bluuebunny/crossref_metadata_2025 huggingface dataset:
Screening and Site Adaptability Evaluation of Qi-Nan Clones (Aquilaria sinensis) in Southern China
Authors: Hu Houzhen , Xu Daping , Li Xiaofei , Fang Xiaoying , Cui Zhiyi , Liu Xiaojin , Hao Jian , Su Yu , Hong Zhou
Published: October 2024

In recent years, plantations of Aquilaria sinensis in China have been dominated by Qi-nan, yet there remains limited research on the growth evaluation and breeding of these clones. In this study, a multi-point joint variance analysis, an additive main effect and multiplicative interaction (AMMI) model, a weighted average of absolute scores (WAASB) stability index, and a genotype main effect plus a genotype-by-environment interaction (GGE) biplot were used to comprehensively analyze the yield, stability, and suitable environment of 25 3-year-old Qi-Nan clones from five sites in southern China. The results showed that all the growth traits exhibited significant differences in the clones, test sites, and interactions between the clones and test sites. The phenotypic variation coefficient (PCV) and genetic variation coefficient (GCV) of the clones’ growth traits at the different sites ranged from 16.56% to 32.09% and 5.24% to 27.06%, respectively, showing moderate variation. The medium–high repeatability (R) of tree height and ground diameter ranged from 0.50 to 0.96 and 0.69 to 0.98, respectively. Among the clones, Clones G04, G05, G10, G11 and G13 showed good growth performance and could be good candidates for breeding. Environmental effects were found to be the primary source of variation, with temperature and light primarily affecting growth, while rainfall influenced survival and preservation rates. Yangjiang (YJ) was found to be the most suitable experimental site for screening high-yield and stable clones across the different sites, whereas the tree height and ground diameter at the Chengmai (CM) site were significantly higher than at the other sites, and the Pingxiang (PX) and Zhangzhou (ZZ) sites showed poor growth performance. The findings suggest that Qi-nan clones are suitable for planting in southern China. There were also abundant genetic variations in germplasm resources for the Qi-nan clones. The five selected clones could be suitable for extensive planting. Therefore, large-scale testing is necessary for determining genetic improvements in Qi-nan clones, which will be conducive to the precise localization of their promotion areas.
Impact of Extreme Drought on Vegetation Greenness in Poyang Lake Wetland
Authors: Lai Xiahua , Zeng Han , Zhao Xiaomin , Shao Yiwen , Guo Xi
Published: October 2024

The Poyang Lake Wetland, an internationally significant ecosystem, frequently experiences drought during the flood season. However, the total impact of extreme drought on wetland vegetation remains poorly understood. This study determined the standardised precipitation evapotranspiration index (SPEI) and analysed drought trends within the Poyang Lake Basin. Additionally, spatiotemporal variations in wetland vegetation under drought conditions were examined by analysing the mean normalised difference vegetation index (NDVI) values and categorising NDVI classifications. The key factors affecting wetland vegetation and its respective thresholds were determined. The Poyang Lake Basin has experienced increasing aridity over the past 3 years. In response to this trend, the wetland vegetation area in Poyang Lake expanded, whereas vegetation greenness declined. Notably, in the year following an extreme drought, Poyang Lake’s vegetation greenness was lower than that during the same period in previous years. Regardless, the correlation analysis showed no significant relationship between the SPEI values and the wetland vegetation greenness; however, water level changes significantly impacted the wetland vegetation, with a correlation coefficient of −0.89 (p < 0.001). A critical water level of 14 m was identified as the threshold at which sudden changes in the mean NDVI were observed. This research offers valuable insights into hydrological management strategies to protect Poyang Lake Wetland’s vegetation under drought conditions. Future studies should enhance the differentiation of drought tolerance among different wetland plant species, thereby achieving differentiated hydrological management.
Forest Restoration Thinning Has Minimal Impacts on Surface Soil Carbon in a Second-Growth Temperate Rainforest
Authors: Quick Steven A. , Fischer Dylan G. , Case Michael J.
Published: October 2024

Forest restoration thinning may accelerate the development of structural complexity toward old-growth conditions faster than a natural forest, yet associated changes in forest carbon (C) are poorly understood. Old-growth forests are characterized by high levels of sequestered C in aboveground biomass and soil C pools, yet active management has well-recognized negative impacts on stored C. Effects of forest restoration thinning on forest C can be determined using longitudinal measurements and modeling based on stand conditions and tree growth. At Ellsworth Creek Preserve in Southwest Washington, forest restoration efforts in a second-growth temperate rainforest have been monitored using permanent plots since 2007. Here, we compare repeat measurements from 2020, modeled forest C, and measurements of O-horizon C pools from 2022 to determine C impacts of silvicultural treatments for old-growth restoration. We found good general agreement between empirical measurements and models of forest C using the Forest Vegetation Simulator (FVS). However, treatment alone was not a strong indicator for C conditions; rather, forest age and age–treatment interactions better predicted soil C responses to restoration treatments. These data may indicate that “light” forest restoration thinning can accelerate old-growth development with minimal effects on soil carbon—a win-win conservation strategy for old-growth forests and the climate.
Decoding Urban Intelligence: Clustering and Feature Importance in Smart Cities
Authors: Barbierato Enrico , Gatti Alice
Published: October 2024

