bluuebunny/crossref_metadata_2025 huggingface dataset:
Circulating Hepcidin Levels Are an Independent Predictor of Survival in Microsatellite Stable Metastatic Colorectal Cancer Patient Candidates for Standard First-Line Treatment
Authors: Formica Vincenzo , Di Grazia Antonio , Bonomo Maria Vittoria , Frascatani Rachele , Mancone Roberto , Monteleone Giovanni
Published: November 2024

Background & Aim. Hepcidin, a key hormone in iron homeostasis, is synthesized by colorectal cancer (CRC) cells, particularly in the late stages of tumorigenesis. This study aimed to ascertain whether the serum levels of hepcidin could serve as a prognostic biomarker in microsatellite stable (MSS) metastatic CRC (mCRC). Specifically, we assessed the predictive value of baseline serum hepcidin levels for the overall survival (OS) of patients with MSS mCRC receiving first-line treatment with FOLFOX-panitumumab (RAS/BRAF wild-type) or FOLFOX-bevacizumab (RAS or BRAF mutations). Methods. Serum samples were prospectively collected from 35 normal healthy volunteers (normal controls) and 55 patients with MSS mCRC and analyzed for their content of hepcidin by ELISA. Results. Serum hepcidin levels were significantly greater in patients with mCRC than in the normal controls. In the mCRC group, patients with baseline levels of hepcidin greater than 40 ng/mL had a significantly shorter 1-year OS rate (39%) than those with hepcidin levels lower than 40 ng/mL (80%) [hazard ratio (HR): 2.94; 95% CI: 1.27–6.84; p = 0.01]. A multivariate Cox regression analysis showed that the pre-treatment serum hepcidin levels were an independent prognostic factor for OS, not influenced by other well-known prognostic factors (i.e., CEA status, Karnofsky performance score, number of metastatic sites, RAS/BRAF mutations), and this was evident across all major patient subgroups. Conclusions. Our data show that baseline serum levels of hepcidin are an independent risk factor for OS in MSS mCRC patients undergoing standard first-line treatment. Further prospective and extensive studies are needed to confirm and validate our findings.
BiVO4-Based Photoelectrochemical Sensors for the Detection of Diclofenac: The Role of Doping, Electrolytes and Applied Potentials
Authors: Petruleviciene Milda , Savickaja Irena , Kovger-Jarosevic Jelena , Skruodiene Monika , Juodkazyte Jurga , Ramanavicius Simonas , Ramanavicius Arunas
Published: November 2024

This study presents the findings of an investigation into the characteristics and capabilities of BiVO₄ and Mo-doped BiVO4 coatings for the detection of diclofenac (DCF). In this study, a neutral sodium sulfate electrolyte and an alkaline sodium borate buffer were selected, and a range of potentials were employed to ascertain the impact of diverse conditions on the sensing performance of diclofenac. The introduction of Mo-doping had a profound impact on the photoelectrochemical response of the BiVO4 coating. However, it was observed that Mo-doping resulted in an increase in the adsorption of diclofenac oxidation products on the surface of the photoanode, which in turn led to a negative blocking effect. To evaluate the structural and morphological properties of the coatings, X-ray diffraction analysis (XRD), scanning electron microscopy (SEM), and energy dispersive analysis (EDX) were conducted. The photoelectrochemical properties were evaluated through the use of cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and chronoamperometry (CA). An increase in the photocurrent density of BiVO4 was observed in response to an increase in the concentration of diclofenac within a range of 0.1 to 1 mg L−1 during the sensing experiments. However, at higher concentrations, saturation of diclofenac was observed at the photoelectrode/electrolyte interface. The results of selectivity experiments demonstrated that the nature of the electrolyte has a significant impact on the selectivity of designed photoelectrochemical sensors.
Bromelain Supplementation in the Management of Otitis Media with Effusion in Children
Authors: Martines Francesco , Malta Ginevra , Cannizzaro Emanuele , Kelly Theodoridou , Salvago Pietro , Plescia Fulvio
Published: November 2024

Background/Objectives: The respiratory system is prone to infectious diseases, especially in children below five years of age. Upper respiratory tract infections in children are often associated with Eustachian tube dysfunction and complicated by otitis media with effusion (OME), an inflammatory process within the middle ear, which can lead to hearing loss. Treatment for these infections involves a combination of medication and symptom relief, depending on the severity and cause of the infection. In recent years, natural therapeutic drugs derived from herbal medicines have been gaining popularity in treating various pathologies. Bromelain, one of the most studied natural compounds, has been investigated extensively due to its numerous pharmacological properties, offering a potential new avenue for treatment. Based on these promising findings, our study was designed to examine the efficacy of supplementation with bromelain in countering symptoms associated with OME. Methods: This study was conducted on data acquired from medical records from the Section of Audiology of the University of Palermo, focusing on the period of January 2022 to June 2023 and selecting 224 children (age range 1–8 years), namely 174 males and 50 females, who were evaluated for presumed OME at the audiology pediatric ambulatory. All patients selected before initiating pharmacological treatment underwent thorough screening regarding the functionality of the tympanic cavities, otoacoustic emissions, the auditory threshold, and the ear canal’s integrity. Results: The preliminary findings of this study are significant, demonstrating that supplementation with bromelain led to notable improvements in the symptoms accompanying OME after 15 days and 60 days of therapy. Notably, patients who received the bromelain supplement reported reduced mucus secretions and improved auditory function. Conclusions: These results underscore the potential of naturally occurring compounds as adjuvants to standard therapeutic strategies in treating OME.
Extracorporeal Membrane Oxygenation as Life Support in Neonatal Respiratory Failure: A Single-Center Cohort Study and a Systematic Review
Authors: Falsaperla Raffaele , Zanai Rosanna , Collotta Ausilia Desiree , Sortino Vincenzo , Vitaliti Giovanna , Cimino Carla , Scalia Bruna , Vaccalluzzo Marco Simone , Spatuzza Michela , Privitera Grete Francesca , Pulvirenti Alfredo , Pavone Piero , Ruggieri Martino , Marino Andrea , Agati Salvatore
Published: November 2024

