bluuebunny/crossref_metadata_2025 huggingface dataset:
An Investigation on the Pore Structure Characterization of Sandstone Using a Scanning Electron Microscope and an Online Nuclear Magnetic Resonance System
Authors: Tian Bo , Deng Xuexiang , Pan Congwang , Meng Xiangxi
Published: August 2024

The micropore structure of porous media (such as natural rocks and man-made materials) is very complex and has strong micro heterogeneity, and pore structure is a critical parameter to estimate the rock quality. However, the pore structure characterization of rocks under load is not studied well. In this paper, sandstone specimens were preloaded to six different stress levels, and then the pore structure of rock was characterized by SEM and NMR, respectively. The results show the following: (1) The damage in sandstone increases with predefined stress, and the rate significantly increases over 0.8 uniaxial compressive strength (UCS). (2) There is a critical value in the process of rock damage (0.8 UCS), and when it is less than this critical value, the microstructure in the rock is mainly composed of pores and micro-cracks, and the length is generally less than 5 μm; when it exceeds the critical value, there are obvious cracks or even groups of cracks inside the rock. (3) The changes in porosity can be divided into three stages, showing a “√” shape tendency. (4) The pore structure can be visually presented using NMR and SEM, and the distribution mode of the pores changes from separated points to concentrated patches to finally interconnected networks of pores with an increase in the predefined stress. Overall, NMR provides a new method for characterizing rock damage and studying rock microstructure.
Frequency Estimation Algorithm for FMCW Beat Signal Based on Spectral Refinement and Phase Angle Interpolation
Authors: Jia Guoqing , Cheng Minglong , Fang Weidong , Guo Shanshan
Published: August 2024

The beat signal obtained from frequency-modulated continuous-wave (FMCW) radar is a waveform that is corrupted by noise and requires filtering out interference components for frequency calibration. Traditional FFT methods are affected by the fence effect and spectral leakage, leading to a reduction in frequency estimation accuracy. Therefore, an improved double-spectrum-line interpolation frequency estimation algorithm is proposed in this paper, utilizing spectral refinement and phase interpolation. Firstly, the post-FFT spectral signal is refined to narrow the frequency search range and enhance frequency resolution, thereby separating the noise signal. Then, a frequency deviation factor is defined based on the relationship between adjacent phase angles. Finally, the signal’s phase angles are interpolated using the frequency deviation factor to estimate the frequency of the beat signal. Experimental results demonstrate that the proposed algorithm reduces the impact of quantization on the frequency distribution and increases the signal’s noise resistance. The proposed algorithm has a higher accuracy and lower standard deviation compared to the recently proposed algorithm.
Biosynthesis of Zinc Oxide Nanoparticles Using Seaweed: Exploring Their Therapeutic Potentials
Authors: Abotaleb Sohaila I. , Gheda Saly F. , Allam Nanis G. , El-Shatoury Einas H. , Cotas João , Pereira Leonel , Saeed Ali M.
Published: August 2024

This study aimed to biosynthesize zinc oxide nanoparticles (ZnO-NPs) using extracts from various seaweeds, including Ulva lactuca, Ulva intestinalis (Chlorophyta), and Sargassum muticum (Phaeophyceae). The biosynthesized ZnO-NPs were characterized using UV spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction, transmission electron microscopy, and zeta potential analysis. Their antimicrobial activity was assessed using the disk diffusion method, revealing significant efficacy against two bacterial species (Klebsiella pneumoniae and Escherichia coli) and two fungal species (Candida albicans and Aspergillus niger). Additionally, the antioxidant potential of the ZnO-NPs was evaluated based on the total antioxidant capacity, ferric reducing antioxidant power, and DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging assays. The antioxidant activity of the ZnO-NPs was confirmed using the three antioxidant assays. The ZnO-NPs of U. lactuca recorded the highest antioxidant activity. The cytotoxicity of the ZnO-NPs was tested on different cell lines using the MTT assay. The ZnO-NPs of U. lactuca showed very weak cytotoxic effects on WI 38 (84.98 ± 4.6 µg/mL) and 23, and this result confirmed its safety on normal cells. The ZnO-NPs of U. lactuca showed moderate cytotoxic effects on the HepG-2 (46.66 ± 2.8 µg/mL) and MCF-7 (30.60 ± 2.1 µg/mL) cell lines. In an in vivo study, the ZnO-NPs of U. lactuca showed a decrease in tumor volume, weight, and serum malondialdehyde in experimental mice, while the total antioxidant capacity of the serum was increased. Histopathological changes in ZnO-NPs indicated a reduction in tumor size, a lower number of mitosis divisions, and a rise in apoptosis correlated with the ZnO-NPs of the U. lactuca-treated groups. In conclusion, biosynthesized ZnO-NPs from seaweed showed potent antimicrobial, antioxidant, and antitumor activities, which can be used in the pharmaceutical industry.
A Unified Seismicity Catalog Development for Saudi Arabia: Multi-Network Fusion and Machine Learning-Based Anomaly Detection
Authors: Moustafa Sayed S. R. , Yassien Mohamed H. , Metwaly Mohamed , Faried Ahmad M. , Elsaka Basem
Published: August 2024