The rapid urbanization trend underscores the need for effective management of city resources and services, making the concept of smart cities increasingly important. This study leverages the IMD Smart City Index (SCI) dataset to analyze and rank smart cities worldwide. Our research has a dual objective: first, we aim to apply a set of unsupervised learning models to cluster cities based on their smartness indices. Second, we aim to employ supervised learning models such as random forest, support vector machines (SVMs), and others to determine the importance of various features that contribute to a city’s smartness. Our findings reveal that while smart living was the most critical factor, with an importance of 0.259014. Smart mobility and smart environment also played significant roles, with the importance of 0.170147 and 0.163159, respectively, in determining a city’s smartness. While the clustering provides insights into the similarities and groupings among cities, the feature importance analysis elucidates the critical factors that drive these classifications. The integration of these two approaches aims to demonstrate that understanding the similarities between smart cities is of limited utility without a clear comprehension of the importance of the underlying features. This holistic approach provides a comprehensive understanding of what makes a city ’smart’ and offers a robust framework for policymakers to enhance urban living standards.
Stance Detection in the Context of Fake News—A New Approach
Authors: Alsmadi Izzat , Alazzam Iyad , Al-Ramahi Mohammad , Zarour Mohammad
Published: October 2024

Online social networks (OSNs) are inundated with an enormous daily influx of news shared by users worldwide. Information can originate from any OSN user and quickly spread, making the task of fact-checking news both time-consuming and resource-intensive. To address this challenge, researchers are exploring machine learning techniques to automate fake news detection. This paper specifically focuses on detecting the stance of content producers—whether they support or oppose the subject of the content. Our study aims to develop and evaluate advanced text-mining models that leverage pre-trained language models enhanced with meta features derived from headlines and article bodies. We sought to determine whether incorporating the cosine distance feature could improve model prediction accuracy. After analyzing and assessing several previous competition entries, we identified three key tasks for achieving high accuracy: (1) a multi-stage approach that integrates classical and neural network classifiers, (2) the extraction of additional text-based meta features from headline and article body columns, and (3) the utilization of recent pre-trained embeddings and transformer models.
Large Language Models Meet Next-Generation Networking Technologies: A Review
Authors: Hang Ching-Nam , Yu Pei-Duo , Morabito Roberto , Tan Chee-Wei
Published: October 2024

The evolution of network technologies has significantly transformed global communication, information sharing, and connectivity. Traditional networks, relying on static configurations and manual interventions, face substantial challenges such as complex management, inefficiency, and susceptibility to human error. The rise of artificial intelligence (AI) has begun to address these issues by automating tasks like network configuration, traffic optimization, and security enhancements. Despite their potential, integrating AI models in network engineering encounters practical obstacles including complex configurations, heterogeneous infrastructure, unstructured data, and dynamic environments. Generative AI, particularly large language models (LLMs), represents a promising advancement in AI, with capabilities extending to natural language processing tasks like translation, summarization, and sentiment analysis. This paper aims to provide a comprehensive review exploring the transformative role of LLMs in modern network engineering. In particular, it addresses gaps in the existing literature by focusing on LLM applications in network design and planning, implementation, analytics, and management. It also discusses current research efforts, challenges, and future opportunities, aiming to provide a comprehensive guide for networking professionals and researchers. The main goal is to facilitate the adoption and advancement of AI and LLMs in networking, promoting more efficient, resilient, and intelligent network systems.
A Solution to Dynamic Weapon Assignment Problem Based on Game Theory for Naval Platforms
Authors: Akbel Oğuzkan , Kalaycıoğlu Aykut
Published: October 2024

Weapon target assignment is a critical challenge in military contexts. Traditionally, commanding officers manually decide weapon assignments, but the problem’s complexity has grown over time. To address this, automated systems have been introduced. These systems fall into two categories, which are static (time-independent) and dynamic (considering changes over time). Static systems solve the problem for a single time step without considering temporal changes. Dynamic systems incorporate time as a variable, adapting to evolving scenarios. Two main approaches exist, which are asset-based and target-based. Asset-based approach maximizes the survival probability of assets, which is our focus in this study. We propose a solution using game theory that spans the entire area and all time frames. We employ game theory, treating continuous functions of time as utility functions for vessels. Continuous probability-to-kill values for weapons are defined across the area. Threat trajectories yield continuous kill probabilities for the weapons, translating to vessel utility. To avoid inefficiencies, we align individual vessel utility with global utility. The Nash Equilibrium provides the optimal weapon assignment strategy. Our study uses a naval environment for analysis. In summary, our research leverages game theory to dynamically assign weapons to naval vessels, aiming to maximize asset survival.
Novel Variant in ANO5 Muscular Dystrophy: Identification by Whole Genome Sequencing and Quad Analysis
Authors: Ćuk Mario , Unal Busra , Lovrenčić Luka , Walker McKenzie , Hayes Connor P. , Abraamyan Feruza , Prutki Maja , Krakar Goran , Srkoč-Majčica Lidija , Ghazani Arezou A.
Published: October 2024