Background: Extracorporeal membrane oxygenation (ECMO) is a life support in newborns with severe respiratory failure. Our main objective was to evaluate the mortality of patients and define positive and negative predictive factors of survival. Methods: We performed a Strengthening the Reporting of Observational Studies in Epidemiology (STROBE)-conformed retrospective observational study and a systematic review, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Our data were analyzed using R (v.4.2.1). We performed survival analysis, correlation analysis, and Fisher’s exact test. The first endpoint was the mortality rate. The second endpoint was to evaluate all factors associated with survival. The third endpoint was focused on complications of ECMO. Results: Our study included 8 patients treated in our centers and 45 patients from the literature review. Survival was 79%. Positive predictive factors of survival were a length of ECMO of less than 10 days and male neonates, while prematurity and the presence of 2 complications were negative predictive factors. Conclusions: ECMO functions as life support, although mortality and morbidity risks are high.
Deviant Peer Affiliation, Depression, and Adolescent Non-Suicidal Self-Injury: The Moderating Effect of the OXTR Gene rs53576 Polymorphism
Authors: Li Jingjing , Yu Chengfu
Published: November 2024

Background: Adolescent non-suicidal self-injury (NSSI) has emerged as a progressively widespread and significant public health concern on a global scale. Research has increasingly documented a positive linkage between deviant peer affiliation and adolescent NSSI; however, there is little known about the underlying moderating or mediating mechanism of NSSI. According to the gene × environment interaction perspective, the current study investigated the intermediary function of depression in linking deviant peer affiliation to NSSI among adolescents, while also considering the moderating effect of the OXTR gene rs53576 polymorphism on this intermediary process. Methods: A total of 469 adolescents (Meanage = 12.81 years; SD = 0.47 years) anonymously finished the study questionnaires. This study used structural equation modeling analysis to verify a moderated mediation model. Gender, age, and family financial difficulties were used as covariates. Results: Mediation analyses suggested that the positive connection between deviant peer affiliation and adolescent NSSI was mediated by depression. Moreover, the moderated mediation analyses revealed that deviant peer affiliation increased depression levels, which in turn contributed to increased NSSI among adolescents with the AA genotype. Nevertheless, the correlation failed to reach statistical significance among adolescents possessing the GA and GG genotypes. Conclusions: These findings emphasize depression’s potential as a bridge linking deviant peer affiliation to adolescent NSSI. The AA genotype of the OXTR gene rs53576 emerges as a critical risk factor in the enhancement of this indirect effect. This study provides valuable perspectives for designing intervention strategies aimed at reducing adolescent NSSI.
Discharge Readiness Among Primary Caregivers in Pediatric Medical–Surgical Units in Jeddah, Saudi Arabia
Authors: Alzahrani Maha A. , Alharbi Manal F.
Published: November 2024

Background/Objectives: Preparing families to support children after hospital discharge is crucial, particularly due to the fragile health of pediatric patients and the care required at home. In this study, the aim was to assess the readiness for hospital discharge among primary caregivers of pediatric patients in medical–surgical units in Jeddah, Saudi Arabia, and to identify factors influencing their preparedness. Methods: A quantitative cross-sectional study was conducted among 258 primary caregivers recruited from two hospitals in Jeddah: King Abdulaziz University Hospital (KAUH) and a Ministry of Health (MOH) hospital. A purposive sampling method was used. Data were collected through the Pediatric Readiness for Hospital Discharge Scale (Ped-RHDS) and the Quality of Discharge Teaching Scale (QDTS), translated into Arabic. Descriptive statistics, t-tests, and multiple regression analyses were employed to identify key predictors of discharge readiness. Results: Caregivers reported moderate to high readiness for discharge, with mean scores of 8.28 (SD = 2.65) for personal strength and 8.62 (SD = 2.26) for their child’s strength. Knowledge scores averaged 7.49 (SD = 3.27). The quality of discharge teaching was higher at KAUH (M = 6.43, SD = 2.56) than at the MOH hospital (M = 5.48, SD = 2.89, p = 0.006). Caregiver age, child age, and discharge teaching quality were significant predictors of readiness (p < 0.05). Conclusions: In this study, the importance of discharge readiness is emphasized, highlighting the role of discharge education in enhancing preparedness. Addressing caregivers’ specific needs, especially for younger children or prolonged stays, can improve readiness and reduce post-discharge complications.
Application of Smart Condensed H-Adsorption Nanocomposites in Batteries: Energy Storage Systems and DFT Computations
Authors: Mollaamin Fatemeh , Monajjemi Majid
Published: November 2024

