bluuebunny/crossref_metadata_2025 huggingface dataset:
The Neuroprotective Flavonoids Sterubin and Fisetin Maintain Mitochondrial Health under Oxytotic/Ferroptotic Stress and Improve Bioenergetic Efficiency in HT22 Neuronal Cells
Authors: Goujon Marie , Liang Zhibin , Soriano-Castell David , Currais Antonio , Maher Pamela
Published: April 2024

The global increase in the aging population has led to a rise in many age-related diseases with continuing unmet therapeutic needs. Research into the molecular mechanisms underlying both aging and neurodegeneration has identified promising therapeutic targets, such as the oxytosis/ferroptosis cell death pathway, in which mitochondrial dysfunction plays a critical role. This study focused on sterubin and fisetin, two flavonoids from the natural pharmacopeia previously identified as strong inhibitors of the oxytosis/ferroptosis pathway. Here, we investigated the effects of the compounds on the mitochondrial physiology in HT22 hippocampal nerve cells under oxytotic/ferroptotic stress. We show that the compounds can restore mitochondrial homeostasis at the level of redox regulation, calcium uptake, biogenesis, fusion/fission dynamics, and modulation of respiration, leading to the enhancement of bioenergetic efficiency. However, mitochondria are not required for the neuroprotective effects of sterubin and fisetin, highlighting their diverse homeostatic impacts. Sterubin and fisetin, thus, provide opportunities to expand drug development strategies for anti-oxytotic/ferroptotic agents and offer new perspectives on the intricate interplay between mitochondrial function, cellular stress, and the pathophysiology of aging and age-related neurodegenerative disorders.
Oxidative Stress and Chronic Myeloid Leukemia: A Balance between ROS-Mediated Pro- and Anti-Apoptotic Effects of Tyrosine Kinase Inhibitors
Authors: Allegra Alessandro , Mirabile Giuseppe , Caserta Santino , Stagno Fabio , Russo Sabina , Pioggia Giovanni , Gangemi Sebastiano
Published: April 2024

The balanced reciprocal translocation t (9; 22) (q34; q11) and the BCR-ABL fusion gene, which produce p210 bcr-abl protein production with high tyrosine kinase activity, are characteristics of chronic myeloid leukemia, a myeloproliferative neoplasm. This aberrant protein affects several signaling pathways connected to both apoptosis and cell proliferation. It has been demonstrated that tyrosine kinase inhibitor treatment in chronic myeloid leukemia acts by inducing oxidative stress and, depending on its level, can activate signaling pathways responsible for either apoptosis or survival in leukemic cells. Additionally, oxidative stress and reactive oxygen species generation also mediate apoptosis through genomic activation. Furthermore, it was shown that oxidative stress has a role in both BCR-ABL-independent and BCR-ABL-dependent resistance pathways to tyrosine kinases, while patients with chronic myeloid leukemia were found to have a significantly reduced antioxidant level. The ideal environment for tyrosine kinase inhibitor therapy is produced by a favorable oxidative status. We discuss the latest studies that aim to manipulate the redox system to alter the apoptosis of cancerous cells.
Profile of Bioactive Components and Antioxidant Activity of Aronia melanocarpa Fruits at Various Stages of Their Growth, Using Chemometric Methods
Authors: Dobros Natalia , Zielińska Agnieszka , Siudem Paweł , Zawada Katarzyna Dorota , Paradowska Katarzyna
Published: April 2024

Aronia (chokeberry, Aronia melanocarpa) is a valuable fruit that combines the health benefits of green tea and red wine and is gaining popularity worldwide. Aronia has a unique chemical composition with strong antioxidant properties, including anthocyanins and chlorogenic acids (CGAs). However, it remains unclear which specific compounds or groups are primarily responsible for the antioxidant properties of chokeberry. Therefore, an analysis of the antioxidant properties of aronia berries based on geographical region and their variability during ripening (from green to frostbitten fruit) was conducted. The fruits were collected from three locations for two years. The aim of our work was to identify the compounds responsible for the antioxidant properties of aronia berry extracts by using chemometric methods. The analyses of anthocyanins and CGAs were performed using HPLC-DAD, and the antioxidant capacity was assessed by FRAP and DPPH methods. The PCA analysis also considered variations in temperature and precipitation. The chemometric analysis revealed a strong correlation between radical-scavenging properties and the content levels of chlorogenic acids. The results obtained in this study show that unripe green chokeberry fruits exhibit the highest antioxidant properties, which can be attributed to the high content of CGAs at this stage.
Biochelates from Spent Coffee Grounds Increases Iron Levels in Dutch Cucumbers but Affects Their Antioxidant Capacity
Authors: Navajas-Porras Beatriz , Cervera-Mata Ana , Fernández-Arteaga Alejandro , Delgado-Osorio Adriana , Navarro-Moreno Miguel , Hinojosa-Nogueira Daniel , Pastoriza Silvia , Delgado Gabriel , Navarro-Alarcón Miguel , Rufián-Henares José Ángel
Published: April 2024

