bluuebunny/crossref_metadata_2025 huggingface dataset:
Traditional Value Identity and Mental Health Correlation Among Chinese Adolescents
Authors: Ren Guofang , Yang Guanghui , Chen Junbo , Xu Qianru
Published: November 2024

This study explores the identity of traditional values among Chinese adolescents and its correlation with their mental health. A questionnaire survey, utilizing the Confucian Traditional Values Scale and the Secondary School Students’ Mental Health Scale, was conducted with 500 students from Grade 7 through the final year of college. Our results showed the following: (1) adolescents generally agree with traditional values; (2) there were no significant differences in overall agreement with traditional values among adolescents based on their gender, place of birth, class cadre status, only-child status, or academic major, though differences were observed in specific dimensions based on these variables; (3) traditional values identity varied across grade levels, with senior high school students showing notably higher identification than junior high school and college students, peaking in the second year of senior high school; and (4) there is a significant negative correlation between adolescents’ traditional values identity scores and their mental health scores, indicating that higher traditional values identity scores are associated with better mental health levels. These findings highlight the positive influence of traditional values on the development and well-being of Chinese adolescents, underscoring the importance of integrating these values into educational and developmental frameworks in China and other East Asian regions with similar cultural backgrounds.
Quantification of Carbon Emissions of Building Decoration Processes
Authors: Zhang Lianxiang , Wu Huanyu , Wang Xin , Wu Fugui , Ding Zhikun , Song Lei , Rong Xin , Liu Jing , Wen Xin , Zhong Ping
Published: November 2024

The continuous growth in building decoration activities has led to significant energy and material consumption, increasing carbon emissions in the construction sector. Existing literature frequently overlooks the carbon impact of building decorations. This study employs the life cycle assessment (LCA) method to quantify the carbon emissions associated with building decorations across five typic building types: residential, hospital, educational, sports cultural, and office buildings. Data were gathered using a mix of field investigations, document reviews, and semi-structured interviews, ensuring comprehensive coverage of all life cycle stages. The results reveal that carbon emission intensities of the studied building decorations ranged from 70.01 to 298.79 kg CO2 eq/m2, with the lowest emissions found in educational buildings and the highest in sports and cultural buildings. The decoration material production stage consistently emerges as the major contributor to emissions, accounting for over 50% of the life cycle of carbon emissions across all building types. The transportation stage also represents a significant share, contributing 18.6% to 24.5% across the building types. It also indicates that ceiling engineering as well as wall and column engineering are the primary carbon emission sources in terms of decoration activities. This study systematically compares the carbon emission characteristics of building decorations across multiple building types, addressing a gap that has been largely overlooked in the existing literature. It highlights the key sources of carbon emissions and proposes targeted mitigation strategies. The findings also suggest future research directions, including the application of innovative low-carbon materials, advanced construction technologies, and optimization of logistics. These insights lay a solid foundation for future low-carbon design and construction practices within the building sector.
Advances in the Management of Lung Cancer Brain Metastases
Authors: Hockemeyer Kathryn G. , Rusthoven Chad G. , Pike Luke R. G.
Published: November 2024

Lung cancer, both non-small cell and small cell, harbors a high propensity for spreading to the central nervous system. Radiation therapy remains the backbone of the management of brain metastases. Recent advances in stereotactic radiosurgery have expanded its indications and ongoing studies seek to elucidate optimal fractionation and coordination with systemic therapies, especially targeted inhibitors with intracranial efficacy. Efforts in whole-brain radiotherapy aim to preserve neurocognition and to investigate the need for prophylactic cranial irradiation. As novel combinatorial strategies are tested and prognostic/predictive biomarkers are identified and tested, the management of brain metastases in lung cancer will become increasingly personalized to optimally balance intracranial efficacy with preserving neurocognitive function and patient values.
Deep Learning in Endoscopic Ultrasound: A Breakthrough in Detecting Distal Cholangiocarcinoma
Authors: Orzan Rares Ilie , Santa Delia , Lorenzovici Noemi , Zareczky Thomas Andrei , Pojoga Cristina , Agoston Renata , Dulf Eva-Henrietta , Seicean Andrada
Published: November 2024