A comprehensive investigation of hydrogen grabbing towards the formation of hetero-clusters of AlGaN–H, Si–AlGaN–H, Ge–AlGaN–H, Pd–AlGaN–H, and Pt–AlGaN–H was carried out using DFT computations at the CAM–B3LYP–D3/6-311+G (d,p) level of theory. The notable fragile signal intensity close to the parallel edge of the nanocluster sample might be owing to silicon or germanium binding-induced non-spherical distribution of Si–AlGaN or Ge–AlGaN hetero-clusters. Based on TDOS, the excessive growth technique of doping silicon, germanium, palladium, or platinum is a potential approach to designing high-efficiency hybrid semipolar gallium nitride devices in a long-wavelength zone. Therefore, it can be considered that palladium or platinum atoms in the functionalized Pd–AlGaN or Pt–AlGaN might have more impressive sensitivity for accepting the electrons in the process of hydrogen adsorption. The advantages of platinum or palladium over aluminum gallium nitride include its higher electron and hole mobility, allowing platinum or palladium doping devices to operate at higher frequencies than silicon or germanium doping devices. In fact, it can be observed that doped hetero-clusters of Pd–AlGaN or Pt–AlGaN might ameliorate the capability of AlGaN in transistor cells for energy storage.
UAV Mission Computer Operation Mode Optimization Focusing on Computational Energy Efficiency and System Responsiveness
Authors: Liubimov Oleksandr , Turkin Ihor , Cheranovskiy Valeriy , Volobuieva Lina
Published: November 2024

The rising popularity of UAVs and other autonomous control systems coupled with real-time operating systems has increased the complexity of developing systems with the proper robustness, performance, and reactivity. The growing demand for more sophisticated computational tasks, proportionally larger payloads, battery limitations, and smaller take-off mass requires higher energy efficiency for all avionics and mission computers. This paper aims to develop a technique for experimentally studying the indicators of reactivity and energy consumption in a computing platform for unmanned aerial vehicles (UAVs). The paper provides an experimental assessment of the ‘Boryviter 0.1’ computing platform, which is implemented on the ATSAMV71 microprocessor and operates under the open-source FreeRTOS operating system. The results are the basis for developing algorithms and energy-efficient design strategies for the mission computer to solve the optimization problem. This paper provides experimental results of measurements of the energy consumed by the microcontroller and estimates of the reduction in system energy consumption due to additional time costs for suspending and resuming the computer’s operation. The results show that the ‘Boryviter 0.1’ computing platform can be used as a UAV mission computer for typical flight control tasks requiring real-time computing under the influence of external factors. As a further work direction, we plan to investigate the proposed energy-saving algorithms within the planned NASA F’Prime software flight framework. Such an investigation, which should use the mission computer’s actual flight computation load, will help to qualify the obtained energy-saving methods and their implementation results.
Dental Practitioners’ Knowledge and Attitudes Toward the Etiology, Diagnosis, and Treatment of Peri-Implantitis
Authors: Zakaria Osama , Tabassum Afsheen , Attia Dina , Alshehri Turki , Alanazi Danya A. , Alshehri Jana , Alshehri Sami , Chopra Aditi , Madi Marwa
Published: November 2024

Objectives: The objective of this study was to assess the level of knowledge and attitude about the etiology, diagnosis, and management of peri-implantitis among dental practitioners. Methods: An online cross-sectional study on 303 dentists in Saudi Arabia was conducted. A closed-ended survey consisting of 28 questions was designed. Three sections were created, i.e., (1) participants’ characteristics; (2) knowledge of peri-implantitis etiology, risk factors, diagnosis, and complications; and (3) the use of antibiotics to manage peri-implantitis and methods used for diagnosis and treatment. The data were analyzed using mean and percentages. Results: A total of 303 dentists participated in this study with a 78.8% response rate, comprising 80% general dentists and 20% specialists. The majority of dentists demonstrated knowledge about peri-implantitis, with 85.5% identifying bacterial plaque as an etiologic factor and 83.8% recognizing it as an inflammatory reaction. Regarding risk factors, 88.1% identified smoking and 86.1% recognized periodontitis as contributors to peri-implant disease development. In terms of clinical decision making, 63% of participants considered implant mobility as a definitive indication for implant removal, and more than half reported using crater-like bone defects surrounding implants as a diagnostic criterion for peri-implantitis. For antimicrobial therapy, amoxicillin alone (30%) was the most commonly prescribed antibiotic, followed by the combination of amoxicillin with metronidazole (29%). Despite these treatment approaches, it is important to note that currently there are no established, predictable protocols for treating any phase of peri-implant disease. Conclusion: While participating dentists demonstrated a strong understanding of peri-implantitis etiology and risk factors, particularly regarding bacterial plaque and smoking as major contributors, there was considerable variation in antibiotic selection and usage patterns. These findings suggest the need for standardized guidelines and further research to establish evidence-based protocols for managing peri-implant diseases.
Can the Use of Digital Finance Promote the Enhancement and Quality Improvement of Household Consumption Among Farmers?
Authors: Xu Sheng , Liu Xichuan , Zhang Lu , Xiao Yu
Published: November 2024

