bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Configuration of Modular Strongrooms Using Multi-Attribute Decision Making
Authors: Đorđević Violeta , Grković Vladan , Kolarević Milan , Radičević Branko , Bjelić Mišo
Published: October 2024

In this paper, we show that it is possible to obtain an optimal configuration variant of Modular Strongrooms (MSR) that satisfies the individual requirements of customers and is most economically advantageous for manufacturers. A model of the automatic configuration system for configuring MSR type MODULPRIM was developed, integrating the procedures for generating product variants, choosing the optimal configuration, and designing detailed products and technological processes. The developed model’s importance lies in its ability to automatically select the optimal configuration from a set of possible configurations on a multidisciplinary basis. The problem of choosing was solved by integrating the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods from the group of Multi-Attribute Decision Making (MADM). Validation of the proposed model was performed on eight examples of Modular Strongrooms type MODULPRIM 5 and showed great opportunities to improve efficiency and effectiveness in the process of innovative product development, as well as to obtain a product configuration with significantly improved quality. The proposed model has a high degree of flexibility and universality; thus, it can be further upgraded and integrated into a company’s business system.
A Novel Approach of the Viscoelasticity of Axially Functional Graded Bar and Application of Harmonic Vibration Analysis of an Isotropic Beam as Support
Authors: Demir Cihan
Published: October 2024

The use of smart materials and passive controllers in modern technologies has stimulated the study of vibration in elastic systems with viscoelastic damping. It is also possible to create components with precise material distribution coefficients and distinct properties, such as Functionally Graded Materials. This work investigates the resonant frequency characteristics of a beam supported at its ends by Axially Functionally Graded (AFG) viscoelastic bars using the finite element method. The set of equations governing motion is obtained by assuming Euler–Bernoulli beam theory for the beam and bar theory for the bars using Lagrange’s equations. The material properties of the functionally graded bar is assumed to vary through the length according to the power law distribution. The longitudinal loss factor values are used to define the internal damping coefficient, which is also dependent on the Young’s modulus value varying along the bar. The effects of the length-varying material properties and internal damping of the FG support bars on the force transmission TR and frequency parameters λ are examined in detail. No study has been found in the literature on the vibration of viscoelastic FG bar-supported beams subjected to a harmonic force at the centre point. It is shown that using bars formed with combinations of different materials considering material damping will be useful to keep the vibration level and force transmission at a certain value and control the frequency parameters.
Exploring the Effectiveness of Advanced Chatbots in Educational Settings: A Mixed-Methods Study in Statistics
Authors: Navas Gustavo , Navas-Reascos Gustavo , Navas-Reascos Gabriel E. , Proaño-Orellana Julio
Published: October 2024

The Generative Pre-trained Transformer (GPT) is a highly advanced natural language processing model. This model can generate conversation-style responses to user input. The rapid rise of GPT has transformed academic domains, with studies exploring the potential of chatbots in education. This research investigates the effectiveness of ChatGPT 3.5, ChatGPT 4.0 by OpenAI, and Chatbot Bing by Microsoft in solving statistical exam-type problems in the educational setting. In addition to quantifying the errors made by these chatbots, this study seeks to understand the causes of these errors to provide recommendations. A mixed-methods approach was employed to achieve this goal, including quantitative and qualitative analyses (Grounded Theory with semi-structured interviews). The quantitative stage involves statistical problem-solving exercises for undergraduate engineering students, revealing error rates based on the reason for the error, statistical fields, sub-statistics fields, and exercise types. The quantitative analysis provided crucial information necessary to proceed with the qualitative study. The qualitative stage employs semi-structured interviews with selected chatbots; this includes confrontation between them that generates agreement, disagreement, and differing viewpoints. On some occasions, chatbots tend to maintain rigid positions, lacking the ability to adapt or acknowledge errors. This inflexibility may affect their effectiveness. The findings contribute to understanding the integration of AI tools in education, offering insights for future implementations and emphasizing the need for critical evaluation and responsible use.
Less Total-Body Fat and Lower-Extremity Fat Are Associated with More High-Intensity Running during Games in Female University Soccer Players
Authors: Di Lemme Stephanie , Accurso Lorenzo , Castonguay Tristan , Fortin Maryse , DeMont Richard , Dover Geoffrey
Published: October 2024

This study examined the relationship between body composition and on-field, in-game physical performance in female collegiate soccer players. Body composition, including total mass, fat mass, and lean tissue mass for the lower extremities and total body, was measured in 10 starting players using dual energy x-ray absorptiometry (DXA). On-field, in-game physical performance was tracked via a global positioning system (GPS) over 14 regular-season games, measuring total distance and distance covered in six speed zones. Players covered 4544.7 ± 495.2 m in the first half of the game and significantly less distance in the second half (3356.5 ± 1211.7 m, p = 0.004). A repeated measures ANOVA revealed decreased distances in jogging, low-, and moderate-intensity running during the second half compared to the first half of the game (p < 0.001). Lower total-body fat mass, total-body fat percentage, and lower-extremities fat mass were correlated with greater distances at moderate- and high-intensity running during the second half and entire game (r values from −0.644 to −0.745, p < 0.01 to 0.04). These findings suggest that body composition can influence the distance covered at moderate- and high-intensity running speed during competitive games. Training strategies aimed at reducing fat mass and incorporating high-intensity training may benefit female soccer players and enhance team success.
How Does Talking with a Human-like Machine in a Self-Driving Car Affect your Experience? A Mixed-Method Approach
Authors: Kim Yong Min , Kwon Jiseok , Park Donggun
Published: October 2024

