxiang , Liu Haitao , Shao Songshi
Published: March 2024

The investigation of the reliability of long-life equipment is typically hindered by the lack of experimental data, which makes accurate assessments challenging. To address this problem, a bootstrap method based on the improved RBF (radial basis function) neural network is proposed. This method utilizes the exponential function to modify the conventional empirical distribution function and fit right-tailed data. In addition, it employs the RBF radial basis neural network to obtain the distribution characteristics of the original samples and then constructs the neighborhood function to generate the input network. The expanded sample is used to estimate the scale and shape parameters of the Weibull distribution and obtain the estimated value of the MTBF (mean time between failures). The bias correction method is then used to obtain the interval estimate for the MTBF. Subsequently, a simulation experiment is conducted based on the failure data of a CNC (computer numerical control) machine tool to verify the effect of this method. The results show that the accuracy of the MTBF point estimation and interval estimation obtained using the proposed method is superior to those of the original and conventional bootstrap methods, which is of major significance to engineering applications.
Robust Learning from Demonstration Based on GANs and Affine Transformation
Authors: An Kang , Wu Zhiyang , Shangguan Qianqian , Song Yaqing , Xu Xiaonong
Published: March 2024

Collaborative robots face barriers to widespread adoption due to the complexity of programming them to achieve human-like movement. Learning from demonstration (LfD) has emerged as a crucial solution, allowing robots to learn tasks directly from expert demonstrations, offering versatility and an intuitive programming approach. However, many existing LfD methods encounter issues such as convergence failure and lack of generalization ability. In this paper, we propose: (1) a generative adversarial network (GAN)-based model with multilayer perceptron (MLP) architecture, coupled with a novel loss function designed to mitigate convergence issues; (2) an affine transformation-based generalization method aimed at enhancing LfD tasks by improving their generalization performance; (3) a data preprocessing method tailored to facilitate deployment on robotics platforms. We conduct experiments on a UR5 robotic platform tasked with handwritten digit recognition. Our results demonstrate that our proposed method significantly accelerates generation speed, achieving a remarkable processing time of 23 ms, which is five times faster than movement primitives (MPs), while preserving key features from demonstrations. This leads to outstanding convergence and generalization performance.
Neuromuscular Performance of World-Class Judo Athletes on Bench Press, Prone Row and Repeated Jump Tests
Authors: Monteiro Luís , Massuça Luís Miguel , Ramos Sérgio , Garcia-Garcia José
Published: March 2024

Judo is a sport that requires multiple high-intensity moments during the fight and high neuromuscular performance. Although not often, the explosive actions of the lower limbs can be decisive to winning in combat. This study aims to identify the differences in the neuromuscular features of the range of movements of the upper and lower limbs between the top-elite and elite male judo athletes. This cross-sectional study included 63 high-level male judo athletes, who were classified into two level groups: (i) top-elite (n = 30; age: 23.5 ± 3.2 years) and (ii) elite (n = 33; age: 22.6 ± 2.9 years). All the participants went to the laboratory for neuromuscular evaluations in the bench press (BP), prone row (PR), and repeated jump in 30 s (RJ30) tests. The results show that the top-elite judo athletes are superior in all the upper-body neuromuscular attributes studied. These differences were significantly superior in (i) BP peak velocity (p < 0.01), maximum load 1RM, power (peak and mean), force (peak and mean), force mean to peak power, and rate of force development (RFD) (all, p < 0.001); and (ii) RP maximum load 1RM (p < 0.01), power load (kg, p < 0.001; % 1RM, p < 0.05), peak power (p = 0.010), power mean (absolute, p < 0.01; relative, p < 0.05), force mean (p < 0.05), force mean to peak power (absolute, p < 0.05) and RFD (p < 0.001). However, no significant differences were observed in the BP and PR time to peak force, time to peak power, and time between peaks (power and force). In the RJ30, it was observed that the initial contact time (T1) of top-elite athletes is significantly lower than that of elite athletes (p < 0.05) and that power at 15 (T2) and 30 (T3) seconds is significantly higher in top-elite athletes (T2, p < 0.05; T3, p < 0.01). The main effect of the performance group was significant in contact time (p < 0.05), and the main effect of time was statistically significant in jump height (p < 0.001), power (p < 0.001), force (p < 0.001) and velocity (p < 0.01). In addition, jump height (p < 0.01; η2p = 0.088) and power (p < 0.05; η2p = 0.068) showed a significant interaction between time and performance group. These results suggested that the observed superiority of the top-elite judo athletes in neuromuscular attributes can determine success in judo competitions. This observation reinforces that neural and metabolic profiles must be considered to increase the effectiveness of maximal power training for the upper and lower body.
A Deep Reinforcement Learning Floorplanning Algorithm Based on Sequence Pairs
Authors: Yu Shenglu , Du Shimin , Yang Chang
Published: March 2024