Background: The phenotypic spectrum of ANO5 muscle disease ranges widely from elevated creatine kinase (CK) levels in the serum of asymptomatic individuals to progressive muscular dystrophy. Due to overlapping clinical features among muscular dystrophies, the diagnosis of ANO5 muscle disease is established by molecular genetic tests. Early diagnosis is crucial for the clinical management of symptoms and to mitigate cardiac and musculoskeletal complications. Methods: Quad-joint analysis was performed on whole genome sequencing (WGS) data obtained from an 18-year-old female with mild myalgia and elevated CK and her unaffected parents and sister. The phenotype-driven analysis was performed to prioritize genomic alterations related to the phenotype. The zygosity-based analysis investigated compound heterozygous and de novo status for all variants. Results: The quad-joint WGS analysis revealed a novel pathogenic heterozygous variant, ANO5:c.1770_1773del (p.Phe593Metfs*15), that was paternally inherited. A second and known pathogenic heterozygous variant, ANO5:c.148C>T (p.Arg50*), was also present that was maternally inherited. The genome finding led to the diagnosis of autosomal recessive ANO5 muscle disease and an early personalized clinical management for the patient regarding her cardiac and musculoskeletal health. Conclusions: This is the first report of the ANO5:c.1770_1773del variant in the literature. This report highlights the spectrum of ANO5 muscle disease and describes the role of quad-joint WGS in the early diagnosis and preventive clinical management of ANO5 muscle disease.
Advancing Geomatics: Innovation, Inclusivity, and Global Perspectives
Authors: Claramunt Christophe
Published: October 2024

In the past few years since its launch, Geomatics has addressed various areas that form the core of the interdisciplinary field of geomatics [...]
European Nurses’ Burnout before and during the COVID-19 Pandemic and Its Impact on Patient Safety: A Scoping Review
Authors: Mogomotsi Goitseone , Creese Jennifer
Published: October 2024

Health systems around the world continue to experience healthcare workforce shortages, including shortages of nurses. This results in staff experiencing prolonged shifts and other stressors, which are linked to burnout, yet burned-out staff are then entrusted with the provision of patient care, despite healthcare facilities being regarded as safety-critical areas. It is assumed that the situation may have been worsened by the COVID-19 pandemic. This scoping review aims to identify the prevalence of burnout among nurses in Europe before and during the pandemic, the factors associated with this burnout, and its impact on patient safety. A literature search was conducted in the MEDLINE database; search terms included Nurse and Burnout and Patient Safety and their synonyms. The search limits used were English language, 2013 to 2023 publication years, original published research only (excluding review papers, dissertations, and unpublished reports), and studies conducted in European countries. A total of 16 papers were included for analysis: four indicated burnout levels of study participants, while 11 gave scores for individual burnout symptoms. Almost all studies indicated factors that were linked to burnout or individual dimensions of burnout. A few papers touched on the implications of these factors on patient safety. The review findings concluded that the few studies providing burnout levels on study participants could not give a clear picture of the burnout prevalence among nurses across Europe, either in general, before, or during the pandemic; therefore, this objective was not achieved and more research is required to establish this. Several factors thematically classified as sociodemographic, personal, organizational, and patient/client-related were linked to burnout. However, there were some contradictions in sociodemographic factors. Low personal accomplishment was the most common symptom of burnout before the pandemic, followed by emotional exhaustion and lastly depersonalization. Emotional exhaustion took the lead during the COVID-19 pandemic, followed by low personal accomplishment, and depersonalization remained the least common. More research is needed to establish the relationship between burnout and these factors.
Social Work Practice in United Arab Emirates (UAE) Schools during and after the COVID-19 Pandemic: A Qualitative Study
Authors: Albrithen Abdulaziz , Alfalasi Shamma
Published: October 2024

Besides their educational mission, public schools ground and support the health and psychological, emotional, and social development of students. The educational system is special because it combines multiple integrated responsibilities and duties that transcend the scope of any other social welfare program. Social workers are crucial constituents of educational systems and are expected to attend to the well-being of students while ensuring the effective performance of the educational system. Given such rigorous demands, this study assesses and compares the actual functions undertaken by social workers in schools in the United Arab Emirates during and after the COVID-19 pandemic. In so doing, it aims to help improve educational systems worldwide. The nuanced results of this study will better elucidate the crucial capabilities of social workers in the dynamic educational system and illuminate the challenges they confront during emergencies.
Domiciliary Carers’ Perspectives on Alcohol Use by Older Adults in Their Care: A Systematic Review and Thematic Synthesis of Qualitative Studies
Authors: Haighton Catherine , Steer Mel , Nichol Beth
Published: October 2024