This investigation concentrates on refining the accuracy of earthquake parameters as reported by various Saudi seismic networks, addressing the significant challenges arising from data discrepancies in earthquake location, depth, and magnitude estimations. The application of sophisticated machine learning techniques, particularly the Isolation Forest algorithm, has markedly enhanced the precision in the estimation of seismicity parameters by effectively identifying and eliminating outliers and discrepancies. A newly developed and refined seismicity catalog was employed to accurately determine key seismic parameters such as the magnitude of completeness (Mc), a-value, and b-value, thereby underlining their indispensable role in regional seismic hazard assessment. The research underscores the substantial impact of data inconsistencies on the evaluation of seismic hazards, thereby advocating for the advancement of research methodologies within the field of seismotectonics. The insights derived from this study significantly contribute to a more profound understanding of the seismotectonic processes in the region. These insights are crucial for the development of comprehensive seismic hazard assessments and the formulation of targeted earthquake preparedness strategies, thereby enhancing resilience against seismic risks in the region.
Numerical Simulation and Flow Field Analysis of Porous Water Jet Nozzle Based on Fluent
Authors: Pan Yue , Geng Zhongcheng , Yuan Hao , Zhai Shengyu , Huo Fulin
Published: August 2024

The water jet nozzle is a penetrating drilling tool, which sends the pumped water to the nozzle through a high-pressure hose. It can work in a variety of working environments. When it dredges the blockage in the pipeline, its structural parameters will affect the jet flow field in the pipeline. Taking the self-propelled water jet nozzle as the research object, SolidWorks was used to establish the nozzle model with different parameter structures. Based on Fluent, the k-ε turbulence model was used to simulate the jet of nozzles with different nozzle sizes and arrangements in the pipeline. The distribution of the jet flow field and the change in velocity and displacement of nozzles with different parameters in the pipeline were compared, and then computational fluid dynamics (CFD) were used to process the simulation data for further research. The results show that when the inclination angle of the rear nozzle is 35°, the attenuation of the front jet velocity and the fluctuation of the wall fluid velocity are the smallest. When the nozzle aperture is increased from 2 mm to 3.5 mm, the vortex area inside the pipe is reduced, and the velocity attenuation of the front jet is also reduced, with the velocity attenuation rate decreasing by about 10%. This study provides a reference for the design and parameter optimization of self-propelled water jet nozzles.
A Novel Algorithm for Optimal Discretization of Stress–Strain Material Curves for Application in Finite Element Analyses
Authors: Marković Ela , Basan Robert , Marohnić Tea
Published: August 2024

The maximal vertical distance (MVD) recursive algorithm, a novel approach for the optimal discretization of stress–strain material curves, is proposed. The algorithm simplifies the process of defining multilinear curves from material stress–strain curves when conducting a finite element analysis (FEA) of components. By directly selecting points on the material curve, the MVD algorithm eliminates the requirement for initial discretization, thereby minimizing information loss. As the measure of goodness of fit of the simplified polyline to the original curve, the percentage of stress deviation (SD) is proposed. The algorithm can generate multiple multilinear curves while keeping the stress deviation of each curve within a predefined limit. This feature is particularly beneficial during the finite element analysis of components exhibiting complex and position-dependent material properties, such as surface-hardened components, ensuring consistent modelling accuracy of material properties across the components’ geometry. Consistent accuracy also proves advantageous when exploring multiple differing material states of quenched and tempered steel, ensuring fair and reliable comparisons. The MVD algorithm was compared with existing algorithms from the literature, consistently maintaining the accuracy of the multilinear curves within predetermined limits using the fewest possible points.
A New Semi-Analytical Method for the Calculation of Multi-Crack Stress-Intensity Factors under Hydro-Mechanical Coupling
Authors: Zhang Lan , Huang Dian-yi , Zhang Lei , Li Changmin , Qi He
Published: August 2024

Calculating the hydro-mechanical coupling stress-intensity factor (SIF) is an important basis for conducting safety evaluations in geotechnical engineering. The current methods used to calculate hydro-mechanical coupling multi-crack SIFs have difficulties concerning their complicated solution processes and unsuitable stress field expressions. In this paper, a new semi-analytical method is proposed based on a new hydro-mechanical coupling stress function and the extended reciprocal theorem of the work integral formula to calculate hydro-mechanical coupling multi-crack SIFs, which can be verified by comparison with the results available in the literature. The new semi-analytical method is applicable to an arbitrary number of cracks under arbitrary hydro-mechanical coupling loading and facilitates a more effective representation of the water pressure effect on the stress field. Moreover, the influence of the integral path and loading conditions is also discussed, and the results revealed an integral path radius of r2 < 0.75 mm when the crack spacing b is 1.5 mm. When σy and Ph are constant at 15 MPa, the SIFs are almost the same for different σy/Ph, while the maximum circumferential stresses at r = 0.25 mm are 15.79 MPa, 20.83 MPa, and 25.78 MPa.
Target-Oriented Multi-Agent Coordination with Hierarchical Reinforcement Learning
Authors: Yu Yuekang , Zhai Zhongyi , Li Weikun , Ma Jianyu
Published: August 2024