In integrated circuit (IC) design, floorplanning is an important stage in obtaining the floorplan of the circuit to be designed. Floorplanning determines the performance, size, yield, and reliability of very large-scale integration circuit (VLSI) ICs. The results obtained in this step are necessary for the subsequent continuous processes of chip design. From a computational perspective, VLSI floorplanning is an NP-hard problem, making it difficult to be efficiently solved by classical optimization techniques. In this paper, we propose a deep reinforcement learning floorplanning algorithm based on sequence pairs (SP) to address the placement problem. Reinforcement learning utilizes an agent to explore the search space in sequence pairs to find the optimal solution. Experimental results on the international standard test circuit benchmarks, MCNC and GSRC, demonstrate that the proposed deep reinforcement learning floorplanning algorithm based on sequence pairs can produce a superior solution.
Temporomandibular Joint (TMJ) Replacement Affects Quality of Life: A Systematic Review and Synthesis of Clinical Trials
Authors: Chęciński Maciej , Chęcińska Kamila , Bliźniak Filip , Lubecka Karolina , Turosz Natalia , Rąpalska Iwona , Michcik Adam , Chlubek Dariusz , Sikora Maciej
Published: March 2024

This systematic review aims to determine the impact of temporomandibular joint (TMJ) replacement on health-related quality of life. The review was reported following the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) guidelines. An electronic search using the Bielefeld Academic Search Engine was performed to identify primary studies reported in English and published up until November 2023. Ten reports fulfilled the inclusion criteria and were assessed according to the Critical Appraisal Skills Programme (CASP): Qualitative Studies Checklist. The overall research value of the studies ranged from high (dominant) to moderate. The synthesis of the results concerning TMJ replacement in severe degenerative disease showed an improvement in (1) quality of life, (2) pain intensity, (3) mastication efficiency, and (4) mandibular mobility. One study presented favorable outcomes for patients suffering from ankylosis.
Evolution Laws of Water-Flowing Fracture Zone and Mine Pressure in Mining Shallow-Buried, Hard, and Extra-Thick Coal Seams
Authors: Wu Zhongya , Sun Qiang , Wang Yunbo
Published: March 2024

Shallow-buried, hard, and extra-thick coal seams are very common in Xinjiang, China, but there are relatively few studies on the mine pressure law and the development characteristics of water-flowing fracture zones (WFFZs) during the mining of such coal seams. In this paper, the mine pressure of the top coal caving face in a shallow, hard coal seam with a hard roof and full bedrock (SHCSHRFB) is analysed, the laws of the surrounding rock deformation and stress of the open-off cut and roadway in the large-mining-height top coal caving face are studied, the characteristics of roof-breaking and overburden fracture development are analysed using the physical similarity simulation method, supporting suggestions for roadways are put forward, and three development stages of the WFFZ are analysed. Field monitoring shows that the hydraulic support stress in SHCSHRFB is weak, but the coal wall and roadway stability are good, which is significantly different from the results in the typical shallow-buried thin bedrock working faces. The measured height of the WFFZ is close to the physical similarity simulation results, but quite different from those arising from use of the empirical formula.
A Time–Frequency Image Quality Evaluation Method Based on Improved LIME
Authors: Bai Yihao , Cheng Weidong , Wen Weigang , Liu Yang
Published: March 2024