This study investigates the impact of human-like machines (HLMs) on the user experience (UX) of young adults during voice interactions between drivers and autonomous vehicles. A mixed-method approach was employed to evaluate three voice agents with varying levels of anthropomorphism: a machine voice without humanized speech strategies (Agent A), a human voice without humanized speech strategies (Agent B), and a human voice with humanized speech strategies (Agent C). A total of 30 participants were invited to interact with the agents in a simulated driving scenario. Quantitative measures were employed to assess intimacy, trust, intention to use, perceived safety, and perceived anthropomorphism based on a 7-point Likert scale, while qualitative interviews were conducted to gain deeper insights. The results demonstrate that increased anthropomorphism enhances perceived anthropomorphism (from 2.77 for Agent A to 5.01 for Agent C) and intimacy (from 2.47 for Agent A to 4.52 for Agent C) but does not significantly affect trust or perceived safety. The intention to use was higher for Agents A and C (4.56 and 4.43, respectively) in comparison to Agent B (3.88). This suggests that there is a complex relationship between voice characteristics and UX dimensions. The findings of this study highlight the importance of balancing emotional engagement and functional efficiency in the design of voice agents for autonomous vehicles.
Anti-Hyperlipidemic Effect of Ruta chalepensis Ethanolic Extract in Triton WR-1339-Induced Hyperlipidemia in Rats
Authors: Althaher Arwa R. , Alwahsh Mohammad , Hasan Aya , Al-Majali Dima , Awadallah Mirna W. , Al-Qirim Tariq
Published: October 2024

High levels of fats like triglycerides and cholesterol in the blood can cause cardiovascular diseases, prompting the search for safer, natural treatments. This study investigates the efficacy of Ruta chalepensis ethanol extract in lowering cholesterol levels using a rat model of hyperlipidemia induced by Triton WR-1339. Leaves and flowers of R. chalepensis were extracted with ethanol, and LC-MS analysis revealed high levels of quercetin (9.5%), 2,2-Dimethyl-3-methylidenebicyclo [2.2.1] heptane (8.1%), and other compounds, with monoterpenes being the most common class. Male Wistar rats received doses of the extract at 20 and 40 mg/kg, while fenofibrate (100 mg/kg) was the positive control. After 20 h, plasma lipid levels were significantly affected, showing a 72.1% reduction in total cholesterol for the 40 mg/kg group (p < 0.01) and a 67.6% reduction for the 20 mg/kg group (p < 0.01). High-density lipoprotein cholesterol levels decreased by 68.8% in the 40 mg/kg group (p < 0.01) and 58.6% in the 20 mg/kg group (p < 0.01). Low-density lipoprotein cholesterol saw reductions of 67.3% (p < 0.001) in the 40 mg/kg group and 60.4% (p < 0.01) in the 20 mg/kg group. Triglycerides dropped by 90.6% in the 40 mg/kg group (p < 0.001) and 86.7% in the 20 mg/kg group (p < 0.001). Overall, the results highlighted a stronger anti-hyperlipidemic effect in the 40 mg/kg group across all lipid parameters measured. The extract outperformed fenofibrate, particularly at the higher dose. These results imply that R. chalepensis extract is a promising natural alternative for managing hyperlipidemia.
Comprehensive Evaluation Method for High-Performance Milling of Inconel 718 Alloy
Authors: Piorkowski Paweł , Borkowski Wojciech , Skoczynski Waclaw
Published: October 2024

The aim of this paper was to develop and verify a method for evaluating the high-performance milling of Inconel 718 alloy under accelerated tool wear conditions. The method considered parameters such as cutting-force components, total machine power consumption, cutting-edge wear, and material removal rate. The study compared high-feed milling and plunge milling, using sets of cutting parameters that are appropriate for both techniques. The results indicate that high-feed milling was more efficient, achieving higher material removal rates and lower tool wear. On the other hand, plunge milling was characterized by a lower axial force component (Fz), which can positively affect machining accuracy. The paper highlights that the proposed evaluation method can also be applied to other hard-to-machine materials, and plunge milling offers a competitive alternative for roughing operations in the milling of Inconel 718 alloy.
Sustainable Diamond Burnishing of Chromium–Nickel Austenitic Stainless Steels: Effects on Surface Integrity and Fatigue Limit
Authors: Maximov Jordan , Duncheva Galya , Anchev Angel , Dunchev Vladimir , Anastasov Kalin , Argirov Yaroslav
Published: October 2024