Spent coffee grounds (SCG) are a type of food waste and are produced in abundance around the world. However, their utilization as a soil organic amendment is challenging due to their phytotoxic effect. In the present work, the impact of agronomic biofortification on Dutch cucumbers was investigated using different chemically modified SCG and analyzing their effects on iron contents, their capacity for releasing antioxidants, and the production of short-chain fatty acids after in vitro digestion–fermentation. The results indicated variations in the iron contents and chemical compositions of cucumbers according to the treatment groups. Functionalized and activated hydrochar from SCG increased Fe levels in cucumbers. Although activated hydrochar obtained at 160 °C and functionalized with Fe showed the highest iron supply per serving, differences in antioxidant capacity and short-chain fatty acid production were observed between the groups. It is concluded that growing conditions and the presence of iron may significantly influence the contribution of these cucumbers to the dietary intake of nutrients and antioxidants, which could have important implications for human health and nutrition.
Layer-Weighted Attention and Ascending Feature Selection: An Approach for Seriousness Level Prediction Using the FDA Adverse Event Reporting System
Authors: Aldughayfiq Bader , Allahem Hisham , Mostafa Ayman Mohamed , Alnusayri Mohammed , Ezz Mohamed
Published: April 2024

In this study, we introduce a novel combination of layer-static-weighted attention and ascending feature selection techniques to predict the seriousness level of adverse drug events using the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). We utilized natural language processing (NLP) to analyze the terms in the active substance field, in addition to considering demographic and event information such as patient sex, healthcare provider qualification, and drug characterization. Our ascending feature selection method, which progressively incorporates additional features based on their importance, demonstrated continuous enhancements in prediction performance. Simultaneously, we employed a layer-static-weighted attention technique, which dynamically adjusts the model’s focus between natural language processing (NLP) and demographic features. This technique achieved its best performance at a balanced weight of 50%, yielding an average test accuracy of 74.56% and CV ROC score of 0.83 when 4000 features were included, indicating a compelling advantage to include a larger volume of meaningful features. By integrating these methodologies, we constructed a robust model capable of effectively predicting seriousness levels, offering significant potential for improving pharmacovigilance and enhancing drug safety monitoring. The results underscore the value of NLP and demographic data in predicting drug event seriousness and demonstrate the effectiveness of our combined techniques. We encourage further research to refine these methods and evaluate their application to other clinical datasets.
Nonlinear Regression Approach as a Correction Factor of Measurements of Low-Cost Electrochemical Air Quality Sensors
Authors: Christakis Ioannis , Tsakiridis Odysseas , Sarri Elena , Triantis Dimos , Stavrakas Ilias
Published: April 2024

Air quality directly affects the health of humans. The health implications of poor air quality are recognized by professionals and the public alike and these concerns have driven both the proliferation of formal sensor networks, but also low-cost sensors which can be used in the home. The advancement of technology in recent years has also led to the rapid development of low-cost sensors. Given that citizens are concerned about the air quality of the environment in which they live, they are turning to the supply of low-cost sensors, as they are affordable. The question of the reliability of measurements from low-cost sensors remains an area of research. In this research work, the optimization of ozone (O3) and nitrogen dioxide (NO2) measurements of low-cost electrochemical air quality sensors is investigated by applying nonlinear regression, using a second-order polynomial equation as a correction factor. The proposed correction method is implementable in IoT devices, as it does not require high computational resources. The results show that the measurements are susceptible to correction, with the effect that the corrected values are close to the actual values obtained by the reference instruments of the Department of Environmental Pollution Control Project of Athens (PERPA), a service of the Greek Ministry of the Environment and Energy.
Precise Positioning of Primary System of Geodetic Points by GNSS Technology in Railway Operating Conditions
Authors: Bures Jiri , Vystavel Ondrej , Bartoněk Dalibor , Barta Ladislav , Havlicek Radomir
Published: April 2024

This article deals with the analysis of the accuracy of the geodetic real-time GNSS measurement procedure used in railway operating conditions in the Czech Republic. The purpose was to determine to what extent the operating conditions affect the accuracy of the measurement result and whether an accuracy of standard deviation σx,y = 5 mm in the horizontal plane could be achieved. The use of geodetic GNSS equipment with an IMU unit was also tested. The accuracy obtained in operational conditions is compared with the accuracy obtained on a calibration base using the same measurement procedure. The consistency between the accuracy of the primary system (satellite-based) and the secondary system (terrestrially measured by the traverse method) is also discussed. The analysis includes the issue of residual inhomogeneities of the uniform transformation key when converted to the Czech national coordinate system S-JTSK. It is shown that a homogeneous accuracy in coordinate standard deviation better than σx,y = 5 mm can be achieved. The results indicate that the accuracy under operational conditions is two–three times worse than the accuracy achieved by the same procedure under ideal conditions on a calibration base. This is due to the non-ideal observing conditions, i.e., horizon occlusion by overlays, surrounding vegetation and multipath effects. It has been shown that the effect of multipath can be reduced by repeating short observations 3–4 h apart. Older GNSS instruments using an IMU unit in combination with an electronic compass (eCompass) are at risk of a systematic bias of up to several tens of millimeters, which can be detected by rotating the antenna by 180°. The current uniform transformation key used in the Czech Republic for the conversion of GNSS coordinates into the national system has residual geometric inhomogeneities (p = 0.90 to 10 mm/km, sporadically up to 20 mm/km), which metrologically deteriorate the results of the calculation of the terrestrially measured secondary system inserted into the GNSS measured primary system. Achieving homogeneous accuracy in coordinate standard deviation in a horizontal plane better than σx,y = 5 mm has been demonstrated in non-ideal railway operating conditions with increased risk of multipath. The innovative aspect of the approach used is that it simplifies and thus increases the efficiency of the measurement with respect to the availability of GPS, GLONASS, Galileo and BeiDou satellites, as well as reducing the effect of multipath on the noise by repeating the measurement procedure.
Bearing Fault Diagnosis Based on Parameter-Optimized Variational Mode Extraction and an Improved One-Dimensional Convolutional Neural Network
Authors: Zhang Dongliang , Tao Hanming
Published: April 2024

