bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neuroplasticity of pain processing mechanisms with long-term meditation: Insights from pain-related EEG oscillations
Authors: Yordanova Juliana 
Published: January 2025

Abstract

The experience of pain is a combined product of bottom-up and top-down influences mediated by attentional and emotional factors. Meditation states and traits are characterized by enhanced attention/emotion regulation and expanded self-awareness that can be expected to modify pain processing. The main objective of the present study was to explore the effects of long-term meditation on neural mechanisms of pain processing. EEG pain-related oscillations (PROs) were analyzed in highly experienced practitioners and novices during a non-meditative resting state with respect to (a) local frequency-specific and temporal synchronizing characteristics to reflect mainly bottom-up mechanisms, (b) spatial synchronizing patterns to reflect the neural communication of noxious information, (c) pre-stimulus oscillations to reflect top-down mechanisms during pain expectancy, and (d) the P3b component of the pain-related potential to compare the emotional/cognitive reappraisal of pain events by expert and novice meditators. Main results demonstrated that in experienced (long-term) meditators as compared to non-experienced (short-term) meditators (1) the temporal and spatial synchronizations of multispectral (from theta-alpha to gamma) PROs were substantially suppressed at primary and secondary somatosensory regions contra-lateral to pain stimulation within 200 ms after noxious stimulus; (2) pre-stimulus alpha activity was significantly increased at the same regions, which predicted the suppressed synchronization of PROs in long-term meditators; (3) the decrease of the P3b component was non-significant. These novel observations provide evidence that even when subjected to pain outside of meditation, experienced meditators exhibit a pro-active top-down inhibition of somatosensory areas resulting in suppressed processing and communication of sensory information at early stages of painful input. The emotional/cognitive appraisal of pain is reduced but remains preserved revealing a capacity of experienced meditators to dissociate pro-active and reactive top-down processes during pain control.
Nesting biology, growth and survival of the Slender-Billed Inezia: Insights into the life history of the South America’s smallest passerine
Authors: Lara Carlos Esteban , Rambaut Jesus David , Gámez Ángel Ramiro 
Published: January 2025

Abstract

The Slender-bill Inezia (Inezia tenuirostris) is notable as the lightest passerine bird in South America. This species is endemic to the lowlands of northwestern Venezuela and northeastern Colombia, where it inhabits seasonal dry and hot environments. Until now, little was known about its reproductive biology. In this study, we described and evaluate key aspects of the nesting biology of I. tenuirostris. To achieve this, we monitored 43 nests located in forest patches within a very dry forest in an early successional stage. The nests were tiny “ventilated” cups constructed from fine woody stems. Clutch size consisted of two immaculate white eggs, which were incubated for an average of 12.5 days. At hatching, nestlings had black skin with sparse whitish down on the dorsal area and fledged after 11.6 days. The growth rate of the nestlings K was 0.42, with the maximum growth rate occurring after 3.73 days post-hatching, reaching 0.49 grams/day. Survival analysis revealed a sharp decline in nest survival during incubation (a 47% reduction) and a steady decline during chick-rearing (a 23% reduction), resulting in an overall low nesting survival rate of 30%. Our findings suggest potentially intriguing adaptations in I. tenuirostris for surviving in harsh environments, including: (1) the ventilated cup-shaped nest, which likely reduces water absorption and/or mitigates overheating; (2) the black skin of nestlings, which may provide photoprotection against harmful UV radiation; and (3) the accelerated growth rate of nestlings is potentially an evolutionary response to the persistent risk of nest predation.
University Students' Motives for Using TikTok and Its Impact on Their Social Values: An Applied Study at Taif University
Authors: Aljohani obaidalah H , Hussein Mohamed G , Alajlan Sarah M 
Published: January 2025