Deep learning has the characteristics of high efficiency, high accuracy and low knowledge dependence, and has become a hot method in the research field of rotating machinery fault diagnosis. The time–frequency transform can show both the time and frequency characteristics of the vibration signal, so the time–frequency image is often used as the input of deep learning networks. At present, there are many time–frequency transform methods, and how to choose one is a problem worth discussing. This paper proposed a time–frequency image quality evaluation method based on improved local interpretable model-agnostic explanations (LIME). With the input of deep learning networks as the application background, this method evaluates the time–frequency image quality of rotating machinery vibration signals from two aspects: the accuracy of the diagnosis results and the consistency of the interpretation results with prior knowledge. The feasibility of the proposed evaluation method is verified by experiments on the measured data set, and engineers’ trust in the deep learning model is improved.
A Method for Evaluating the Spatial Layout of Fire Stations in Chemical Industrial Parks
Authors: Li Liming , Li Ningning , Wu Xiaochuan , Liu Bo
Published: March 2024

The development of chemical industrial parks has resulted in the accumulation of a significant amount of hazardous substances, thereby increasing the demand for enhanced firefighting security, which directly relates to fire stations. This article presents a method for the layout evaluation of fire stations within chemical industrial parks. A practical technique for conducting fire risk assessments of each point to be rescued (PTBR) is proposed. The PTBRs are categorized according to their levels of fire risk. The required rescue time for each PTBR is determined based on the fire risk assessment. The estimated rescue times from each PTBR to each fire station are evaluated based on the actual road network and the speed of the fire engines. The adequacy of the fire stations is assessed through comparing the required and estimated rescue times. The working process of this method is illustrated using an engineering instance. The evaluation results of this engineering instance indicate its feasibility. This method takes into account the impact of irregular road paths and the influence of PTBR fire risks on the layouts of fire stations, which results in a more objective evaluation.
Measurement of Road Transport Emissions, Case Study: Centinela-La Rumorosa Road, Baja California, México
Authors: Calderón-Ramírez Julio , Gutiérrez-Moreno José Manuel , Montoya-Alcaraz Marco , Casillas Ángel
Published: March 2024

Air pollution is a global issue, and the transportation sector is recognized as the third-largest contributor to anthropogenic greenhouse gas emissions. Vehicles emit a range of chemical compounds because of the combustion process. The nature and quantity of these emissions depend on the vehicle’s characteristics, the road, and weather conditions. These emissions require special attention due to the adverse effects contributing to global warming and human health. In this regard, diagnosing and monitoring air quality is crucial for understanding the number of emissions generated by various sources. However, in developing countries, the necessary data for conducting such analyses are not always available. The purpose of this study is to estimate emissions specifically generated from road operations. To achieve this, the HDM-4 calculation tool is utilized to estimate emissions. This tool was applied in Baja California, Mexico, on the Centinela-La Rumorosa highway. The results obtained show that annually, 372.5 tons of pollutant emissions are generated, composed of HC, CO, CO2, NOx, PM, SO2, and PB, covering a mere 128 km of length within a state road network spanning 11,429 km. This highlights the necessity of implementing strategies to reduce the environmental impact generated by vehicular operations on roads in developing countries.
Optimal Trajectories of Diffractive Sail to Highly Inclined Heliocentric Orbits
Authors: Mengali Giovanni , Quarta Alessandro A.
Published: March 2024