As global populations continue to age, alcohol consumption rises, and we strive to age in place, it is important to have an up-to-date understanding of domiciliary carers’ perspectives on older adults’ alcohol use in their care. Therefore, a systematic review and thematic synthesis of qualitative studies of the unique challenges faced by domiciliary care workers in front line roles regarding older adults’ alcohol use was conducted (PROSPERO registration number: CRD42024516660). Eight databases were searched on 22 February 2024 for qualitative studies focusing on older adults’ (defined as aged 50 or over) alcohol consumption and domiciliary care. The Critical Appraisal Skills Programme checklist was utilised for quality appraisal. Twenty articles reporting 14 unique studies of mainly medium to low quality were included. Three overarching themes (and associated subthemes) were identified as follows: identification (alcohol problems are common, no assessment for alcohol problems, and additional overt signs of excessive alcohol use), management (to buy or not to buy that is the question, balancing rights and risks, monitor and report but do not intervene, maintaining the vicious circle, home as a barrier to accessing support and services, and more support needed from healthcare professionals), and training (lack of alcohol education). Domiciliary carers are well placed to make every contact count to target alcohol consumption but would benefit from support and resources for alcohol consumption identification and management. Clear guidance on how to manage alcohol consumption to harmoniously balance rights and risks is crucial, particularly when caring for older adults with cognitive difficulties.
Lessons Learned from the Experiences of Domestic Violence Service Providers in Times of Crisis: Insights from a Central Asian Country
Authors: Karabay Akmaral , Akhmetova Saltanat , Durrani Naureen
Published: October 2024

Domestic violence is a widespread problem in both stable and crisis contexts. During crisis-driven periods, such as environmental, economic, political, and health emergencies, existing gender inequalities are exacerbated, and the risks of violence against women (VAW) are amplified. This qualitative study explores the experiences of professionals working in VAW organisations in a Central Asian country during the COVID-19 pandemic. By interviewing 45 professionals from social care organisations in Kazakhstan, this study aims to understand the impact of COVID-19 on the ability of VAW organisations to assist victims of domestic violence and comprehend the adjustments they made to support victims. The findings shed light on the challenges faced by VAW organisations, including reduced capacity, increased service demand, the shift to remote services, and funding cuts. The study highlights the critical role of these organisations in crises and urges the consideration of lessons learned to prevent VAW in emergency and non-emergency situations. In the Central Asian region, where domestic violence is persistent, this research offers valuable insights for interventions during and after crises. The study offers effective strategies for achieving Sustainable Development Goal 5.2, which aims to eliminate violence against women, and SDG 3.8, ensuring access to healthcare, psychological support, and safe environments.
Where and Why Travelers Visit? Classifying Coastal Tourism Activities Using Geotagged Image Content from Social Media Data
Authors: Kim Gang Sun , Kim Choong-Ki , Lee Woo-Kyun
Published: October 2024

Accurate information regarding the size, activity, and distribution of coastal tourists is essential for the effective management and planning of coastal tourism. In this study, geotagged photos uploaded to social network services were classified to identify coastal tourism activities. These activities were linked with spatial-scale data on tourist numbers estimated from social media data. To classify the activities, which included recreation, appreciation, education, and other activities, an image-supervised classification model was trained using 12,229 images, and the test accuracy was found to be 0.7244. On the Flickr platform, 43% of the image data located in the coastal land of South Korea are other activities, 39% are appreciation activities, and 18% are recreation and education activities. Other activities are mainly located in urban areas with a high population density and are spatially concentrated, while appreciation activities are mainly located in the natural environment and tend to be spatially spread out. Data on tourist activity categorization through content classification, combined with traditional tourist volume estimates, can help us understand previously overlooked information and context about a space.
Traumatic Brain Injury Structure Detection Using Advanced Wavelet Transformation Fusion Algorithm with Proposed CNN-ViT
Authors: Abdullah  , Siddique Ansar , Fatima Zulaikha , Shaukat Kamran
Published: October 2024

Detecting Traumatic Brain Injuries (TBI) through imaging remains challenging due to limited sensitivity in current methods. This study addresses the gap by proposing a novel approach integrating deep-learning algorithms and advanced image-fusion techniques to enhance detection accuracy. The method combines contextual and visual models to effectively assess injury status. Using a dataset of repeat mild TBI (mTBI) cases, we compared various image-fusion algorithms: PCA (89.5%), SWT (89.69%), DCT (89.08%), HIS (83.3%), and averaging (80.99%). Our proposed hybrid model achieved a significantly higher accuracy of 98.78%, demonstrating superior performance. Metrics including Dice coefficient (98%), sensitivity (97%), and specificity (98%) verified that the strategy is efficient in improving image quality and feature extraction. Additional validations with “entropy”, “average pixel intensity”, “standard deviation”, “correlation coefficient”, and “edge similarity measure” confirmed the robustness of the fused images. The hybrid CNN-ViT model, integrating curvelet transform features, was trained and validated on a comprehensive dataset of 24 types of brain injuries. The overall accuracy was 99.8%, with precision, recall, and F1-score of 99.8%. The “average PSNR” was 39.0 dB, “SSIM” was 0.99, and MI was 1.0. Cross-validation across five folds proved the model’s “dependability” and “generalizability”. In conclusion, this study introduces a promising method for TBI detection, leveraging advanced image-fusion and deep-learning techniques, significantly enhancing medical imaging and diagnostic capabilities for brain injuries.
A Novel Method Based on the Fuzzy Entropy Measure to Optimize the Fuzziness in Trapezoidal Strong Fuzzy Partitions
Authors: Cardone Barbara , Di Martino Ferdinando
Published: October 2024