Abstract

Values ​​are significantly involved in the organization of society, its activities and its differentiation from other societies. However, it should be noted that social media services, especially TikTok, have become so successful recently due to their localized features and simplicity, allowing young users to create content freely. The aim of this study was to identify the reasons that motivate university students to use TikTok and its influence on their social values. The research employed a quantitative design using a questionnaire aimed at a sample of 3270 students of Taif University. The results showed that the reasons students gave for using Tiktok were quite high and included entertainment, social interaction, and self-expression. The study also found that TikTok led to a significant change in students' social values, with both positive changes such as better communication skills and negative changes including less family interaction and time-consuming activities. The study suggests raising awareness about the negative aspects of using TikTok and instead highlighting the beneficial uses and students' engagement to solve the problems, improve their social values ​​and fulfill their positive role in society.
Document-level causal event extraction enhanced by temporal relation using dual-channel neural network
Authors: Liu Zishu , Liang Yongquan , Ni Weijian 
Published: January 2025

Abstract

Event-event causal relation extraction (ECRE) represents a critical yet challenging task in natural language processing. Existing studies primarily focus on extracting causal sentences and events, despite the use of joint extraction methods for both tasks. However, both pipeline methods and joint extraction approaches often overlook the impact of document-level event temporal sequences on causal relationships. To address this limitation, we propose a model that incorporates document-level event temporal order information to enhance the extraction of implicit event causal relations. The proposed model comprises two channels: Event-event causal relation extraction channel (ECC) and event-event temporal relation extraction channel (ETC). Temporal features provide critical support for modeling node weights in the causal graph, thereby improving the accuracy of causal reasoning. Association link network (ALN) is introduced to construct event causality graph (ECG), incorporating an innovative design that computes node weights using Kullback-Leibler divergence and Gaussian kernels. Experimental results indicate that our model significantly outperforms baseline models in terms of accuracy and weighted average F1 scores.
Incorporation of straw from maize and early rice differentiated sequestration and stability of soil organic carbon---A field incubation of 13C-labelled straw under maize -rice and double rice cropping
Authors: Zhan Ming , Qin Mingguang , Fang Xuedong , Traore Moussa , Cao Yingjian , Li Chengfang 
Published: January 2025

Abstract

Background and aims The impact of straw incorporation on the transformation and stability of soil organic carbon (SOC) has not been fully understood with the changes in cropping systems. To address this issue, we investigated how return of straw from different preceding crops of rice-based double croppings affects retention and allocation of straw-C and intrinsic SOC across SOC fractions in paddy soil.
Methods An 816-day field incubation of 13C-enriched maize straw from maize-late rice cropping (MR-SM) and early rice straw from double rice cropping (RR-ER) were conducted in the respective rice-based cropping plots.
Results Compared to RR-ER incubation, MR-SM treatment demonstrated a significantly lower retention percentage of straw-C and intrinsic SOC by the conclusion of 816 days, had a lower sequestration rate of straw-derived C and a higher loss rate of the intrinsic SOC over this period, resulting in 5.49% reduction in TOC than that of RR-ER treatment. Meanwhile, MR-SM treatment showed significantly higher contributions of straw-C in the intra-microaggregate particulate fraction (iPOC) and the mineral-associated fraction (MAOC), but it contributed lower straw-C to the microbial biomass carbon (MBC). In contrast to RR-ER treatment, MR-SM treatment partitioned more SOC within iPOC but less SOC in MAOC, thus it had a higher index of the carbon quality, indicating a decline in SOC stability in the MR cropping despite a notable increase in TOC over the incubation period.
Conclusion MR cropping presents a lowerr potential for sequestration of newly added straw-C and the maintenance of SOC stability compared to RR cropping.
Age is Just a Number? Unveiling How Perceptions of Age Influence Safety and Motivation in the Workplace
Authors: Mariani Marco Giovanni , Mazzetti Greta , Piccolo Elena Lo , Guglielmi Dina , Hera Carlos Maria Alcover De La 
Published: January 2025