When faults occur in rolling bearings, vibration signals exhibit sensitivity to periodic impact components, susceptibility to complex background noise, and non-stationary and nonlinear characteristics. Consequently, using traditional signal processing methods to effectively identify bearing faults presents significant challenges. To facilitate the accurate fault diagnosis of bearings in noisy conditions, we propose an intelligent fault diagnosis method using the Archimedes optimization algorithm (AOA), coupled with a one-dimensional multi-scale residual convolutional neural network (1D-MRCNN), to optimize the variational mode extraction (VME) parameters. First, we introduce a weighted correlated kurtosis (WCK) indicator, formulated using the correlation coefficient and correlated kurtosis as the objective function, to optimize the VME’s center frequency ω and penalty factor α, enabling targeted signal extraction. Second, deep learning techniques are employed to construct the 1D-MRCNN. The neural network then processes the extracted signal for feature extraction and automated fault-type identification. Our simulation results show that the WCK objective function effectively isolates impact components under fault conditions, and our experimental validation confirms that the proposed method accurately identifies diverse fault types across multiple noise levels.
Scapular Motor Control and Upper Limb Movement Quality in Subjects with and without Chronic Shoulder Pain: A Cross-Sectional Study
Authors: Melo Ana S. C. , Guedes Diana C. , Matias Ricardo , Cruz Eduardo B. , Vilas-Boas J. Paulo , Sousa Andreia S. P.
Published: April 2024

Despite the existence of several studies about the scapula’s position and motion, in shoulder pain conditions, there are still conflicting findings regarding scapular adaptations and reduced research about the scapula’s role during functional tasks. The present study aimed to compare scapular-related kinematic and electromyographic outcomes during different shoulder movements (with and without load) and the drinking task, between symptomatic and asymptomatic subjects. Forty subjects (divided into two groups) participated in this cross-sectional observational study. Scapulothoracic motion, scapulohumeral rhythm, and movement quality (considering trunk compensation, time-to-peak acceleration, and smoothness), as well as the relative surface electromyographic activity and muscle ratio considering the trapezius, serratus anterior, and levator scapulae (LS), were assessed. The symptomatic group presented the following: (1) changes in scapular upward rotation (p = 0.008) and winging (p = 0.026 and p = 0.005) during backward transport and drink phases; (2) increased muscle activity level of the middle trapezius (MT) in all tasks (p < 0.0001 to p = 0.039), of LS during shoulder elevation with load (p = 0.007), and of LS and LT during most of the drinking task phases (p = 0.007 to p = 0.043 and p < 0.0001 to p = 0.014, respectively); (3) a decreased serratus anterior lower portion activity level (SAlow) during shoulder lowering with load (p = 0.030) and drink phase (p = 0.047); and (4) an increased muscular ratio between scapular abductors/adductors (p = 0.005 to p = 0.036) and elevators/depressors (p = 0.008 to p = 0.028). Compared to asymptomatic subjects, subjects with chronic shoulder pain presented scapular upward rotation and winging adaptations; increased activity levels of MT, LT, and LS; decreased activity levels of SAlow; and increased scapular muscle ratios.
Effects of Pulsed Electric Field on Oil Extraction Rate and Tocopherol in Peony Seeds
Authors: Xu Wei , Liu Jianfei , Tian Ye , Liu Junchi , Chang Zhengshi
Published: April 2024

Peony seed oil, known for its high nutritional value and low production yield, has become a crucial component in high-quality health products. Consequently, enhancing the extraction efficiency of peony seed oil has become an industry objective. Pulse electric field (PEF) technology, as a non-thermal extraction method, has shown promising advancements in improving plant oil yield by enhancing cell permeability. In this study, we designed a static parallel plate PEF treatment unit to process peony seed particles. By manipulating pulse voltage parameters, we investigated the effects of particle size and PEF strength on the oil yield. We also analyzed and evaluated tocopherol in the oil before and after treatment. The results demonstrated that PEF significantly increased the oil yield. Both treated and control groups exhibited gradually increased oil yields with decreasing particle size until reaching saturation at a certain particle size. Increasing voltage frequency did not have a significant impact on the oil yield; however, increasing voltage amplitude resulted in an optimal point for maximum oil yield. Analysis of oil composition indicated that PEF appropriately increased tocopherol content. These findings provide a foundation for further optimization of PEF parameters to assist in extracting peony seed oil and facilitate its industrial application.
The Difference in Shear Behavior and Strength between Loess and Paleosol and Their Prediction of Unsaturated Strength
Authors: Liu Pan , Dai Fuchu , Huang Zhiquan , Wu Jiaqi
Published: April 2024