Introduction: Cholangiocarcinoma (CCA) is a highly lethal malignancy originating in the bile ducts, often diagnosed late with poor prognosis. Differentiating benign from malignant biliary tumors remains challenging, necessitating advanced diagnostic techniques. Objective: This study aims to enhance the diagnostic accuracy of endoscopic ultrasound (EUS) for distal cholangiocarcinoma (dCCA) using advanced convolutional neural networks (CCNs) for the classification and segmentation of EUS images, specifically targeting dCCAs, the pancreas, and the bile duct. Materials and Methods: In this retrospective study, EUS images from patients diagnosed with dCCA via biopsy and an EUS-identified bile duct tumor were evaluated. A custom CNN was developed for classification, trained on 156 EUS images. To enhance the model’s robustness, image augmentation techniques were applied, generating a total of 1248 images. For tumor and organ segmentation, the DeepLabv3+ network with ResNet50 architecture was utilized, employing Tversky loss to manage unbalanced classes. Performance evaluation included metrics such as accuracy, sensitivity, specificity, and Intersection over Union (IoU). These methods were implemented in collaboration with the ADAPTED Research Group at the Technical University of Cluj-Napoca. Results: The classification model achieved a high accuracy of 97.82%, with precision and specificity both at 100% and sensitivity at 94.44%. The segmentation models for the pancreas and bile duct demonstrated global accuracies of 84% and 90%, respectively, with robust IoU scores indicating good overlap between predicted and actual contours. The application performed better than the UNet model, particularly in generalization and boundary delineation. Conclusions: This study demonstrates the significant potential of AI in EUS imaging for dCCA, presenting a robust tool that enhances diagnostic accuracy and efficiency. The developed MATLAB application serves as a valuable aid for medical professionals, facilitating informed decision-making and improving patient outcomes in the diagnosis of cholangiocarcinoma and related pathologies.
Deep-Learning-Based Approach in Cancer-Region Assessment from HER2-SISH Breast Histopathology Whole Slide Images
Authors: Rehman Zaka Ur , Ahmad Fauzi Mohammad Faizal , Wan Ahmad Wan Siti Halimatul Munirah , Abas Fazly Salleh , Cheah Phaik-Leng , Chiew Seow-Fan , Looi Lai-Meng
Published: November 2024

Fluorescence in situ hybridization (FISH) is widely regarded as the gold standard for evaluating human epidermal growth factor receptor 2 (HER2) status in breast cancer; however, it poses challenges such as the need for specialized training and issues related to signal degradation from dye quenching. Silver-enhanced in situ hybridization (SISH) serves as an automated alternative, employing permanent staining suitable for bright-field microscopy. Determining HER2 status involves distinguishing between “Amplified” and “Non-Amplified” regions by assessing HER2 and centromere 17 (CEN17) signals in SISH-stained slides. This study is the first to leverage deep learning for classifying Normal, Amplified, and Non-Amplified regions within HER2-SISH whole slide images (WSIs), which are notably more complex to analyze compared to hematoxylin and eosin (H&E)-stained slides. Our proposed approach consists of a two-stage process: first, we evaluate deep-learning models on annotated image regions, and then we apply the most effective model to WSIs for regional identification and localization. Subsequently, pseudo-color maps representing each class are overlaid, and the WSIs are reconstructed with these mapped regions. Using a private dataset of HER2-SISH breast cancer slides digitized at 40× magnification, we achieved a patch-level classification accuracy of 99.9% and a generalization accuracy of 78.8% by applying transfer learning with a Vision Transformer (ViT) model. The robustness of the model was further evaluated through k-fold cross-validation, yielding an average performance accuracy of 98%, with metrics reported alongside 95% confidence intervals to ensure statistical reliability. This method shows significant promise for clinical applications, particularly in assessing HER2 expression status in HER2-SISH histopathology images. It provides an automated solution that can aid pathologists in efficiently identifying HER2-amplified regions, thus enhancing diagnostic outcomes for breast cancer treatment.
The Hippo Signaling Pathway, Reactive Oxygen Species Production, and Oxidative Stress: A Two-Way Traffic Regulation
Authors: Amanda Bella , Pragasta Rangga , Cakrasana Haris , Mustika Arifa , Faizah Zakiyatul , Oceandy Delvac
Published: November 2024

The Hippo signaling pathway is recognized for its significant role in cell differentiation, proliferation, survival, and tissue regeneration. Recently, the Hippo signaling pathway was also found to be associated with oxidative stress and reactive oxygen species (ROS) regulation, which are important in the regulation of cell survival. Studies indicate a correlation between components of the Hippo signaling pathway, including MST1, YAP, and TAZ, and the generation of ROS. On the other hand, ROS and oxidative stress can activate key components of the Hippo signaling pathway. For example, ROS production activates MST1, which subsequently phosphorylates FOXO3, leading to apoptotic cell death. ROS was also found to regulate YAP, in addition to MST1/2. Oxidative stress and ROS formation can impair lipids, proteins, and DNA, leading to many disorders, including aging, neurodegeneration, atherosclerosis, and diabetes. Consequently, understanding the interplay between the Hippo signaling pathway, ROS, and oxidative stress is crucial for developing future disease management strategies. This paper aimed to review the association between the Hippo signaling pathway, regulation of ROS production, and oxidative stress to provide beneficial information in understanding cell function and pathological processes.
Development of a Chemical Sensor Device for Monitoring Hazardous Gases Generated in the Semiconductor Manufacturing Process
Authors: Nguyen My Thi Ngoc , Lee Jun Seop
Published: November 2024

The semiconductor industry plays a crucial role in various fields but also contributes to environmental degradation. Throughout the semiconductor chip manufacturing process, hazardous gases are released at each stage, despite stringent treatment procedures. These gases can be categorized into four groups: acidic and alkaline gases, volatile organic compounds, flammable and corrosive gases, and greenhouse gases. To meet stricter emission standards, further advancements in gas sensor technology are essential. This review examines recent research on monitoring these gases, highlighting the capabilities and limitations of existing sensor technologies. Additionally, the paper discusses current challenges in gas sensing research and proposes future directions for improving technologies.
Serum Sodium Concentration During Arginine Vasopressin Infusion in Critically Ill Children
Authors: Muff Rafael , Gotta Verena , Jaeggi Vera , Schlapbach Luregn J. , Baumann Philipp
Published: November 2024