This study aims to evaluate the influence of lubrication and cooling conditions in the diamond burnishing (DB) process on the surface integrity and fatigue limit of chromium–nickel austenitic stainless steels (CNASSs) and, on this basis, identify a cost-effective and sustainable DB process. Evidence was presented that DB of CNASS performed without lubricating cooling liquid satisfies the requirements for a sustainable process: the three key sustainability dimensions (environmental, economic, and social) are satisfied, and the cost/quality ratio is favorable. DB was implemented with the same values of the main governing factors; however, four different lubrication and cooling conditions were applied: (1) flood lubrication (process F); (2) dry without cooling (process D); (3) dry with air cooling at a temperature of −19 °C (process A); and (4) dry with nitrogen cooling at a temperature of −31 °C (process N). Conditions A and N were realized via a device based on the principle of vortex tubes. All four DB processes provide mirror-finished surfaces with Ra roughness parameter values from 0.041 to 0.049 μm, zones with residual compressive stresses deeper than 0.5 mm, and increases in the specimens’ fatigue limit (as determined by the accelerated Locati’s method) compared to turning and polishing. Processes F and D produce the highest microhardness on the surface and at depth. The process D introduces maximum compressive residual axial and hoop stresses in the surface layer. The dry DB processes (D, A, and N) form a submicrocrystalline structure with high atomic density, which is most strongly developed under process D. When high fatigue strength is required, DB with air cooling should be chosen, as it provides a more favorable cost/quality ratio, whereas dry DB without cooling is the most suitable choice for applications that require increased wear resistance.
Personalised High Tibial Osteotomy Surgery Is Accurate: An Assessment Using 3D Distance Mapping
Authors: Varaschin Andrea , Gill Harinderjit Singh , Zaffagnini Stefano , Leardini Alberto , Ortolani Maurizio , Norvillo Fabio , MacLeod Alisdair , Dal Fabbro Giacomo , Cassiolas Giorgio , Grassi Alberto , Belvedere Claudio
Published: October 2024

Early-stage knee osteoarthritis is often suitable for treatment with high tibial osteotomy (HTO). This is an effective joint-preserving treatment, resulting in good postoperative outcomes. To overcome the limitations of traditional HTO, the surgical technique and correction accuracy can be enhanced by personalised procedures using three-dimensional digital planning and metal additive manufacturing, The purpose of this clinical trial study was to evaluate the three-dimensional accuracy of a new personalised HTO procedure, using modern imaging techniques, 3D modelling, and distance map analysis (DMA). Twenty-five patients were treated with the personalised HTO procedure. Before surgery and after 6 months, they underwent clinical evaluation scoring, radiographic imaging, and computed-tomography scanning to generate morphological models. Specifically, preoperative tibia models were used to plan the tibia correction and the design and position of the fixation plate. Preoperative, planned, and postoperative models were imported in computer-aided and designing software (Geomagic ControlTM 2014, 3D Systems, Rock Hill, SC, USA) for DMA implementation to assess geometrical differences between model surfaces. A very good reproduction of the planned tibia morphology was achieved postoperatively (average differences between −0.9 mm and 1.4 mm). DMA values associated with fixation-plate deformation were less than 1 mm, similar to those for plate-to-tibia surface-contour matching. Overall, personalised digitally planned HTO utilising three-dimensional printed surgical guides and plates enables accurate planned correction and plate placement.
Hybrid Machine-Learning Model for Accurate Prediction of Filtration Volume in Water-Based Drilling Fluids
Authors: Davoodi Shadfar , Al-Rubaii Mohammed , Wood David A. , Al-Shargabi Mohammed , Mehrad Mohammad , Rukavishnikov Valeriy S.
Published: October 2024

Accurately predicting the filtration volume (FV) in drilling fluid (DF) is crucial for avoiding drilling problems such as a stuck pipe and minimizing DF impacts on formations during drilling. Traditional FV measurement relies on human-centric experimental evaluation, which is time-consuming. Recently, machine learning (ML) proved itself as a promising approach for FV prediction. However, existing ML methods require time-consuming input variables, hindering the semi-real-time monitoring of the FV. Therefore, employing radial basis function neural network (RBFNN) and multilayer extreme learning machine (MELM) algorithms integrated with the growth optimizer (GO), predictive hybrid ML (HML) models are developed to reliably predict the FV using only two easy-to-measure input variables: drilling fluid density (FD) and Marsh funnel viscosity (MFV). A 1260-record dataset from seventeen wells drilled in two oil and gas fields (Iran) was used to evaluate the models. Results showed the superior performance of the RBFNN-GO model, achieving a root-mean-square error (RMSE) of 0.6396 mL. Overfitting index (OFI), score, dependency, and Shapley additive explanations (SHAP) analysis confirmed the superior FV prediction performance of the RBFNN-GO model. In addition, the low RMSE (0.3227 mL) of the RBFNN-NGO model on unseen data from a different well within the studied fields confirmed the strong generalizability of this rapid and novel FV prediction method.
Horizontal Distribution of Liquid in an Over-Row Sprayer with a Secondary Air Blower
Authors: Markowski Piotr , Kaliniewicz Zdzisław , Lipiński Adam , Lipiński Seweryn , Burg Patrik , Mašán Vladimír
Published: October 2024

