bluuebunny/crossref_metadata_2025_split huggingface dataset:
Method of determining the maximum flight range of a UAV using the FPV mode and using the centimeter frequency range of radio-link in laboratory conditions
Authors: Salii Oleksandr , Hol Vladyslav 
Published: December 2024

At the current stage of production of various unmanned aerial vehicles (UAVs) in the flight mode “first person view” (FPV), there are no individual passports with information on the maximum possible flight range for individual UAV-FPV kits and ground control stations (GSC) application of a suitable model of a digital video camera (including a thermal imaging camera) and the use of a radio line of communication in the centimeter frequency range. Therefore, the main goal of the article is the selection and development of methods for measuring the main parameters of the receiver-transmitter of UAVs and GSC in laboratory conditions in the combat zone, using the developed “simulator of the radio communication line of data transmission”; with further calculation, on the basis of relevant international standards, of the maximum possible flight range and drawing up the corresponding “flight map”. The main results of the article are: the method of determining the maximum possible flight range of UAVs in FPV mode in laboratory conditions for the frequency range of GHz has been developed, which is based on a set of developed experimental and empirical measurement methods and theoretical calculation methods, according to the recommendations of the ITU (International Telecommunication Union). The materials of the article are of practical value for the planning and organization of the flight mission of multi-rotor UAVs of the tactical level for a given distance, as well as for the activities of the UAV routine maintenance units of the Unmanned Systems Forces of the Armed Forces of Ukraine upon the fact that UAVs return from flight missions in order to check their technical parameters.
The population frequency of Marfan syndrome and the associated cardiac risks in a normal population
Authors: Choi K , Huang M , Savige J 
Published: December 2024

Abstract

Marfan syndrome is an autosomal dominantly (AD)-inherited disease that results from pathogenic variants in the Fibrillin 1 (FBN1) gene, and is characterised by tall stature, elongated limbs and digits, lens abnormalities and aortic root dilatation, aneurysms and dissection but milder forms also occur. Radiological imaging suggests that Marfan syndrome affects between one in 3000 and 5000 of the population. The aim of this study was to determine the population frequency of Marfan syndrome from the number of pathogenic FBN1 variants found in a normal variant database. FBN1 variants were downloaded from gnomAD v2.1.1 and annotated with ANNOVAR. The population frequency was determined from the number of pathogenic null and structural variants, and the number of predicted pathogenic missense changes classified by rarity and computational scores. This population frequency was then compared with the frequencies in the control subset, and from gnomAD variants assessed as Pathogenic or Likely pathogenic in the ClinVar or LOVD databases. Our strategy identified predicted pathogenic FBN1 variants in one in 416 individuals, which was confirmed in the control subset (one in 356, p NS). Predicted pathogenic variants were most common in East Asian people (one in 243, p < 0.0001) and least common in Ashkenazim (one in 5,185, p = 0.0082). The population frequencies based on pathogenic variants in the ClinVar or LOVD databases were one in 718 and one in 1014 respectively. Null variants which are associated with aortic aneurysms affected only one in 8624. Thus, Marfan syndrome is more common than previously recognised. Emergency departments and cardiac clinics in particular should be aware of undiagnosed Marfan syndrome and its cardiac risks, but many individuals may have a milder phenotype.
evoke and evoke+: design of two large-scale, double-blind, placebo-controlled, phase 3 studies evaluating efficacy, safety, and tolerability of semaglutide in early-stage symptomatic Alzheimer’s disease
Authors: Cummings Jeffrey L. , Atri Alireza , Feldman Howard H. , Hansson Oskar , Sano Mary , Knop Filip K. , Johannsen Peter , León Teresa , Scheltens Philip 
Published: December 2024