The key strategic point for facilitating domestic circulation is to enhance and expand household consumption. Based on a survey of 1080 farming households in Hunan, Hubei, and Jilin Provinces, this study examines the impact of digital finance use on the scale and structural upgrading of household consumption among farmers. The findings indicate that digital finance use effectively expands the scale of household consumption and promotes structural upgrades. The results remain robust through various endogenous and robust methods. Heterogeneity analysis reveals that the benefits of digital finance use are greater for middle- to high-income groups and those with lower education levels, indicating the presence of a digital divide effect. Furthermore, the construction of village communities, skill training, improvements in village logistics services, and the availability of medical clinic facilities can enhance the consumption-promoting effects of digital finance use. Mechanism analysis shows that digital finance primarily operates through alleviating credit constraints, enhancing risk prevention, and improving financial returns to influence the scale and structural upgrading of household consumption. This study provides policy insights for rural revitalization and unlocking the consumption potential of rural residents.
Middle-Level Teacher Certification/Licensure: Current Status and Future Directions
Authors: Dever Robin , Hurd Ellis , Miller Nicole C. , Whitaker Nicole
Published: November 2024

The Successful Middle School: This We Believe calls for specialized middle-level certification/licensure and teacher development. Certification/licensure has an impact on teacher preparation and, likely, the recruitment and retention of middle-level educators. In order to continue to advocate for specialized certification/licensure, research needs to determine the nature of certification/licensure, the origins and impacts of their shifts, and the recruitment and retention of middle-level educators, especially related to their pathway. This literature review is part of the development of a research agenda for the American Educational Research Association’s (AERA) Middle Level Education Research (MLER) Special Interest Group (SIG). The purpose of this review is to examine the current status of the research related to middle-level certification/licensure and the research questions generated for the MLER SIG research agenda. The literature from the last 23 years was explored to conduct this combination of literature and scoping literature review. Gaps of research were identified, and some questions were unable to be answered through this type of study. From this literature review, it is clear that ongoing and additional research needs to be conducted related to middle-level certification/licensure related to the research questions we initially generated as part of the research agenda.
Automatic Classification of Rotating Rectifier Faults in Brushless Synchronous Machines
Authors: Mahtani Kumar , Decroix Julien , Pascual Rubén , Guerrero José M. , Platero Carlos A.
Published: November 2024

This paper presents an advanced automatic fault classification method for detecting rotating rectifier faults in brushless synchronous machines (BSMs). The proposed approach employs a multilayer perceptron (MLP) neural network to classify the operational states of the rotating rectifier, including healthy conditions and common fault types: open-diode (OD), shorted-diode (SD), and open-phase (OP). Key machine measurements, available on an ordinary basis in the industry, such as active power (P), reactive power (Q), stator voltage (U), and excitation current (Ie), are used as inputs for this model, allowing for non-invasive, real-time fault detection. This model achieved an overall classification accuracy of 93.4%, with a precision of 94.9% for fault detection and strong recall performance across multiple fault types. The neural network’s robustness is enhanced by advanced data processing techniques, including Gaussian filtering and class balancing through the synthetic minority over-sampling technique (SMOTE). Experimental testing on a modified 5-kVA BSM setup, where rectifier faults were systematically induced, was used to train the network and validate the model’s performance. This method provides a promising tool for real-time condition monitoring of BSMs, improving machine reliability and minimizing downtime in industrial applications.
KoHMT: A Multimodal Emotion Recognition Model Integrating KoELECTRA, HuBERT with Multimodal Transformer
Authors: Yi Moung-Ho , Kwak Keun-Chang , Shin Ju-Hyun
Published: November 2024

With the advancement of human-computer interaction, the role of emotion recognition has become increasingly significant. Emotion recognition technology provides practical benefits across various industries, including user experience enhancement, education, and organizational productivity. For instance, in educational settings, it enables real-time understanding of students’ emotional states, facilitating tailored feedback. In workplaces, monitoring employees’ emotions can contribute to improved job performance and satisfaction. Recently, emotion recognition has also gained attention in media applications such as automated movie dubbing, where it enhances the naturalness of dubbed performances by synchronizing emotional expression in both audio and visuals. Consequently, multimodal emotion recognition research, which integrates text, speech, and video data, has gained momentum in diverse fields. In this study, we propose an emotion recognition approach that combines text and speech data, specifically incorporating the characteristics of the Korean language. For text data, we utilize KoELECTRA to generate embeddings, and for speech data, we extract features using HuBERT embeddings. The proposed multimodal transformer model processes text and speech data independently, subsequently learning interactions between the two modalities through a Cross-Modal Attention mechanism. This approach effectively combines complementary information from text and speech, enhancing the accuracy of emotion recognition. Our experimental results demonstrate that the proposed model surpasses single-modality models, achieving a high accuracy of 77.01% and an F1-Score of 0.7703 in emotion classification. This study contributes to the advancement of emotion recognition technology by integrating diverse language and modality data, suggesting the potential for further improvements through the inclusion of additional modalities in future work.
Underwater Horizontal Attitude Determination Technology Based on Fusion Power Circle Theory and Improved 3D Cone Hough Transform
Authors: Zhang Haosu , Wang Zihao , Zhou Shiyin , Ma Cheng , Wang Sheng , Zhang Fafu , Xu Lingji
Published: November 2024