Background: Intravenous arginine vasopressin is increasingly used for the treatment of critically ill children. It bears the risk of hyponatraemia with potential severe long-term sequelae, but data on hyponatraemia as a side effect of continuous vasopressin infusion for paediatric intensive care patients is scarce. Methods: In this retrospective analysis performed at a tertiary care paediatric intensive care unit with 2000 annual admissions, patients were included if they were treated with intravenous vasopressin between 2016 and 2022. Baseline sodium concentrations, lowest sodium concentrations during arginine vasopressin treatment, and time to lowest sodium concentration (nadir) were derived. Results: In total, 170 patients with a median age of 4 months [interquartile range, IQR, 0–33] were included, 92.4% underwent surgery, and 28.8% died. Median arginine vasopressin dose rate was 0.027 IU/kg/h [0.019–0.036] and arginine vasopressin was started 3.2 [0–26] h after intensive care admission. Median arginine vasopressin application duration was 13.6 h [6.2–32.6]. Baseline sodium was 141 mmol/L [138–145], and lowest median sodium during arginine vasopressin infusion was 137 mmol/L [132–141] (nadir at 8.4 h [1.0–28.1] after arginine vasopressin start). Hyponatraemia (<135 mmol/L) occurred in 38.2% of patients during AVP treatment, and physicians administered a median of 10.2 mmol/kg/d [6.2–16.4] sodium during arginine vasopressin therapy. Conclusions: Under arginine vasopressin infusion, hyponatraemia was common, although high daily doses of sodium were administered to keep the serum values in physiologic ranges. This emphasises the need for close electrolyte monitoring and sodium substitution in children and adolescents under arginine vasopressin treatment to avoid hyponatraemia and related sequelae.
Health Disparities in Hospitalized Pediatric Patients with Autism Spectrum Disorder and COVID-19
Authors: Lee Janet , Ferretti Lisa , Nelson Camden , Nigam Priya , Zawacki Jessica , McCallion Philip
Published: November 2024

Background/Objectives: Pediatric patients with autism spectrum disorder (ASD) face unique challenges, especially amongst individuals from historically minoritized racial groups. ASD has also been associated with an increased mortality from COVID-19. This study aims to explore the differences in sociodemographic factors and health outcomes (as measured by length of stay) amongst hospitalized pediatric patients with COVID-19 infections and a diagnosis of ASD compared to individuals with a COVID-19 infection alone; Methods: We performed a retrospective cohort study examining pediatric patients (ages birth to 21) who were hospitalized with a diagnosis of ASD and COVID-19 compared to patients with a diagnosis of COVID-19 alone between January 2019 and June 2023 using Epic Systems Corporation’s Cosmos, a de-identified dataset aggregated from electronic health record data. We examined differences in demographic factors and length of stay (LOS) between groups by utilizing chi-square and Wilcoxon rank sum tests. Multiple logistic regression models were utilized to assess the association between length of stay and diagnosis; Results: A total of 21,708 distinct pediatric patients with a diagnosis of ASD and COVID-19 or COVID-19 alone were included in the analytical dataset. Patients with ASD and COVID-19, compared to patients with COVID-19 alone, had a higher proportion of individuals identifying as male and White. Patients with COVID-19 alone, compared to individuals with ASD and COVID-19, had higher proportions of individuals identifying as Black or African American. Higher proportions of individuals with ASD and COVID-19 had public insurance, compared to individuals with COVID-19 alone. Having a diagnosis of ASD and COVID, after controlling for covariates, was associated with higher odds of having a length of stay greater than the three days (cutoff value determined by the median LOS of three days) compared to having a diagnosis of COVID alone (aOR 1.19, 95% CI 1.04–1.35); Conclusions: Our study highlights the health disparities experienced during hospitalizations by pediatric patients with ASD and COVID-19. Further studies should address barriers and support health outcomes for pediatric patients with ASD.
Respiratory Physiotherapy Interventions in Paediatric Population with Atelectasis: A Systematic Review
Authors: Esteban-Gavilán Carlota Beatriz , Rico-Mena Patricia , Güeita-Rodríguez Javier , Navarro-López Víctor , Escudero-Romero Raúl
Published: November 2024