In recent decades, loess landslide events have attracted increasing attention in the South Jingyang tableland. To elucidate the mechanical mechanism of landslide initiation in the region, this work collected undisturbed loess and paleosol samples taking from the Q2 strata in the South Jingyang tableland. A range of direct shear tests were carried out to explore the strength evolution law of shear zone soil subjected to a varying initial moisture content. In addition, soil water characteristic curves (SWCCs) were also charted and used for predicting the unsaturated shear strength. The findings show that the basic physical properties of the paleosol are different from those of loess due to their different pedogenic environments. The normal stress level and initial moisture content jointly determine whether the shear behavior is strain hardening or strain softening. The shear strength and strength parameters evidently diminish with an increasing initial moisture content, and cohesion contributes to the vast majority of strength attenuation. Paleosol samples possess higher values in shear strength and strength parameters than loess samples due to their stronger inter-particle cementation. The predictive formulas of unsaturated shear strength for undisturbed loess and paleosol are proposed, respectively, based on the Vanapalli model, and the calculated values of the strength prediction model are in perfect agreement with the experimental values.
A Survey of UV Filters Used in Sunscreen Cosmetics
Authors: Pniewska Alicja , Kalinowska-Lis Urszula
Published: April 2024

The aim of this study was to determine the types of UV filters used in adult and children’s sunscreen products sold in Poland (part of the EU market) and their frequency of use. The INCI compositions of sunscreen products were collected and analyzed for the presence of UV filters. The study included 150 randomly selected preparations for adults (from 71 brands) and 50 for children (from 33 brands). The survey concerned the UV filters listed in Annex VI to Regulation (EC) No 1223/2009 of the European Parliament and Council of 30 November 2009 on cosmetic products. The most frequently used UV filters in the child sunscreens were triazine derivatives: bis-ethylhexyloxyphenol methoxyphenyl triazine (60.0%) and ethylhexyl triazone (52.0%), and ethylhexyl salicylate (46.0%), a derivative of salicylic acid. The most common in adult sunscreens were butyl methoxydibenzoylmethane (56.0%), a dibenzoylmethane derivative, followed by the salicylic acid derivative ethylhexyl salicylate (54.7%) and the triazine derivatives bis-ethylhexyloxyphenol methoxyphenyl triazine (54.7%) and ethylhexyl triazone (50.0%). Physical filters, including their nano and non-nano forms, were more popular in sunscreens for children, i.e., 50.0% (TiO2) and 22.0% (ZnO), than for adults: 21.3% (TiO2) and 6.7% (ZnO). For both adults and children, many cosmetic products contained four or five UV filters per preparation; however, the child preparations often used two UV filters. To summarize, the following UV filters dominate in photoprotectors for both adults and children: butyl methoxydibenzoylmethane, bis-ethylhexyloxyphenol methoxyphenyl triazine, ethylhexyl triazone, ethylhexyl salicylate, and diethylamino hydroxybenzoyl hexyl benzoate.
Research on Human Lung Impedance Tomography Based on Soft Thresholding Image Segmentation and Reduced-Order Tikhonov Regularization
Authors: Song Yang , Xiong Lan , Liu Zhenyou , Wu Yongye , Zhang Zhanlong
Published: April 2024

The lung is one of the most vital organs in the human body, and its condition is closely correlated with overall health. Electrical impedance tomography (EIT), as a biomedical imaging technique, often produces low-quality reconstructed images due to its inherent ill-posedness in solving the inverse problem. To address this issue, this paper proposes a soft-threshold region segmentation algorithm with a relaxation factor. This algorithm segments the reconstructed lung images into internal regions, edge regions, and background regions, resulting in clearer boundaries in the reconstructed images. This facilitates the intuitive identification of regions of interest by healthcare professionals. Additionally, this segmentation algorithm is suitably combined with a dimension-reduced Tikhonov regularization algorithm. By utilizing the joint capabilities of these algorithms, the partition points belonging to the background region can be excluded from the sought grayscale vector, thereby improving the ill-posedness of the image reconstruction process and enhancing the quality of image reconstruction. Finally, a 16-electrode human lung EIT simulation model is established for the thoracic region and verified through simulation. Experimental validation is conducted using a human lung tank simulation platform to further demonstrate the effectiveness of the proposed method.
Unveiling Medication-Related Osteonecrosis of the Jaw: A Rapid Review of Etiology, Drug Holidays, and Treatment Strategies
Authors: Oh Ji-Hyeon , Kim Seong-Gon
Published: April 2024

