bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimating mandibular growth stage based on cervical vertebral maturation in lateral cephalometric radiographs using artificial intelligence
Authors: Shoari Sajjad Alipour , Sadrolashrafi Seyed Vahid , Sohrabi Aydin , Afrouzian Reza , Ebrahimi Pooya , Kouhsoltani Maryam , Soltani Minou Kouh 
Published: June 2024

Abstract
Introduction
Determining the right time for orthodontic treatment is one of the most important factors affecting the treatment plan and its outcome. The aim of this study is to estimate the mandibular growth stage based on cervical vertebral maturation (CVM) in lateral cephalometric radiographs using artificial intelligence. Unlike previous studies, which use conventional CVM stage naming, our proposed method directly correlates cervical vertebrae with mandibular growth slope.

Methods and materials
To conduct this study, first, information of people achieved in American Association of Orthodontics Foundation (AAOF) growth centers was assessed and after considering the entry and exit criteria, a total of 200 people, 108 women and 92 men, were included in the study. Then, the length of the mandible in the lateral cephalometric radiographs that were taken serially from the patients was calculated. The corresponding graphs were labeled based on the growth rate of the mandible in 3 stages; before the growth peak of puberty (pre-pubertal), during the growth peak of puberty (pubertal) and after the growth peak of puberty (post-pubertal). A total of 663 images were selected for evaluation using artificial intelligence. These images were evaluated with different deep learning-based artificial intelligence models considering the diagnostic measures of sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV). We also employed weighted kappa statistics.

Results
In the diagnosis of pre-pubertal stage, the convolutional neural network (CNN) designed for this study has the higher sensitivity and NPV (0.84, 0.91 respectively) compared to ResNet-18 model. The ResNet-18 model had better performance in other diagnostic measures of the pre-pubertal stage and all measures in the pubertal and post-pubertal stages. The highest overall diagnostic accuracy was also obtained using ResNet-18 model with the amount of 87.5% compared to 81% in designed CNN.

Conclusion
The artificial intelligence model trained in this study can receive images of cervical vertebrae and predict mandibular growth status by classifying it into one of three groups; before the growth spurt (pre-pubertal), during the growth spurt (pubertal), and after the growth spurt (post-pubertal). The highest accuracy is in post-pubertal stage with the designed networks.
Computing grounded theory: a quantitative method to develop theories
Authors: Chen Zhuo , Chen Yunsong 
Published: June 2024

AbstractThe inductive logic of grounded theory and the principle of avoiding theoretical preconceptions are significantly different from the deductive logic and hypothesis testing of traditional quantitative research. Based on the limitations of theory production in quantitative research, this paper proposes a Computing Grounded Theory (CGT) approach that directly quantitatively assists theories. With the help of machine learning and attribution algorithms, CGT identifies variables that have not been the focus of previous studies based on the predictive power of the independent variables to propose new theoretical hypotheses, following the principle that causality is a sufficient and unnecessary condition for predictability. This paper systematically discusses CGT’s basic idea, logical premise, and methodological foundation while providing an empirical example. This method bridges the gap in the theoretical production of quantitative research and is of great value in theory, discipline, knowledge systems and social governance.
Double burden of malnutrition and its socio-demographic determinants among children and adolescents in Malaysia: National Health And Morbidity Survey 2019
Authors: Lai Wai Kent , Palaniveloo Lalitha , Mohd Sallehuddin Syafinaz , Ganapathy Shubash Shander 
Published: June 2024

Abstract
Introduction
Malaysia faces the threat of a double burden of malnutrition where undernutrition and overweight (including obesity) coexist in the same population. This study aimed to determine the anthropometric assessment among children and adolescents aged 5 to 17 years and its association with socio-demographic factors.

Methods
Data were extracted from the National Health and Morbidity Survey conducted in 2019. This cross-sectional survey applied a two-stage stratified sampling design. Socio-demographic characteristics were obtained. Weight and height were measured, age- and sex-specific standard scores for height and BMI were calculated to establish individual’s anthropometric assessment. Having either stunting or thinness was considered undernutrition, while being overweight (including obesity) was considered overnutrition. If someone had undernutrition and/or overnutrition, they were classified as having malnutrition. The prevalence was determined using complex sampling analysis, while the association was assessed through logistic regression. The analysis included a total of 3,185 respondents.