The aim of this study was to determine the influence of boom height above a crop stand and the spacing between nozzles and diffusers in an over-row sprayer on the uniformity of the horizontal spray distribution and the uniformity of the air velocity distribution. The experimental setup involved a prototype over-row sprayer equipped with a boom with a working width of 8 m and ten air diffusers with spray nozzles. Air diffusers were connected to one or two nozzles each, and they were installed on the boom at intervals of 60, 80, and 90 cm. Terminal airflow velocity at a canopy is determined by the height of a sprayer boom and the diffuser spacing, ranging from around 2 m s–1 to around 27 m s–1. The sprayer boom should be positioned at a height of 50 cm above a crop stand due to the difference between the minimum and maximum airflow velocities. The horizontal spray distribution was more uniform when the sprayer was equipped with hollow-cone nozzles instead of flat-fan nozzles; hollow-cone nozzles should be applied if the distance between nozzles needs to be adjusted to the row width and row spacing. The analyzed coefficients did not exceed 10% when the boom was positioned 50 cm above the crop stand and when the nozzles were spaced 80 cm apart, which suggests that, in this configuration, sprayers equipped with hollow-cone nozzles can also be applied to close-grown crops.
A Study on the Coarse-to-Fine Error Decomposition and Compensation Method of Free-Form Surface Machining
Authors: Chen Yueping , Wang Junchao , Tang Qingchun , Li Jie
Published: October 2024

To improve the machining accuracy of free-form surface parts, a coarse-to-fine free-form surface machining error decomposition and compensation method is proposed in this paper. First, the machining error was coarsely decomposed using variational mode decomposition (VMD), and the correlation coefficients between the intrinsic mode function (IMF) and the machining error were obtained to filter out the IMF components that were larger than the thresholding value of the correlation coefficients, which was the coarse systematic error. Second, the coarse systematic errors were finely decomposed using empirical mode decomposition (EMD), which still filters out the IMF components that are larger than the thresholding value of the set correlation coefficient based on the correlation coefficient. Then, the wavelet thresholding method was utilized to finely decompose all the IMF components whose correlation coefficients in the first two decomposition processes were smaller than the threshold value of the correlation coefficient set. The decomposed residual systematic errors were reconstructed with the IMF components screened in the EMD fine decomposition, which gave the fine systematic error. Finally, the machining surface was reconstructed according to the fine systematic error, and its corresponding toolpath was generated to compensate for the machining error without moving the part. The simulation and analysis results of the design show that the method has a more ideal processing error decomposition ability and can decompose the systematic error contained in the processing error in a more complete way. The results of actual machining experiments show that, after using the method proposed in this paper to compensate for the machining error, the maximum absolute machining error decreased from 0.0580 mm to 0.0159 mm, which was a 72.5% reduction, and the average absolute machining error decreased from 0.0472 mm to 0.0059 mm, which was an 87.5% reduction. It was shown that the method was effective and feasible for free-form surface part machining error compensation.
Analyzing Machine Learning Models for Activity Recognition Using Homomorphically Encrypted Real-World Smart Home Datasets: A Case Study
Authors: Attaullah Hasina , Sanaullah Sanaullah , Jungeblut Thorsten
Published: October 2024

The era of digitization and IoT devices is marked by the constant storage of massive amounts of data. The growing adoption of smart home environments, which use sensors and devices to monitor and control various aspects of daily life, underscores the need for effective privacy and security measures. HE is a technology that enables computations on encrypted data, preserving confidentiality. As a result, researchers have developed methodologies to protect user information, and HE is one of the technologies that make it possible to perform computations directly on encrypted data and produce results using this encrypted information. Thus, this research study compares the performance of three ML models, XGBoost, Random Forest, and Decision Classifier, on a real-world smart home dataset using both with and without FHE. Practical results demonstrate that the Decision Classifier showed remarkable results, maintaining high accuracy with FHE and even surpassing its plaintext performance, suggesting that encryption can enhance model accuracy under certain conditions. Additionally, Random Forest showed efficiency in terms of execution time and low prediction errors with FHE, making it a strong candidate for encrypted data processing in smart homes. These findings highlight the potential of FHE to set new privacy standards, advancing secure and privacy-preserving technologies in smart environments.
Physical Properties of Selected Fruit Fibre and Pomace in the Context of Their Sustainable Use for Food Applications
Authors: Pakulska Anna , Kawecka Ludwika , Galus Sabina
Published: October 2024