This rapid review critically evaluates recent advancements in the management of medication-related osteonecrosis of the jaw (MRONJ) from 2022 to 2023, employing a specific article selection protocol to focus on the latest literature. Initially screening 262 articles and ultimately selecting 22 based on their relevance and uniqueness, the process involved meticulous screening, methodological evaluation, and data extraction by the authors. The findings, organized into epidemiology, treatment effectiveness, and drug holidays, are synthesized following rapid review guidelines. The review addresses the risk of MRONJ associated with tooth extraction in patients undergoing antiresorptive medication therapy, such as bisphosphonates (BPs) and denosumab (DS), and evaluates the effectiveness of drug holidays in reducing this risk. Recent studies suggest that drug holidays may not effectively mitigate MRONJ risks as previously believed. Furthermore, it highlights that conservative treatment can benefit asymptomatic early-stage MRONJ patients, whereas surgical intervention is more effective for those in advanced stages. Ultimately, this review synthesizes current findings to enhance clinical practice, suggesting that while drug holidays may not significantly reduce MRONJ risks, treatment strategies should be tailored, ranging from conservative approaches in early stages to surgical interventions in advanced stages, thereby guiding evidence-based clinical decisions.
Exploiting Frequency Characteristics for Boosting the Invisibility of Adversarial Attacks
Authors: Li Chen , Liu Yong , Zhang Xinpeng , Wu Hanzhou
Published: April 2024

Mainstream transferable adversarial attacks tend to introduce noticeable artifacts into the generated adversarial examples, which will impair the invisibility of adversarial perturbation and make these attacks less practical in real-world scenarios. To deal with this problem, in this paper, we propose a novel black-box adversarial attack method that can significantly improve the invisibility of adversarial examples. We analyze the sensitivity of a deep neural network in the frequency domain and take into account the characteristics of the human visual system in order to quantify the contribution of each frequency component in adversarial perturbation. Then, we collect a set of candidate frequency components that are insensitive to the human visual system by applying K-means clustering and we propose a joint loss function during the generation of adversarial examples, limiting the frequency distribution of perturbations during attacks. The experimental results show that the proposed method significantly outperforms existing transferable black-box adversarial attack methods in terms of invisibility, which verifies the superiority, applicability and potential of this work.
The Role of Physical Fitness on FRAN CrossFit® Workout Performance
Authors: Polydorou Rafaellos , Kyriacou-Rossi Andreas , Hadjipantelis Andreas , Ioannides Christos , Zaras Nikolaos
Published: April 2024

The purpose of this study was to investigate the role of physical fitness on the FRAN CrossFit® workout time-trial. Twenty male athletes were divided into a fast group (FG) and a slow group (SG) according to the median value of the FRAN time-trial. Measurements included the FRAN time-trial, body composition analysis, isometric handgrip and isometric mid-thigh pull strength, countermovement jump (CMJ), 30 s continuous jumping test (CJ30), and one repetition maximum (1-RM) strength in the squat, thrusters, snatch, clean and jerk, and dead-lift. The FG had significantly lower body fat (p < 0.018), higher CMJ (p < 0.05), lower percentage decrement in CJ30 height (p = 0.023), and higher 1-RM strength (p < 0.05) compared to the SG. A significant correlation was found between the FRAN time-trial with percentage body fat (r = 0.512, p = 0.021) and with percentage decrement in CJ30 height (r = 0.454, p = 0.044). Performance in the FRAN time-trial was also correlated with CMJ variables (r ranged from 0.634 to 0.663, p < 0.05) and 1-RM strength (r ranged from 0.510 to 0.701, p < 0.05). These results suggest that the FG has a higher tolerance to fatigue and is stronger, more powerful, and has less body fat compared to the SG. Consequently, body fat, 1-RM strength, power, and anaerobic capacity may predict the FRAN time-trial in CrossFit® athletes.
Synthesis of a Multi-Template Molecular Imprinted Bulk Polymer for the Adsorption of Non-Steroidal Inflammatory and Antiretroviral Drugs
Authors: Sigonya Sisonke , Mokhena Teboho Clement , Mayer Paul Micheal , Mdluli Phumlane Selby , Makhanya Talent Raymond , Mokhothu Thabang Hendrica
Published: April 2024

In this paper, we report the synthesis of a multi-template molecularly imprinted polymer (MIP) to target and extract naproxen, ibuprofen, diclofenac, emtricitabine, tenofovir disoproxil, and efavirenz from wastewater bodies. A bulk polymerization procedure was used to synthesize the MIP and non-imprinted polymer (NIP). The specific recognition sites for each target were obtained through the removal of the imprinted targeted compounds. The interaction of antiretroviral drugs (ARVs) and non-steroidal anti-inflammatory drugs (NSAIDs) compounds with the MIP was studied under various conditions such as pH, mass, concentration, and time factors. The results demonstrated the optimum conditions were 55 mg of MIP, pH 7.0, a concentration of 5 mg L−1, and a contact time of 10 min. For every compound studied, the extraction efficiencies for ARVs and NSAIDs in aqueous solutions was >96%. The adsorption capacity for the MIP was >0.91 mg·g−1. Adsorption obeys a second-order rate, and the Freundlich model explains the adsorption isotherm data. This study demonstrated that the synthesized multi-template MIP has huge potential to be employed for the removal of ARVs and NSAIDs from the environment as well as in drug purification or recovery processes.
SC-YOLOv8 Network with Soft-Pooling and Attention for Elevator Passenger Detection
Authors: Wang Zhiheng , Chen Jiayan , Yu Ping , Feng Bin , Feng Da
Published: April 2024