Recent literature indicates that the diffractive sail concept is an interesting alternative to the more conventional reflective solar sail, which converts solar radiation pressure into a (deep space) thrust using a thin, lightweight highly reflective membrane, usually metalized. In particular, a diffractive sail, which uses a metamaterial-based membrane to diffract incoming solar rays, is able to generate a steerable thrust vector even when the sail nominal plane is perpendicular to the Sun–spacecraft line. This paper analyzes the optimal transfer performance of a diffractive-sail-based spacecraft in a challenging heliocentric scenario that is consistent with the proposed Solar Polar Imager mission concept. In this case, the spacecraft must reach a near-circular (heliocentric) orbit with a high orbital inclination with respect to the Ecliptic in order to observe and monitor the Sun’s polar regions. Such a specific heliocentric scenario, because of the high velocity change it requires, is a mission application particularly suited for a propellantless propulsion system such as the classical solar sail. However, as shown in this work, the same transfer can be accomplished using a diffractive sail as the primary propulsion system. The main contribution of this paper is the analysis of the spacecraft transfer trajectory using a near-optimal strategy by dividing the entire flight into an approach phase to a circular orbit of the same radius as the desired final orbit but with a smaller inclination, and a subsequent cranking phase until the desired (orbital) inclination is reached. The numerical simulations show that the proposed strategy is sufficiently simple to implement and can provide solutions that differ by only a few percentage points from the optimal results obtainable with a classical indirect approach.
Sports Analysis of Wheelchair Basketball Game Statistics
Authors: Hernández-Beltrán Víctor , Ibáñez Sergio J. , Espada Mário C. , Gamonales José M.
Published: March 2024

Game statistics are used for the analysis of the performance of athletes. This allows the strengths and weaknesses of the players to be understood, and to design and implement training sessions for performance enhancement. Therefore, the objective of this study was to analyse the game statistics of the 2021 and 2023 European Champions and the 2023 World Champions in Wheelchair Basketball (WB), both male and female. For this purpose, the game statistics of all the championships were collected, and the differences according to gender and competition analysed through a statistical and inferential analysis, considering the functional classification of the players, based on the Mann–Whitney U test for the comparison of gender, and the Kruskal–Wallis H test for the comparison between championships. The results showed that players with a classification higher than 3.0 have higher three-point and two-point throws, while players with a classification of 1.0 have lower effectiveness in shooting. Depending on the championship, a greater number of three-point throws and respective effectiveness was found in the 2023 World Championships, with the male athletes presenting a greater number of points. This information will support WB coaches in designing and implementing training sessions and patterns of play and movements in competitive moments to improve individual and team performance.
Experimental Study on the Forced Ventilation Safety during the Construction of a Large-Slope V-Shaped Tunnel
Authors: Yi Linghong , Wang Xiaoni , Shen Yongjiang
Published: March 2024

The special large-slope V-shaped structure of underwater tunnels changes the ventilation characteristics during tunnel construction, making the traditional experience limited. Therefore, it is urgent to study the influence of the special structure on the safety of the air environment during construction. In this paper, a series of small-scale experiments were conducted to investigate the ventilation characteristics of V-shaped tunnels. The coupled effects of ventilation parameters (distance of duct outlet from working face L0, air velocity at the duct outlet u0) and structural characteristics (digging length Ld, slope of the uphill section θ) were considered. The extreme slope of the V-shaped tunnel of 8% was considered. The flow field and pollutant transport law were determined by using CO as a tracer in the experiments. The results show that u0 has a positive impact on the air return velocity, while Ld has a negative impact, and neither of the other two factors has a significant effect. The transport characteristics of CO in V-shaped tunnels differ from those in flat tunnels, with the former tending to cause unconventional areas of high pollutant concentrations in the horizontal sections. Furthermore, the correlations between CO concentration and distance, ventilation time, and the influence factors discussed in this paper are derived from the experimental results. The conclusions provide guidance for the construction of V-shaped tunnels to prevent air pollution in the construction environment and to improve the working conditions of laborers. Additionally, it can also enrich the ventilation experience in tunnel construction.
Unconventional Wells Interference: Supervised Machine Learning for Detecting Fracture Hits
Authors: Liu Guoxiang , Wu Xiongjun , Romanov Vyacheslav
Published: March 2024