Pomace, a waste product, generates a huge problem in the fruit and vegetable industry. Numerous studies prove that pomace and fibre are valuable sources of many nutrients. Due to their properties, their popularity is growing in many industries. Water vapour isotherms and kinetics were determined for selected fruit fibre and pomace. The activity and water content, colour, apparent and bulk density, and material structure were also investigated. In addition, the thermal stability of the tested fibres and pomace was examined. Fibre and pomace from chokeberries, apples and currants were used in the research. The determined kinetic curves proved that apple fibre absorbed more water vapour. The isotherms were found to have a shape characteristic of type III sorption isotherms. The Guggenheim–Anderson–de Boer model (GAB) described experimental data for sorption isotherms well (taking an RMS value of less than 10% as a good fit of the model to the sorption data). Thermogravimetric analysis showed good thermal stability, and all analysed fruit fibre and pomace showed similar behaviour in the three main stages of weight loss. The results suggest that the analysed waste materials can be used for different applications, including flour replacements for food products or filling materials in edible packaging films.
Fungal Biostarter and Bacterial Occurrence of Dry-Aged Beef: The Sensory Quality and Volatile Aroma Compounds after 21 Days of Aging
Authors: Przybylski Wiesław , Jaworska Danuta , Kresa Paweł , Ostrowski Grzegorz , Płecha Magdalena , Korsak Dorota , Derewiaka Dorota , Adamczak Lech , Siekierko Urszula , Pawłowska Julia
Published: October 2024

In this study, we decided to test the hypothesis that the fungal biostarter M. flavus used during a 21-day beef dry-aging process significantly impacts the composition of other microorganisms, the profile of volatile compounds, meat hardness characteristics, and, consequently, the sensory quality. The experiments were performed on samples derived from animals crossbred between Holstein–Fresian cows and meat breed bulls. Two groups of samples were studied, including the control group, without biostarter, and a group inoculated with the M. flavus biostarter. Both sample groups were seasoned for 21 days in the dry-aging fridge. The physicochemical parameters (pH, color parameters), the chemical composition of muscle, the determination of the shear force, the profile of volatile compounds (VOCs), and the sensory quality were evaluated after aging. During this study, classical microbiological methods were used to investigate the influence of fungal biostarters on the growth and survival of bacteria and other fungi (e.g., yeasts) during the dry-aging process of beef (DAB). The M. flavus biostarter improved the sensory quality of DAB, allowing high sensory quality to be achieved after just 21 days. This is likely due to the diverse VOCs produced by the fungus, including 1-tetradecanol, 2-nonenal, trans-2-undecenoic acid, and the following esters: formic acid hexyl ester, 10-undecenoic acid methyl ester, and 4-methylpentanoic acid methyl ester. The presence of the biostarter had no significant effect on the number of the bacteria or the survivability of the L. monocytogenes on the meat’s surface in laboratory conditions.
Monotonicities of Quasi-Normed Orlicz Spaces
Authors: Ji Dong , Cui Yunan
Published: October 2024

In this paper, we introduce a new Orlicz function, namely a b-Orlicz function, which is not necessarily convex. The Orlicz spaces LΦ generated by the b-Orlicz function Φ equipped with a Luxemburg quasi-norm contain both classical spaces Lp(p≥1) and Lp(0<p<1). The Orlicz spaces LΦ are quasi-Banach spaces. Some basic properties in quasi-normed Orlicz spaces are discussed, and the criteria that a quasi-normed Orlicz space is strictly monotonic and lower (upper) locally uniformly monotonic are given.
GBMPhos: A Gating Mechanism and Bi-GRU-Based Method for Identifying Phosphorylation Sites of SARS-CoV-2 Infection
Authors: Huang Guohua , Xiao Runjuan , Chen Weihong , Dai Qi
Published: October 2024

Phosphorylation, a reversible and widespread post-translational modification of proteins, is essential for numerous cellular processes. However, due to technical limitations, large-scale detection of phosphorylation sites, especially those infected by SARS-CoV-2, remains a challenging task. To address this gap, we propose a method called GBMPhos, a novel method that combines convolutional neural networks (CNNs) for extracting local features, gating mechanisms to selectively focus on relevant information, and a bi-directional gated recurrent unit (Bi-GRU) to capture long-range dependencies within protein sequences. GBMPhos leverages a comprehensive set of features, including sequence encoding, physicochemical properties, and structural information, to provide an in-depth analysis of phosphorylation sites. We conducted an extensive comparison of GBMPhos with traditional machine learning algorithms and state-of-the-art methods. Experimental results demonstrate the superiority of GBMPhos over existing methods. The visualization analysis further highlights its effectiveness and efficiency. Additionally, we have established a free web server platform to help researchers explore phosphorylation in SARS-CoV-2 infections. The source code of GBMPhos is publicly available on GitHub.
Connecting the Dots: Telomere Shortening and Rheumatic Diseases
Authors: Han Fang , Riaz Farooq , Pu Jincheng , Gao Ronglin , Yang Lufei , Wang Yanqing , Song Jiamin , Liang Yuanyuan , Wu Zhenzhen , Li Chunrui , Tang Jianping , Xu Xianghuai , Wang Xuan
Published: October 2024