Due to the complexity of underwater conditions, achieving stable long-endurance autonomous underwater navigation has always been a challenging issue. Polarized light navigation, which utilizes the polarization field in the underwater downward radiation field to determine the heading angle, requires a known horizontal attitude beforehand. In response to the significant deviations caused by interference in the existing underwater polarization attitude determination algorithms, this paper proposes an edge recognition method that integrates the Power theorem of circles and Improved 3D Conical Hough Transformation (PTC–3D-CoHT). This method has the advantages of pre-screening effective pixel points, better handling of distorted circles, and improving the deviation in extracting Snell’s window. The theoretical basis, model, and detailed calculation process of this method are provided in this paper. Underwater experiments show that, compared to the Circular Hough Transformation (CiHT) and 3D Conical Hough Transformation (3D-CoHT) algorithms, PTC–3D-CoHT enhances the robustness of Snell’s window extraction, verifying the effectiveness of the proposed method.
Prediction of Pollutant Emissions from a Low-Speed Marine Engine Based on Harris Hawks Optimization and Lightgbm
Authors: Chen Yue , Shen Yulong , Wen Miaomiao , Wei Cunfeng , Liang Junjie , Li Yuanqiang , Sun Ying
Published: November 2024

With the rapid development of data science, machine learning has been widely applied to research on pollutant emission prediction in internal combustion engines due to its excellent responsiveness and generalization ability. This article introduces Lightgbm (LGB), which belongs to ensemble learning, to predict the pollutant emissions from a low-speed two-stroke marine engine. The dataset used to train LGB was derived from a one-dimensional performance simulation model of the engine, which was rigorously verified for its reliability by experimental data. To further improve the forecast performance of the LGB model, we used Harris Hawks Optimization (HHO) to automatically optimize the hyperparameters of the model, and finally, we analyzed the importance of the model features. The results show that changes in engine control parameters have significant influences on NOx and soot emissions from the engine, which can serve as the basis for the selection of the LGB model features; the LGB model was able to accurately predict pollutant concentrations from the engine with much higher accuracy than a single decision tree (DT) model; combining with HHO, the predictive ability of the LGB model was significantly improved, such as for the validation set prediction results, the mean absolute error (MAE) was reduced by about 20%, the mean squared error (MSE) was reduced by about 30%, and the coefficient of determination (R2) was increased by about 0.005; and the importance analysis of the model features indicated that the combustion condition of the fuel was highly correlated with the generation of the pollutants, and the fuel injection phases can be adjusted in practice to achieve highly efficient and low-emission processes of combustion. The results of this study can provide references for the development of a new generation of highly efficient and low-pollution marine engines.
Research on Defect Detection for Overhead Transmission Lines Based on the ABG-YOLOv8n Model
Authors: Yu Yang , Lv Hongfang , Chen Wei , Wang Yi
Published: November 2024

In the field of smart grid monitoring, real-time defect detection for overhead transmission lines is crucial for ensuring the safety and stability of power systems. This paper proposes a defect detection model for overhead transmission lines based on an improved YOLOv8n model, named ABG-YOLOv8n. The model incorporates four key improvements: Lightweight convolutional neural networks and spatial–channel reconstructed convolutional modules are integrated into the backbone network and feature fusion network, respectively. A bidirectional feature pyramid network is employed to achieve multi-scale feature fusion, and the ASFF mechanism is used to enhance the sensitivity of YOLOv8n’s detection head. Finally, comprehensive comparative experiments were conducted with multiple models to validate the effectiveness of the proposed method based on the obtained prediction curves and various performance metrics. The validation results indicate that the proposed ABG-YOLOv8n model achieves a 4.5% improvement in mean average precision compared to the original YOLOv8n model, with corresponding increases of 3.6% in accuracy and 2.0% in recall. Additionally, the ABG-YOLOv8n model demonstrates superior detection performance compared to other enhanced YOLO models.
Application of Machine Learning Models in Social Sciences: Managing Nonlinear Relationships
Authors: Kyriazos Theodoros , Poga Mary
Published: November 2024