Results
The prevalence of stunting, thinness, overweight and obesity among the respondents aged 5 to 17 years was 12.7%, 10.0%, 15.0% and 14.8%, respectively. The overall prevalence of malnutrition was 48.3%. Respondents residing in rural had 1.35 times more likelihood of experiencing undernutrition [AOR = 1.35, 95% CI (1.04, 1.77)] compared to their urban counterparts. Boys exhibited a greater likelihood of being overweight and obese than girls [AOR = 1.40, 95% CI (1.13, 1.73)]. Respondents aged 10 to 14 years were 1.37 times more likely to be overnutrition than those aged 5 to 9 years old [AOR = 1.37, 95% CI (1.09, 1.73)].

Conclusion
There is growing evidence of the increasing prevalence of coexistence of undernutrition along with overweight and obesity among children and adolescents in Malaysia. Moving forward, greater initiatives and efforts are required to formulate strategies for planning and implementing programs and policies to expedite progress in improving nutrition.
Body image of university students: a systematic review of the characteristics of interventions
Authors: Huguenin Felipe Machado , de Almeida Vitor Alexandre Rabelo , Rodrigues Marcus Vinícius Freitas , Ferreira Maria Elisa Caputo , Morgado Fabiane Frota da Rocha 
Published: June 2024

Abstract
Background
Body image is the mental representation of the body and can be influenced by cognitive, biological, behavioral, sociocultural, and environmental factors. University students often encounter challenges related to it.

Objective
This systematic review examined interventions aimed at holistically developing a positive body image within this population.

Methods
The PRISMA 2020 guidelines and the PICO method were employed to identify, select, assess, and synthesize studies. The consulted databases included Scopus, Web of Science, and PsycINFO, with inclusion criteria targeting body image interventions for university students aged 18 to 39. Study quality was evaluated using the QATSDD tool.

Results
Twenty-one relevant studies were identified, primarily from the United States, mostly employing quantitative methods, with a focus on female participants. Various intervention strategies were utilized, including cognitive-behavioral approaches, media literacy, and physical/resistance training, with a growing use of technology like mobile applications. The majority of studies reported effective outcomes, such as reduced body dissatisfaction and increased self-esteem following interventions. Nevertheless, literature gaps were identified, such as the scarcity of formative interventions and limited use of qualitative approaches.

Conclusion
While technology in interventions offers promising opportunities, careful assessments and judicious selection of evaluation instruments are fundamental for reliable results. Future research should focus on addressing identified gaps, such as exploring more formative interventions and incorporating qualitative methodologies to provide a more comprehensive understanding of the effectiveness of body image interventions among university students.
Spontaneous posterior fossa hemorrhage: profile and functional outcome in patients attending Tanta stroke unit
Authors: Nassar Mahmoud Hamed , Fouda Basem Hamdy , Elsaid Ahmed Safwat Abd ElMohsen , Bahnasy Wafik Said , El-Seidy Ehab Ahmed Shawky , Kishk Ahmed Mustafa 
Published: June 2024

Abstract
Background
The most dangerous and least curable type of stroke is spontaneous intracerebral hemorrhage (ICH), and prognosis is highly correlated with location and size in the posterior fossa. The objective of this work was to estimate the frequency of posterior fossa hemorrhage (PFH) in Tanta University Hospitals, as well as identify functional outcomes and mortality in PFH.

Methods
This study was performed on 33 posterior fossa hemorrhagic patients and 119 posterior ischemic stroke patients (PCIS) submitted to the CT brain and the MRI brain, using the following scales: GCS and NIHSS, and the intracerebral hemorrhage scale (ICH score).

Results
Posterior fossa hemorrhage (PFH) represents 16.83% of total hemorrhagic stroke in the ER. Vertigo and DCL are more common in PFH (60.6%, 48.4%) than in PCIS. 82% of PFH patients had hypertension (HTN) hemorrhage. The cerebellum is the most common site for PFH (48%), pontine (24%), thalamic (18%), and midbrain (9%). PFH had unfavorable outcomes in 55% of the studied patients; the MRS mean was 4; and 39% died in the follow-up.