Telomeres, repetitive sequences located at the extremities of chromosomes, play a pivotal role in sustaining chromosomal stability. Telomerase is a complex enzyme that can elongate telomeres by appending telomeric repeats to chromosome ends and acts as a critical factor in telomere dynamics. The gradual shortening of telomeres over time is a hallmark of cellular senescence and cellular death. Notably, telomere shortening appears to result from the complex interplay of two primary mechanisms: telomere shelterin complexes and telomerase activity. The intricate interplay of genetic, environmental, and lifestyle influences can perturb telomere replication, incite oxidative stress damage, and modulate telomerase activity, collectively resulting in shifts in telomere length. This age-related process of telomere shortening plays a considerable role in various chronic inflammatory and oxidative stress conditions, including cancer, cardiovascular disease, and rheumatic disease. Existing evidence has shown that abnormal telomere shortening or telomerase activity abnormalities are present in the pathophysiological processes of most rheumatic diseases, including different disease stages and cell types. The impact of telomere shortening on rheumatic diseases is multifaceted. This review summarizes the current understanding of the link between telomere length and rheumatic diseases in clinical patients and examines probable telomere shortening in peripheral blood mononuclear cells and histiocytes. Therefore, understanding the intricate interaction between telomere shortening and various rheumatic diseases will help in designing personalized treatment and control measures for rheumatic disease.
A Low-Cost, Portable, Multi-Cancer Screening Device Based on a Ratio Fluorometry and Signal Correlation Technique
Authors: Alghamdi Abdulaziz S. , Aldhaheri Rabah W.
Published: October 2024

The autofluorescence of erythrocyte porphyrins has emerged as a potential method for multi-cancer early detection (MCED). With this method’s dependence on research-grade spectrofluorometers, significant improvements in instrumentation are necessary to translate its potential into clinical practice, as with any promising medical technology. To fill this gap, in this paper, we present an automated ratio porphyrin analyzer for cancer screening (ARPA-CS), a low-cost, portable, and automated instrument for MCED via the ratio fluorometry of porphyrins. The ARPA-CS aims to facilitate cancer screening in an inexpensive, rapid, non-invasive, and reasonably accurate manner for use in primary clinics or at point of care. To accomplish this, the ARPA-CS uses an ultraviolet-excited optical apparatus for ratio fluorometry that features two photodetectors for detection at 590 and 630 nm. Additionally, it incorporates a synchronous detector for the precision measurement of signals based on the Walsh-ordered Walsh–Hadamard transform (WHT)w and circular shift. To estimate its single-photodetector capability, we established a linear calibration curve for the ARBA-CS exceeding four orders of magnitude with a linearity of up to 0.992 and a low detection limit of 0.296 µg/mL for riboflavin. The ARPA-CS also exhibited excellent repeatability (0.21%) and stability (0.60%). Moreover, the ratio fluorometry of three serially diluted standard solutions of riboflavin yielded a ratio of 0.4, which agrees with that expected based on the known emission spectra of riboflavin. Additionally, the ratio fluorometry of the porphyrin solution yielded a ratio of 49.82, which was ascribed to the predominant concentration of protoporphyrin IX in the brown eggshells, as confirmed in several studies. This study validates this instrument for the ratio fluorometry of porphyrins as a biomarker for MCED. Nevertheless, large and well-designed clinical trials are necessary to further elaborate more on this matter.
Structure of Spectral Composition and Synchronization in Human Sleep on the Whole Scalp: A Pilot Study
Authors: Pastor Jesús , Garrido Zabala Paula , Vega-Zelaya Lorena
Published: October 2024

We used numerical methods to define the normative structure of the different stages of sleep and wake (W) in a pilot study of 19 participants without pathology (18–64 years old) using a double-banana bipolar montage. Artefact-free 120–240 s epoch lengths were visually identified and divided into 1 s windows with a 10% overlap. Differential channels were grouped into frontal, parieto-occipital, and temporal lobes. For every channel, the power spectrum (PS) was calculated via fast Fourier transform and used to compute the areas for the delta (0–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands, which were log-transformed. Furthermore, Pearson’s correlation coefficient and coherence by bands were computed. Differences in logPS and synchronization from the whole scalp were observed between the sexes for specific stages. However, these differences vanished when specific lobes were considered. Considering the location and stages, the logPS and synchronization vary highly and specifically in a complex manner. Furthermore, the average spectra for every channel and stage were very well defined, with phase-specific features (e.g., the sigma band during N2 and N3, or the occipital alpha component during wakefulness), although the slow alpha component (8.0–8.5 Hz) persisted during NREM and REM sleep. The average spectra were symmetric between hemispheres. The properties of K-complexes and the sigma band (mainly due to sleep spindles—SSs) were deeply analyzed during the NREM N2 stage. The properties of the sigma band are directly related to the density of SSs. The average frequency of SSs in the frontal lobe was lower than that in the occipital lobe. In approximately 30% of the participants, SSs showed bimodal components in the anterior regions. qEEG can be easily and reliably used to study sleep in healthy participants and patients.
Improvements in Safety Outcomes Following Brief Healthcare-Based Intimate Partner Violence Interventions among Women Who Screen Positive for Intimate Partner Violence-Related Traumatic Brain Injuries
Authors: Pebole Michelle M. , Beck Brigitta M. , Mahoney Colin T. , Iverson Katherine M.
Published: October 2024