The increasing complexity of social science data and phenomena necessitates using advanced analytical techniques to capture nonlinear relationships that traditional linear models often overlook. This chapter explores the application of machine learning (ML) models in social science research, focusing on their ability to manage nonlinear interactions in multidimensional datasets. Nonlinear relationships are central to understanding social behaviors, socioeconomic factors, and psychological processes. Machine learning models, including decision trees, neural networks, random forests, and support vector machines, provide a flexible framework for capturing these intricate patterns. The chapter begins by examining the limitations of linear models and introduces essential machine learning techniques suited for nonlinear modeling. A discussion follows on how these models automatically detect interactions and threshold effects, offering superior predictive power and robustness against noise compared to traditional methods. The chapter also covers the practical challenges of model evaluation, validation, and handling imbalanced data, emphasizing cross-validation and performance metrics tailored to the nuances of social science datasets. Practical recommendations are offered to researchers, highlighting the balance between predictive accuracy and model interpretability, ethical considerations, and best practices for communicating results to diverse stakeholders. This chapter demonstrates that while machine learning models provide robust solutions for modeling nonlinear relationships, their successful application in social sciences requires careful attention to data quality, model selection, validation, and ethical considerations. Machine learning holds transformative potential for understanding complex social phenomena and informing data-driven psychology, sociology, and political science policy-making.
Evaluation of Quality of Nitrite-Free Fermented Roe Deer (Capreolus capreolus) Sausage with Addition of Ascorbic Acid and Reduced NaCl
Authors: Wójciak Karolina M. , Kęska Paulina , Kačániová Miroslava , Čmiková Natália , Solska Elżbieta , Ogórek Agata
Published: November 2024

This study aimed to investigate the possibility of producing fermented roe deer sausages using acid whey without the addition of sodium nitrite. Additionally, ascorbic acid was added to improve the oxidative stability of the product, and sodium chloride (NaCl) was partially replaced by potassium chloride (KCl) (7:3). The sausages were analyzed after fermentation (on day 30) and during post-production aging (i.e., 60 and 90 days after production at 4 °C) for their pH, water activity (aw), redox potential (ORP), thiobarbituric acid value (TBARS), and color parameters (CIE L*, a*, and b*). The microbiological status of the products was also profiled. During aging, the aw and pH values were significantly lower (p < 0.05) in the variant with the addition of ascorbic acid. In all samples with the addition of acid whey, an increase in the TBARS value compared to the variant with sodium nitrite was observed, but among them, the variant with the substitution of NaCl by KCl was characterized by the lowest intensity of lipid oxidation. During post-production aging, the effect of acid whey on the loss of redness (a*) of the roe deer sausages was confirmed, with the lowest a* observed in samples with the addition of ascorbic acid. A total of 281 and 219 isolates with high scores were identified in the fermented deer sausages after fermentation (30 days) and storage (90 days), respectively. The most frequently isolated species from the fermented roe deer sausages were from the Latilactobacillu genus (Latilactobacillus curvatus, Lati-lactobacillus sakei subsp. carnosus) and Leuconostoc genus (Leuconostoc mesenteroides, L. mesenteroides subsp. dextrani-cum, and Leuconostoc mesenteroides subsp. mesenteroides).
Recent Advance on Biological Activity and Toxicity of Arecoline in Edible Areca (Betel) Nut: A Review
Authors: Huang Gang , Zeng Deyong , Liang Tisong , Liu Yaping , Cui Fang , Zhao Haitian , Lu Weihong
Published: November 2024

Areca nut (Areca catechu L. AN), which is the dried, mature seed of the palm species Areca catechu L., is consumed by over 600 million individuals, predominantly in South Asia, East Africa, and certain regions of the tropical Pacific. The International Agency for Research on Cancer (IARC) has classified it as a species carcinogenic to humans and designated it as a Group 1 human carcinogen. Arecoline, which has attracted attention for its therapeutic potential in the treatment of mental illness and the relief of gastrointestinal disorders, is the main active alkaloid in the areca nut. However, in 2020, the IARC said that arecoline might be a “probable human carcinogen”. Arecoline can cause various types of cellular damage, primarily leading to the destruction of cell morphology, reduced survival rates, abnormal physiological functions, and even cell apoptosis. The research on its toxic mechanisms includes several aspects, such as increased levels of reactive oxygen species, autophagy, epigenetic dysregulation, and immune dysfunction, but these research findings are scattered and lack systematic integration. This article summarizes the effect mechanisms of arecoline on the oral cavity, neurological and cardiovascular systems, and other organs, as well as embryogenesis, and provides detailed and valuable insights for the clinical practice and targeted therapy of arecoline.
Preparation of Low-Fishy Microencapsulated DHA-Rich Algal Oil Powder Using Infant Rice Powder
Authors: Zhang Yuqing , Xie Zuohua , Zhang Siqiong , Li Jing , Luo Ting
Published: November 2024

Commercial DHA-rich algal oil has some issues, such as an unpleasant odor and susceptibility to oxidation. The main fishy odor compounds in commercial DHA-rich algal oil powder and DHA-rich algal oil microcapsules are hexanal and (E, E)-2,4-heptadienal. To address this issue, a microencapsulation process was designed for DHA-rich algal oil using infant rice powder (IRP), maltodextrin (MD), and whey protein concentrate (WPC) as wall materials, with sodium starch octenyl succinate (SSOS) and monoacylglycerol (MAC) as emulsifiers. The spray-drying method was used for microencapsulation. The experimental data showed that microcapsules with wall materials in a ratio of IRP/MD/WPC = 1:3:1 and an emulsifier content of 3.5% (SSOS and MAC) had the highest encapsulation efficiency (85.20 ± 6.03%) and the lowest aldehyde content (65.38 ± 3.23%). This microcapsule showed a good appearance and better oxidation stability compared with the crude oil, with a water content and average particle size of 1.69 ± 0.57% and 631.60 ± 23.19 nm, respectively. The results indicated that DHA-rich algal oil microcapsules prepared with infant rice powder had a lower fishy odor and better sensory acceptability compared to commercial DHA-rich algal oil powder.
Lactiplantibacillus plantarum for the Preparation of Fermented Low-Bitter Enzymatic Skim Milk with Antioxidant Ability
Authors: Jiang Yi , Zhang Longfei , Jin Yushi , Xu Haiyan , Liang Yating , Xia Zihan , Zhang Chenchen , Guan Chengran , Qu Hengxian , Wa Yunchao , Wang Wenqiong , Huang Yujun , Gu Ruixia , Chen Dawei
Published: November 2024