Abstract

Purpose
This study explores the dynamics of workplace safety, specifically examining how both objective and subjective age moderate the relationships between safety climate, safety motivation, compliance, and participation. It aims to understand how subjective age perceptions shape safety attitudes and behaviors, underscoring the importance of psychological and environmental factors in promoting workplace safety.
Method
A cross-sectional survey was conducted with 333 Italian employees from various sectors, using an online questionnaire to collect data.
Results
The findings reveal that a positive safety climate significantly enhances motivation for safety compliance, with motivation acting as a key mediator in this process. Subjective age interacts in complex ways with both safety climate and motivation, indirectly influencing safety behaviors. Notably, the impact of subjective age on safety outcomes is mediated through safety motivation, rather than exerting a direct effect.
Original Value:
By incorporating the concept of subjective age into the study of workplace safety, this research provides new insights into the intersection of psychological states and safety behaviors. This approach addresses the increasing age diversity in the workforce, contributing to the occupational safety and health literature with a deeper understanding of how age-related perceptions shape safety practices.
Quantifying the relationship between third sector size and political polarization
Authors: MacKay Kelsey J. , Schiltz Fritz , Avis Amy , Sauvé Conrad , Vandekerckhove Philippe 
Published: January 2025

Abstract

Political polarization affects our daily lives. Previous research identified trust in others, income inequality, and social media use as determinants of political polarization while third sector size is a potential, yet unexamined factor (Grechyna, 2016; Gu & Wang, 2022; Kubin & von Sikorski, 2021; Mintzberg, 2015). Using available data on third sector size (Schiltz et al., 2024) and political polarization (Coppedge et al., 2023), a significant linear regression showed countries with a larger third sector size had lower political polarization in 120 countries. Exploratory mediation analyses of high and upper-middle income countries found that trust in others and one-person households partially mediated the relationship between third sector size and political polarization, while income inequality and social media use did not. The results suggest that the third sector is related to political polarization within a country, which is particularly relevant for policy makers who have the aim to reduce political polarization.
Proactive Detection of Cyber-Physical Grid Attacks: A Pre-Attack Phase Identification and Analysis Using Anomaly-Based Machine Learning Models
Authors: Kabir Shaharier , Chowdhury Mehnaz , Zishan Md. Saniat Rahman 
Published: January 2025

Abstract

Cyber-physical power systems (CPPS), such as smart grids, are increasingly vital to modern infrastructure but are also highly vulnerable to sophisticated cyber-attacks. Traditional security measures often detect these attacks only after significant damage has occurred, highlighting the need for proactive approaches that can identify potential threats before they fully manifest. This research presents a comprehensive investigation into the use of machine learning models for the early detection of cyber-attacks in a smart grid environment, with a particular focus on identifying pre-attack phases. We employed several unsupervised learning algorithms, including Isolation Forest, K-Means Clustering, DBSCAN, and One-Class SVM, to analyze a time series dataset that simulates normal operations and various attack scenarios. Among these models, Isolation Forest demonstrated superior performance, achieving an Area Under Curve (AUC) score of 1.0, accuracy of 100%, and a sensitivity of 100% in detecting anomalies. DBSCAN also performed well, with an AUC of 0.79 and accuracy of 97.3%, although it exhibited a slightly higher false positive rate compared to Isolation Forest. To detect pre-attack phases, we focused on the anomaly scores generated by the Isolation Forest model. By adjusting the sensitivity threshold, we identified periods of abnormal behavior that precede actual attacks. A threshold of 0.3 for anomaly scores provided a balanced detection, revealing multiple pre-attack phases while maintaining a low false positive rate. However, a higher threshold of 0.97, while reducing false positives, resulted in the detection of fewer pre-attack phases, indicating that the attacks may occur more abruptly without significant pre-attack indicators. These findings underscore the potential of machine learning models in enhancing the security of cyber-physical systems by not only detecting attacks but also providing early warnings through the identification of pre-attack phases. This proactive approach could significantly mitigate the impact of cyber-attacks on critical infrastructure, offering a valuable tool for cybersecurity professionals in safeguarding these systems.
Camelot: a Computer Automated Micro Extensometer with Low-cost Optical Tracking
Authors: Trozzi Nicola , Wodniok Wiktoria , Kelly-Bellow Robert , Meraviglia Andrea , Chételat Aurore , Adkins Nova , Smith Richard S , Kwiatkowska Dorota , Majda Mateusz 
Published: January 2025