Background: Traumatic brain injuries (TBIs) are a common consequence of experiencing intimate partner violence (IPV). IPV-related TBI contributes to adverse health outcomes among women, but it is unknown whether a history of IPV-related TBI negatively impacts safety outcomes following healthcare-based interventions for IPV. Methods: Using data from a larger randomized clinical trial, we explored the impact of IPV-related TBI status on safety-related outcomes in two healthcare-based IPV interventions. At baseline, 35% (n = 21) of the sample screened positive for IPV-related TBI history. We used repeated measures ANOVAs to examine differences in safety outcomes at post-treatment and 1-month follow-up based on treatment condition and IPV-related TBI status. Results: Significant interaction effects were found for safety outcomes, such that women with IPV-related TBI history experienced larger reductions in the frequency of physical IPV and similar reductions in sexual IPV across both treatment conditions compared to women without IPV-TBI (F(2, 102) = 10.88, p < 0.001; F(2, 98) = 3.93, p = 0.036). Conclusions: Findings suggest that brief healthcare-based IPV interventions may result in improvements in safety outcomes for women with a history of IPV-TBI. This highlights the continued need for implementation of promising IPV-focused interventions to promote safety and protect women from experiencing further IPV.
Neuroergonomic Attention Assessment in Safety-Critical Tasks: EEG Indices and Subjective Metrics Validation in a Novel Task-Embedded Reaction Time Paradigm
Authors: Bjegojević Bojana , Pušica Miloš , Gianini Gabriele , Gligorijević Ivan , Cromie Sam , Leva Maria Chiara
Published: October 2024

Background/Objectives: This study addresses the gap in methodological guidelines for neuroergonomic attention assessment in safety-critical tasks, focusing on validating EEG indices, including the engagement index (EI) and beta/alpha ratio, alongside subjective ratings. Methods: A novel task-embedded reaction time paradigm was developed to evaluate the sensitivity of these metrics to dynamic attentional demands in a more naturalistic multitasking context. By manipulating attention levels through varying secondary tasks in the NASA MATB-II task while maintaining a consistent primary reaction-time task, this study successfully demonstrated the effectiveness of the paradigm. Results: Results indicate that both the beta/alpha ratio and EI are sensitive to changes in attentional demands, with beta/alpha being more responsive to dynamic variations in attention, and EI reflecting more the overall effort required to sustain performance, especially in conditions where maintaining attention is challenging. Conclusions: The potential for predicting the attention lapses through integration of performance metrics, EEG measures, and subjective assessments was demonstrated, providing a more nuanced understanding of dynamic fluctuations of attention in multitasking scenarios, mimicking those in real-world safety-critical tasks. These findings provide a foundation for advancing methods to monitor attention fluctuations accurately and mitigate risks in critical scenarios, such as train-driving or automated vehicle operation, where maintaining a high attention level is crucial.
Neuroticism Mediates the Association between Autistic Traits and Choice Reaction Time among Young Adults
Authors: De Jesus Cintron Kassandra , Yang Xiao
Published: October 2024

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that influences an individual’s cognitive functions and social interaction. While most studies have focused on children and adolescents diagnosed with ASD, elevated levels of autistic traits in subclinical populations may also influence individuals’ daily functioning. Autistic traits are also linked to the Big Five personality. In particular, neuroticism (emotion instability) has been shown to be positively associated with autistic traits, which may contribute to behavioral symptoms of autistic traits. The present study aimed to investigate the association between autistic symptoms and sensorimotor processing among a subclinical population. One hundred young adults (Mage = 20.32 years; SD = 3.69 years; 69 female) completed a choice reaction time (RT) task, and their behavioral performance was analyzed using the ex-Gaussian modeling. The Autism Quotient (AQ) and the Ten-Item Personality Inventory (TIPI) were used to assess autistic traits and neuroticism, respectively. The mediation analysis was conducted to examine the behavioral mechanism through which autistic traits influence sensorimotor processing. The results showed that the AQ score was negatively correlated with RT and positively correlated with neuroticism score. Importantly, the mediation analysis indicated an indirect effect, suggesting that neuroticism mediates the association between the AQ score and RT. The findings indicated a possible mechanism of the association between autistic traits and sensorimotor responses and suggested that neuroticism should be included as an intervention target for ASD. The present study contributes to the research on autistic traits and has practical implications for future intervention programs to improve daily functioning among individuals with ASD.
Machine Learning Valuation in Dual Market Dynamics: A Case Study of the Formal and Informal Real Estate Market in Dar es Salaam
Authors: Nyanda Frank , Muyingo Henry , Wilhelmsson Mats
Published: October 2024