Conclusion
Posterior fossa hemorrhage is a potentially serious neurovascular emergency associated with complex symptomatology. PFH demonstrates diverse prognoses depending on the location of the intracerebral hemorrhage and the size of the hematoma.
Gossen’s first law in the modeling for demand side management: a thorough heat pump case study with deep learning based partial time series data generation
Authors: Li Chang , Brecher Gina , Kovačević Jovana , Çakmak Hüseyin K. , Förderer Kevin , Matthes Jörg , Hagenmeyer Veit 
Published: June 2024

AbstractGossen’s First Law describes the law of diminishing marginal utility. This paper aims to further verify the proposed hypothesis that Gossen’s First Law also holds in the modeling for Demand Side Management (DSM) with a thorough heat pump case study. The proposed hypothesis states that in general the complexity-utility relationship in the field of DSM modeling could be represented by a diminishing marginal utility curve. On the other hand, in data based modeling, when utilizing a large dataset for validation, the data integrity is critical to the reliability of the results. However, the absence of partial time series data may occur during the measurement due to missing sensors or IT related issues. In this work, an extensive real-world open dataset of a ground source heat pump is utilized for the case study. In the raw data, one key variable namely the flow rate is missing. Thus, three different algorithms based on machine learning and deep learning architectures namely Random Forest (RF), Long Short-Term Memory (LSTM) and Transformer are applied to predict the flow rate by utilizing an open loop forecasting. The raw data are first pre-processed with a time interval of one hour and then used for training, validation and forecast. Furthermore, a modified persistence model as the baseline is also defined. The predicted flow rate using LSTM yields the lowest error of 7.47$$\%$$
%
nMAE and 10.56$$\%$$
%
nRMSE respectively. The forecast results are then utilized in the following step of modeling of a heat pump use case. With the introduced quantification method for complexity and a modified version for utility, we further verify the proposed hypothesis with a longer time horizon of 7 days.
Predicting acute complications in endoscopic retrograde cholangiopancreatography based on the severity and onset of post-procedural pain
Authors: Ejtehadi Fardad , Shahramian Iraj , Befrouei Mojtaba Khademi , Sivandzadeh Gholam Reza , Taghavi Seyed Alireza , Niknam Ramin , Tahani Masoud 
Published: June 2024

Abstract
Background
Endoscopic retrograde cholangiopancreatography (ERCP), a standard procedure used for diagnosing and treating pancreaticobiliary disorders, has the highest rate of complications among endoscopic procedures. We aimed to evaluate the association of post-ERCP pain onset and its severity with the development of acute complications.

Methods
This cross-sectional study included 172 candidates for ERCP who were referred to Namazi Hospital, Shiraz, from January 21, 2021, to January 21, 2022. Demographic features of the participants, including age and gender, were recorded. ERCP indications, complications during and after ERCP, and narcotic requirements were also noted. Post-ERCP pain severity was evaluated using a 10-point visual analogue scale (VAS), with 0 indicating no pain and 10 indicating the worst pain. Pain severity was evaluated twice: once by the physician and once by the patient. The interval between the procedure and the onset of pain was also recorded.

Results
Out of the 172 participants of this study with a mean age of 53.77 ± 20.20 years, 98 (57%) were male. The most typical indication of ERCP was common bile duct stone (36%). Complications during and after ERCP occurred in 2.3% and 2.9%, respectively, with retroperitoneal/sphincterotomy perforation (1.2%) being the most common post-ERCP complication. Post-ERCP pain score (both by patient and physician) was significantly higher in patients with complications compared to those without complications (P < 0.001). The interval between the ERCP procedure and the onset of pain was significantly shorter in patients with post-ERCP complications (P = 0.003). Also, a significantly higher percentage of patients with complications required narcotics (40% vs 1.2%, P = 0.004).

Conclusions
Although the presence of post-ERCP pain may not necessarily be indicative of complications, post-ERCP pain severity and onset, as well as narcotic requirement, appear to be associated with the development of post-ERCP complications.
Comparative study of UV spectroscopy, RP-HPLC and HPTLC methods for quantification of antiviral drug lamivudine in tablet formulation
Authors: Somkuwar Komal , Sabale Prafulla , Sawale Vaibhav , Rahangdale Priya 
Published: June 2024

