bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incidence of stroke and its association with metabolic abnormalities in patients with atrial fibrillation: The Jordan Atrial Fibrillation (JoFib) study
Authors: Alkouri Osama , Khader Yousef , Qaladi Omar Aawadh , Jarrah Mohamad , Alawaisheh Raed , Alqarni Aidah Sanad , Gonzales Ferdinand , Ramadan Anoud , harbi Abdulhafith Al 
Published: July 2023

Abstract
Background Evidence regarding the concomitant impact of multiple metabolic comorbidities on stroke risk in patients with atrial fibrillation is still equivocal. Despite the high prevalence of these comorbidities in the Middle East, no studies were conducted to predict their combined effect on stroke risk in patients with atrial fibrillation. This study aimed at identifying stroke incidence and the association between metabolic abnormalities and one-year risk of stroke in patients with atrial fibrillation.
Methods: The study enrolled 2020 consecutive patients with atrial fibrillation. The incidence of stroke was compared across categories of different variables using the chi-square test. Two binary logistic regression models were developed to identify the significant predictors of stroke.
Results: The 1-year incidence of stroke was 3.1%. Only diabetes was significantly associated with increased odds of stroke (OR = 2.15; 95% CI: 1.26, 3.66; p = 0.005) after adjusting for significant predictors of stroke including age, past history of stroke, and CHA2DS2VAS score. The combination of metabolic abnormalities was significantly associated with increased odds of stroke. The odds ratio increased from 2.53 (95% CI 1.10-8.85, P=0.028) for patients with only one metabolic abnormality to 3.90 (95% CI 1.16-13.10, P=0.028) for patients who had two metabolic abnormalities to 4.95 (95% CI 1.47-16.71, P=0.041) for patients with three metabolic abnormalities.
Conclusion: Adequate glycemic control for patients with diabetes is crucial for patients with coexisting atrial fibrillation. Stroke prevention should focus on the concomitant impacts of multiple metabolic comorbidities rather than on a particular or single risk factor such as atrial fibrillation (AF). Comprehensive nursing assessment and management of coexisting metabolic abnormalities in patients with atrial fibrillation is substantial to minimize the stroke risk and prevent serious health complications. Nursing education helps patients with DM and hypertension to adhere to their treatment regimen, understand their condition, follow dietary restrictions, and seek medical attention if needed. Our findings postulate that the presence of multiple metabolic comorbidities may eliminate the effect of atrial fibrillation on stroke risk. Thus, further research is warranted to identify the coincident impact of multiple metabolic abnormalities on stroke risk in patients without atrial fibrillation.
Body image victimization and eating distress in young adult females
Authors: SINGH PRIYA , GUPTA AARZOO 
Published: July 2023

Abstract
Background
Eating distress syndrome (EDS) is characterized by distressing and conflicting thoughts about the body shape and eating behaviours accompanied by self-imposition of strict dietary and/or exercise regimes in the absence of any significant weight loss. EDS has prevalence of nearly 11% and is associated with psychological distress, internalizing and externalizing problems, lesser well-being, and reduced quality of life.
Methods
The study aimed to assess the relationship between eating-related messages, and body image victimization with eating distress syndrome in young adult females. Purposive sampling was employed to approach an estimated sample size of 151 young adults (18–26 years). The data was collected online by using e-consent through social media platforms such as Facebook, Twitter, Instagram, etc. via Google Form (GF). There was a total of 403 respondents to GF comprising of Caregiver Eating Messages Scale (CEMS), Body Image Victimisation Experience Scale (BIVES), Eating Disorder Examination - Questionnaire Short (EDE-QS). Total 151 were recruited from 403 as per defined criteria.
Results
Restrictive or critical messages (RCM) had a positive relationship and accounted 12% chance of occurrence of EDS. Frequency of experiences of body image victimization from peers (6%) had a greater predictive value than that from the parents (3%). Similarly, the impact of body image victimization by peers (9%) contributed more than that from the parents (4%) in the occurrence of EDS.
Conclusion
Remarks or comments related to eating and appearance tend to determine how an individual perceived oneself and the course of one’s food habits or choices.
Case study: modeling and robust control of two wheeled self-balancing mobile with µ approach
Authors: Delavar Abolfazl 
Published: July 2023