Abstract

Background: Disease-modifying therapies targeting the diverse pathophysiology of Alzheimer’s disease (AD), including neuroinflammation, represent potentially important and novel approaches. The glucagon-like peptide-1 receptor agonist semaglutide is approved for the treatment of type 2 diabetes and obesity and has an established safety profile. Semaglutide may have a disease-modifying, neuroprotective effect in AD through multimodal mechanisms including neuroinflammatory, vascular, and other AD-related processes. Large randomized controlled trials are needed to assess the efficacy and safety of semaglutide in early-stage symptomatic AD.
Methods: evoke and evoke+ are randomized, double-blind, placebo-controlled phase 3 trials investigating the efficacy, safety, and tolerability of once-daily oral semaglutide versus placebo in early-stage symptomatic AD. Eligible participants were men or women aged 55–85 years with mild cognitive impairment or mild dementia due to AD with confirmed amyloid abnormalities (assessed by positron emission tomography or cerebrospinal fluid [CSF] analysis). After a maximum 12-week screening phase, an anticipated 1840 patients in each trial are randomized (1:1) to semaglutide or placebo for 156 weeks (104-week main treatment phase and 52-week extension). Randomized participants follow an 8-week dose escalation regimen (3 mg [weeks 0–4], 7 mg [weeks 4–8], and 14 mg [weeks 8–156]). The primary endpoint is the semaglutide–placebo difference on change from baseline to week 104 in the Clinical Dementia Rating– Sum of Boxes score. Analyses of plasma biomarkers, collected from all participants, and a CSF sub-study (planned n=210) will explore semaglutide effects on AD biomarkers and neuroinflammation.
Results: Enrollment was undertaken between May 18, 2021, and September 8, 2023. Completion of the trials’ main phase is expected in September 2025, and the 52-week extension (in which participants and investigators remain blinded to treatment assignment) will continue to October 2026.
Conclusions: evoke and evoke+ are the first large-scale trials to investigate the disease-modifying potential of semaglutide in participants with early-stage symptomatic AD, including exploration of effects on AD biomarkers and neuroinflammation. The trials will provide data on the potential disease-modifying effects of semaglutide and will be important in evaluating its utility in the treatment of early-stage symptomatic AD.
Trial registration: Clinicaltrials.gov, NCT04777396 and NCT04777409. Date: 02/03/2021.
The relationship between the classroom environment, trait emotional intelligence, and the level of hope and burnout: insights from Chinese college EFL learners
Authors: Li Xiaomeng , Li Huan , Xiong Wei 
Published: December 2024

Abstract

This study explores the relationship between the classroom environment (CE), trait emotional intelligence (TEI), hope, and burnout among 425 Chinese vocational college students. Data were collected using the Classroom Environment Scale, the Adult Dispositional Hope Scale (ADHS), the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), and burnout measures. The results revealed significant associations between TEI, hope, and burnout, with CE playing a pivotal role in influencing hope and burnout levels. These findings offer important insights for educators and policymakers. By fostering a supportive and emotionally engaging classroom environment, educators can enhance students' emotional intelligence, cultivate hope, and mitigate academic burnout. The results underscores the necessity for teacher training programs that emphasize the development of emotional and social competencies to improve classroom dynamics and student success.
Socioeconomic Determinants of Affordability of Medication: A Panel Data Econometric Analysis in Iran
Authors: Rajabi Mohammad Javad , Ghasemi Mojtaba , Peikanpour Mohammad , Rasekh Hamid Reza 
Published: December 2024

Abstract

Background
one of the key aspects of fair access to healthcare is access to affordable medications, that is important almost for every government. Exploring and estimation the effects of the Social Determinants of Health (SDH) on affordability is an important step to clear and picture the equity health and targets for policy making. This paper attempt to estimate these effects on medication affordability in Iran.
Methods
We used data from Iran Households Survey (IHS) in a 26-year period from 1997 to 2022. We developed a panel data econometric model to estimate the effects of Socioeconomic Determinants (SEDs) on medication expenses and three ratios including: medication expense/ health costs, income and all costs, as affordability indices. We employ Fixed Effect (FE) estimators, Random Effect (RE) estimators, Panel Tobit estimators and Maximum Likelihood Estimators (MLE) for this purpose.
Results
the mean of medication expenses for each household is about 1.45E + 07 IRR adjusted in 2021(1400 Persian calendar) inflation rate. the Concentration Index (CI) is about 0.12. median of the medication expenses/ health expenses is near and about 33.5%, and we don’t see inequality for this ratio between provinces (CI = -0.01), increase prevalence of rare disease, age oh households’ head, increase the share of food and housing expenses, increase family size can increase the expenses and financial burden for households. instead getting transfer payment as cash subside, having insurance can reduce the medication costs.
Conclusion
we saw a little inequality in medication expanses tend to richer provinces, in contract no inequality in the ratio of medication expenses to health expanses. Our findings confirm previous studies that old aged members and family size are barrier to access to affordable medications. our results also show the negative effect of rare disease on affordability of medicines. we didn’t find relation between availability and insurance with affordability of medication, future research could explore these connections further, along with examining the impact of occupation on affordability.
YouTube and Bilibili as sources of information on oral cancer: cross-sectional content analysis study
Authors: zhang Qilei , Li Zhe , Zhang Huiping , Han Ling , Zhao Shugang , Jia Siyu 
Published: December 2024