In target-oriented multi-agent tasks, agents collaboratively achieve goals defined by specific objects, or targets, in their environment. The key to success is the effective coordination between agents and these targets, especially in dynamic environments where targets may shift. Agents must adeptly adjust to these changes and re-evaluate their target interactions. Inefficient coordination can lead to resource waste, extended task times, and lower overall performance. Addressing this challenge, we introduce the regulatory hierarchical multi-agent coordination (RHMC), a hierarchical reinforcement learning approach. RHMC divides the coordination task into two levels: a high-level policy, assigning targets based on environmental state, and a low-level policy, executing basic actions guided by individual target assignments and observations. Stabilizing RHMC’s high-level policy is crucial for effective learning. This stability is achieved by reward regularization, reducing reliance on the dynamic low-level policy. Such regularization ensures the high-level policy remains focused on broad coordination, not overly dependent on specific agent actions. By minimizing low-level policy dependence, RHMC adapts more seamlessly to environmental changes, boosting learning efficiency. Testing demonstrates RHMC’s superiority over existing methods in global reward and learning efficiency, highlighting its effectiveness in multi-agent coordination.
Decoding National Innovation Capacities: A Comparative Analysis of Publication Patterns in Cybersecurity, Privacy, and Blockchain
Authors: Bran Emanuela , Rughiniș Răzvan , Țurcanu Dinu , Stăiculescu Ana Rodica
Published: August 2024

This study examines the factors influencing scientific productivity in blockchain, privacy, and cybersecurity research across countries. While previous research has explored the determinants of general scientific output, less is known about the patterns of influence in these technological fields, which have been dominantly studied with a bibliometric focus. Using regression models, we analyze the impact of economic, political, educational, and social factors on the publication rates in these domains. Data from international databases on country-level indicators and scientific publications form the basis of our analysis. The results show that Gross National Income per capita is the strongest predictor of research output across all the fields studied. Research spending as a percentage of GDP also demonstrates a consistent positive relationship with publication rates. However, the impact of the factors varies across fields. This research provides insights for policymakers and institutions aiming to enhance research capabilities in these critical areas of technology.
Domain Adaptation for Arabic Machine Translation: Financial Texts as a Case Study
Authors: Alghamdi Emad A. , Zakraoui Jezia , Abanmy Fares A.
Published: August 2024

Neural machine translation (NMT) has shown impressive performance when trained on large-scale corpora. However, generic NMT systems have demonstrated poor performance on out-of-domain translation. To mitigate this issue, several domain adaptation methods have recently been proposed which often lead to better translation quality than genetic NMT systems. While there has been some continuous progress in NMT for English and other European languages, domain adaption in Arabic has received little attention in the literature. The current study, therefore, aims to explore the effectiveness of domain-specific adaptation for Arabic MT (AMT), in yet unexplored domain, financial news articles. To this end, we developed a parallel corpus for Arabic-English (AR-EN) translation in the financial domain to benchmark different domain adaptation methods. We then fine-tuned several pre-trained NMT and Large Language models including ChatGPT-3.5 Turbo on our dataset. The results showed that fine-tuning pre-trained NMT models on a few well-aligned in-domain AR-EN segments led to noticeable improvement. The quality of ChatGPT translation was superior to other models based on automatic and human evaluations. To the best of our knowledge, this is the first work on fine-tuning ChatGPT towards financial domain transfer learning. To contribute to research in domain translation, we made our datasets and fine-tuned models available.
(2+1)-Dimensional Fifth-Order KdV Equation and (2+1)-Dimensional Gardner Equation Obtained from Ideal Fluid Model Revisited—Solitary Wave Solutions
Authors: Karczewska Anna , Rozmej Piotr
Published: August 2024

The (2+1)-dimensional fifth-order KdV equation and (2+1)-dimensional Gardner equation obtained by us using Euler equations for an ideal fluid model in 2023 are revisited. Including additional second-order corrections enabled the derivation of the (2+1)-dimensional fifth-order KdV and Gardner equations without relying on the additional assumptions previously required. The new forms of these equations include an additional non-local term, which allows for the existence of families of solitary wave solutions analogous to solutions to those of the (1+1)-dimensional fifth-order KdV and Gardner equations.
Association between Resting Heart Rate and Homeostatic Model Assessment of Insulin Resistance in South Korean Adults
Authors: Heo An-Sik , Lee Jung-Chul
Published: August 2024

Insulin resistance is closely associated with metabolic diseases such as type 2 diabetes and cardiovascular disease, and the resting heart rate (RHR) is an important marker of the autonomic nervous system’s status. This study aimed to investigate the association between the RHR and the homeostatic model assessment of insulin resistance (HOMA-IR) in Korean adults. Using data from the 2019 Korea National Health and Nutrition Examination Survey (KNHANES 2019), we analyzed 6118 adults and classified the participants into four groups based on their RHR (≤67, 68–71, 72–79, and ≥80 beats/min [bpm]). Logistic regression analysis considering demographic, lifestyle, and biochemical factors revealed that the odds of having a HOMA-IR of 2.5 or higher were significantly increased in the higher RHR groups. Specifically, compared to the ≤67 bpm group, the 68–71, 72–79, and ≥80 bpm groups had increased odds of 1.277, 1.599, and 1.919 times, respectively. These results are expected to contribute to the development of strategies for the early diagnosis and management of metabolic diseases through the RHR, and further research is needed to deepen the understanding of the physiological mechanisms of this relationship, including the management of the RHR through lifestyle modification and regular exercise and the effect of reducing insulin resistance.
Infection Control with Antimicrobial Solid-State ZnO Nanoparticles on Silk Fibroin Gauze
Authors: Vieira Daniela , Dang Cat-Thy , Monk Rachel , Angel Samuel , Marion Alexis , Gbureck Uwe , Harvey Edward , Merle Geraldine
Published: August 2024