This paper concentrates on the elevator passenger detection task, a pivotal element for subsequent elevator passenger tracking and behavior recognition, crucial for ensuring passenger safety. To enhance the accuracy of detecting passenger positions inside elevators, we improved the YOLOv8 network and proposed the SC-YOLOv8 elevator passenger detection network with soft-pooling and attention mechanisms. The main improvements in this paper encompass the following aspects: Firstly, we transformed the convolution module (ConvModule) of the YOLOv8 backbone network by introducing spatial and channel reconstruction convolution (SCConv). This improvement aims to reduce spatial and channel redundancy in the feature extraction process of the backbone network, thereby improving the overall efficiency and performance of the detection network. Secondly, we propose a dual-branch SPP-Fast module by incorporating a soft-pooling branch into the YOLOv8 network’s SPP-Fast module. This dual-branch SPP-Fast module can preserve essential information while reducing the impact of noise. Finally, we propose a soft-pooling and multi-scale convolution CBAM module to further enhance the network’s performance. This module enhances the network’s focus on key regions, allowing for more targeted feature extraction, thereby further improving the accuracy of object detection. Additionally, the attention module enhances the network’s robustness in handling complex backgrounds. We conducted experiments on an elevator passenger dataset. The results show that the precision, recall, and mAP of our improved YOLOv8 network are 94.32%, 91.17%, and 92.95%, respectively, all surpassing those of the original YOLOv8 network.
Experimental Investigation of the Effect of Fault Reactivation Induced by Water Injection
Authors: Liu Wenjing , Si Hu
Published: April 2024

An understanding of fault reactivation induced by water injection is of great significance for geothermal energy development and utilization. We conducted a series of water injection shear tests on low-permeability granite samples that each contained a single saw-cut fault under locally undrained conditions. Slip characteristics were analyzed by varying the fluid pressurization rate, confining pressure, and stress state of the fault to understand fault reactivation. The experimental results demonstrated that at a high pressurization rate, a higher local fluid pressure was needed to reactivate the fault than had been estimated theoretically, and the required fluid pressure increased with an increase in pressurization rate. The fluid pressurization rate and confining pressure both controlled the slip mode of the fault. The slip mode changed from dynamic slip to quasi-static slip at a high pressurization rate, and the peak slip rate of dynamic slip increased with an increasing pressurization rate. The fault showed significant stick-slip characteristics under a high confining pressure, as fault locking and reactivation phenomena occurred repeatedly. Faults with different initial stress states had little influence on the slip mode after the onset of slip.
Efficient Sizing and Layout Optimization of Truss Benchmark Structures Using ISRES Algorithm
Authors: Avcı Muhammed Serdar , Yavuz Demet , Ercan Emre , Nuhoğlu Ayhan
Published: April 2024

This paper presents a comprehensive investigation into the application of the Improved Stochastic Ranking Evolution Strategy (ISRES) algorithm for the sizing and layout optimization of truss benchmark structures. Truss structures play a crucial role in engineering and architecture, and optimizing their designs can lead to more efficient and cost-effective solutions. The ISRES algorithm, known for its effectiveness in multi-objective optimization, is adapted for the single-objective optimization of truss designs with multiple design constraints. This study encompasses a wide range of truss benchmark structures, including 10-bar, 15-bar, 18-bar, 25-bar, and 72-bar configurations, each subjected to distinct loading conditions and stress constraints. The objective is to minimize the truss weight while ensuring stress and displacement limits are met. Through extensive experimentation, the ISRES algorithm demonstrates its ability to efficiently explore the solution space and converge to optimal solutions for each truss benchmark structure. The algorithm effectively handles the complexity of the problems, which involve numerous design variables, stress constraints, and nodal displacement limits. A comparative analysis is conducted to assess the performance of the ISRES algorithm against other state-of-the-art optimization methods reported in the literature. The comparison evaluates the quality of the solutions and the computational efficiency of each method. Furthermore, the optimized truss designs are subjected to finite element analysis to validate their structural integrity and stability. The verification process confirms that the designs adhere to the imposed constraints, ensuring the safety and reliability of the final truss configurations. The results of this study demonstrate the efficacy of the ISRES algorithm in providing practical and reliable solutions for the sizing and layout optimization of truss benchmark structures. The algorithm’s competitive performance and robustness make it a valuable tool for structural engineers and designers, offering a versatile and powerful approach for complex engineering optimization tasks. Overall, the findings contribute to the advancement of optimization techniques in structural engineering, promoting the development of more efficient and cost-effective truss designs for a wide range of engineering and architectural applications. The study’s insights empower practitioners to make informed decisions in selecting appropriate optimization strategies for complex truss-design scenarios, fostering advancements in structural engineering and sustainable design practices.
Reverse Engineering Based on Digital Data Capture In Situ as a Methodology for the Study of Space Labor Risk in Construction Works and Its Applicability in BIM
Authors: Moyano Juan , Romero José , Nieto-Julián Juan E. , Marín-García David
Published: April 2024