Analyzing the uncertainty of outcomes based on estimates of the data’s membership degrees to fuzzy sets is essential for making decisions. These fuzzy sets are often designated by experts as strong fuzzy partitions of the data domain with trapezoidal fuzzy numbers. Some indices of the fuzzy set’s fuzziness provide an assessment of the degree of uncertainty of the results. It is feasible to bring the fuzzy sets’ fuzziness below a tolerable level by suitably redefining the strong fuzzy partition. Significant differences in the original fuzzy partition, however, result in disparities concerning the decision maker’s approximative reasoning and the interpretability of the results. In light of this, we provide in this study a technique applied to trapezoidal strong fuzzy partitions that, while not appreciably altering the original fuzzy partition, reduces the fuzziness of its fuzzy sets. The fuzziness of the fuzzy sets is assessed using the De Luca and Termini fuzzy entropy. An iterative process is then executed, with the aim of modifying the cores of the trapezoidal fuzzy partitions to decrease their fuzziness. This technique is tested on datasets containing average daily temperatures measured in various cities. The findings demonstrate that this approach strikes a great balance between the goal of lessening the fuzziness of the fuzzy sets and the goal of not appreciably altering the original fuzzy partition.
The Nutritional Quality of Commercially Bred Yellow Mealworm (Tenebrio molitor) Compared to European Union Nutrition Claims
Authors: Noyens Isabelle , Van Peer Meggie , Goossens Sarah , Ter Heide Carmen , Van Miert Sabine
Published: October 2024

Due to its potential as a sustainable protein source, the industrial relevance of Tenebrio molitor, known as yellow mealworm, is set to increase substantially. Given the novelty of its application in the food industry, knowledge is lacking regarding the nutritional quality of commercially farmed mealworms. This study investigated the nutritional composition of larvae from four different rearing facilities in Belgium and specifically investigated whether their nutritional profiles adhered to defined European nutrition claims (Regulation (EC) No. 1924/2006). In particular, the European nutrition claims “high in protein”, “high unsaturated fat”, “high in fibre” and “rich in P, Mg, K, Zn and Mn” were applicable for all mealworm samples on a dry matter basis. On a fresh matter basis, yellow mealworms were found to be “high in protein”, “high unsaturated fat” and “low in sugar”.
Prediction and Analysis of the Global Suitable Habitat of the Oryctes rhinoceros (Linnaeus, 1758) (Coleoptera: Scarabaeidae) Based on the MaxEnt Model
Authors: Fu Chun , Qian Qianqian , Deng Xinqi , Zhuo Zhihang , Xu Danping
Published: October 2024

The Asiatic rhinoceros beetle, Oryctes rhinoceros (Linnaeus, 1758) (Coleoptera: Scarabaeidae), is a destructive invasive species that poses a serious threat to palms, oil palms, and other plants. Defining a suitable area for the distribution of O. rhinoceros is essential for the development of appropriate policies and preventive measures. In this work, the MaxEnt niche model and ArcGIS software were used to predict the potential geographic distribution of O. rhinoceros in the world based on occurrence data and related environmental variables and to speculate on the influence of environmental variables on the distribution of O. rhinoceros. The results showed that the suitable areas of O. rhinoceros beetle were mainly distributed in 30° N–30° S, and the highly suitable areas were concentrated in South Asia, East Asia, Southeast Asia, and northern Oceania. The key environmental variables that determine the distribution location of O. rhinoceros are Precipitation of Wettest Month (bio13), Temperature of July (tmin7), Minimum Temperature of November (tmin11), and Precipitation of September (prec9). The prediction results of the MaxEnt model can reflect the global distribution of O. rhinoceros. This study can provide a theoretical basis for the prevention and control of O. rhinoceros and the development of relevant quarantine measures.
Feasibility and Safety of Post-Transcatheter Aortic Valve Replacement Coronary Revascularization Guided by Stress Cardiac Imaging
Authors: Leclercq Florence , Akodad Mariama , Prunet Elvira , Huet Fabien , Meunier Pierre-Alain , Manna François , Macia Jean-Christophe , Robert Pierre , Steinecker Matthieu , Berdeu Jean-Michel , Schmutz Laurent , Gandet Thomas , Roubille François , Cayla Guillaume , Mariano-Goulart Denis , Lattuca Benoît
Published: October 2024