Conventional antibiotic treatments for wound infections have the risk of developing microbial resistance, necessitating the search for innovative, alternative solutions like nanoparticles as advanced antibiotics. This work introduces a novel approach for managing acute and chronic wounds by creating an active wound dressing designed to both protect and eliminate bacteria from the injury site. We focused on the electroless deposition of large zinc oxide nanoparticles (ZnO NPs,), aiming for a particle size of around 200 nm to reduce cytotoxicity, onto electrospinned silk fibroin (SF) gauze. We assessed the biocompatibility and antimicrobial effectiveness of the ZnO NP-embedded silk dressing against gram-positive (Staphylococcus aureus) and gram-negative (Pseudomonas aeruginosa) bacteria. Our analysis indicates that incorporating ZnO nanoparticles into silk wound dressings maintains biocompatibility, achieving 70% cell viability while suppressing the growth of S. aureus and P. aeruginosa, particularly during the initial 24 h after application. By employing 200 nm particle sizes, we facilitated a significant release of zinc ions without producing harmful reactive oxygen species (ROSs) that could damage both bacteria and host tissues. These findings emphasize the therapeutic potential of bioresorbable bandages enhanced with large ZnO nanoparticles, presenting an innovative approach to clinical wound treatment.
Adaptive Hybrid Beamforming Codebook Design Using Multi-Agent Reinforcement Learning for Multiuser Multiple-Input–Multiple-Output Systems
Authors: Bhuyan Manasjyoti , Sarma Kandarpa Kumar , Misra Debashis Dev , Guha Koushik , Iannacci Jacopo
Published: August 2024

This paper presents a novel approach to designing beam codebooks for downlink multiuser hybrid multiple-input–multiple-output (MIMO) wireless communication systems, leveraging multi-agent reinforcement learning (MARL). The primary objective is to develop an environment-specific beam codebook composed of non-interfering beams, learned by cooperative agents within the MARL framework. Machine learning (ML)-based beam codebook design for downlink communications have been based on channel state information (CSI) feedback or only reference signal received power (RSRP), consisting of an offline training and user clustering phase. In massive MIMO, the full CSI feedback data is of large size and is resource-intensive to process, making it challenging to implement efficiently. RSRP alone for a stand-alone base station is not a good marker of the position of a receiver. Hence, in this work, uplink CSI estimated at the base station along with feedback of RSRP and binary acknowledgment of the accuracy of received data is utilized to design the beamforming codebook at the base station. Simulations using sub-array antenna and ray-tracing channel demonstrate the proposed system’s ability to learn topography-aware beam codebook for arbitrary beams serving multiple user groups simultaneously. The proposed method extends beyond mono-lobe and fixed beam architectures by dynamically adapting arbitrary shaped beams to avoid inter-beam interference, enhancing the overall system performance. This work leverages MARL’s potential in creating efficient beam codebooks for hybrid MIMO systems, paving the way for enhanced multiuser communication in future wireless networks.
Forearm Intravenous Detection and Localization for Autonomous Vein Injection Using Contrast-Limited Adaptive Histogram Equalization Algorithm
Authors: Said Hany , Mohamed Sherif , Shalash Omar , Khatab Esraa , Aman Omar , Shaaban Ramy , Hesham Mohamed
Published: August 2024

Occasionally intravenous insertion forms a challenge to a number of patients. Inserting an IV needle is a difficult task that requires a lot of skill. At the moment, only doctors and medical personnel are allowed to do this because it requires finding the right vein, inserting the needle properly, and carefully injecting fluids or drawing out blood. Even for trained professionals, this can be done incorrectly, which can cause bleeding, infection, or damage to the vein. It is especially difficult to do this on children, elderly people, and people with certain skin conditions. In these cases, the veins are harder to see, so it is less likely to be done correctly the first time and may cause blood clots. In this research, a low-cost embedded system utilizing Near-Infrared (NIR) light technology is developed, and two novel approaches are proposed to detect and select the best candidate veins. The two approaches utilize multiple computer vision tools and are based on contrast-limited adaptive histogram equalization (CLAHE). The accuracy of the proposed algorithm is 91.3% with an average 1.4 s processing time on Raspberry Pi 4 Model B.
Extensions of Orders to a Power Set vs. Scores of Hesitant Fuzzy Elements: Points in Common of Two Parallel Theories
Authors: Induráin Esteban , Munárriz Ana , Sara M. Sergio
Published: August 2024