Abstract
Background
In the current study, estimation of lamivudine (LMU) by UV spectroscopy, reverse-phase HPLC (RP-HPLC) and HPTLC methods in tablet formulation was developed, and comparative studies between the methods were investigated by analytical results and statistical test analysis of variance (ANOVA) to find out best method. In the UV spectral method, LMU was quantified at 271 nm absorption maxima using methanol as the solvent. In the RP-HPLC method, the Shimadzu C18 column (250 mm × 4.6 mm i.d., 5 µm particle size) was employed for chromatographic separation. The mobile phase used consists of methanol: water (70:30 v/v) in an isocratic mode with a 1.0 mL/min flow rate. In the HPTLC method, the chromatogram was developed on a pre-coated plate of silica gel 60 F254 with a mobile phase composition of chloroform: methanol (8:2 v/v). The quantification was performed at an absorbance mode of 271 nm by densitometry. The methods were validated according to the International Conference on Harmonization (ICH) guideline Q2 (R1). The degradation conditions were employed as per ICH guidelines Q1A(R2) and Q1B which include acid, alkaline, neutral, thermal and photostability to determine the intrinsic stability of the drug in varied environmental conditions.

Results
LMU absorption maxima was found to be 271 nm. The retention time of LMU was 3.125 min, and the total analysis time was 5 min. The Rf value of LMU was 0.49–0.62. The methods were linear within 2–12 μg/mL range. The correlation coefficient (r2) for UV, HPLC and HPTLC was 0.9980, 0.9993 and 0.9988, and percent recoveries were calculated as 98.40–100.52%, 99.27–101.18% and 98.01–100.30%, respectively, with percentage relative standard deviation (RSD) less than 2% showing that methods were precise and accurate.

Conclusion
Developed UV, RP-HPLC and HPTLC methods are free from intervention caused by excipients present in tablets and thus can be used for regular quantitative analysis of LMU in tablet formulation. Based on analytical results and statistical tests, ANOVA, it is inferred that the HPLC method is best for LMU quantification tablet formulation due to its high reproducibility, good retention time and sensitivity; it has a higher percent recovery and has less analysis time, i.e., 5 min. The degradation peaks were well separated from the LMU peak indicating stability of the HPLC method.
Accuracy of Glucagon Testing Across Transition in Young Adults With Childhood-Onset GH Deficiency
Authors: Fava Daniela , Guglielmi Davide , Pepino Carlotta , Angelelli Alessia , Casalini Emilio , Varotto Carolina , Panciroli Marta , Tedesco Caterina , Camia Tiziana , Naim Alessandro , Allegri Anna Elsa Maria , Patti Giuseppa , Napoli Flavia , Gastaldi Roberto , Parodi Stefano , Salerno Mariacarolina , Maghnie Mohamad , Di Iorgi Natascia 
Published: June 2024

Abstract

Context
The 2019 American Association of Clinical Endocrinologists guidelines suggested peak GH-cutoffs to glucagon test (GST) of ≤3 and ≤1 µg/L in the diagnosis of permanent GH deficiency (GHD) during the transition phase.

Objective
The aim of the study was to evaluate the accuracy of GST compared to insulin tolerance test (ITT) in the definition of GHD at adult height achievement.

Patients and methods
Ninety-seven subjects with childhood-onset GHD (median age, 17.39 years) underwent ITT, GST, and IGF-1 testing; 44 subjects were idiopathic (isolated GHD), 35 moderate organic GHD (0-2 hormone deficiencies) and 18 severe organic GHD (≥3 hormone deficiencies).

Results
Bland and Altman analysis showed a high consistency of GH peak measures after ITT and GST. Receiver operating characteristic analysis identified 7.3 μg/L as the optimal GH peak cutoff to GST [95% confidence interval (CI) 4.15-8.91; sensitivity 95.7%, specificity 88.2%, positive predictive value (PPV) 88.0%, negative predictive value (NPV) 95.7%] able to correctly classify 91.8% of the entire cohort while 5.8 μg/L was the best GH peak cutoff able to correctly classify 91.4% of moderate organic GHD patients (95% CI 3.16-7.39; sensitivity 96.0%, specificity 80.0%, PPV 92.3%, NPV 88.9%). Patients with ≥3 hormone deficiencies showed a GH peak &lt;5 μg/L at ITT and &lt;5.8 μg/L at GST but 1. The optimal cutoff for IGF-1 was −1.4 SD score (95% CI −1.94 to 0.77; sensitivity 75%, specificity 94%, PPV 91.7%, NPV 81.0%) that correctly classified 85.1% of the study population.