The primary objective of the study was development of a machine learning (ML)-based workflow for fracture hit (“frac hit”) detection and monitoring using shale oil-field data such as drilling surveys, production history (oil and produced water), pressure, and fracking start time and duration records. The ML method takes advantage of long short-term memory (LSTM) and multilayer perceptron (MLP) neural networks to identify the frac hits due to hydraulic communication between the fracking child well(s) and the producing parent well(s) within the same pad (intra-pad interaction) and/or on different pads (inter-pad interaction). It utilizes time series of pressure and production data from within a pad and from adjacent pads. The workflow can capture time variable features of frac hits when the model architecture is deep and wide enough, with enough trainable parameters for deep learning and feature extraction, as demonstrated in this paper by using training and testing subsets of the field data from selected neighboring pads with over a couple of hundred wells. The study was focused on frac-hit interaction among paired wells and demonstrated that the ML model, once trained, can predict the frac-hit probability.
Channel Modeling Based on Transformer Symbolic Regression for Inter-Satellite Terahertz Communication
Authors: He Yuanzhi , Sheng Biao , Li Zhiqiang
Published: March 2024

Channel modeling is crucial for inter-satellite terahertz communication system design. The conventional method involves manually constructing a mathematical channel model, which is labor-intensive, and using a neural network directly as a channel model lacks interpretability. This paper introduces a channel modeling approach based on symbolic regression. It is the first time that using transformer neural networks as the implementation tool of symbolic regression to generate the mathematical channel model from the channel data directly. It can save manpower and avoid the interpretability issue of using neural networks as a channel model. The feasibility of the proposed method is verified by generating a free space path loss model from simulation data in the terahertz frequency band.
Effect of the Incorporation of Compounds into Digitally Manufactured Dental Materials—A Systematic Review
Authors: Bettencourt Ana , Jorge Catarina , Anes Vitor , Neves Cristina Bettencourt
Published: March 2024

The aim of this review was to evaluate if the properties of digitally produced dental acrylic resins improved when reinforced with compounds. A literature search was conducted in PubMed, Web of Science, and Scopus databases for the past 10 years. Combinations of keywords were chosen to reflect the PICO question: Do digitally produced dental acrylic resins loaded with compounds have better mechanical, surface and/or biological properties than resins without compounds? The selection was carried out by two independent researchers according to the PRISMA flowchart and specific eligibility criteria. Results: The 19 in vitro studies included dealt with incorporated compounds such as zirconium dioxide nanoparticles, graphene nanoplatelets, and zwitterionic compounds. It was found that some compounds had a negative impact on the mechanical and surface properties, while others showed improvements. Most of the loaded resins had more effective antimicrobial activity compared to the controls. There were also differences in biocompatibility depending on the type of compound incorporated. The compounds affect the mechanical and surface properties of loaded acrylic resins, depending on the type and concentration of the compound. In the case of antimicrobial activity and biocompatibility, the results depended on other factors than the chemical composition of the compound included in the resin.
Perspective of Using Apple Processing Waste for the Production of Edible Oil with Health-Promoting Properties
Authors: Kolanowski Wojciech
Published: March 2024

(1) Background: The effective management of waste and by-products generated in the food industry helps development and implementation of ranges of health-promoting products. The manufacturing of apple juice and cider results in the generation of large quantities of apple pomace. (2) Methods: This paper outlines the concept of a technological process for industrial-scale production of edible oil with a health-promoting fatty acids profile using dried apple pomace as a raw material. (3) Results: Described approach allows for innovative and profitable industrial-scale utilization of the pomace generated from apple juice production. This paper presents a new technological line for apple seed separation intended for oil pressing. (4) Conclusions: The new technological approach could increase the production of apple seed oil. Because of the growing needs in managing post-production waste and by-products, apple seed oil produced from apple pomace on an industrial scale may become a new, attractive product in the functional food market. The fatty acids profile of apple seed oil is high in polyunsaturated fatty acids and can beneficially influence health. The technology outlined here is in the conceptual phase and requires further research.
Multi-Material Optimization for Lattice Materials Based on Nash Equilibrium
Authors: Xiao Yangyang , Hu Wei , Li Shu
Published: March 2024