A high degree of hydrolysis can reduce the allergenicity of milk, while lactic acid bacteria (LAB) fermentation can further enhance the antioxidant ability of enzymatic milk. LAB with a strong antioxidant ability was screened, and the effects of LAB on the bitterness, taste and flavor of enzymatic skim milk (ESM) with a high degree of hydrolysis were investigated in this paper, in addition to the response surface methodology optimized the conditions of the LAB fermentation of ESM. The results indicate that the skim milk hydrolyzed by Protamex has a higher degree of hydrolysis and lower bitterness. The scavenging rate of 2,2-Diphenyl-1-picrylhydrazyl (DPPH) free radical, the inhibition rate of hydroxyl radical (·OH) and the superoxide dismutase (SOD) activity of Lactiplantibacillus plantarum 16 and Lactococcus lactis subsp. lactis m16 are significantly higher than those of other strains (p < 0.05), while the improvement effect of L. plantarum 16 on the bitterness and flavor of ESM is better than that of L. lactis subsp. lactis m16. The fermented ESM has a strong antioxidant ability and low bitterness when the inoculum quantity of L. plantarum 16 is 5%, fermentation at 37 °C for 18 h and the pH of the ESM is 6.5, for which the DPPH free radical scavenging rate is 61.32%, the ·OH inhibition rate is 83.35%, the SOD activity rate is 14.58 and the sensory evaluation is 4.25. The contents of amino acids related to bitterness and antioxidants were reduced and increased, respectively. The ESM fermented by L. plantarum 16 has a good flavor, antioxidant ability and low bitterness.
Understanding Early Risk Factors of Preschool Disruptive Behaviors in a Population-Based Birth Cohort: Why Does Comorbidity Matter?
Authors: Carbonneau Rene , Vitaro Frank , Brendgen Mara , Boivin Michel , Tremblay Richard E.
Published: November 2024

Background/Objectives: Research on early risk factors for disruptive behaviors (DBs: hyperactivity–impulsivity/HI, non-compliance/NC, or physical aggression/PA) has predominantly focused on individual DBs in silos (i.e., HI, NC, or PA) or the broader category of externalizing, reporting mostly common risk factors among them. However, studies addressing DB comorbidity, i.e., the simultaneous occurrence of more than one DB, showed differences in risk factors among DB comorbid profiles. Aiming to clarify this discrepancy, the present study compared the early risk factors associated with different longitudinal patterns (i.e., trajectories) of single-DBs (HI, NC, PA) with risk factors associated with monomorbid (HIonly, NConly, PAonly) and comorbid (HI + NC, NC + PA, HI + NC + PA) joint-DBs trajectories during the preschool period. Methods: In a population-based birth cohort (N = 2045), parents’ pre-conception characteristics, pregnancy and perinatal conditions, and age 5 months child and family characteristics were used to compare children following single-DB and joint-DBs high trajectories to children following low or moderate trajectories. The DB trajectories were derived from mother ratings at ages 1½, 2½, 3½, 4½, and 5 years. Results: More risk factors were identified for single-DB high trajectories than for joint-DBs high trajectories. On average, children on a single-DB high trajectory shared only 44.2% of their risk factors with children on a related joint-DBs high trajectory. Moreover, high trajectories of single-DBs shared a larger proportion of their risk factors than did high trajectories of joint-DBs. The findings show that categories of DBs include different subgroups of children based on their comorbidity patterns across DBs, which are differentially linked to early risk factors. Conclusions: Addressing comorbidity when investigating early risk factors of preschool DBs may improve our understanding of the etiological processes leading to these distinct but related behaviors and increase our ability to intervene upstream to prevent the earliest forms of potentially life-altering psychopathological conditions.
Efficacy and Safety of Useul for Dry Eye Disease: Protocol for a Randomized, Double-Blind, Placebo-Controlled, Parallel, Phase 2 Clinical Trial
Authors: Lyu Yee-Ran , Kwon O-Jin , Park Bongkyun , Jung Hyun-A , Lee Ga-Young , Kim Chan-Sik
Published: November 2024