We deal with two apparently disparate theories. One of them studies extensions of orderings from a set to its power set. The other one defines suitable scores on hesitant fuzzy elements. We show that both theories have the same mathematical substrate. Thus, important possibility/impossibility results concerning criteria for extensions can be transferred to new results on scores. And conversely, conditions imposed a priori on scores can give rise to new extension criteria. This enhances and enriches both theories. We show examples of translations of classical results on extensions in the context of scores. Also, we state new results concerning the impossibility of finding a utility function representing some kind of extension order if some restrictions are imposed on the utility function considered as a score.
Quiescence-Origin Senescence: A New Paradigm in Cellular Aging
Authors: Yao Guang
Published: August 2024

Cellular senescence, traditionally viewed as a consequence of proliferating and growing cells overwhelmed by extensive stresses and damage, has long been recognized as a critical cellular aging mechanism. Recent research, however, has revealed a novel pathway termed “quiescence-origin senescence”, where cells directly transition into senescence from the quiescent state, bypassing cell proliferation and growth. This opinion paper presents a framework conceptualizing a continuum between quiescence and senescence with quiescence deepening as a precursor to senescence entry. We explore the triggers and controllers of this process and discuss its biological implications. Given that the majority of cells in the human body are dormant rather than proliferative, understanding quiescence-origin senescence has significant implications for tissue homeostasis, aging, cancer, and various disease processes. The new paradigm in exploring this previously overlooked senescent cell population may reshape our intervention strategies for age-related diseases and tissue regeneration.
Association of Methylated DNA Markers with High-Risk HPV Infections in Oral Site and Precancer Anal Lesions in HIV-Positive MSM
Authors: Pauciullo Silvia , Colombo Daniele , Zulian Verdiana , Sciamanna Roberta , Coppola Antonio , Scarabello Alessandra , Del Nonno Franca , Garbuglia Anna Rosa
Published: August 2024

Background: Human papillomavirus (HPV) infection is linked to several cancers, including anal and oral cancers. The incidence of anal cancer is particularly high among HIV-positive men who have sex with men (MSM). DNA methylation markers have shown promise as biomarkers for identifying precancerous lesions and cancer in HPV-infected individuals. The aim of this study was to investigate the correlation of DNA methylation with HPV infection in oral samples and the correlation of DNA methylation with lesion degree in the anal samples of HIV-positive MSM. Methods: This study investigated DNA methylation in oral and anal samples from HIV-positive MSM at the National Institute for Infectious Diseases (INMI) in Rome, Italy. Exfoliated oral epithelial cells and anal samples were collected and analyzed for 28 HPV genotypes using the Allplex 28 HPV assay. DNA methylation was assessed with the PrecursorM+ kit for oral samples and the AnoGyn kit for anal samples, focusing on the promoter regions of specific genes. Results: The study included 63 participants, with a median age of 49 and a median CD4+ count of 705 cells/µL. The oral samples showed HPV16 as the most common type, with 22% testing positive for DNA methylation. The anal samples exhibited HPV-related methylation changes linked to cytological lesions, with a 30% increase in the observed ddCt ratio. Significant differences were found in both ASCL1 and ZNF582 genes, particularly for HSILvsNILM and HSILvsLSIL lesions. Of the samples with an increased ddCt ratio, 80% were from patients over 35 years old, and multiple HPV infections were common. Conclusions: DNA methylation markers could be valuable in identifying high-risk HPV infections in oral samples and detecting potential precancerous lesions in anal samples. These markers may enhance the early detection and prevention strategies for HPV-related cancers in high-risk populations, with follow-up data indicating potential for monitoring lesion progression.
Biologic and Small Molecule Therapy in Atopic Dermatitis
Authors: Shergill Mahek , Bajwa Barinder , Yilmaz Orhan , Tailor Karishma , Bouadi Naila , Mukovozov Ilya
Published: August 2024

Atopic dermatitis is a chronic inflammatory dermatosis characterized by pruritic, scaly, erythematous lesions. Its incidence varies but is estimated to be approximately 20% in children and between 7 and 14% in adults, with variation amongst countries. It is a multifactorial condition, with a complex interplay between genetic, immunological, and environmental factors. Research into the inflammatory response has identified new therapeutic targets that work to reduce inflammation and subsequently reduce flares. This study explores existing therapeutic agents for atopic dermatitis as well as newer therapies such as biologics and small molecules, drawing upon each agent’s mechanism of action, relevant landmark clinical trials, efficacy, and safety profile. Current therapies include emollients, corticosteroids, cyclosporine A, calcineurin inhibitors, phototherapy, and methotrexate. Biologics described include dupilumab, tralokinumab, lebrikizumab, nemolizumab, and rocatinlimab. Small molecules inhibitors include Janus kinase inhibitors, phosphodiesterase 4 inhibitors, transient receptor potential vanilloid subfamily V member 1 antagonist, and aryl hydrocarbon receptor antagonist.
Characterization of the Secretome from Spheroids of Adipose-Derived Stem Cells (SASCs) and Its Potential for Tissue Regeneration
Authors: Urrata Valentina , Toia Francesca , Cammarata Emanuele , Franza Mara , Montesano Luigi , Cordova Adriana , Di Stefano Anna Barbara
Published: August 2024