Lattice materials are regarded as a new family of promising materials with high specific strength and low density. However, in the optimization of lattice materials, it is difficult in general to determine the material distribution in lattice structures due to the complex optimization formulations and overlaps between different materials. Thus, the article proposes to use the Nash equilibrium to address the multi-material optimization problem. Moreover, a suppression formula is investigated to tackle the issue of material overlapping. The proposed method is validated using a cantilever beam example, showing superior optimization results compared to single-material methods, with a maximum improvement of 20.5%. Moreover, the feasibility and stability of the approach are evaluated through L-shaped beam examples, demonstrating its capability to effectively allocate materials based on their properties and associated stress conditions within the design. Additionally, an MBB test demonstrates superior stiffness in the proposed optimized specimen compared to the unoptimized one.
Prediction Intervals for Bus Travel Time Based on Road Segment Sharing, Multiple Routes’ Driving Style Similarity, and Bootstrap Method
Authors: Yin Zhenzhong , Wang Bin , Zhang Bin , Shen Xinpu
Published: March 2024

Providing accurate information about bus travel times can help passengers plan their itinerary and reduce waiting time. However, due to various uncertainty factors and the sparsity of single-route data, traditional travel time predictions cannot accurately describe the credibility of the prediction results, which is not conducive to passengers waiting based on the predicted results. To address the above issues, this paper proposes a bus travel time prediction intervals model based on shared road segments, multiple routes’ driving style similarity, and the bootstrap method. The model first divides the predicted route into segments, dividing adjacent stations shared by multiple routes into one section. Then, the hierarchical clustering algorithm is used to group all drivers in multiple bus routes in this section according to their driving styles. Finally, the bootstrap method is used to construct a bus travel time prediction interval for different categories of drivers. The travel time data sets of Shenyang 239, 134, and New Area Line 1 were selected for experimental verification. The experimental results indicate that the quality of the prediction interval constructed using a data set fused with multiple routes is better than that constructed using a single-route data set. In the two cases studied, the MPIW of the three time periods decreased by 101.04 s, 151.72 s, 33.87 s, and 126.58 s, 127.47 s, 17.06 s, respectively.
Design and On-Orbit Performance of the Payload Rack Thermal Management System for China Space Station Experimental Lab Module
Authors: Guo Dong , Xie Ming , Xia Xinlin , Wang Wei , Xue Jing , Cao Jiaokun , Wang Ze , Sheng Qiang , Wang Ke
Published: March 2024

An efficient and reliable spacecraft payload thermal management method is one of the key problems to build China Space Station (CSS). Aiming at the outstanding characteristics and difficulties of the payloads rack in the experimental lab module of CSS, in the aspects of thermal control interface, boundary constraint, scale quantity, space layout, diversity of temperature control, operation mode and working life, etc., a two-stage thermal management scheme based on single-phase fluid loop is proposed and constructed. A fluid drive unit is designed to drive the fluid circulation and health management of the module thermal control bus (TCB). In view of the different characteristics of the payload racks, three different types of second-stage thermal control systems are proposed, and different thermal control terminals are designed, in order to solve the problem of thermal control resource allocation and health management in payload racks. A method based on “pump bypass” and “valve resistance ratio” is used to control the flow rate of the thermal management system. Based on the overall scheme of the thermal management system and the developed flight products, on-orbit verification and data analysis are carried out. Flight verification shows that the key parameters of the fluid loop in the thermal management system on orbit are basically consistent with the ground data; the maximum deviation is 1.84%. The pressure control accuracy of the bypass system reaches ±2%, and the active heat transfer efficiency of the integrated thermal management system is over 83%, which can effectively meet the thermal control requirements of the two-stage payloads in the module and rack. After on-orbit flight verification, the designed thermal control system works well on orbit and exhibits good stability.
Recommendation Algorithm Based on Survival Action Rules
Authors: Hermansa Marek , Sikora Marek , Sikora Beata , Wróbel Łukasz
Published: March 2024