Background: Systematic revascularization of asymptomatic coronary artery stenosis before transcatheter aortic valve replacement (TAVR) is controversial. Purpose: The purpose of this study was to evaluate the feasibility and safety of functional evaluation of coronary artery disease (CAD) followed by selective ischemia-guided percutaneous coronary revascularization following TAVR. Methods: This prospective, bi-centric, single-arm, open-label trial included all patients with severe aortic stenosis (AS) eligible for TAVR and with significant CAD defined as ≥1 coronary stenosis ≥ 70%. Patients with left main stenosis ≥ 50%, proximal left anterior descending artery (LAD) stenosis ≥ 90% or > class 2 Canadian Classification Society (CCS) angina were excluded. Myocardial ischemia was evaluated by stress cardiac imaging one month after TAVR. The primary endpoint was a composite of all-cause death, stroke, major bleeding (Bleeding Academic Research Consotium ≥ 3), major vascular complication (Valve Academic Research Consortium 3 criteria), acute coronary syndrome (ACS) and hospitalization for cardiac causes within 6 months of receiving TAVR. Results: Between June 2020 and June 2022, 64 patients were included in this study. The mean age was 84 ± 5.2 years. CAD mostly involved LAD (n = 27, 42%) with frequent multivessel disease (n = 30, 47%) and calcified lesions (n = 39, 61%). Stress cardiac imaging could be achieved in 70% (n = 46) of the patients, while 30% (n = 18) did not attend the stress test. Significant myocardial ischemia was observed in only three patients (4.5%). At 6-month follow-up, fifteen patients (23%) reached the primary endpoint, including death in six patients (9%), stroke in three patients (5%) and major bleeding in three patients (5%). ACS was observed in only two patients (3%) but both had severe coronary stenosis (≥90%) and did not refer for stress imaging for personal reasons. Hospital readmission (n = 27, 41%) was mostly related to non-cardiac causes (n = 17, 27%). Conclusions: In patients with asymptomatic CAD scheduled to undergo TAVR, a selective ischemia-guided coronary revascularization after TAVR seems to be safe, with a very low rate of ACS and few cases of myocardial ischemia requiring revascularization, despite low adherence to medical follow-up in this elderly population. This strategy could be evaluated in a randomized study.
Unmet Financial Needs of People with Psychotic Disorders—A Cross-Sectional Study in People with Psychotic Disorders, Parents, Siblings, and Controls
Authors: Jansen Josephien L. , Hao Jiasi , Bruggeman Richard , Simons Claudia J. P. , Van der Pluijm Marieke , Koerts Janneke , Krabbendam Lydia
Published: October 2024

Background. Psychotic disorders have a strong negative impact on people’s lives, including their financial situation. This study aimed to examine differences in unmet financial needs between people with psychotic disorders, parents, siblings, and controls. Secondly, we aimed to examine whether family clustering contributes to unmet financial needs. Lastly, we aimed to examine to what extent demographic, economic, psychiatric, functional, and cognitive characteristics and substance use predict unmet financial needs in people with psychosis. Methods. Data from the first assessment of people with psychosis (n = 956), siblings (n = 889), parents (n = 858), and controls (n = 496) included in the Genetic Risk and Outcome of Psychosis study were used. Group differences were assessed with Kruskal–Wallis tests (aim 1), while a mixed-effects logistic regression analysis and explorative and confirmative ordinal logistic regression analyses were conducted for aims 2 and 3, respectively. Results. Twenty-four percent of people with psychotic disorders reported unmet financial needs. These levels of unmet financial needs were significantly higher than levels for siblings, parents, and controls. We found a negligible influence of (direct) familial clustering on unmet financial needs. Lastly, cannabis and tobacco use significantly and consistently predicted higher levels of unmet financial needs of people with psychosis. Conclusions. Relatively high levels of unmet financial needs occurred in a heterogeneous group of people with psychosis, especially when people used cannabis or tobacco. Unmet financial needs can have detrimental consequences for mental health, stigmatization, leisure time activities, and social engagement. Thus, it is pivotal to recognize unmet financial needs, especially combined with substance use, as a crucial stressor for people with psychosis.
Association between Visit-to-Visit Ultrafiltration Volume Variability, Vascular Biomarkers and Cardiovascular Parameters in Chronic Hemodialysis Patients
Authors: Sági Balázs , Vas Tibor , Jakabfi-Csepregi Rita Klaudia , Sulyok Endre , Csiky Botond
Published: October 2024

Background. Cardiovascular (CV) diseases are the most common causes of morbidity and mortality in hemodialysis (HD) patients. We studied the effect of high visit-to-visit ultrafiltration (UF) variability on CV abnormalities in HD patients. Methods. Twenty-nine consecutive patients (age: 65.6 ± 10.4 years) were recruited. Samples for routine lab tests were drawn pre-HD for syndecan-1 (SDC-1) and endothelin-1 (ET-1) measurements pre-, mid- and post-HD. Applanation tonometry was performed pre-, mid- and post-HD. Visit-to-visit ultrafiltration volume variability (UVSD) was calculated as the standard deviation of the UF volume/dialysis session in the preceding 12 months. Echocardiography was performed post-HD. Results. Patients were divided into two groups based on the median of UVSD (500 mL). The average UF volume/HD was not different between the groups. Blood pressure (BP) values were similar. Pre-HD cfPWV (10.75 m/s) was lower in the high UVSD group (14.1 m/s, p = 0.03). In the high UVSD group, post-HD cfPWV (13.9 m/s) was higher than the pre-HD cfPWV (p < 0.05). Pre-HD ET-1 was lower in the high UVSD group (8.6 ± 3.9 vs. 10.8 ± 2.7 pg/mL, p < 0.05). Left ventricular end-diastolic diameter (LVEDD) and left ventricular mass index (LVMI) were higher in the high UVSD group (55.7 ± 7.3 vs. 51.0 ± 5.4 mm and 449.9 ± 180.5 vs. 350.3 ± 85.9 g/m², p < 0.005, respectively). Left ventricular ejection fraction (LVEF) was lower in the high UVSD group (53.5 vs. 60, p < 0.05). Conclusions. High UVSD was associated with increased left ventricular hypertrophy and dysfunction and decreased LVEF compared to low visit-to-visit UV variability despite similar UF volumes temporarily compensated by more elastic arteries. The observed abnormalities may increase CV risk.
A Comprehensive Review and Assessment of Cybersecurity Vulnerability Detection Methodologies
Authors: Bennouk Khalid , Ait Aali Nawal , El Bouzekri El Idrissi Younès , Sebai Bechir , Faroukhi Abou Zakaria , Mahouachi Dorra
Published: October 2024