Conclusion
A GH peak to GST &lt;5.8 μg/L represents an accurate diagnostic cutoff for young adults with childhood-onset GHD and high pretest probability of permanent GHD.
A Novel Kidney Failure Prediction Model in Individuals With CKD: Impact of Serum Bilirubin Levels
Authors: Inoguchi Toyoshi , Okui Tasuku , Nojiri Chinatsu , Yamashita Takanori , Nakayama Masaru , Haruyama Naoki , Fukuizumi Kunitaka , Wakata Yoshifumi , Nakashima Naoki 
Published: June 2024

Abstract

Context
Predicting the progression of chronic kidney disease (CKD) to end-stage kidney disease (ESKD) is crucial for improving patient outcomes.

Objective
To reveal the highly predictive activity of serum bilirubin levels for the progression of CKD to ESKD, and to develop and validate a novel ESKD prediction model incorporating serum bilirubin levels.

Methods
We assessed the relative importance of 20 candidate predictors for ESKD, including serum bilirubin levels, in a CKD cohort (15 ≤ estimated glomerular filtration rate [eGFR] &lt; 60 mL/min/1.73 m2), and subsequently developed a prediction model using the selected variables. The development cohort comprised 4103 individuals with CKD who underwent follow-up at Kyushu University Hospital, Japan, from 2008 to 2018. The primary outcome was incident ESKD, defined as an eGFR &lt; 15 mL/min/1.73 m2, chronic dialysis, or renal transplantation.

Results
The mean follow-up time was 7.0 ± 4.2 years, during which 489 individuals (11.9%) progressed to ESKD. The Cox proportional hazard model selected eGFR, serum bilirubin, proteinuria, age, diabetes, gender, hypertension, serum albumin, and hemoglobin in order of their importance. The predictive performance of the model was optimized by incorporating these 9 variables in discrimination evaluated by time-dependent area under the curve (AUC). This model also demonstrated excellent calibration. Additionally, this model exhibited excellent predictive performance in both discrimination (2-year AUC: 0.943, 5-year AUC: 0.935) and calibration in a validation cohort (n = 2799).

Conclusion
Serum bilirubin levels were strong predictors for the progression of CKD to ESKD. Our novel model that incorporates serum bilirubin levels could accurately predict ESKD in individuals with CKD.
Academic Case Management and College Student Retention
Authors: Dills Angela , Traywick Deaver 
Published: June 2024

Abstract
Many institutions of higher education struggle with low retention rates. One state liberal arts college addressed this concern by assigning an academic case manager to higher risk students. This project evaluated the effectiveness of the case manager on student credit hours and retention using a randomized control trial. The case manager contacted assigned students regularly, meeting with students and helping them navigate college and their classes. We found that students randomly assigned to the case manager earned higher grades, completed more credits, and were more likely to return to campus the second semester of the academic year.
Examining Experiences of Academic Advisors of Color Using a Critical Race Framework
Authors: Spratley Sophie L. , Suarez Cecilia E. 
Published: June 2024

Abstract
Part of a larger study exploring leadership development opportunities for academic advisors of color at a predominantly white institution, this paper focuses on the lived experiences of academic advisors of color. Through an understanding of race theory, a critical race lens is used to examine the predominantly white institution and the narratives of academic advisors of color in this racialized setting. This qualitative study explored advisors’ experiences with the structure of academic advising, their racialized experiences, and how race is addressed in the workplace. Implications for institutions of higher education are discussed, including how an understanding of the experiences of academic advisors of color can aid in challenging dominant narratives and practices within institutions of higher education.
A scoping review of pain resulting from the endotracheal suctioning of paediatric intensive care patients
Authors: Alaca Aslı , Sarı Hatice Yıldırım , Yilmaz Medine , Yayla Kemal 
Published: June 2024

Background: This scoping review was conducted to summarise and map studies on pain resulting from endotracheal suctioning in paediatric intensive care patients. Method: This scoping review conducted in June 2022 was performed by screening articles published in English. Scopus, PubMed, Cochrane, Web of Science, MedLine and Ovid databases were used for screening. The keywords ‘endotracheal suctioning’, ‘pain’, ‘paediatric intensive care’ and their synonyms were used in the search. Results: During the review, 280 articles were accessed, and the full texts of 14 articles were evaluated for suitability. After some of the articles were excluded from the study, abstracts of nine articles were given below. Conclusion: It is recommended that a greater number of randomised controlled studies should be conducted, because the number of studies with a high level of evidence on the effect of endotracheal suctioning on the pain levels of patients in the paediatric intensive care unit is very few.