Abstract

This study aims to assess the informational quality of oral cancer-related videos on YouTube and Bilibili. A total of 300 oral cancer-related videos meeting the inclusion criteria were selected from YouTube (150 videos from 111 uploaders) and Bilibili (150 videos from 134 uploaders) for evaluation and analysis. YouTube videos were more popular in terms of views and likes, whereas the average likes per 30 days and comments showed no significant difference between the two platforms. The uploaders from YouTube mainly consisted of hospitals/non-profit organizations (66.7%) and companies with profit (17.1%), while Bilibili's uploaders mainly were self-media (55.2%) and doctors (29.1%). YouTube videos covered more topics than those on Bilibili. Solo narration was the most common video style across all platforms, but TV shows/documentaries were more popular on YouTube (31.3%). The video quality was assessed using the four tools as follows: Though mDISCERN (modified DISCERN) and PEMAT-Actionability (Patient Education Materials Assessment Tool) were similar across platforms, YouTube videos scored higher on PEMAT-Understandability, VIQI (Video Information and Quality Index), and GQS (Global Quality Score) than Bilibili videos. Videos from health professionals were deemed more reliable. Spearman correlation analysis revealed no strong relationships between the video quality and the audience interaction. In conclusion, YouTube videos demonstrated higher audience interactions and quality but both platforms still require improvements. More professional content creators and platform algorithm optimization are necessary to promote high-quality health information.
Functional near-infrared spectroscopy responses to facial stimuli in infants
Authors: Silva Cintia Ricaele Ferreira da , de Almeida Valéria Azevedo , Morya Edgard , Pereira Silvana Alves 
Published: December 2024

Abstract

The ability to interpret emotional expressions is crucial for human social interactions. Recognizing these expressions during interpersonal interactions allows individuals to identify others' emotional states, providing important cues for appropriate responses in various social contexts. From birth, babies are biologically prepared to rapidly develop emotion-related perceptual skills, extracting vital information from faces and voices. The present study investigated brain activity related to emotions in infants aged 4 to 11 months, using functional near-infrared spectroscopy (fNIRS) and eye tracking. The study focused on identifying neural responses to emotional stimuli (happy and anger) presented in social (human faces) and nonsocial objects (toys). Brain activity in frontotemporal, parietal, and occipital regions was analyzed. The results offer valuable insights into emotional and social development in infants and contribute to improving early assessment and intervention strategies.
Effect of Twin Block on Intracranial Pressure
Authors: Hezenci Yasin , Bulut Musa , Demirel Oğuzhan 
Published: December 2024