The number of new vulnerabilities continues to rise significantly each year. Simultaneously, vulnerability databases have challenges in promptly sharing new security events with enough information to improve protections against emerging cyberattack vectors and possible exploits. In this context, several organizations adopt strategies to protect their data, technologies, and infrastructures from cyberattacks by implementing anticipatory and proactive approaches to their system security activities. To this end, vulnerability management systems play a crucial role in mitigating the impact of cyberattacks by identifying potential vulnerabilities within an organization and alerting cyber teams. However, the effectiveness of these systems, which employ multiple methods and techniques to identify weaknesses, relies heavily on the accuracy of published security events. For this reason, we introduce a discussion concerning existing vulnerability detection methods through an in-depth literature study of several research papers. Based on the results, this paper points out some issues related to vulnerability databases handling that impact the effectiveness of certain vulnerability identification methods. Furthermore, after summarizing the existing methodologies, this study classifies them into four approaches and discusses the challenges, findings, and potential research directions.
A Short Review on Radiopaque Polyurethanes in Medicine: Physical Principles, Effect of Nanoparticles, Processing, Properties, and Applications
Authors: Garavatti Julia , Ornaghi Jr. Heitor Luiz
Published: October 2024

Polyurethanes are used in a wide range of biomedical applications due to their variety of physical–chemical, mechanical, and structural properties, and biotic and abiotic degradation. They are widely used in bio-imaging procedures when metallic-based filler particles are incorporated, making the final product radiopaque. It would be advantageous, however, if polyurethanes with intrinsic radiopacity could be produced in their synthesis, avoiding a series of disadvantages in the processing and final product and also presenting potential antimicrobial activities. This review’s objective was to study the radiopacifying characteristics of nanoparticles, the physical principles of radiopacity, and the variety of medical applications of polyurethanes with nanoparticles. It was found in this study that the synthetization of radiopaque polyurethanes is not only possible but the efficiency of synthetization was improved when using atoms with high electron density as part of the backbone or when grafted, making them great multipurpose materials.
Turning Discarded Agricultural Remnants and Poultry Waste into Usable Hybrid Polymer Matrix Reinforcements: An Experimental Study
Authors: Balasubramanian NagarajaGanesh , Balasubramanian Rekha
Published: October 2024

The primary objective of the present study was to transform discarded agricultural remnants and poultry waste into value-added materials. Rice straw and chicken feathers are disposed of after their primary consumption into landfills or are incinerated, causing pollution and environmental threats. In this study, epoxy composites were fabricated using different volume proportions (5–45%) of these raw and alkali-treated remnants, and their mechanical strength was tested. The flexural strength of the rice straw composites and chicken feather composites initially decreased with the addition of fibers from 5 to 35 vol% and then the values increased when the fiber content was more than 35 vol%. The chicken feather composites showed increased impact strength with fiber addition. Alkali treatment of the rice straw resulted in improved flexural and impact strengths of the composites due to the removal of the waxy layer on the fiber surface, which was observed in the FTIR studies. Alkali treatment of the chicken feathers did not produce any significant change in the flexural strength of the composites, but their impact strength increased with fiber addition. Hybrid composites fabricated using rice straw and chicken feathers exhibited enhanced flexural and impact strength properties both with and without the alkali treatment, corroborating the synergistic effect of these fibers. SEM analysis of the fractured samples showed noteworthy interfacial adhesion between the fibers and matrix. This study presents a better method for converting these disposable materials into value-added usable materials and increasing their life cycle in the circular economy.
Theoretical Model for In Vivo Induction of Chemotherapy Sensitization Using miRNA Packaged in Distinct Layered Liposomes
Authors: Cipu Ruxandra-Ioana , Stănişteanu Mihai-Laurențiu , Andrei Mihaela-Aurelia , Banciu Daniel Dumitru , Banciu Adela
Published: October 2024

Resistance to chemotherapy is a problem of major social and economic importance, when looking at factors like the decrease in life expectancy, the associated therapeutic costs, and a significant number of cancers that resist current chemotherapy. The development of chemotherapeutics for all theoretically possible tumor variants is an approach that requires unreasonable resources. We propose a theoretical model that serves the purpose of overcoming resistance to chemotherapeutic agents used in cancer therapy. The model describes a gene delivery system based on liposomes, which are optically guided to the tumor’s location. The main aim of the gene delivery system is inhibiting the activity of enzymes involved in drug metabolism, hence offering the opportunity to use inexpensive chemotherapeutics that are already on the market. This model will reduce the costs of chemotherapy and will assure a positive outcome for patients.
Long-Term Afterglow Measurement of Scintillators after Gamma Irradiation
Authors: Viererbl Ladislav , Assmann Vratislavská Hana , Kolros Antonín
Published: October 2024