Objective: This systematic review aims to assess the effectiveness of respiratory physiotherapy techniques in oxygenation, chest X-ray findings, and lung auscultation in paediatric patients aged 0 to 18 years diagnosed with atelectasis. Methods: A comprehensive search was conducted in the PubMed, PEDro, Web of Science, and Cochrane Library databases. Results: Eight randomised clinical trials were included, involving 430 children ranging from 35 weeks of gestational age to 14 years. These trials evaluated various respiratory physiotherapy techniques and their effects on oxygenation and chest radiograph outcomes. The methodological quality of the studies ranged from acceptable to good, according to the PEDro scale. Conclusions: Recent evidence indicates that respiratory physiotherapy is effective and safe in the paediatric population with atelectasis. Both manual and instrumental techniques demonstrated efficacy, with instrumental techniques showing superior outcomes in many cases.
Coupling APS/SPS Techniques for Cu-TiO2 Antibacterial Coating Deposition: Application to Water Treatment
Authors: Youssef Laurène , Prorot Audrey , Gnodé Laurène , Verdieu Pierre Th’Madiou , Vardelle Armelle , Rat Vincent , Denoirjean Alain
Published: November 2024

Since the COVID-19 pandemic, efforts in the field of surface decontamination have been redoubled. Finding innovative self-cleaning devices has become a challenge, and several solutions have been proposed in the market in recent years. In this work, an optimized powder/suspension plasma spray process at atmospheric pressure, using a Triplex Pro 210TM torch, is implemented to produce Cu-TiO2 surface coatings on stainless steel. The purpose is to investigate the potential improvement of antibacterial efficacy by the reactive surface species generated from TiO2 photoactivity under irradiation. A water-based suspension, prepared with AnalaR NORMAPURTM TiO2, is used as a precursor to incorporate the photocatalyst into an antibacterial copper matrix. Surface antibacterial tests according to ASTM 2180 standards were performed, and experiments were performed in treated contaminated water. Sub-stoichiometric blue TiO2 coatings showed complete bacterial elimination after 90 min of visible light irradiation, and Cu-TiO2 surface coatings were even able to disinfect the surfaces under white light, making the application interesting for bacterial destruction under natural illumination. These materials are also intended for application in water treatment, including both pathogens and chemical micropollutants, which is a pressing issue facing many countries today.
Influence of ZrB2 Nanoparticles on Microstructure and Mechanical Properties of Ni-Co Coating
Authors: Wang Yijia , Li Binzhou , Zhang Dayue , Si Shanshan
Published: November 2024

To improve the service life of continuous casting crystallizer, the NiCo-ZrB2 coating was prepared using nanocomposite plating technology. Uniformly dispersed nano-ZrB2 particles significantly enhanced the hardness and wear resistance of the coating. Upon testing, the hardness of the coating exceeded 700 HV, with a friction coefficient below 0.2, which was superior to those of pure NiCo or other nanocomposite NiCo coatings reported previously. Microscopic analysis revealed that the addition of dispersants and ultrasonic vibration treatment had facilitated the homogeneous distribution of nano-ZrB2 within the matrix, thereby promoting the formation of numerous nano-twins. Due to dispersion strengthening, fine grain strengthening, and twinning strengthening, the wear behavior of the coating changed from fatigue wear to abrasive wear, and the wear volume was significantly reduced by 82%. The above findings could potentially extend the service life of the coating, reduce the cost of steel loss per ton, and have broad application prospects in other surface protection fields.
The Preparation of Biomass-Derived Carbon Dots and Its Application Prospect in the Field of Vascular Stent Coating
Authors: Duan Huimin , Wang Yanchao , Zhang Zhongna , Akram Ambreen , Chen Lan , Li Jingan
Published: November 2024

Biomass material serves as one of the most advantageous carbon sources for the synthesis of carbon dots (CDs) due to its abundant availability, cost-effectiveness, and environmental sustainability. Biomass-derived carbon dots (B-CDs), which are new zero-dimensional carbon nanomaterials, have presented broad application prospects in the medical field and have become a research focus. In recent years, the death rate caused by vascular diseases has been high, and interventional therapy is one of the important means to treat vascular stenosis. As a material with excellent biocompatibility and fluorescence properties, B-CDs have shown great potential in the field of vascular stents, and their unique properties provide new ideas and possibilities for improving the biocompatibility of vascular stents and realizing real-time tracer diagnosis. This paper reviews the preparation methods, modification techniques, and application prospects of B-CDs in the coating of vascular stents. It discusses current challenges and potential solutions while forecasting future development directions, thereby providing innovative insights and pathways for the research and development of a new generation of vascular stents.
Effect of Electrofriction Treatment on Microstructure, Corrosion Resistance and Wear Resistance of Cladding Coatings
Authors: Sagdoldina Zhuldyz , Baizhan Daryn , Sulyubayeva Laila , Berdimuratov Nurbol , Buitkenov Dastan , Bolatov Sanzhar
Published: November 2024