Survival analysis is widely used in fields such as medical research and reliability engineering to analyze data where not all subjects experience the event of interest by the end of the study. It requires dedicated methods capable of handling censored cases. This paper extends the collection of techniques applicable to censored data by introducing a novel algorithm for interpretable recommendations based on a set of survival action rules. Each action rule contains recommendations for changing the values of attributes describing examples. As a result of applying the action rules, an example is moved from a group characterized by a survival curve to another group with a significantly different survival rate. In practice, an example can be covered by several induced rules. To decide which attribute values should be changed, we propose a recommendation algorithm that analyzes all actions suggested by the rules covering the example. The efficiency of the algorithm has been evaluated on several benchmark datasets. We also present a qualitative analysis of the generated recommendations through a case study. The results indicate that the proposed method produces high-quality recommendations and leads to a significant change in the estimated survival time.
Development of a Bio-Inspired TES Tank for Heat Transfer Enhancement in Latent Heat Thermal Energy Storage Systems
Authors: Cabeza Luisa F. , Mani Kala Saranprabhu , Zsembinszki Gabriel , Vérez David , Risco Amigó Sara , Borri Emiliano
Published: March 2024

Thermal energy storage (TES) systems play a very important part in addressing the energy crisis. Therefore, numerous researchers are striving to improve the efficiency of TES tanks. The TES technology has the potential to reach new heights when the biological behavior of nature is incorporated into the design of TES tanks. By mimicking the branched vein pattern observed in plants and animals, the heat transfer fluid (HTF) tube of a TES tank can enhance the heat transfer surface area, hence improving its thermal efficiency without the need to add other enhancements of heat transfer methods. Accordingly, in this study, a unique additive-manufacturing-based bio-inspired TES tank was designed, developed, and tested. A customized testing setup was used to assess the bio-inspired TES tank’s thermal performance. A comparison was made between the bio-inspired TES tank and a conventional shell-and-tube TES tank. The latent TES system’s thermal performance was significantly enhanced by the biomimetic approach for the design of a TES tank, even before the optimization of its design. The results showed that, compared to the shell-and-tube TES tank, the bio-inspired TES tank had a higher discharging rate and needed 52% less time to release the stored heat.
Development of a Thermal Separation Probe Gas Chromatography–Mass Spectrometry Method for Evaluating Wax–Resin Removal by Evolon® CR
Authors: Rogge Corina E. , Dijkema Desirae , Epley Bradford A.
Published: March 2024

Historically, many canvas paintings were infused with wax–resin mixtures that have discolored over time, distorting the aesthetics of the work, limiting treatment options, and introducing unstable materials into the object. Removal of the wax–resin is often desirable, but before works of art can be treated, a protocol to evaluate the efficacy of the treatment must be established. A mock-up painting was infused with a known amount of a wax–resin mixture made from beeswax and dammar; this material was then extracted through six intervals of exposure to solvent-loaded and dry sheets of Evolon® CR, a non-woven textile with a high sorbent capacity. Samples from the Evolon® CR sheets from each extraction round were analyzed using thermal separation probe gas chromatography–mass spectrometry (TSP-GC/MS). Normalization of peak areas related to beeswax and dammar to those of Evolon® CR revealed the relative amount of wax and resin removed throughout the extraction. The data show that, under these test conditions, the beeswax and dammar appear to be extracted with the same relative efficiency, information that cannot be provided through UV-induced visible fluorescence imaging of the Evolon® CR sheets or weight data alone, but which is critical to capture as it has implications for treatment success and the long-term stability of an artwork.