Introduction: Spheroids are spherical aggregates of cells that mimic the three-dimensional (3D) architecture of tissues more closely than traditional two dimensional (2D) cultures. Spheroids of adipose stem cells (SASCs) show special features such as high multilineage differentiation potential and immunomodulatory activity. These properties have been attributed to their secreted factors, such as cytokines and growth factors. Moreover, a key role is played by the extracellular vesicles (EVs), which lead a heterogeneous cargo of proteins, mRNAs, and small RNAs that interfere with the pathways of the recipient cells. Purpose: The aim of this work was to characterize the composition of the secretome and exosome from SASCs and evaluate their regenerative potential. Materials and Methods: SASCs were extracted from adipose samples of healthy individuals after signing informed consent. The exosomes were isolated and characterized by Dinamic Light Scattering (DLS), Scanning Electron Microscopy (SEM), and Western blotting analyses. The expression of mRNAs and miRNAs were evaluated through real-time PCR. Lastly, a wound-healing assay was performed to investigate their regenerative potential on different cell cultures. Results: The SASCs’ exosomes showed an up-regulation of NANOG and SOX2 mRNAs, typical of stemness maintenance, as well as miR126 and miR146a, related to angiogenic and osteogenic processes. Moreover, the exosomes showed a regenerative effect. Conclusions: The SASCs’ secretome carried paracrine signals involved in stemness maintenance, pro-angiogenic and pro-osteogenic differentiation, immune system regulation, and regeneration.
Adaptive Adjustments in Lower Limb Muscle Coordination during Single-Leg Landing Tasks in Latin Dancers
Authors: Gao Xiangli , Jie Tianle , Xu Datao , Gál János , Fekete Gusztáv , Liang Minjun , Gu Yaodong
Published: August 2024

Previous research has primarily focused on evaluating the activity of individual muscles in dancers, often neglecting their synergistic interactions. Investigating the differences in lower limb muscle synergy during landing between dancers and healthy controls will contribute to a comprehensive understanding of their neuromuscular control patterns. This study enrolled 22 Latin dancers and 22 healthy participants, who performed a task involving landing from a 30 cm high platform. The data were collected using Vicon systems, force plates, and electromyography (EMG). The processed EMG data were subjected to non-negative matrix factorization (NNMF) for decomposition, followed by classification using K-means clustering algorithm and Pearson correlation coefficients. Three synergies were extracted for both Latin dancers and healthy participants. Synergy 1 showed increased contributions from the tibialis anterior (p < 0.001) and medial gastrocnemius (p = 0.024) in Latin dancers compared to healthy participants. Synergy 3 highlighted significantly greater contributions from the vastus lateralis in healthy participants compared to Latin dancers (p = 0.039). This study demonstrates that Latin dancers exhibit muscle synergies similar to those observed in healthy controls, revealing specific adjustments in the tibialis anterior and medial gastrocnemius muscles among dancers. This research illustrates how dancers optimize control strategies during landing tasks, offering a novel perspective for comprehensively understanding dancers’ neuromuscular control patterns.
Overt and Covert Effects of Mental Fatigue on Attention Networks: Evidence from Event-Related Potentials during the Attention Network Test
Authors: Pauletti Caterina , Mannarelli Daniela , Fattapposta Francesco
Published: August 2024

Mental fatigue is a variation in the psychophysiological state that subjects encounter during or after prolonged cognitive activity periods, affecting top-down attention and cognitive control. The present study aimed to investigate the effects of mental fatigue on attention in the context of the three attention networks according to the Posnerian model (alerting, orienting, and executive networks) by combining the Attentional Network Test (ANT) and event-related potentials technique. Thirty healthy subjects were enrolled in the study. A continuous arithmetic task lasting one hour induced mental fatigue, and EEG recordings were conducted before and after the task while subjects were performing the ANT. The efficiencies of three networks were comparable between groups, while RTs shortened only in the control group and the accuracy related to the alerting and conflict networks declined only after mental effort. Mental fatigue reduced N1 amplitude during alerting network engagement and p3 amplitude during orienting. It also reduced N2 and P3 amplitude during the conflict, particularly the incongruent target-locked response. These findings underscore the covert effects of mental fatigue on attention, suggesting that even in healthy young subjects, compensatory mechanisms may maintain adequate overt performances, but fatigue still has a detrimental effect on top-down attentional mechanisms.
The Dream Experience and Its Relationship with Morning Mood in Adolescents Hospitalized after a Suicide Attempt
Authors: Desjardins Emma , Gaber Lina , Larkin Emily , Benoit Antoine , Boafo Addo , De Koninck Joseph
Published: August 2024