The long-term afterglow of scintillators is an important aspect, especially when the light signal from a scintillator is evaluated in the current mode. Scintillators used for radiation detection exhibit an afterglow, which usually comes from multiple components that have different decay times. A high level of afterglow usually has a negative influence on the detection parameters for the energy resolution in spectrometry measurements or X-ray and neutron imaging. The paper deals with the long-term afterglow of some types of scintillators, which is more significant for integral measurement when the current is measured in a photodetector. The range of decay times studied was in the order of tens of seconds to days. Seven types of scintillators were examined: BGO, CaF2(Eu), CdWO4, CsI(Tl), LiI(Eu), NaI(Tl), and plastic scintillator. The scintillators were excited by gamma-ray radiation. After irradiation, the detection unit, along with the scintillator, was moved to a laboratory where the anode current of the photomultiplier tube was measured using a picoammeter for at least a day. The measurements showed that CdWO4 and plastic scintillators have relatively low long-term afterglow signals in comparison to the other scintillators studied.
Soft Tissue Facial Morphology in Growing Patients with Different Occlusal Classes
Authors: Cenzato Niccolò , Farronato Marco , Tartaglia Francesco Carlo , Giannini Lucia , Inchingolo Angelo Michele , Dipalma Gianna , Maspero Cinzia , Inchingolo Francesco
Published: October 2024

Introduction: The study of facial profiles in the dental field is very important for the diagnosis and the dental and orthodontic treatment plan. The aim of this study is to analyze the three-dimensional morphology of the faces of 269 growing patients with Class I and II occlusions, focusing on children aged between 6 and 9 years old. The analysis was conducted using a non-invasive computerized system, which allowed for the automatic collection of facial landmarks and the subsequent reconstruction of three-dimensional coordinates. Materials and methods: The sample comprised 269 children within the specified age range. Each child’s facial features were captured using the non-invasive computerized system, which utilized two infrared CCD cameras, real-time hardware for label recognition, and software for three-dimensional landmark reconstruction. Sixteen cutaneous facial landmarks were automatically collected for each participant. From these landmarks, 10 angular and 15 linear measurements, as well as five direct distance rates, were derived. The mean values for each age class were calculated separately for children with bilateral Angle Class I occlusion and compared with those for children with bilateral Class II occlusion. In all children, the left and right occlusal classes were measured as suggested by Katz. Results: The analysis revealed notable differences, primarily in the three-dimensional angular measurements between children with Class I and II occlusions. Specifically, Class II children exhibited more convex faces in the sagittal plane and a less prominent lower jaw compared to Class I children. However, no significant differences were observed in linear measurements, except for the lower facial height rate, which varied inconsistently across age groups between the two occlusion types. Discussion and Conclusions: the findings of this research highlight distinct three-dimensional facial morphological differences between children with Class I and II occlusions. While Class II children tended to have more convex facial profiles and less prominent lower jaws, linear measurements showed minimal variation between the two occlusion types. These results underscore the importance of three-dimensional analysis in understanding facial morphology in growing patients with different occlusal patterns.
From Imbalance to Synergy: The Coupling Coordination of Digital Inclusive Finance and Urban Ecological Resilience in the Yangtze River Economic Belt
Authors: Chen Xi , Huang Xuan , Yu Tonghui , Zhang Yu , Cui Xufeng
Published: October 2024

In the context of rapid urbanization and digitalization, scientifically assessing the spatio-temporal interaction between digital inclusive finance (DIF) and urban ecological resilience (UER) is crucial for promoting the coordinated development of the regional ecology and economy. This study investigates the spatiotemporal evolution of the coupled coordination degree (CCD), the decoupling phenomenon, and its hindering factors in the Yangtze River Economic Belt (YREB) by utilizing the kernel density analysis, standard deviation ellipse, decoupling model, and obstacle degree analysis. Through systematic analyses, this paper aims to elucidate the development disparities among regions within the YREB, identify problematic areas, and propose targeted improvement measures. The results show that (1) The CCD between DIF and UER in the YREB has increased annually from 2011 to 2020. However, there are persistent imbalances, with an overall low level of coordination and uneven spatial development, and a trend of “higher coordination in the east and lower coordination in the west”. (2) The overall CCD of the YREB has reached at least the primary coordination level, with the coupling enhancement speed ranked as “downstream > midstream > upstream”, and regional differences decreasing. (3) The decoupling analysis reveals a predominant decoupling trend between DIF and UER, indicating that the digitization of financial services has not concurrently increased ecological pressures. (4) The obstacle degree analysis identifies resilience and digitalization as major barriers hindering CCD. This study provides a scientific basis and analytical framework for understanding the current spatiotemporal interaction between DIF and UER in the YREB, offering an important reference for formulating more effective policies.