Abstract
Robots are one of the most useful tools in today’s world. They are widely used to move objects and perform everyday tasks. Segways are one of these tools that are commonly used nowadays for transportation and even entertainment. In this case study, the dynamical model of a two-wheeled self-balancing mobile device has been proposed. Additionally, a µ robust controller for the device has been designed. All necessary sources are available in the repository: https://github.com/abolfazldelavar/Two_wheeled_self_balancing_mu_approach_CS
Nonstandard approach to fixed point of 2nd-order orbit asymptotic contraction
Authors: Shi Jie 
Published: July 2023

Abstract
In this paper, the 2nd-order orbit asymptotic contraction is given. The local iterative fixed point problem of the new 2nd-order orbit asymptotic contraction is considered by nonstandard analysis methods. We have conducted further research based on the relevant achievements of some scholars. We obtained the results of the corresponding iterative sequence converging to the local iterative fixed point of the asymptotic contraction T without the continuity.
Mathematics Subject Classification (2010). Primary 47H10,54H25; Secondary 03H05,54J05.
Plasticity and not adaptation is the primary source of temperature-mediated variation in flowering phenology in North America
Authors: Ramirez-Parada Tadeo , Park Isaac , Record Sydne , Davis Charles , Ellison Aaron , Mazer Susan 
Published: July 2023

Abstract
Phenology varies widely over space and time because of its sensitivity to climate. However, whether phenological variation is primarily generated by rapid organismal responses (i.e., plasticity) or local adaptation remains unresolved. Here, we used 1,038,027 herbarium specimens representing 1,605 species to measure flowering time sensitivity to temperature over time (‘Stime’) and space (‘Sspace’). By comparing these estimates, we inferred how adaptation and plasticity historically influenced phenology along temperature gradients and how their contributions vary among species with different phenology and native climates, and among ecoregions differing in species composition. Sspace and Stime were highly positively correlated (r = 0.87), of similar magnitude, and more frequently consistent with plasticity than adaptation. Apparent plasticity and adaptation generated earlier flowering in spring, limited responsiveness in summer, and delayed flowering in fall in response to temperature increases. Nonetheless, ecoregions differed in the relative contributions of adaptation and plasticity, from consistently greater importance of plasticity (e.g., Southeastern USA Plains) to their nearly equal importance throughout the season (e.g., Western Sierra Madre Piedmont). Our results support the hypothesis that plasticity is the primary driver of flowering time variation along climatic gradients, with local adaptation having a widespread but comparatively limited role.
Hierarchical bionic neural network-like architecture towards high- performance microwave absorption and corrosion protection
Authors: Li Shuaizhen , Xie Tianwen , Ma Lin , Liu Daheng , Huang Nan , Liu Wei , Ma Song , Zhang Zhidong 
Published: July 2023

Abstract
It remains challenging to develop multifunctional electromagnetic wave (EMW) absorbers to enhance the environmental adaptability and survivability of target devices in harsh environment. Herein, this study innovatively constructs a three-dimensional (3D) hierarchical bionic neural network-like Ni3Fe@N-doped carbon nanotube@Carbon foam (Ni3Fe@NCNT@CF) composite via dip-coating and carbonization operation, realizing the integration of microwave absorption and corrosion protection. The optimal Ni3Fe@NCNT@CF composite demonstrates competitive EMW absorption with a minimum reflection loss of −51.5 dB and a maximum effective absorption bandwidth (EAB) of 6.4 GHz at 10 wt%, due to superior interlinked conductive channels (with flexible and adjustable conduction loss) and magnetic-dielectric matching of the 3D hierarchical bionic neural network, including 3D CF skeleton (matrical neural network), short CNTs network (enrich “dendrites”), and ultra-long CNTs network (enhance “axons”). Besides, Ni3Fe@NCNT@CF composite exhibits a reliable anti-corrosion performance with a low corrosion current density ~10-8 A·cm-2 after 30 days of immersion in corrosive medium, owing to the physical shield provided by the impermeable, inert CNT shells and carbon foam. Our findings may provide design inspiration of versatile EMW materials for applications in complicated environments.
Relationship Between Fear of Earthquakes and Sleep Quality in Patients with Hypertension Living in Istanbul
Authors: Koç Zeynep , Meterelliyoz Kumru Yaşar , Etlik Arzu Aksoy , Sürücü Merve , Vardal Tuba Olcay , Çetinavcı Dilara , Akın Seydahmet 
Published: July 2023