Suicidality in adolescents has been associated with emotional distress, stressful life events, relationship issues, and nightmares to name a few. This study explored the actual dream content and the mood at pre-sleep, during a reported dream, and in the morning in 33 adolescents admitted to the hospital on account of a suicide attempt. In all aspects, hospitalized adolescents were compared to 33 matched adolescents who had followed the same protocol. In accordance with the Continuity and the Threat Simulation theories of dream formation, it was hypothesized that the waking-life experiences of suicidal adolescents would transpire in both dream mood and content as well as in the frequency of nightmares. Dreams were analyzed by independent judges using traditional dream content scales, including for the presence of negative and destructive themes and types of interpersonal relationships. As predicted, more suicidal adolescents experienced frequent nightmares, which was significant. A higher negative mood at pre-sleep, within dreams, and at post-sleep was also observed. Furthermore, their dreams contained a higher prevalence of destructive themes and failures, as well as self-directed and death-resulting aggressions. Regression analyses indicated that morning mood was most accurately predicted by positive and negative dream mood in the normative adolescents, whereas only negative dream mood appeared to predict subsequent waking affect in suicidal participants. Our results underline the valuable potential of implementing nightmare-reducing therapies in the presence of suicidal adolescents who suffer from frequent nightmares.
Obesity as Inducer of Cognitive Function Decline via Dysbiosis of Gut Microbiota in Rats
Authors: Mabrok Hoda B. , Ramadan Asmaa A. , Hamed Ibrahim M. , Mohamed Doha A.
Published: August 2024

Diet-induced obesity is a global phenomenon that affects the population worldwide with manifestations at both the phenotypic and genotypic levels. Cognitive function decline is a major global health challenge. The relation between obesity and cognitive function is a debatable issue. The main goal of the current research was to study the implications of obesity on cognitive function and gut microbiota diversity and its impact on plasma and brain metabolic parameters in rats. Obesity was induced in rats by feeding on a high-fat (HF) or a high-fat/high-sucrose (HFHS) diet. The results reveal that both the HF (0.683) and HFHS (0.688) diets were effective as obesity inducers, which was confirmed by a significant increase in the body mass index (BMI). Both diet groups showed dyslipidemia and elevation of oxidative stress, insulin resistance (IR), and inflammatory markers with alterations in liver and kidney functions. Obesity led to a reduction in cognitive function through a reduction in short-term memory by 23.8% and 30.7% in the rats fed HF and HFHS diets, respectively, and learning capacity and visuo-spatial memory reduced by 8.9 and 9.7 s in the rats fed an HF or HFHS diet, respectively. Bacteroidetes, Firmicutes, Proteobacteria, Fusobacteria, and Spirochaetes phyla were detected. The Firmicutes/Bacteroidetes ratio (F/B) significantly decreased in the HF group, while it increased in the HFHS group compared to the normal control. The two species, Bacteroides acidifaciens and Bacteroides ovatus, which are associated with IR, were drastically compromised by the high-fat/high-sucrose diet. Some species that have been linked to reduced inflammation showed a sharp decrease in the HFHS group, while Prevotella copri, which is linked to carbohydrate metabolism, was highly enriched. In conclusion: Obesity led to cognitive impairment through changes in short-term and visuo-spatial memory. A metagenomic analysis revealed alterations in the abundance of some microbial taxa associated with obesity, inflammation, and insulin resistance in the HF and HFHS groups.
Cognitive Workload Detection of Air Traffic Controllers Based on mRMR and Fewer EEG Channels
Authors: Hui Li , Pei Zhu , Quan Shao , Ke Xue , Zhe Sun
Published: August 2024

For air traffic controllers, the extent of their cognitive workload can significantly impact their cognitive function and response time, consequently influencing their operational efficiency or even resulting in safety incidents. In order to enhance the accuracy and efficiency in determining the cognitive workload of air traffic controllers, a cognitive workload detection method for air traffic controllers based on mRMR and fewer EEG channels was proposed in this study. First of all, a set of features related to gamma waves was initially proposed; subsequently, an EEG feature evaluation method based on the mRMR algorithm was employed to pinpoint the most relevant indicators for the detection of the cognitive workload. Consequently, a model for the detection of the cognitive workload of controllers was developed, and it was optimized by filtering out channel combinations that exhibited higher sensitivity to the workload using the mRMR algorithm. The results demonstrate that the enhanced model achieves the accuracy and stability required for practical applications. Notably, in this study, only three EEG channels were employed to achieve the highly precise detection of the cognitive workload of controllers. This approach markedly increases the practicality of employing EEG equipment for the detection of the cognitive workload and streamlines the detection process.
Basic Psychological Needs in the Face of Achievement Vulnerability: A Study in Young Team Athletes
Authors: Triguero Martín Mirella , Manzano-Sánchez David , Gómez-López Manuel , González-Hernández Juan
Published: August 2024

The susceptibility of athletes to experience of emotional and psychological difficulties arising from the pressure and expectations associated with achieving and maintaining high performance can become a vulnerability in the desire to achieve success in sport. This study aims to investigate the protective value in the perception of satisfaction in basic psychological needs against the vulnerability that perfectionism generates in the appearance of reactivity linked to fear of failure. A cross-sectional, relational, and semi-randomized research design was used, applying perfectionism, fear of failure, and basic psychological needs measures adapted to both the competitive sports context and the Spanish language in a sample of 372 young Spanish athletes, under descriptive analyses and predictive models. The results showed that as the age of the participants increased, the indicators of perfectionism and fear of failure decreased, with no gender differences. The results offer and confirm the positive relationships between the dimensions of perfectionism and fear of making mistakes (where processes such as self-devaluation and fear of failing the people that participants deemed as important to them are intertwined). The perception of satisfaction of the basic psychological needs of autonomy, social relationships, and competence emerges as protective factors that mediate the perfectionism–fear of failure relationship. On the other hand, discrepancies are shown between the perfectionist dimensions concerning the relationships with the BPNs, describing certain sources of vulnerability, although there are adjustments of mental effort and discomfort in the young athletes. The conclusions offer the opportunity to investigate the aspects that facilitate the emergence of fear of failure in young athletes, mainly the performance of coaches connected to the emergence of patterns in pursuit of perfection.
Exploring the Impact of Sustainability Trade-Offs: The Role of Product and Sustainability Types in Consumer Purchases Mediated by Moral Regulation
Authors: Suh Munshik , Yoo Je Eun
Published: August 2024