In recent years, the issue of increasing the wear resistance of the working bodies of agricultural machinery designed for cutting and breaking the soil has received special attention. The surface layers of working bodies of agricultural machinery during operation are subjected to intensive abrasive wear, which leads to rapid wear of equipment and a reduction in its service life. The induction cladding method using materials such as Sormait-1 is widely used to increase the wear resistance of tool working surfaces. However, after coating, additional heat treatment is required to improve the physical and mechanical properties of the material and increase its durability. In electrofriction technology (EFT) hardening, the surfaces of the parts are subjected to melting under the influence of electric arcs. In this work, three types of surface treatment of L53 steel have been investigated: induction cladding using Sormait-1, electrofriction treatment, and a combination of induction cladding followed by electrofriction treatment. The microstructure was analyzed using optical microscopy and scanning electron microscopy. Erosion and abrasion tests were carried out in accordance with ASTM G65 and ASTM G76-04 international standards to evaluate the wear resistance of the materials under mechanical stress. A dendritic structure was formed after the induction cladding of the Sormait-1 material, but subsequent electrofriction treatment resulted in a reduction of this dendritic structure, which contributed to an increase in the hardness of the material. However, the highest hardness, reaching 965 HV, was recorded after electrofriction treatment of L53 steel. This is explained by needle martensite in the structure, which is formed as a result of quenching. Further, the influence of structural characteristics and hardness on erosion and abrasion wear resistance was examined. The analysis showed that the material microstructure and hardness have a decisive influence on the improvement of wear resistance, especially under conditions of intensive erosion and abrasive friction.
A Secure Approach Out-of-Band for e-Bank with Visual Two-Factor Authorization Protocol
Authors: de Melo Laerte Peotta , Macedo Amaral Dino , de Oliveira Albuquerque Robson , de Sousa Júnior Rafael Timóteo , Sandoval Orozco Ana Lucila , García Villalba Luis Javier
Published: November 2024

The article presents an innovative approach for secure authentication in internet banking transactions, utilizing an Out-of-Band visual two-factor authorization protocol. With the increasing rise of cyber attacks and fraud, new security models are needed that ensure the integrity, authenticity, and confidentiality of financial transactions. The identified gap lies in the inability of traditional authentication methods, such as TANs and tokens, to provide security in untrusted terminals. The proposed solution is the Dynamic Authorization Protocol (DAP), which uses mobile devices to validate transactions through visual codes, such as QR codes. Each transaction is assigned a unique associated code, and the challenge must be responded to within 120 s. The customer initiates the transaction on a computer and independently validates it on their mobile device using an out-of-band channel to prevent attacks such as phishing and man-in-the-middle. The methodology involves implementing a prototype in Java ME for Android devices and a Java application server, creating a practical, low-computational-cost system, accessible for use across different operating systems and devices. The protocol was tested in real-world scenarios, focusing on ensuring transaction integrity and authenticity. The results show a successful implementation at Banco do Brasil, with 3.6 million active users, demonstrating the efficiency of the model over 12 years of use without significant vulnerabilities. The DAP protocol provides a robust and effective solution for securing banking transactions and can be extended to other authentication environments, such as payment terminals and point of sale devices.
Is Osteopathic Manipulative Treatment Clinically Superior to Sham or Placebo for Patients with Neck or Low-Back Pain? A Systematic Review with Meta-Analysis
Authors: Ceballos-Laita Luis , Jiménez-del-Barrio Sandra , Carrasco-Uribarren Andoni , Medrano-de-la-Fuente Ricardo , Robles-Pérez Román , Ernst Edzard
Published: November 2024

Objectives: The aim of this systematic review and meta-analysis was to compare whether osteopathic manipulative treatment (OMT) for somatic dysfunctions was more effective than sham or placebo interventions in improving pain intensity, disability, and quality of life for patients with neck pain (NP) or low-back pain (LBP). Methods: A systematic review and meta-analysis was carried out. Searches were conducted in PubMed, Physiotherapy Evidence Database, Cochrane Library, and Web of Science from inception to September 2024. Studies applying a pragmatic intervention based on the diagnosis of somatic dysfunctions in patients with NP or LBP were included. The methodological quality was assessed with the PEDro scale. The quantitative synthesis was performed using random-effect meta-analysis calculating the standardized mean difference (SMD) with RevMan 5.4. The certainty of evidence was evaluated using GRADEPro. Results: Nine studies were included in the qualitative synthesis, and most of them showed no superior effect of OMTs compared to sham or placebo in any clinical outcome. The quantitative synthesis reported no statistically significant differences for pain intensity (SMD = −0.15; −0.38, 0.08; seven studies; 1173 patients) or disability (SMD = −0.09; −0.25, 0.08; six studies; 1153 patients). The certainty of evidence was downgraded to moderate, low, or very low. Conclusions: The findings of this study reveal that OMT is not superior to sham or placebo for improving pain, disability, and quality of life in patients with NP or LBP.
Exploring Sex-Based Neuropsychological Outcomes in Pediatric Brain Cancer Survivors: A Pilot Study
Authors: Colliva Chiara , Rivi Veronica , Sarti Pierfrancesco , Cobelli Isabel , Blom Johanna M. C.
Published: November 2024