Abstract
Introduction:
It is known that emotional stress affects individuals with hypertension. Sleep quality is also associated with blood pressure regulation. In our study, we aimed to investigate the effect of Kahramanmaraş earthquakes on sleep quality in individuals with hypertension residing in Istanbul.
Method
This randomized and controlled study included hypertensive patients who visited the internal medicine outpatient clinic between March 7, 2023 and May 7, 2023. Individuals with hypertension consulted a psychiatrist for the presence of earthquake fear. The Pittsburg Sleep Quality Index (PSQI) was used to assess sleep quality.
Results
Seventy patients with hypertension aged 35–64 years, 35 with earthquake fear and 35 without, were included. While the mean PSQI sleep quality score of the group with earthquake fear was 7.26 ± 3.94, the mean score of the group without earthquake fear was 5.17 ± 3.89, which was higher (p = 0.013; p < 0.05). Based on the presence of earthquake fear, poor sleep quality was found in 71.4% (n = 25) of patients with earthquake fear and in 42.9% (n = 15) without, and a statistically significant difference was found (p = 0.016; p < 0 .05). The risk of impaired sleep quality in the earthquake-fear group was 3.333 times higher than that in the without earthquake-fear group (ODSS: 3.333; 95%CI 1.235–8.997).
Conclusion
Our study has shown that the sleep quality of individuals with hypertension residing in Istanbul is adversely affected by the fear of earthquakes. We believe that it may be useful to review the pharmacological treatments of individuals with hypertension whose sleep quality is impaired owing to the fear of earthquakes and provide close psychological support.
Landslide Hazard Mapping in Son La Province, Vietnam Under Climate Change Scenarios for 2025 &amp; 2050
Authors: Tuan Le Canh , Khanh Nguyen Quoc , Giang Nguyen Khac Hoang 
Published: July 2023

Abstract
In recent years, landslides in mountainous provinces are increasing. Whenever the rainy season comes, landslides occur, causing casualties to people and damages to the infrastructure. Son La, a mountainous province in the North of Vietnam, has suffered significant damage from landslides. Therefore, the purpose of this research is to introduce an application of the analytic hierarchy process (AHP) method with the integration of representative concentration pathways (RCP) scenario 4.5 to study landslides in Son La province, Vietnam. With the integration of the digital elevation model (DEM) and collected data into ArcGIS software, we obtained different factor maps: Slope map, Aspect map, Cleavage density map, River density map, Rainfall map, Lithology map, Fault density map, Vegetation cover map, Distance to roads. These were the important input parameters for the AHP method. The data collected from 2009 to the present and the research documents of the authors based on the field investigations in 2018, 2019, 2020, and 2021 were the basis for us to complete this article. The landslide risk maps with the integration of maximum daily rainfall from the climate change scenario for 2025 and 2050 were produced. The results revealed that the landslide risk in Son La province increases with time. The results from this research will assist local authorities in land use planning, disaster control, and achieving sustainable development goals.
Functional Precision Medicine Enhances Clinical Outcomes of Relapsed/Refractory Pediatric and Adolescent Cancer Patients
Authors: Azzam Diana , Rocha Arlet Acanda de la , Berlow Noah , Fader Maggie , Coats Ebony , Saghira Cima , Espinal Paula , Galano Jeanette , Khatib Ziad , Abdella Haneen , Maher Ossama , Vorontsova Yana , Andrade-Feraud Cristina , Daccache Aimee , Reis Victoria , Holcomb Baylee , Ghurani Yasmin , Rimblas Lilliam , Guilarte Tomas , Hu Nan , Salyakina Daria , Jacome Alexa 
Published: July 2023