Abstract

Background: Plant growth and morphogenesis is a mechanical process controlled by genetic and molecular networks. Measuring mechanical properties at various scales is necessary to understand how these processes interact. However, obtaining a device to perform the measurements on plant samples of choice poses technical challenges and is often limited by high cost and availability of specialized components, the adequacy of which needs to be verified. Developing software to control and integrate the different pieces of equipment can be a complex task.
Results: To overcome these challenges, we have developed a computer automated micro-extensometer combined with low-cost optical tracking (Camelot) that facilitates measurements of elasticity, creep, and yield stress. It consists of three primary components: a force sensor with a sample attachment point, an actuator with a second attachment point, and a camera. To monitor force, we use a parallel beam sensor, commonly used in digital weighing scales. To stretch the sample, we use a stepper motor with a screw mechanism moving a stage along linear rail. To monitor sample deformation, a compact digital microscope or a microscope camera are used. The system is controlled by MorphoRobotX, an integrated open-source software environment for mechanical experimentation. We first tested the basic Camelot setup, equipped with a digital microscope to track landmarks on the sample surface. We demonstrate that the system has sufficient precision to measure the stiffness in delicate plant samples, the etiolated hypocotyls of Arabidopsis, and were able to measure stiffness differences between wild type and a xyloglucan-deficient mutant. Next, we placed Camelot on an inverted microscope and used C-mount microscope camera to track displacement of cell junctions. We stretched onion epidermal peels in longitudinal and transverse directions and obtained results similar to those previously published. Finally, we used the setup coupled with an upright confocal microscope and measured anisotropic deformation of individual epidermal cells during stretching of an Arabidopsisleaf.
Conclusions: The portability and suitability of Camelot for high-resolution optical tracking under a microscope make it an ideal tool for researchers in resource-limited settings or those pursuing exploratory biomechanics work.
Mechanism of Qilong Capsule against Myocardial Ischemia-Reperfusion Injury Based on Network Pharmacology and Experimental Validation
Authors: Li Lingxu , Ye Jingxue , Zhou Jiahui , Wang Zhihui , Li Ruoyun , Wang Min , Sun Guibo 
Published: January 2025

Introduction:
Qilong capsule (QC) has been used clinically to treat ischemic stroke in
China. This study evaluated the therapeutic effects of QC on myocardial ischemia-reperfusion
injury (MIRI) and its potential mechanisms.

Method:
The components and candidate targets of QC against MIRI were predicted by network
pharmacology via relevant databases such as TCMSP, BATMAN-TCM, GeneCards. The potential
mechanisms were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and
Genomes (KEGG) pathway enrichment analyses and verified by enzyme-linked immunosorbent
assay (ELISA) and Western blot.

Results:
Network pharmacology analysis indicated that the cardioprotective effect of QC
against MIRI was associated with inflammatory pathways. We further confirmed that QC effectively
decreased the levels of inflammatory factors, including hs-CRP and MCP-1, and suppressed
the expression of TNF-α and the phosphorylation of STAT3.

Conclusion:
This study provides evidence for further clinical applications of QC for MIRI therapy.

conclusion:
This study provides evidence for further clinical applications of QC for MIRI therapy.
In silico Investigation of Coumarin-based Compounds Targeting Keap1-Nrf2 Pathway Involved in the Development of Alzheimer’s Disease
Authors: Gote Sharmila , Dubey Sonal , Nargund Shachindra L. , Thapa Shankar 
Published: January 2025

Background:
The Nrf2-Keap1 pathway holds great significance in antioxidant defense
mechanisms. This pathway has emerged as a pivotal clinical target for the development of highly
potent therapeutic agents for neurodegenerative diseases. The Keap1-Nrf2 inhibitors covalently bind
to the Keap1 protein, leading to modifications in cysteine residues. This computational study focused
on the investigation of coumarin derivatives through in silico methods.