Background: The increasing survival rates among pediatric cancer patients underscore the critical need to understand the long-term psychosocial impacts of cancer treatments, such as cisplatin and carboplatin. While these treatments are lifesaving, they may pose risks to neurodevelopmental processes. Despite the substantial body of research highlighting cognitive impairments associated with cancer treatments, there remains a gap in understanding how these effects differ by sex. As sex differences could inform tailored interventions and support mechanisms for affected individuals, this pilot study aimed to examine the sex differences in neuropsychological outcomes in patients treated for brain cancer with cisplatin and/or carboplatin. Methods: Our study employed rigorous/structured neuropsychological assessments to evaluate executive functions in pediatric cancer survivors treated with cisplatin and/or carboplatin. We utilized the BRIEF and TOL tests to assess the key domains of executive function, including inhibitory control, cognitive flexibility, and problem-solving abilities. Additionally, psychosocial factors were evaluated using the Resiliency Scale to measure resilience and the PAT test to assess family psychosocial risk. Results: In our cohort of 17 patients, significant sex differences emerged, where males outperformed females in areas such as inhibitory control, impulse regulation, and strategic planning. Conclusions: These findings highlight the complexity of cognitive outcomes in pediatric cancer survivors. Understanding sex-specific differences is essential for developing tailored interventions that optimize cognitive and psychosocial outcomes. Future research should focus on larger cohorts and longitudinal studies to validate these findings and guide targeted interventions to improve survivorship outcomes.
Adjuvants for Drone-Based Aerial Chemical Applications to Mitigate Off-Target Drift
Authors: Kannan Narayanan , Martin Daniel , Srinivasan Rajani , Zhang Weiqiang
Published: November 2024

Off-target drift from aerial pesticide applications in croplands can be a major source of pesticide exposure to pollinators. Pesticide adjuvants (PAs) are added to pesticides but can be as toxic as pesticides’ active ingredients. Ongoing experiments have identified sodium alginate (SA) as a drift-reducing PA less toxic to honeybees. Hence, SA and fenugreek polymer (FP) have been tested as drift-reducing PAs for aerial applications using the Remotely Piloted Aerial Application System (RPAAS). Two spray experiments were carried out in the field: (i) water only (W) and (ii) water and adjuvant (WA). Droplet spectrum and on-target coverage were collected using a VisiSize P15 image analyzer and kromekote cards, respectively. The drift reduction potentials (DRPs) of the adjuvants were analyzed based on droplet size (diameters of 10%, 50%, and 90% volume) and the proportion of driftable volume with droplets < 200 µm. Compared to the W only, the W-A treatment produced larger droplets, suggesting the presence of DRP. There were 14.5%, 8.3% to 14.4%, and 2.3% to 7.7% driftable fines in the W, WA (SA), and WA (FP) treatments, respectively. The FP treatment improved the on-target coverage (3.0% to 3.1%) compared to water (2.7%). Our results indicate that SA and FP have the potential to mitigate off-target drift and protect pollinator health.
Macroeconomic Uncertainty and Sectoral Output in Nigeria
Authors: Oyadeyi Olajide O.
Published: November 2024

The paper examined the impact of macroeconomic uncertainty on the ten largest subsectors of the Nigerian economy using quarterly data from Q1 1981 to Q4 2023. The rationale behind selecting the subsectors is that these sectors constitute about 89 percent of the entire productive activities in the economy. To achieve the objectives, the paper created an index for macroeconomic uncertainty using exchange rate uncertainty, interest rate uncertainty, inflation uncertainty, and real gross domestic product (GDP) uncertainty to create this index. Furthermore, the paper explored the impacts of macroeconomic uncertainty and these individual economic uncertainty indexes on sector output. The study employed the novel dynamic autoregressive distributed lag (novel dynamic ARDL) technique to estimate the results and used the canonical cointegrating regression (CCR) and fully modified ordinary least square (FMOLS) techniques as robustness on the main findings. The findings demonstrated that during periods of recession, macroeconomic uncertainty tends to heighten or reach its peak in Nigeria. Furthermore, the paper showed that the sectors react homogenously to macroeconomic uncertainty. In addition, the impulse response results from the novel dynamic ARDL estimation show that macroeconomic uncertainty can predict robust negative movements in sector output for Nigeria. Indeed, these findings are insightful as they show the importance of macroeconomic uncertainties as key drivers of sector output in Nigeria. The paper argues that the policy authorities should improve their efforts to reduce macroeconomic uncertainty and foster a stable real sector/sectoral output to enhance the macroeconomic environment for Nigeria to aim for higher levels of growth.
The Role of Spatial Ability in Academic Success: The Impact of the Integrated Hybrid Training Program in Architecture and Engineering Higher Education
Authors: Porat Ronen , Ceobanu Ciprian
Published: November 2024