In the intelligent manufacturing process and digitization, new research spaces have been created, such as reverse engineering and its use for the detection of risks in construction. For this reason, in this research, an analysis methodology is proposed that, through terrestrial laser scanner records in different phases of the work, allows for an analysis and evaluation of the identification of security risks. In addition, by capturing different processes, it can be determined not only interferences from different operators that can generate risk but also establish quality standards in construction, such as determining the thicknesses of the coating of the concrete manufactured “in situ”. Therefore, this research responds to quality analysis in the material execution of the activity and construction of formwork systems and their safety, as well as defining the location of the static and dynamic elements of the model. This value of the morphometric parameter of the building and the scene to be represented characterizes the morphometrics of the work execution activities and finally evaluates the semantic information model of the BIM construction, in which the deformations between the ideal model and what was executed. With the results of this study, it can be concluded that the latest 3D model reconstruction techniques (BIM), together with comparison algorithms, can determine millimeter precision, and with that, it can establish a better method for inspection, evaluation, and control through non-destructive technology.
PID Control Assessment Using L-Moment Ratio Diagrams
Authors: Domański Paweł D. , Dziuba Krzysztof , Góra Radosław
Published: April 2024

This paper presents an application of L-moments and respective L-moment ratio diagrams (LMRD) to the task of control performance assessment (CPA). An L-moment ratio diagram is a graphical approach to the visualization of statistical properties for a given time series. Moreover, it enables comparing various data, showing their similarities and homogeneity. Simultaneously, CPA aims at measuring the control loop quality, supporting decision-making about their tuning and maintenance. This paper shows that control system quality can be efficiently visualized using LMRDs. The method was analyzed using simulations and further validated at a real chemical engineering industrial ammonia synthesis plant.
Holoscopic Elemental-Image-Based Disparity Estimation Using Multi-Scale, Multi-Window Semi-Global Block Matching
Authors: Almatrouk Bodor , Meng Hongying , Swash Mohammad Rafiq
Published: April 2024

In Holoscopic imaging, a single aperture is used to acquire full-colour spatial images like a fly’s eye by gently altering angles between nearby lenses with a micro-lens array. Due to its simple data collection and visualisation methods, which provide robust and scalable spatial information, and its motion parallax, binocular disparity, and convergence, this technique may be able to overcome traditional 2D imaging issues like depth, scalability, and multi-perspective problems. A novel disparity-map-generating method uses angular information from a single Holoscopic image’s micro-images, or Elemental Images (EIs), to create a scene’s disparity map. Not much research has used EIs instead of Viewpoint Images (VPIs) for disparity estimation. This study investigates whether angular perspective data may replace spatial orthographic data. Using noise reduction and contrast enhancement, EIs with a low resolution and lack of texture are pre-processed to calculate the disparity. The Semi-Global Block Matching (SGBM) technique is used to calculate the disparity between EI pixels. A multi-resolution approach overcomes EIs’ resolution constraints, and a content-aware analysis dynamically modifies the SGBM window size settings to generate disparities across different texture and complexity levels. A background mask and nearby EIs with accurate backgrounds detect and rectify EIs with erroneous backgrounds. Our method generates disparity maps that outperform two state-of-the-art deep learning algorithms and VPIs in real images.
Inv-ReVersion: Enhanced Relation Inversion Based on Text-to-Image Diffusion Models
Authors: Zhang Guangzi , Qian Yulin , Deng Juntao , Cai Xingquan
Published: April 2024

Diffusion models are widely recognized in image generation for their ability to produce high-quality images from text prompts. As the demand for customized models grows, various methods have emerged to capture appearance features. However, the exploration of relations between entities, another crucial aspect of images, has been limited. This study focuses on enabling models to capture and generate high-level semantic images with specific relation concepts, which is a challenging task. To this end, we introduce the Inv-ReVersion framework, which uses inverse relations text expansion to separate the feature fusion of multiple entities in images. Additionally, we employ a weighted contrastive loss to emphasize part of speech, helping the model learn more abstract relation concepts. We also propose a high-frequency suppressor to reduce the time spent on learning low-frequency details, enhancing the model’s ability to generate image relations. Compared to existing baselines, our approach can more accurately generate relation concepts between entities without additional computational costs, especially in capturing abstract relation concepts.
Randomness Test of Thinning Parameters for the NBRCINAR(1) Process
Authors: Zhang Shuanghong
Published: April 2024

Non-negative integer-valued time series are usually encountered in practice, and a variety of integer-valued autoregressive processes based on various thinning operators are commonly used to model these count data with temporal dependence. In this paper, we consider a first-order integer-valued autoregressive process constructed by the negative binomial thinning operator with random coefficients, to address the problem of constant thinning parameters which might not always accurately represent real-world settings because of numerous external and internal causes. We estimate the model parameters of interest by the two-step conditional least squares method, obtain the asymptotic behaviors of the estimators, and furthermore devise a technique to test the constancy of the thinning parameters, which is essential for determining whether or not the proposed model should consider the parameters’ randomness. The effectiveness and dependability of the suggested approach are illustrated by a series of thorough simulation studies. Finally, two real-world data analysis examples reveal that the suggested approach is very useful and flexible for applications.
Jordan-Type Inequalities and Stratification
Authors: Mićović Miloš , Malešević Branko
Published: April 2024

In this paper, two double Jordan-type inequalities are introduced that generalize some previously established inequalities. As a result, some new upper and lower bounds and approximations of the sinc function are obtained. This extension of Jordan’s inequality is enabled by considering the corresponding inequalities through the concept of stratified families of functions. Based on this approach, some optimal approximations of the sinc function are derived by determining the corresponding minimax approximants.
The Future of Energy Storage in Vietnam: A Fuzzy Multi-Criteria Decision-Making Approach to Metal-Ion Battery Assessments
Authors: Wang Chia-Nan , Nhieu Nhat-Luong , Wang Yen-Hui
Published: April 2024