Abstract
Current genomics-driven precision oncology identifies actionable mutations in < 10% of cancer patients. Pediatric cancer is especially challenging due to limited mutations and fewer genomics-guided options. Functional precision medicine (FPM) addresses this by integrating genomic profiling with rapid, high-throughput functional ex vivo drug testing on live patient-derived cells. However, there is lack of FPM prospective data showing clinical utility in pediatric cancers. In this prospective, non-randomized, single-arm study (NCT03860376), we investigated feasibility and impact of FPM in pediatric/adolescent with refractory/relapsed solid and hematologic cancers. Of 25 patients, 19 (76%) had FPM data reviewed by the FPM tumor board within four weeks (FPMTB), meeting the primary outcome of the study. Additionally, six patients received FPM-guided treatment. Among these 6 patients, 83% (5 patients) experienced a greater than 1.3-fold improved progression-free survival compared to their previous therapy, and together demonstrated a significant increase in progression-free survival and objective response rate versus physician’s choice-treated patients (8 patients). Post-hoc analysis showed that patients with the same subtype of cancer do not cluster together, reinforcing the concept of optimizing cancer treatments one patient at a time (n-of-1 approach). Additionally, our study used a novel artificial intelligence/machine learning (AI/ML) platform that leveraged drug responses and sequencing data to identify novel biomarkers of drug efficacy and gain potential mechanistic insights within specific subsets of pediatric cancer patients. The findings from our proof-of-principle study illustrate the impact of FPM for relapsed/refractory pediatric/adolescent cancer patients, highlight future integrations of FPM and AI/ML, and support ongoing patient cohort expansion (NCT05857969).
Point-MDA: Progressive Point Cloud Analysis for Extreme Multi-scale Detail Activation
Authors: Li Manwen , Zhao Yanming , Wang Chun , Zhou Yun , Jiang Wei 
Published: July 2023

Abstract
The point cloud is a form of three-dimensional data that comprises various detailed features at multiple scales. Due to this characteristic and its irregularity, point cloud analysis based on deep learning is challenging. While previous works utilize the sampling-grouping operation of PointNet++ for feature description and then explore geometry by means of sophisticated feature extractors or deep networks, such operations fail to describe multi-scale features effectively. Additionally, these techniques have led to performance saturation. And it is difficult for standard MLPs to directly ``mine" point cloud. To address above problems, we propose the Detail Activation (DA) module, which encodes data based on Fourier transform after sampling and grouping. We activate the channels at different frequency levels from low to high in the DA module to gradually recover finer point cloud details. As training progresses, the proposed Point-MDA can uncover local and global geometries of point cloud progressively. Our experiments show that Point-MDA achieves superior classification accuracy, outperforming PointNet++ by 3.3\% and 7.9\% in terms of overall accuracy on the ModelNet40 and ScanObjectNN dataset, respectively. Furthermore, it accomplishes this without employing complicated operations, while exploring the full potential of PointNet++.
Whole-brain structural connectivity predicts cognitive deficits in pretreated glioma patients
Authors: Friedrich Michel , Filss Christian P. , Lohmann Philipp , Mottaghy Felix M. , Stoffels Gabriele , Lucas Carolin Weiss , Ruge Maximilian I. , Shah N. Jon , Caspers Svenja , Langen Karl-Josef , Fink Gereon R. , Galldiks Norbert , Kocher Martin 
Published: July 2023

AbstractPurpose Glioma patients frequently suffer from cognitive dysfunction potentially caused by tumor invasion or treatment effects. We hypothesized that cognitive functioning in pretreated glioma patients critically depends on the maintained structural connectivity of multiple brain networks. Methods The study included 121 pretreated glioma patients (median age, 52 years; median ECOG score 1; CNS WHO grade 3 or 4) who had biopsy or resection plus chemoradiation. Cognitive performance was assessed by ten tests in five main cognitive domains 14 (1-214) months after therapy initiation. Hybrid amino acid PET/MRI using the tracer O-(2-[18F]fluoroethyl)-L-tyrosine, a network-based cortical parcellation, and advanced tractography methods were used to generate whole-brain fiber count-weighted connectivity matrices. The matrices were applied to cross-validated machine learning-based models to identify fiber connections and underlying networks predictive for cognitive performance in the evaluated domains. Results Compared to healthy controls (n = 121), the cognitive scores were significantly lower in nine cognitive tests. The models well predicted 7/10 scores (median correlation coefficient, 0.47; range, 0.39–0.57) from 24–230 (0.5–4.6%) of the possible connections/edges, 84% were between nodes of different networks. Critically involved cortical regions/nodes (≥ 10 adjacent predictive edges) included predominantly left-sided nodes of the visual, somatomotor, dorsal/ventral attention, and default mode networks. Highly critical nodes (≥ 15–20 edges) included the default-mode network’s left temporal and bilateral posterior cingulate cortex. Conclusions These results suggest that the cognitive performance of pretreated glioma patients is strongly related to structural connectivity between multiple brain networks and depends on the integrity of known network hubs also involved in other neurological disorders.
Wildfire Detection Via Transfer Learning: A Survey
Authors: Hong Ziliang , Hamdan Emadeldeen , Zhao Yifei , Ye Tianxiao , Pan Hongyi , Cetin Ahmet Enis 
Published: July 2023