Spatial ability (SA) is a critical cognitive skill across various disciplines, particularly in architecture and engineering. This research, comprising two main studies, investigates the relationship between SA and academic performance among first-year students. The first study examines the impact of the targeted Integrated Hybrid Training (IHT) SA intervention on the achievements of two main groups: engineering (electrical, software, and chemical) students and architecture students. The results indicate that, while the intervention significantly improved SA, the impact on academic performance varied. Architecture students, whose curriculum relies heavily on spatial reasoning, showed significant gains in courses such as studio design, with higher SA scores correlating with improved grades. Engineering students exhibited SA improvement without corresponding gains in the first-year core courses like calculus and physics. The second study focuses on architecture students who did not receive the intervention, revealing a strong positive correlation between inherent SA and success in architecture-specific courses. Correlation coefficients (r) ranged from 0.46 to 0.67, with adjusted p-values between 0.007 and 0.024, underscoring SA’s importance in architecture. These findings suggest that integrating SA training into architectural education can enhance academic performance, while disciplines might benefit from specialized SA training introduced or expanded in later years. This research contributes to educational theory by demonstrating SA’s impact across disciplines and supports the development of customized SA training programs. Future studies should explore long-term benefits, advanced SA training technologies, and individual differences in response to spatial interventions, providing insights for curriculum development in spatially demanding fields.
Hydropower Station Status Prediction Using RNN and LSTM Algorithms for Fault Detection
Authors: Al-Hardanee Omar Farhan , Demirel Hüseyin
Published: November 2024

In 2019, more than 16% of the globe’s total production of electricity was provided by hydroelectric power plants. The core of a typical hydroelectric power plant is the turbine. Turbines are subjected to high levels of pressure, vibration, high temperatures, and air gaps as water passes through them. Turbine blades weighing several tons break due to this surge, a tragic accident because of the massive damage they cause. This research aims to develop predictive models to accurately predict the status of hydroelectric power plants based on real stored data for all factors affecting the status of these plants. The importance of having a typical predictive model for the future status of these plants lies in avoiding turbine blade breakage and catastrophic accidents in power plants and the resulting damages, increasing the life of these plants, avoiding sudden shutdowns, and ensuring stability in the generation of electrical energy. In this study, artificial neural network algorithms (RNN and LSTM) are used to predict the condition of the hydropower station, identify the fault before it occurs, and avoid it. After testing, the LSTM algorithm achieved the greatest results with regard to the highest accuracy and least error. According to the findings, the LSTM model attained an accuracy of 99.55%, a mean square error (MSE) of 0.0072, and a mean absolute error (MAE) of 0.0053.
Exploring the Application of Large Language Models Based AI Agents in Leakage Detection of Natural Gas Valve Chambers
Authors: Wei Qian , Sun Hongjun , Xu Yin , Pang Zisheng , Gao Feixiang
Published: November 2024

Leakage problems occur from time to time due to the large number of equipment and complex processes during oil and gas production and transportation. The traditional detection methods highly depend on manpower with large workload and are prone to missed and false alarms, which seriously affects the efficiency and safety of oil and gas production and transportation. With the continuous improvement of information technology and the rapid advancement of artificial intelligence (AI), the research on leakage detection technology based on AI methods has attracted more and more attention. This paper discusses the application scenarios of an AI agent based on the recently emerged large language model (LLM) technology in oil and gas production leakage detection: (1) Compared with the traditional leakage detection methods, this paper innovatively employs a combination of AI-based diagnostics and infrared temperature measurement technologies to develop a specialized small model for oil and gas leakage detection, which has been proven to significantly improve the accuracy of detecting industrial venting events in natural gas valve chambers; (2) By employing retrieval-augmented generation (RAG) technology, a knowledge vector library is constructed, utilizing a series of leakage-related documents, assisting the LLM to carry out knowledge questioning and inference. Compared with the traditional SimBERT, the accuracy can be improved by about 15% in the Q&A search ability test. The correct rate is about 70% higher than the SimBERT in the Chinese complex reasoning quiz. Also, it can still remain stable under high load conditions, with the interruption rate of retrieval closing to zero. (3) By combining the specialized small model and the knowledge Q&A tool, the natural gas valve chambers’ leakage detection AI agent based on the open-source LLM model was designed and developed, which preliminarily achieved the leakage detection based on the specialized small model, and the automatic processing of the retrieval reasoning process based on the knowledge Q&A tool and the intelligent generation of corresponding leakage disposal scheme. The effectiveness of the method has been verified by actual project data. This article conducts preliminary explorations into the in-depth applications of AI agents based on LLMs in the oil and gas energy industry, demonstrating certain positive outcomes.
Comparative Life Cycle Assessment of Landfilling with Sustainable Waste Management Methods for Municipal Solid Wastes
Authors: Ouedraogo Angelika Sita , Kumar Ajay , Frazier Robert , Sallam Khaled A.
Published: November 2024