Lithium-ion (Li-ion) batteries, despite their prevalence, face issues of resource scarcity and environmental concerns, prompting the search for alternative technologies. This study addresses the need to assess and identify viable metal-ion battery alternatives to Li-ion batteries, focusing on the rapidly industrializing context of Vietnam. It acknowledges the criticality of developing a sustainable, cost-effective, and resource-efficient energy storage solution that aligns with the country’s growth trajectory. The primary objective is to evaluate the suitability of emerging metal-ion batteries—specifically sodium-ion (SIB), sodium-ion saltwater (SIB-S), magnesium-ion (MIB), and zinc-ion (ZIB)—for Vietnam’s energy storage needs, guiding future investment and policy decisions. A Fuzzy Multiple-Criteria Decision-Making (MCDM) approach is employed, incorporating both quantitative and qualitative criteria. This study utilizes the Fuzzy Best-Worst Method (BWM) to determine the relative importance of various performance indicators and then applies the Bonferroni Fuzzy Combined Compromise Solution (Bonferroni FCoCoSo) method to rank the battery alternatives. The SIBs emerged as the most promising alternative, scoring the highest in the overall evaluation. The MIBs and SIB-saltwater batteries displayed competitive potential, while the ZIBs ranked the lowest among the considered options. This research provides a strategic framework for energy policy formulation and investment prioritization. It contributes to the field by applying a fuzzy-based MCDM approach in a novel context and offers a structured comparative analysis of metal-ion batteries, enhancing the body of knowledge on sustainable energy storage technologies.
The MCM2-7 Complex: Roles beyond DNA Unwinding
Authors: Rankin Brooke D. , Rankin Susannah
Published: April 2024

The MCM2-7 complex is a hexameric protein complex that serves as a DNA helicase. It unwinds the DNA double helix during DNA replication, thereby providing the single-stranded replication template. In recent years, it has become clear that the MCM2-7 complex has additional functions that extend well beyond its role in DNA replication. Through physical and functional interactions with different pathways, it impacts other nuclear events and activities, including folding of the genome, histone inheritance, chromosome segregation, DNA damage sensing and repair, and gene transcription. Collectively, the diverse roles of the MCM2-7 complex suggest it plays a critical role in maintaining genome integrity by integrating the regulation of DNA replication with other pathways in the nucleus.
Innate Immunity and MASLD
Authors: Meyer Moritz , Schwärzler Julian , Jukic Almina , Tilg Herbert
Published: April 2024

Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as the most common liver disease worldwide in recent years. MASLD commonly presents as simple hepatic steatosis, but ~25% of patients develop liver inflammation, progressive fibrosis, liver cirrhosis and related hepatocellular carcinoma. Liver inflammation and the degree of fibrosis are key determinants of the prognosis. The pathophysiology of liver inflammation is incompletely understood and involves diverse factors and specifically innate and adaptive immune responses. More specifically, diverse mediators of innate immunity such as proinflammatory cytokines, adipokines, inflammasomes and various cell types like mononuclear cells, macrophages and natural killer cells are involved in directing the inflammatory process in MASLD. The activation of innate immunity is driven by various factors including excess lipids and lipotoxicity, insulin resistance and molecular patterns derived from gut commensals. Targeting pathways of innate immunity might therefore appear as an attractive therapeutic strategy in the future management of MASLD and possibly its complications.
Metabolic Syndrome and Biotherapeutic Activity of Dairy (Cow and Buffalo) Milk Proteins and Peptides: Fast Food-Induced Obesity Perspective—A Narrative Review
Authors: Abdisa Kenbon Beyene , Szerdahelyi Emőke , Molnár Máté András , Friedrich László , Lakner Zoltán , Koris András , Toth Attila , Nath Arijit
Published: April 2024

Metabolic syndrome (MS) is defined by the outcome of interconnected metabolic factors that directly increase the prevalence of obesity and other metabolic diseases. Currently, obesity is considered one of the most relevant topics of discussion because an epidemic heave of the incidence of obesity in both developing and underdeveloped countries has been reached. According to the World Obesity Atlas 2023 report, 38% of the world population are presently either obese or overweight. One of the causes of obesity is an imbalance of energy intake and energy expenditure, where nutritional imbalance due to consumption of high-calorie fast foods play a pivotal role. The dynamic interactions among different risk factors of obesity are highly complex; however, the underpinnings of hyperglycemia and dyslipidemia for obesity incidence are recognized. Fast foods, primarily composed of soluble carbohydrates, non-nutritive artificial sweeteners, saturated fats, and complexes of macronutrients (protein-carbohydrate, starch-lipid, starch-lipid-protein) provide high metabolic calories. Several experimental studies have pointed out that dairy proteins and peptides may modulate the activities of risk factors of obesity. To justify the results precisely, peptides from dairy milk proteins were synthesized under in vitro conditions and their contributions to biomarkers of obesity were assessed. Comprehensive information about the impact of proteins and peptides from dairy milks on fast food-induced obesity is presented in this narrative review article.