Abstract
This paper presents a comprehensive survey of publicly available neural network models specifically designed for detecting wildfires using regular visible-range cameras positioned on hilltops or forest lookout towers. The surveyed models are first pre-trained on the ImageNet-1K dataset and then fine-tuned on a custom wildfire dataset to enhance their performance. Evaluations are conducted on diverse wildfire images, enabling a thorough assessment of their capabilities. The survey findings provide valuable insights for individuals interested in leveraging transfer learning techniques for wildfire detection. Among the examined models, Swin Transformer-tiny achieves the highest Area Under the Curve (AUC) value, indicating strong overall performance in distinguishing wildfire events. However, ConvNext-tiny stands out for its exceptional ability to detect all instances of wildfires while maintaining the lowest false alarm rate within our dataset. These results highlight the varying strengths of different neural network models and offer valuable guidance for selecting an appropriate model based on specific detection requirements and priorities.
Six-Month Post-Intensive Care Outcomes During High and Low Bed Occupancy due to the COVID-19 Pandemic: a Multicenter Prospective Cohort Study
Authors: Castro-Ávila Ana , Merino-Osorio Catalina , González-Seguel Felipe , Camus-Molina Agustín , Muñoz-Muñoz Felipe , Leppe Jaime 
Published: July 2023

Abstract
Purpose: The COVID-19 pandemic can be seen as a natural experiment to test how bed occupancy affects post-intensive care unit (ICU) patient's functional outcomes. Therefore, we compared by bed occupancy the frequency of mental, physical, and cognitive impairments in patients admitted to ICU during the COVID-19 pandemic.
Methods: Prospective cohort of adults mechanically ventilated >48 hours in one of 19 ICUs in seven Chilean public and private hospitals. Ninety per cent of nationwide beds occupied was the cut-off for low versus high bed occupancy. At ICU discharge, 3- and 6-month follow-up, we assessed disability using the World Health Organization Disability Assessment Schedule 2.0, quality of life, mental, physical, and cognitive outcomes following the core outcome set for acute respiratory failure.
Results: 252 eligible participants were enrolled, 103(41%) during low and 149(59%) during high occupancy. Patients treated during high occupancy were younger (P50[P25-P75]: 55[44-63] vs 61[51-71]; p<0.001), more likely to be admitted due to COVID-19 (126[85%] vs 65[63%]; p<0.001), and have higher education qualification (94[63%] vs 48[47%]; p=0.03). No differences were found in the frequency of at least one mental, physical or cognitive impairment by bed occupancy at ICU discharge (low vs high: 93% vs 91%; p=0.6), 3-month (74% vs 63%; p=0.2) and 6-month (57% vs 57%; p=0.9) follow-up.
Conclusions: There were no differences in post-ICU outcomes between high and low bed occupancy. Most patients had at least one mental, physical or cognitive impairment at ICU discharge, which remained high at 6-month follow-up.
Effect of Climate fluctuation in Building construction
Authors: Hussein Abtehaj , Hasan Taha , Ibrahim Amer M. 
Published: July 2023

Abstract
The largest industry in America is construction, which accounts for 10% of jobs and 10% of the GNP. It has a high labor intensity, a low technology intensity, and has had mediocre profitability and competitiveness over the past 20 years. The purpose of the study is to look at the factors that contribute to temperature, humidity, and CO2 variations during building construction and how they affect such buildings.