Introduction: Dry eye disease (DED) is a very frequently encountered ocular disease, making it a growing public health burden. However, current treatments for DED present unmet medical needs owing to their side effects or ineffectiveness. Therefore, an effective and safe therapeutic agent to manage DED is needed. Method and Analysis: We planned a phase 2, dose-finding, double-blind, randomized placebo-controlled trial to evaluate the efficacy and safety of two different doses of USL (Useul), the extract of Achyranthis Radix, compared with placebo, for DED. USL has been found to protect against DED by inducing tear secretion and improving corneal irregularity via anti-inflammatory effects, which will provide new therapeutic options. One hundred and twenty participants will be enrolled, after assessing the inclusion/exclusion criteria, at Daejeon University Daejeon Korean Medicine Hospital. Enrolled participants will be allocated to standard-dose USL, high-dose USL, or placebo groups in a 1:1:1 ratio and will be required to administer the trial medication twice a day for 12 weeks and visit the clinic five times. For efficacy outcomes, objective endpoints of fluorescein corneal staining score, tear break-up time, Schirmer’s test, and meibomian test and subjective endpoints of Ocular Surface Disease Index, visual analog scale, Standard Patient Evaluation for Eye Dryness-II, and biomarkers will be assessed throughout the trial. Safety will be assessed based on adverse events, vital signs, laboratory tests, visual acuity, and intraocular pressure. Discussion: Our study results are expected to provide clinical evidence for the use of DED as an effective and safe agent for DED.
Genetic Diversity and Gains from Selection for Fruit and Bean Physical Traits from the Conilon Coffee Genotype
Authors: Dalazen Jessica Rodrigues , Rocha Rodrigo Barros , Oliosi Gleison , de Araújo Larissa Fatarelli Bento , Espindula Marcelo Curitiba , Rodrigues Weverton Pereira , Partelli Fabio Luiz
Published: November 2024

Plant breeding of Coffea canephora is based on the characterization and use of the natural genetic variability of the species. Thus, the objective of this study was to quantify the genetic diversity and gains from selection of the fruit and bean physical traits of the C. canephora plant, seeking to understand the relations among the yield components and identify genotypes with superior traits. For this purpose, 42 genotypes were evaluated over two crop years while considering a randomized block design in a factorial arrangement to quantify the effects of genotypes, crop years, and the interaction between these two factors. Coffee fruit samples in the cherry stage were used to evaluate the weights, volumes, and dimensions of the fresh fruit and beans after drying. Genotypic variance prevailed over environmental variance for all of the fruit and bean physical traits of the coffee plants, except for the greatest fruit width (FWG). These associations indicate that the constituent parts of the fruit increased in a manner proportional to an increase in weight. Such associations can facilitate or hinder plant selection. The total gains obtained through the selection indices were similar to those obtained through direct selection for greater bean weights. However, the use of selection indices made it possible to identify clones with more balanced traits.
Does Fun Matter? Using Chatbots for Customer Services
Authors: Wut Tai Ming , Chan Elaine Ah-heung , Wong Helen Shun-mun
Published: November 2024

Chatbots are widely used in customer services contexts today. People using chatbots have their pragmatic reasons, like checking delivery status and refund policies. The purpose of the paper is to investigate what are those factors that affect user experience and a chatbot’s service quality which influence user satisfaction and electronic word-of-mouth. A survey was conducted in July 2024 to collect responses in Hong Kong about users’ perceptions of chatbots. Contrary to previous literature, entertainment and warmth perception were not associated with user experience and service quality. Social presence was associated with user experience, but not service quality. Competence was relevant to user experience and service quality, which reveals important implications for digital marketers and brands of adopting chatbots to enhance their service quality.
Non-Sleep Deep Rest Relaxation and Virtual Reality Therapy for Psychological Outcomes in Patients with Coronary Artery Disease: A Pilot Randomized Controlled Trial
Authors: Wrzeciono Adam , Cieślik Błażej , Kiper Pawel , Szczepańska-Gieracha Joanna , Gajda Robert
Published: November 2024

Background: While cardiac rehabilitation (CR) primarily focuses on restoring physical strength, preventing relapse, and reducing rehospitalization rates, psychological interventions play a complementary role by supporting mental health, which is crucial for patients’ long-term adherence and overall recovery. The effectiveness of psychological interventions in CR is debated, and while technologies like virtual reality (VR) therapy show promise, they have limitations for patients with coronary artery disease (CAD). Therefore, this study examines non-sleep deep rest (NSDR) relaxation, a novel and easily implementable technique, and compares its impact on depression, anxiety, and stress with VR therapy and standard care. Methods: Forty-five CAD patients undergoing CR in ambulatory conditions were divided into three groups: the NSDR group, which received eight sessions of NSDR relaxation as part of their rehabilitation; the VR group, which received eight sessions of VR therapy as part of their rehabilitation; and the control group, which received standard care including Schultz Autogenic Training (SAT). The outcomes were measured using the Hospital Anxiety and Depression Scale (HADS) and the Perception of Stress Questionnaire (PSQ). Results: Both NSDR relaxation and VR therapy were effective in reducing the HADS total score, anxiety levels, the PSQ general score, and emotional tension. No significant differences were observed between the two treatment approaches. However, SAT was found to be insufficient for effectively improving the mental state of cardiac patients. Conclusions: This study suggests that NSDR relaxation is an effective psychotherapeutic intervention in CR. NSDR and VR therapy showed similar benefits, offering promising alternatives to traditional methods. Integrating these techniques could enhance patient outcomes and adherence in CR. Further research is needed to refine these interventions and optimize their clinical application.