The housing market in Dar es Salaam, Tanzania, is expanding and with it a need for increased market transparency to guide investors and other stakeholders. The objective of this paper is to evaluate machine learning (ML) methods to appraise real estate in formal and informal housing markets in this nascent market sector. Various advanced ML models are applied with the aim of improving property value estimates in a market with limited access to information. The dataset used included detailed property characteristics and transaction data from both market types. Regression, decision trees, neural networks, and ensemble methods were employed to refine property appraisals across these settings. The findings indicate significant differences between formal and informal market valuations, demonstrating ML’s effectiveness in handling limited data and complex market dynamics. These results emphasise the potential of ML techniques in emerging markets where traditional valuation methods often fail due to the scarcity of transaction data.
Vibrator Rack Pose Estimation for Monitoring the Vibration Quality of Concrete Using Improved YOLOv8-Pose and Vanishing Points
Authors: Ren Bingyu , Zheng Xiaofeng , Guan Tao , Wang Jiajun
Published: October 2024

Monitoring the actual vibration coverage is critical for preventing over- or under-vibration and ensuring concrete’s strength. However, the current manual methods and sensor techniques fail to meet the requirements of on-site construction. Consequently, this study proposes a novel approach for estimating the pose of concrete vibrator racks. This method integrates the Linear Spatial Kernel Aggregation (LSKA) module into the You Only Look Once (YOLO) framework to accurately detect the keypoints of the rack and then employs the vanishing point theorem to estimate the rotation angle of the rack without any 3D datasets. The method enables the monitoring of the vibration impact range for each vibrator’s activity and is applicable to various camera positions. Given that measuring the rotation angle of a rack in reality poses is challenging, this study proposes employing a simulation environment to validate both the feasibility and accuracy of the proposed method. The results demonstrate that the improved YOLOv8-Pose achieved a 1.4% increase in accuracy compared with YOLOv8-Pose, and the proposed method monitored the rotation angle with an average error of 6.97° while maintaining a working efficiency of over 35 frames per second. This methodology was successfully implemented at a construction site for a high-arch dam project in China.
Effects of Anisotropic Mechanical Behavior on Nominal Moment Capability of 3D Printed Concrete Beam with Reinforcement
Authors: Park Keunhyoung , Memari Ali M. , Hojati Maryam , Radlińska Aleksandra , Duarte José Pinto , Nazarian Shadi
Published: October 2024

In this study, 3D-printed reinforced concrete beams were tested for flexural performance and compared with the analytical model based on the material test results. Two cementitious mixes (PSU and GCT) were designed for concrete printing and were mechanically tested and compared. Anisotropies in the compressive strength and modulus of elasticity of printed concrete were observed, applied to the analytical prediction of flexural bending behavior, and validated by actual test results. Significant differences between analytical predictions and experimental tests of the bending behaviors of the printed concrete beams were observed. Furthermore, higher compressive strengths and moduli of elasticity were observed when the loading direction was perpendicular to the printed layers or with the PSU mix. The effect of anisotropic mechanical properties on a reinforced beam was compared to the flexural bending tests for both mixes. The analytical model based on the material test results was compared to the flexural bending test results. The significant errors in the prediction of printed concrete’s structural performance, from 10% to 50%, suggest that factors other than reduced compressive strengths may influence the structural behaviors of printed concrete beams.
Experimental Studies on Joints of Wooden Elements with Proposed “CM Insert”
Authors: Tusnin Alexander , Nikolay Linkov , Aleksandr Klyukin
Published: October 2024

The article examines the results of testing a series of samples, where the joint operation of wooden elements is ensured by a composite material based on fiberglass. A method for ensuring joint operation is adopted according to the insert scheme on the contact surfaces. The strength and deformation characteristics of the samples are obtained, and the calculated bearing capacity is established. Statistical processing of the obtained parameters is performed.
Measurement of Innovative Green Façades in the Central European Climate
Authors: Juras Peter
Published: October 2024

Green structures, such as green roofs or green façades, are great examples of climate change mitigation. Their impact is mainly focused on roofs in the area of overheating reduction. In this paper, initial measurement results of a green façade experimental test setup are provided. The green façade uses an innovative board from recycled materials with vegetation rooted directly on the board. The tested green façade is divided into three segments. These segments differ from each other in their watering regimes, which are crucial for cooling effectiveness. Watering operates with the assistance of gravity; water flows from the top gutter through the boards. In this paper, these three segments are compared to each other with respect to temperatures on the surface of a regular external thermal insulation composite system façade (ETICS) during two summer days. The green façade showed an impact on the temperature in the ventilated air gap, where the temperature is almost the same as the outdoor air temperature in the morning with direct solar radiation on the façade and lower than the outdoor air temperature in the afternoon. At the peaks, the surface temperatures within the air cavity surface are up to 8 °C lower than those on a new white ETICS coating. This demonstrates a cooling potential, although the surface temperatures are always higher than the outdoor air temperatures during daylight hours.