Abstract

Objectives
This study aimed to investigate the impact of Twin Block appliances on intracranial pressure (ICP) in adolescents by measuring the optic nerve sheath diameter (ONSD) using ultrasonography.
Methods
We conducted a prospective study involving 20 adolescents (8 girls and 12 boys) with skeletal mandibular retrognathia undergoing treatment with Twin Block appliances. ONSD measurements were taken at six different time points: before appliance placement (T0), 1 minute after placement (T1), 10 minutes after placement (T2), one month after appliance use (T3), immediately after appliance removal (T4), and 10 minutes after removal (T5). Mean arterial pressure (MAP), heart rate, and peripheral oxygen saturation (SpO2) were also monitored. Statistical analyses were performed using Friedman and Wilcoxon Signed-Rank tests with Bonferroni correction, considering p < 0.05 as statistically significant.
Results
Significant increases in ONSD were observed at T1 and T2 compared to T0 (p < 0.05), with the highest ONSD recorded at T1. No significant changes in ONSD were noted at T3 or T5, indicating that the initial increase in ONSD was temporary. MAP showed a significant decrease at T2, but no significant changes were observed in SpO2 or heart rate across the time points.
Conclusion
This study is the first to report a significant increase in ICP, as indicated by ONSD, in adolescents using Twin Block appliances. The observed rise in ONSD shortly after appliance placement suggests a temporary increase in ICP. These findings highlight the importance of monitoring intracranial pressure during orthodontic treatment, particularly in adolescents.
Evaluation of Health Laboratory Ethical Compliance Among Laboratory Practitioners in Kinondoni District, Tanzania.
Authors: Lwenge Catherine , Mahiti Gladys , Paul Heavenlight 
Published: December 2024

Abstract

Background: Laboratory science rears a special pattern in medicine, which helps promote different biological phenomena, which will aid in the management of disease through analysis of samples and laboratory tests. Laboratory practitioners provide results that are used to make critical decisions. The aim of the study was to evaluate how health laboratory practitioners understand and comply with the laboratory ethical conduct as per ISO 15189:2012
Methodology: An exploratory study design that involved a qualitative approach for data collection. A total of 16 laboratory personnels participated in an in depth Primary data was collected from the laboratory practitioners through in-depth interviews, semi - structured questions that were audio recorded then verified for accuracy and completeness by the researcher. Audio recorded interviews were then transcribed into text, translated, and then analyzed using a thematic method of analyzing qualitative data.
Results: Despite most of the laboratory practitioners claiming of being aware and follow of laboratory ethical conducts there were several misconducts that still exists in the laboratories e.g., mislabeling, miscommunication with clients. study has brought about valuable knowledge on the ethical conducts among laboratory practitioners and importance of abiding the ethical standards while performing laboratory activities and impacts on the results.
Conclusion: There were still some incidences of information breaching that still happen to some of the laboratories. More frequent trainings were of concern, it should be a mandatory for each laboratory staff to attend all ethical trainings.
Revolutionizing Disease Diagnosis with Large Language Models: A Systematic Review
Authors: Bojesomo Alabi , Seghier Mohamed , Hadjileontiadis Leontios , AlShehhi Aamna 
Published: December 2024

Abstract

Purpose: The underlining success of large language models (LLMs) in general language understanding has revolutionized many domains, including healthcare. This systematic review aims to explore the application of LLM in disease diagnosis, acknowledging its success in reducing diagnosis delays in areas with limited health resources or when health costs are not affordable.
Methods: We systematically reviewed the literature on LLMs used for disease diagnosis tasks, such as differential diagnosis, question-answering, and report generation, from January 2014 to September 2024. The included studies are categorized based on input data types (text, images, others), learning approaches (zero-shot, few-shot, retrieval-augmented generation, fine-tuning, etc.), and diagnostic contexts.
Results: We observe that LLMs used for disease diagnosis primarily employ zero-shot learning, prompting, and retrieval-augmented generation techniques. While some LLMs are explicitly fine-tuned for this purpose, only a few have been trained from scratch. Most LLMs are trained using data from the Internet and research publications. Despite this, LLM models have successfully diagnosed many common chronic diseases and addressed some rare and uncommon diseases with reasonable accuracy. Despite these promising trends and successes, concerns about the potential for misdiagnosis persist, particularly with less common and rare diseases.
Conclusion: The use of LLMs in disease diagnosis has a promising future in reducing diagnostic delay and complementing the work of health professionals in resource-constrained environments. The success of LLM in disease diagnosis calls for proper analysis of data from health domains and for encouraging the inclusion of information on otherwise uncommon diseases.
Consequence of Gibberellic Acid and Vermicomposting on Vegetative Development, Mineral Content and Features of Persian Shallot
Authors: Askari Kaveh Ostad Ali , Ghane Mohsen 
Published: December 2024