Objective:
The aim of this study was to conduct an in silico exploration of coumarin derivatives as
potential Keap1 inhibitors in the context of Alzheimer's disease.

Methods:
Coumarin derivatives were obtained from the ZINC 15 database in the sdf (simple dimension
file) format. The docking process utilized the crystal structure of the Keap1 protein (PDB ID:
4XMB), which was sourced from the RCSB Protein Data Bank (https://www.rcsb.org/). Molecular
docking was conducted using the AutoDock Vina1.5.7 software. Following this, the top ten coumarin
derivatives with the highest binding energy underwent an ADME study, SAR study, toxicity
study, and medicinal chemistry score study. In the in silico study, resveratrol was employed as the
standard drug.

Results:
We sourced ligand molecules from the ZINC 15 database in pdf format, while the Keap1
protein, identified by its PDB ID: 4XMB, was obtained from the RCSB website
(https://www.rcsb.org/) in pdb format. We used resveratrol as the standard drug for the molecular
docking analysis. The in silico molecular docking procedures were conducted using Autodock Vina
1.5.7 software.

Conclusion:
Among the 75 coumarin derivatives assessed, 9 exhibited the most favourable binding
energies towards Keap1. The top 9 derivatives of coumarin were further scrutinized in terms of their
pharmacokinetic profiling and evaluation of bioactivity. Both compounds S1 and S2 exhibited noteworthy
docking scores of -7.44 and -7.52 Kcal/mol, respectively. Our investigation revealed that all
nine derivatives of coumarin exhibited properties characteristic of drug-like compounds. The investigation
conducted suggested the potential development of coumarin derivatives as effective Keap1-
Nrf2 inhibitors. Further validation of the computational findings requires both in vivo and in vitro
studies.
Penicillin G Acylase: A Multifunctional Catalyst with Broad Implications in Pharmaceutical Science and Industrial Applications
Authors: L. Roopa , V. Shanthi 
Published: January 2025

Abstract:
Penicillin G Acylase (PGA) has emerged as a critical biocatalyst in pharmaceutical sciences,
exceeding its traditional role in penicillin synthesis. Despite its industrial significance, challenges,
including substrate specificity, stability under industrial conditions, and efficiency in immobilization,
persist. Engineering enhanced enzyme variants and developing advanced immobilization
techniques along with process optimization shall be possible solutions to further improve
reaction efficiency and scalability. Green chemistry integration can make PGA-based processes
more sustainable. Moreover, the use of computational tools, including AI-driven optimization, can
guide enzyme design and reaction condition refinement. A review synthesizing these advancements
not only consolidates existing knowledge but also identifies opportunities for further innovation,
ensuring the enzyme’s continued industrial and scientific relevance. The review discusses the
structure and functionality of PGA, highlighting its diverse applications beyond penicillin production.
Beyond antibiotic synthesis, PGA's usefulness extends to ester synthesis, resolving racemic
mixtures and peptide bond formation, underlining its importance in various bioconversions and
synthetic reactions. This adaptability is crucial for green chemistry, promoting sustainable practices
in industrial processes. The kinetic parameters of PGA are discussed, providing insights into its
operational efficiency. Despite its significant potential, PGA faces limitations in commercial applications,
primarily due to stability issues under industrial conditions. Efforts to enhance PGA's stability,
including engineering approaches, are explored to improve its industrial applicability. The
review concludes by emphasizing PGA's role as a catalyst with vast implications in science and
medicine, particularly in an era of rising antibiotic resistance. It underscores the enzyme's interconnected
roles in production and therapeutics, its broad spectrum of applications, and the shift
from traditional penicillin synthesis to broad-spectrum bioconversions. The scope of PGA engineering
is also highlighted, indicating future directions for research and application in the pharmaceutical
industry.