The attitude–behavior gap in sustainable product purchasing persists despite prior attempts to address it, thus indicating a need for more research. This study examines contextual factors in sustainable consumption, particularly the sustainability trade-offs (STOs) faced by consumers during product purchases and the impact of conditional morality. We investigate STOs in terms of sustainability type and attribute type and indicate that moral regulation enhances the impact of sustainability trade-offs on purchase intention. Four experiments were conducted with 457 participants in South Korea, focusing on STOs in terms of sustainability type (social vs. environmental) and attribute type (utilitarian vs. hedonic). The findings indicate that attitudes towards sustainability have a positive influence on purchase intention, though sustainability- and attribute-type STOs do not significantly affect this relationship. However, the combination of STOs in environmental sustainability with utilitarian attributes does have a significant impact on the relationship between attitude and purchase intention. Furthermore, while moral regulation mediates this relationship, morality does not have an impact. This research highlights the moderating role of sustainability trade-offs in the relationship between attitudes towards sustainability and purchase intention, underscoring the importance of contextual factors in sustainable product purchasing. Firms can leverage sustainability trade-offs in their marketing strategies, incorporating product features and advertising messages.
Youth Perspectives of Neglect Signs and Help-Seeking
Authors: Cohen Ayala , Marey-Sarwan Ibtisam , Gross Manos Daphna
Published: August 2024

Child neglect, recognized as the most prevalent form of child maltreatment with profound repercussions on children’s development, has received limited scholarly attention compared to abuse. The current study addresses this shortfall with a qualitative research investigation involving 10 multicultural focus groups of youths aged 12 to 15. The research examined how young individuals identify signs of child neglect and discern whether formal and informal sources of assistance may be relied upon to assist in addressing this issue. Through qualitative–thematic analysis, three primary themes emerged: (1) Characteristics of neglected children, (2) challenges in identifying child neglect, and (3) official and unofficial sources to appeal for assistance when child neglect is identified. This study’s insights concern peers’ recognition of signs indicating neglect in children and their perspectives on potential assistance.
Capturing the Heterogeneity of Word Learners by Analyzing Persons
Authors: Jones Ian T. , Kucker Sarah C. , Perry Lynn K. , Grice James W.
Published: August 2024

Accurately capturing children’s word learning abilities is critical for advancing our understanding of language development. Researchers have demonstrated that utilizing more complex statistical methods, such as mixed-effects regression and hierarchical linear modeling, can lead to a more complete understanding of the variability observed within children’s word learning abilities. In the current paper, we demonstrate how a person-centered approach to data analysis can provide additional insights into the heterogeneity of word learning ability among children while also aiding researchers’ efforts to draw individual-level conclusions. Using previously published data with 32 typically developing and 32 late-talking infants who completed a novel noun generalization (NNG) task to assess word learning biases (i.e., shape and material biases), we compare this person-centered method to three traditional statistical approaches: (1) a t-test against chance, (2) an analysis of variance (ANOVA), and (3) a mixed-effects regression. With each comparison, we present a novel question raised by the person-centered approach and show how results from the corresponding analyses can lead to greater nuance in our understanding of children’s word learning capabilities. Person-centered methods, then, are shown to be valuable tools that should be added to the growing body of sophisticated statistical procedures used by modern researchers.
Utilizing E-Waste as a Sustainable Aggregate in Concrete Production: A Review
Authors: Kumar Gaurav , Bansal Tushar , Haq Moinul , Sharma Utsav , Kumar Amit , Jha Pooja , Sharma Dayanand , Kamyab Hesam , Valencia Edison Alejandro Villacreses
Published: August 2024

The accumulation of electronic waste (E-waste) has become a significant global environmental issue, driven by the characteristics of the modern era and the ever-increasing use of electronic devices. Thus, a sustainable approach is necessary to overcome this issue. In this paper, an overview of utilizing E-waste as a sustainable aggregate in concrete production was comprehensively reviewed. The basic composition, characteristics, and production techniques were discussed. In addition to that, the colour, shape, size, aggregate crushing value, and water absorption of E-waste concrete were also discussed. Furthermore, the workability properties such as slump flow, mechanical properties (compressive strength, flexural strength, tensile strength) and thermal resistance of E-waste concrete identified by the various researchers were summarised. Based on the literature review, it is concluded that the shape and size distributions of E-waste particles greatly influenced the aggregate properties, and the percentage of replacement of E-waste aggregate affect the workability and mechanical and thermal properties of E-waste concrete.