Abstract

Persian Shallot (Allium hirtifolium boiss) is a valuable medicinal plant that is native to Iran. This herb belongs to the Alliaceae family and a perennial herb. This research was conducted to investigate the effect of vermicompost and gibberellic acid on vegetative growth, mineral content and characteristics of Allium bulb. The results of this study showed that the highest level of leaf area (19.12 cm2) was related to 0.7 kg/m2 and (21.66 cm2) treated with 206 ppm of gibberellic acid, the most number of leaves (4.95) in the treatment of 410 ppm gibberellic acid, the most number of daughter bulb were (7.36), respectively, for treatment of 1.2 kg/m2 vermicompost and (7. 24) for 410 ppm treatments Gibberellic acid, the highest diameter of daughter bulb (10.82 mm) was related to 0.6 kg/m2 vermicompost treatment, the highest dry weight of bulb (1.92 gr) was 0.7 kg/m2 vermicompost, highest percentage bulb’s dry content (32.93%) was related to 1.2 kg/m2 vermicompost treatment and (33.72%) was related to 410 ppm of gibberellic acid, the highest amount of phosphorus (0.37%) was related to the treatment of 410 ppm gibberellic acid and the highest amount of potassium (1.92%) was related to 1.2 kg/m2 vermicompost treatment.
Groundwater weakness evaluation of Meshginshahr aquifer by GIS depend SEVERE Prototypical
Authors: Askari Kaveh Ostad Ali , Kianmehr Peiman 
Published: December 2024

Abstract

Groundwater possessions need appropriate organization in situation of contamination owing to decontamination problems. In view of the position of Meshginshahr Plain aquifer in providing the consumption in addition to agronomy water, its weakness was assessed in this investigation. Over assembling the input components of the SEVERE prototypical together with groundwater depth, net recharger, aquifer media, soil broadcasting, landscape, the effect of vadose region and hydraulic conductivity of the aquifer and making plans and participating them with the ArcGIS 10.5 software, the weakness map of this plain was formed. The results of the current investigation exposed that the aquifer weakness in Meshginshahr Plain could be considered into four scales, explicitly very low, low, low to medium and medium to high, with proportions of 10, 52, 33 and 7 percent, separately. Conferring to the SEVERE prototypical, the maximum pollution possible was originated in the southeast, north and northwest of Meshginshahr Plain where the residues in the aquifer’s vadose districts are usually more bristly-coarse than the residues of other portions and the groundwater level is also low; as a consequence, the groundwater pollution possible has enlarged in this district. The nitrate quantified in 17 wells displayed that the quantity of groundwater nitrate was amongst 7 to 22 mg/l; consequently, it could be determined that no nitrate risk endangered Meshginshahr Plain groundwater. The relationship quantity amongst the SEVERE indicator and nitrate absorption in this plain was 0.9. The zoning map of Meshginshahr Plain’s groundwater pollution possible, applying the SEVERE indicator, displayed high precision in the current investigation.
Uncovering Niche Insights in Long-Tail Markets: A Unified LNRE Framework
Authors: Sur Ratul 
Published: December 2024

Abstract

In long-tail markets, analysis predominantly is skewed towards the "head," while the "tail," rich with niche insights, often goes uninvestigated. The tail, however, stores valuable information that can expose the emergent trends while sometimes contradictory to general findings derived from the head. This research highlights that while conventional machine learning algorithms struggle to model rare events due to token sparsity, our model successfully captures these elusive insights. By leveraging the mathematical properties of G-functions and Q-functions, this study integrates their behavior into traditional fabric of machine learning frameworks, which improves rare event modelling. We show that uniform partitioning of data into subintervals facilitates granular analysis, enabling the detection of rare events. The findings highlight how long-tail contributions not only dominate but also grow with specific thresholds, uncovering emergent trends. Additionally, our approach analyzes temporal trends, dynamically tracking their evolution over time. This research highlights the need of integrating LNRE models with partitioning and convergence techniques, offering a robust tool for decoding the hidden value in long-tail markets and empowering businesses to access previously invisible opportunities.