Municipal solid waste (MSW) generation continues to increase exponentially, leading to the need for better disposal methods. Approximately 50% of the MSW is landfilled in the United States (US). Landfilling is known for its negative effects on the environment and human health. The objective of this study was to conduct a life cycle assessment (LCA) of some of the most common waste treatment methods and propose an alternative and environmentally friendly integrated waste management method (IWM). The LCA was conducted using OpenLCA. Replacing landfilling, incineration, and composting with recycling, gasification, and anaerobic digestion (IWM) reduced the global warming potential from 899 kg CO2 eq to −14.6 kg CO2 eq. The same trend was observed for acidification (from 0.21 kg SO2 eq to −1.1 kg SO2 eq), ecotoxicity (from 2363.8 CTUe to 1.22 CTUe), eutrophication (from 0.5 kg N eq to 0.3 kg N eq), smog formation (from 4.4 kg O3 eq to 1.85 kg O3 eq), ozone depletion (from 2.1 × 10−5 kg CFC-11 eq to 0 kg CFC-11 eq), respiratory effects (from 2.8 × 10−3 kg PM2.5 eq to −7.25 × 10−3 kg PM2.5 eq), cancer (from 2 × 10−5 CTUh to 1.2 × 10−7 CTUh), and non-cancer effects (from 6 × 10−5 to 1.4 × 10−5 CTUh). The results show that an integrated waste management approach with recycling, gasification, and anaerobic digestion can dramatically reduce the environmental and health impacts of municipal solid waste disposal. Policy reforms, technical innovation, economic investment, and social engagement are needed to change waste management paradigm.
Spatiotemporal Evolution, Driving Mechanisms, and Zoning Optimization Pathways of Ecosystem Health in China
Authors: Zhu Weihan , Huang Jixing , Yang Shuqi , Liu Wanyi , Dai Yongwu , Huang Guoxing , Lin Jinhuang
Published: November 2024

The health status of ecosystems is an important prerequisite for ensuring regional ecological security. Exploring the spatiotemporal patterns, driving mechanisms, and zoning regulation pathways of ecosystem health is of great significance for achieving co-ordinated and sustainable regional ecosystems. This study uses China as a case area and applies the InVEST model to measure integrated ecosystem services and incorporates it into an evaluation framework for ecosystem health based on the “Vigor-Organization-Resilience-Ecosystem Services” (VORS) model. It reveals the spatiotemporal evolution characteristics of ecosystem health in China from 2000 to 2020 and employs the geodetector and spatiotemporal geographically weighted regression model to analyze the main influencing factors and spatial differentiation characteristics, thereby exploring ecological management zoning and optimization pathways. The study results show that (1) during the study period, the overall ecosystem health level in China showed a declining trend, dropping from 0.397 in 2000 to 0.377 in 2020. (2) Overall, China’s ecosystem health exhibits strong spatial positive correlation and spatial clustering characteristics, with a basic pattern of lower values in the northwest and higher values in the southeast. (3) Vegetation coverage, population density, density of road network, and per capita GDP are the main influencing factors of ecosystem health in China. (4) China is divided into five types of Ecological Management Zones: Ecological Conservation Zone, Ecological Enhancement Zone, Ecological Buffer Zone, Ecological Remediation Zone, and Ecological Reshaping Zone, with differentiated strategies proposed for optimizing ecosystem health in each zone.
Three Ophiostomatalean Fungi Associated with Bark Beetles from Pinus thunbergii Infested by Bursaphelenchus xylophilus in Laoshan Mountain (Shandong, China)
Authors: Song Xiuyue , Tie Yingjie , Wang Zheng , Kong Lingguang , Liu Huixiang , Lu Quan
Published: November 2024

Pine wilt disease (PWD) is a devastating disease that occurs worldwide and affects conifers infested by the pine wood nematode (PWN, Bursaphelenchus xylophilus). PWD has caused serious economic and ecological losses in China. The mechanism of disease outbreak is complex, with the associated fungi, specifically ophiostomatoid fungi, thought to play an essential role. However, few ophiostomatoid fungal associates of PWD have been accurately identified. In the present study, we isolated fungi from bark beetles collected from Pinus thunbergii infested by the pine wood nematode on Laoshan Mountain, Shandong province. Three ophiostomatalean fungi were identified and assigned to Graphilbum and Ophiostoma based on phylogenetic analyses and comparison of morphological and cultural features, namely Gra. laoshanense sp. nov., Gra. translucens, and O. ips. This study increases the understanding of the diversity of ophiostomatoid fungi associated with PWD and provides resources for parsing this complex disease.
Polysaccharide Functionality in Wine-like Model Systems with Oat and Egg White Model Proteins
Authors: Burken Olivia , Sommer Stephan
Published: November 2024

Interactions between wine proteins and polysaccharides have the capacity to regulate the stability, shelf-life, and turbidity of red wines. Understanding these macromolecular interactions helps with maintaining stability and reproducing high quality wines. Model polysaccharides (carboxymethyl cellulose, mannoproteins, and fruit pectin) and model proteins (egg white and oat protein) were selected to assess protein–polysaccharide interactions within a model wine solution. The wine-like solution was created to simulate the correct pH, ethanol strength, and pigment content. Any interactions with polymeric pigments—anthocyanins and tannins—can also be investigated in this matrix. To analyze the aggregative potential of the macromolecules, particle size and Zeta-potential (ζ-potential) measurements were recorded for the samples with increasingly complex compositions. Carboxymethyl cellulose was found to increase particle sizes, likely binding more than proteins, but also improved the overall stability of the solution. Fruit pectin and mannoprotein were effective at causing precipitation while not removing the color of the model wine. The use of mannoprotein ensued in overall smaller particles for both suspended aggregate and precipitate sizes, indicating higher selectivity. Fruit pectin increased precipitate sizes and decreased suspended aggregate sizes. This study implements model proteins to evaluate complex macromolecular interactions using measurements of ζ-potential and particle size.